@article{taylor-lapole_colebank_weigand_olufsen_puelz_2022, title={A computational study of aortic reconstruction in single ventricle patients}, volume={11}, ISSN={["1617-7940"]}, url={https://doi.org/10.1007/s10237-022-01650-w}, DOI={10.1007/s10237-022-01650-w}, journal={BIOMECHANICS AND MODELING IN MECHANOBIOLOGY}, author={Taylor-LaPole, Alyssa M. and Colebank, Mitchel J. and Weigand, Justin D. and Olufsen, Mette S. and Puelz, Charles}, year={2022}, month={Nov} }
 @article{bartolo_qureshi_colebank_chesler_olufsen_2022, title={Numerical predictions of shear stress and cyclic stretch in pulmonary hypertension due to left heart failure}, volume={1}, ISSN={["1617-7940"]}, url={https://doi.org/10.1007/s10237-021-01538-1}, DOI={10.1007/s10237-021-01538-1}, abstractNote={Isolated post-capillary pulmonary hypertension (Ipc-PH) occurs due to left heart failure, which contributes to 1 out of every 9 deaths in the United States. In some patients, through unknown mechanisms, Ipc-PH transitions to combined pre-/post-capillary PH (Cpc-PH) and is associated with a dramatic increase in mortality. Altered mechanical forces and subsequent biological signaling in the pulmonary vascular bed likely contribute to the transition from Ipc-PH to Cpc-PH. However, even in a healthy pulmonary circulation, the mechanical forces in the smallest vessels (the arterioles, capillary bed, and venules) have not been quantitatively defined. This study is the first to examine this question via a computational fluid dynamics model of the human pulmonary arteries, arterioles, venules, and veins. Using this model, we predict temporal and spatial dynamics of cyclic stretch and wall shear stress with healthy and diseased hemodynamics. In the normotensive case for large vessels, numerical simulations show that large arteries have higher pressure and flow than large veins, as well as more pronounced changes in area throughout the cardiac cycle. In the microvasculature, shear stress increases and cyclic stretch decreases as vessel radius decreases. When we impose an increase in left atrial pressure to simulate Ipc-PH, shear stress decreases and cyclic stretch increases as compared to the healthy case. Overall, this model predicts pressure, flow, shear stress, and cyclic stretch that providing a way to analyze and investigate hypotheses related to disease progression in the pulmonary circulation.}, journal={BIOMECHANICS AND MODELING IN MECHANOBIOLOGY}, author={Bartolo, Michelle A. and Qureshi, M. Umar and Colebank, Mitchel J. and Chesler, Naomi C. and Olufsen, Mette S.}, year={2022}, month={Jan} }
 @article{geddes_ottesen_mehlsen_olufsen_2022, title={Postural orthostatic tachycardia syndrome explained using a baroreflex response model}, volume={19}, ISSN={["1742-5662"]}, DOI={10.1098/rsif.2022.0220}, abstractNote={Patients with postural orthostatic tachycardia syndrome (POTS) experience an excessive increase in heart rate (HR) and low-frequency (∼0.1 Hz) blood pressure (BP) and HR oscillations upon head-up tilt (HUT). These responses are attributed to increased baroreflex (BR) responses modulating sympathetic and parasympathetic signalling. This study uses a closed-loop cardiovascular compartment model controlled by the BR to predict BP and HR dynamics in response to HUT. The cardiovascular model predicts these quantities in the left ventricle, upper and lower body arteries and veins. HUT is simulated by letting gravity shift blood volume (BV) from the upper to the lower body compartments, and the BR control is modelled using set-point functions modulating peripheral vascular resistance, compliance, and cardiac contractility in response to changes in mean carotid BP. We demonstrate that modulation of parameters characterizing BR sensitivity allows us to predict the persistent increase in HR and the low-frequency BP and HR oscillations observed in POTS patients. Moreover, by increasing BR sensitivity, inhibiting BR control of the lower body vasculature, and decreasing central BV, we demonstrate that it is possible to simulate patients with neuropathic and hyperadrenergic POTS.}, number={193}, journal={JOURNAL OF THE ROYAL SOCIETY INTERFACE}, author={Geddes, Justen R. and Ottesen, Johnny T. and Mehlsen, Jesper and Olufsen, Mette S.}, year={2022}, month={Aug} }
 @article{talaei_garan_quintela_olufsen_cho_jahansooz_bhullar_suen_piszker_martins_et al._2021, title={A Mathematical Model of the Dynamics of Cytokine Expression and Human Immune Cell Activation in Response to the Pathogen Staphylococcus aureus}, volume={11}, ISSN={["2235-2988"]}, DOI={10.3389/fcimb.2021.711153}, abstractNote={Cell-based mathematical models have previously been developed to simulate the immune system in response to pathogens. Mathematical modeling papers which study the human immune response to pathogens have predicted concentrations of a variety of cells, including activated and resting macrophages, plasma cells, and antibodies. This study aims to create a comprehensive mathematical model that can predict cytokine levels in response to a gram-positive bacterium, S. aureus by coupling previous models. To accomplish this, the cytokines Tumor Necrosis Factor Alpha (TNF-α), Interleukin 6 (IL-6), Interleukin 8 (IL-8), and Interleukin 10 (IL-10) are included to quantify the relationship between cytokine release from macrophages and the concentration of the pathogen, S. aureus, ex vivo. Partial differential equations (PDEs) are used to model cellular response and ordinary differential equations (ODEs) are used to model cytokine response, and interactions between both components produce a more robust and more complete systems-level understanding of immune activation. In the coupled cellular and cytokine model outlined in this paper, a low concentration of S. aureus is used to stimulate the measured cellular response and cytokine expression. Results show that our cellular activation and cytokine expression model characterizing septic conditions can predict ex vivo mechanisms in response to gram-negative and gram-positive bacteria. Our simulations provide new insights into how the human immune system responds to infections from different pathogens. Novel applications of these insights help in the development of more powerful tools and protocols in infection biology.}, journal={FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY}, author={Talaei, Kian and Garan, Steven A. and Quintela, Barbara de Melo and Olufsen, Mette S. and Cho, Joshua and Jahansooz, Julia R. and Bhullar, Puneet K. and Suen, Elliott K. and Piszker, Walter J. and Martins, Nuno R. B. and et al.}, year={2021}, month={Nov} }
 @article{colebank_qureshi_rajagopal_krasuski_olufsen_2021, title={A multiscale model of vascular function in chronic thromboembolic pulmonary hypertension}, volume={321}, ISSN={["1522-1539"]}, url={https://doi.org/10.1152/ajpheart.00086.2021}, DOI={10.1152/ajpheart.00086.2021}, abstractNote={Chronic thromboembolic pulmonary hypertension (CTEPH) is caused by recurrent or unresolved pulmonary thromboemboli, leading to perfusion defects and increased arterial wave reflections. CTEPH treatment aims to reduce pulmonary arterial pressure and reestablish adequate lung perfusion, yet patients with distal lesions are inoperable by standard surgical intervention. Instead, these patients undergo balloon pulmonary angioplasty (BPA), a multi-session, minimally invasive surgery that disrupts the thromboembolic material within the vessel lumen using a catheter balloon. However, there still lacks an integrative, holistic tool for identifying optimal target lesions for treatment. To address this insufficiency, we simulate CTEPH hemodynamics and BPA therapy using a multiscale fluid dynamics model. The large pulmonary arterial geometry is derived from a computed tomography (CT) image, whereas a fractal tree represents the small vessels. We model ring- and web-like lesions, common in CTEPH, and simulate normotensive conditions and four CTEPH disease scenarios; the latter includes both large artery lesions and vascular remodeling. BPA therapy is simulated by simultaneously reducing lesion severity in three locations. Our predictions mimic severe CTEPH, manifested by an increase in mean proximal pulmonary arterial pressure above 20 mmHg and prominent wave reflections. Both flow and pressure decrease in vessels distal to the lesions and increase in unobstructed vascular regions. We use the main pulmonary artery (MPA) pressure, a wave reflection index, and a measure of flow heterogeneity to select optimal target lesions for BPA. In summary, this study provides a multiscale, image-to-hemodynamics pipeline for BPA therapy planning for inoperable CTEPH patients.}, number={2}, journal={AMERICAN JOURNAL OF PHYSIOLOGY-HEART AND CIRCULATORY PHYSIOLOGY}, publisher={American Physiological Society}, author={Colebank, Mitchel J. and Qureshi, M. Umar and Rajagopal, Sudarshan and Krasuski, Richard A. and Olufsen, Mette S.}, year={2021}, month={Aug}, pages={H318–H338} }
 @article{dobreva_brady-nicholls_larripa_puelz_mehlsen_olufsen_2021, title={A physiological model of the inflammatory-thermal-pain-cardiovascular interactions during an endotoxin challenge}, volume={599}, ISSN={["1469-7793"]}, DOI={10.1113/JP280883}, abstractNote={Key points Inflammation in response to bacterial endotoxin challenge impacts physiological functions, including cardiovascular, thermal and pain dynamics, although the mechanisms are poorly understood. We develop an innovative mathematical model incorporating interaction pathways between inflammation and physiological processes observed in response to an endotoxin challenge. We calibrate the model to individual data from 20 subjects in an experimental study of the human inflammatory and physiological responses to endotoxin, and we validate the model against human data from an independent study. Using the model to simulate patient responses to different treatment modalities reveals that a multimodal treatment combining several therapeutic strategies gives the best recovery outcome. Abstract Uncontrolled, excessive production of pro‐inflammatory mediators from immune cells and traumatized tissues can cause systemic inflammatory conditions such as sepsis, one of the ten leading causes of death in the USA, and one of the three leading causes of death in the intensive care unit. Understanding how inflammation affects physiological processes, including cardiovascular, thermal and pain dynamics, can improve a patient's chance of recovery after an inflammatory event caused by surgery or a severe infection. Although the effects of the autonomic response on the inflammatory system are well‐known, knowledge about the reverse interaction is lacking. The present study develops a mathematical model analyzing the inflammatory system's interactions with thermal, pain and cardiovascular dynamics in response to a bacterial endotoxin challenge. We calibrate the model with individual data from an experimental study of the inflammatory and physiological responses to a one‐time administration of endotoxin in 20 healthy young men and validate it against data from an independent endotoxin study. We use simulation to explore how various treatments help patients exposed to a sustained pathological input. The treatments explored include bacterial endotoxin adsorption, antipyretics and vasopressors, as well as combinations of these. Our findings suggest that the most favourable recovery outcome is achieved by a multimodal strategy, combining all three interventions to simultaneously remove endotoxin from the body and alleviate symptoms caused by the immune system as it fights the infection.}, number={5}, journal={JOURNAL OF PHYSIOLOGY-LONDON}, author={Dobreva, Atanaska and Brady-Nicholls, Renee and Larripa, Kamila and Puelz, Charles and Mehlsen, Jesper and Olufsen, Mette S.}, year={2021}, month={Mar}, pages={1459–1485} }
 @article{gilmore_hart_geddes_olsen_mehlsen_gremaud_olufsen_2021, title={Classification of orthostatic intolerance through data analytics}, volume={59}, ISSN={["1741-0444"]}, DOI={10.1007/s11517-021-02314-0}, abstractNote={Imbalance in the autonomic nervous system can lead to orthostatic intolerance manifested by dizziness, lightheadedness, and a sudden loss of consciousness (syncope); these are common conditions, but they are challenging to diagnose correctly. Uncertainties about the triggering mechanisms and the underlying pathophysiology have led to variations in their classification. This study uses machine learning to categorize patients with orthostatic intolerance. We use random forest classification trees to identify a small number of markers in blood pressure, and heart rate time-series data measured during head-up tilt to (a) distinguish patients with a single pathology and (b) examine data from patients with a mixed pathophysiology. Next, we use Kmeans to cluster the markers representing the time-series data. We apply the proposed method analyzing clinical data from 186 subjects identified as control or suffering from one of four conditions: postural orthostatic tachycardia (POTS), cardioinhibition, vasodepression, and mixed cardioinhibition and vasodepression. Classification results confirm the use of supervised machine learning. We were able to categorize more than 95% of patients with a single condition and were able to subgroup all patients with mixed cardioinhibitory and vasodepressor syncope. Clustering results confirm the disease groups and identify two distinct subgroups within the control and mixed groups. The proposed study demonstrates how to use machine learning to discover structure in blood pressure and heart rate time-series data. The methodology is used in classification of patients with orthostatic intolerance. Diagnosing orthostatic intolerance is challenging, and full characterization of the pathophysiological mechanisms remains a topic of ongoing research. This study provides a step toward leveraging machine learning to assist clinicians and researchers in addressing these challenges.}, number={3}, journal={MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING}, author={Gilmore, Steven and Hart, Joseph and Geddes, Justen and Olsen, Christian H. and Mehlsen, Jesper and Gremaud, Pierre and Olufsen, Mette S.}, year={2021}, month={Mar}, pages={621–632} }
 @article{randall_randolph_alexanderian_olufsen_2021, title={Global sensitivity analysis informed model reduction and selection applied to a Valsalva maneuver model}, volume={526}, ISSN={["1095-8541"]}, DOI={10.1016/j.jtbi.2021.110759}, abstractNote={In this study, we develop a methodology for model reduction and selection informed by global sensitivity analysis (GSA) methods. We apply these techniques to a control model that takes systolic blood pressure and thoracic tissue pressure data as inputs and predicts heart rate in response to the Valsalva maneuver (VM). The study compares four GSA methods based on Sobol' indices (SIs) quantifying the parameter influence on the difference between the model output and the heart rate data. The GSA methods include standard scalar SIs determining the average parameter influence over the time interval studied and three time-varying methods analyzing how parameter influence changes over time. The time-varying methods include a new technique, termed limited-memory SIs, predicting parameter influence using a moving window approach. Using the limited-memory SIs, we perform model reduction and selection to analyze the necessity of modeling both the aortic and carotid baroreceptor regions in response to the VM. We compare the original model to systematically reduced models including (i) the aortic and carotid regions, (ii) the aortic region only, and (iii) the carotid region only. Model selection is done quantitatively using the Akaike and Bayesian Information Criteria and qualitatively by comparing the neurological predictions. Results show that it is necessary to incorporate both the aortic and carotid regions to model the VM.}, journal={JOURNAL OF THEORETICAL BIOLOGY}, author={Randall, E. Benjamin and Randolph, Nicholas Z. and Alexanderian, Alen and Olufsen, Mette S.}, year={2021}, month={Oct} }
 @article{colebank_qureshi_olufsen_2021, title={Sensitivity analysis and uncertainty quantification of 1-D models of pulmonary hemodynamics in mice under control and hypertensive conditions}, volume={37}, ISSN={["2040-7947"]}, url={https://doi.org/10.1002/cnm.3242}, DOI={10.1002/cnm.3242}, abstractNote={Abstract Pulmonary hypertension (PH), defined as an elevated mean blood pressure in the main pulmonary artery (MPA) at rest, is associated with vascular remodeling of both large and small arteries. PH has several sub‐types that are all linked to high mortality rates. In this study, we use a one‐dimensional (1‐D) fluid dynamics model driven by in vivo measurements of MPA flow to understand how model parameters and network size influence MPA pressure predictions in the presence of PH. We compare model predictions with in vivo MPA pressure measurements from a control and a hypertensive mouse and analyze results in three networks of increasing complexity, extracted from micro‐computed tomography (micro‐CT) images. We introduce global scaling factors for boundary condition parameters and perform local and global sensitivity analysis to calculate parameter influence on model predictions of MPA pressure and correlation analysis to determine a subset of identifiable parameters. These are inferred using frequentist optimization and Bayesian inference via the Delayed Rejection Adaptive Metropolis (DRAM) algorithm. Frequentist and Bayesian uncertainty is computed for model parameters and MPA pressure predictions. Results show that MPA pressure predictions are most sensitive to distal vascular resistance and that parameter influence changes with increasing network complexity. Our outcomes suggest that PH leads to increased vascular stiffness and decreased peripheral compliance, congruent with clinical observations.}, number={11}, journal={INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING}, publisher={Wiley}, author={Colebank, Mitchel J. and Qureshi, M. Umar and Olufsen, Mette S.}, year={2021}, month={Nov} }
 @article{geddes_mehlsen_olufsen_2020, title={Characterization of Blood Pressure and Heart Rate Oscillations of POTS Patients via Uniform Phase Empirical Mode Decomposition}, volume={67}, ISSN={["1558-2531"]}, DOI={10.1109/TBME.2020.2974095}, abstractNote={Objective: Postural Orthostatic Tachycardia Syndrome (POTS) is associated with the onset of tachycardia upon postural change. The current diagnosis involves the measurement of heart rate (HR) and blood pressure (BP) during head-up tilt (HUT) or active standing test. A positive diagnosis is made if HR changes with more than 30 bpm (40 bpm in patients aged 12-19 years), ignoring all of the BP and most of the HR signals. This study examines 0.1 Hz oscillations in systolic arterial blood pressure (SBP) and HR signals providing additional metrics characterizing the dynamics of the baroreflex. Methods: We analyze data from 28 control subjects and 28 POTS patients who underwent HUT. We extract beat-to-beat HR and SBP during a 10 min interval including 5 minutes of baseline and 5 minutes of HUT. We employ Uniform Phase Empirical Mode Decomposition (UPEMD) to extract 0.1 Hz stationary modes from both signals and use random forest machine learning and k-means clustering to analyze the outcomes. Results show that the amplitude of the 0.1 Hz oscillations is higher in POTS patients and that the phase response between the two signals is shorter (p <; 0.005). Conclusion: POTS is associated with an increase in the amplitude of SBP and HR 0.1 Hz oscillation and shortening of the phase between the two signals. Significance: The 0.1 Hz phase response and oscillation amplitude metrics provide new markers that can improve POTS diagnostic augmenting the existing diagnosis protocol only analyzing the change in HR.}, number={11}, journal={IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING}, author={Geddes, Justen and Mehlsen, Jesper and Olufsen, Mette S.}, year={2020}, month={Nov}, pages={3016–3025} }
 @article{colunga_kim_woodall_dardas_gennari_olufsen_carlson_2020, title={Deep phenotyping of cardiac function in heart transplant patients using cardiovascular system models}, volume={598}, ISSN={["1469-7793"]}, DOI={10.1113/JP279393}, abstractNote={Key points Right heart catheterization data from clinical records of heart transplant patients are used to identify patient‐specific models of the cardiovascular system. These patient‐specific cardiovascular models represent a snapshot of cardiovascular function at a given post‐transplant recovery time point. This approach is used to describe cardiac function in 10 heart transplant patients, five of which had multiple right heart catheterizations allowing an assessment of cardiac function over time. These patient‐specific models are used to predict cardiovascular function in the form of right and left ventricular pressure‐volume loops and ventricular power, an important metric in the clinical assessment of cardiac function. Outcomes for the longitudinally tracked patients show that our approach was able to identify the one patient from the group of five that exhibited post‐transplant cardiovascular complications. Abstract Heart transplant patients are followed with periodic right heart catheterizations (RHCs) to identify post‐transplant complications and guide treatment. Post‐transplant positive outcomes are associated with a steady reduction of right ventricular and pulmonary arterial pressures, toward normal levels of right‐side pressure (about 20 mmHg) measured by RHC. This study shows that more information about patient progression is obtained by combining standard RHC measures with mechanistic computational cardiovascular system models. The purpose of this study is twofold: to understand how cardiovascular system models can be used to represent a patient's cardiovascular state, and to use these models to track post‐transplant recovery and outcome. To obtain reliable parameter estimates comparable within and across datasets, we use sensitivity analysis, parameter subset selection, and optimization to determine patient‐specific mechanistic parameters that can be reliably extracted from the RHC data. Patient‐specific models are identified for 10 patients from their first post‐transplant RHC, and longitudinal analysis is carried out for five patients. Results of the sensitivity analysis and subset selection show that we can reliably estimate seven non‐measurable quantities; namely, ventricular diastolic relaxation, systemic resistance, pulmonary venous elastance, pulmonary resistance, pulmonary arterial elastance, pulmonary valve resistance and systemic arterial elastance. Changes in parameters and predicted cardiovascular function post‐transplant are used to evaluate the cardiovascular state during recovery of five patients. Of these five patients, only one showed inconsistent trends during recovery in ventricular pressure–volume relationships and power output. At the four‐year post‐transplant time point this patient exhibited biventricular failure along with graft dysfunction while the remaining four exhibited no cardiovascular complications.}, number={15}, journal={JOURNAL OF PHYSIOLOGY-LONDON}, author={Colunga, Amanda L. and Kim, Karam G. and Woodall, N. Payton and Dardas, Todd F. and Gennari, John H. and Olufsen, Mette S. and Carlson, Brian E.}, year={2020}, month={Aug}, pages={3203–3222} }
 @article{wright_fayad_selgrade_olufsen_2020, title={Mechanistic model of hormonal contraception}, volume={16}, ISSN={["1553-7358"]}, DOI={10.1371/journal.pcbi.1007848}, abstractNote={Contraceptive drugs intended for family planning are used by the majority of married or in-union women in almost all regions of the world. The two most prevalent types of hormones associated with contraception are synthetic estrogens and progestins. Hormonal based contraceptives contain a dose of a synthetic progesterone (progestin) or a combination of a progestin and a synthetic estrogen. In this study we use mathematical modeling to understand better how these contraceptive paradigms prevent ovulation, special focus is on understanding how changes in dose impact hormonal cycling. To explain this phenomenon, we added two autocrine mechanisms essential to achieve contraception within our previous menstrual cycle models. This new model predicts mean daily blood concentrations of key hormones during a contraceptive state achieved by administering progestins, synthetic estrogens, or a combined treatment. Model outputs are compared with data from two clinical trials: one for a progestin only treatment and one for a combined hormonal treatment. Results show that contraception can be achieved with synthetic estrogen, with progestin, and by combining the two hormones. An advantage of the combined treatment is that a contraceptive state can be obtained at a lower dose of each hormone. The model studied here is qualitative in nature, but can be coupled with a pharmacokinetic/pharamacodynamic (PKPD) model providing the ability to fit exogenous inputs to specific bioavailability and affinity. A model of this type may allow insight into a specific drug’s effects, which has potential to be useful in the pre-clinical trial stage identifying the lowest dose required to achieve contraception.}, number={6}, journal={PLOS COMPUTATIONAL BIOLOGY}, author={Wright, A. Armean and Fayad, Ghassan N. and Selgrade, James F. and Olufsen, Mette S.}, year={2020}, month={Jun} }
 @article{randall_randolph_olufsen_2020, title={Persistent instability in a nonhomogeneous delay differential equation system of the Valsalva maneuver}, volume={319}, ISSN={["1879-3134"]}, DOI={10.1016/j.mbs.2019.108292}, abstractNote={Delay differential equations are widely used in mathematical modeling to describe physical and biological systems, often inducing oscillatory behavior. In physiological systems, this instability may signify (i) an attempt to return to homeostasis or (ii) system dysfunction. In this study, we analyze a nonlinear, nonautonomous, nonhomogeneous open-loop neurological control model describing the autonomic nervous system response to the Valsalva maneuver (VM). We reduce this model from 5 to 2 states (predicting sympathetic tone and heart rate) and categorize the stability properties of the reduced model using a two-parameter bifurcation analysis of the sympathetic delay (Ds) and time-scale (τs). Stability regions in the Ds τs-plane for this nonhomogeneous system and its homogeneous analog are classified numerically and analytically, identifying transcritical and Hopf bifurcations. Results show that the Hopf bifurcation remains for both the homogeneous and nonhomogeneous systems, while the nonhomogeneous system stabilizes the transition at the transcritical bifurcation. This analysis was compared with results from blood pressure and heart rate data from three subjects performing the VM: a control subject exhibiting sink behavior, a control subject exhibiting stable focus behavior, and a patient with postural orthostatic tachycardia syndrome (POTS) also exhibiting stable focus behavior. Results suggest that instability caused from overactive sympathetic signaling may result in autonomic dysfunction.}, journal={MATHEMATICAL BIOSCIENCES}, author={Randall, E. Benjamin and Randolph, Nicholas Z. and Olufsen, Mette S.}, year={2020}, month={Jan} }
 @article{chambers_colebank_qureshi_clipp_olufsen_2020, title={Structural and hemodynamic properties of murine pulmonary arterial networks under hypoxia-induced pulmonary hypertension}, volume={234}, ISSN={["2041-3033"]}, url={https://doi.org/10.1177/0954411920944110}, DOI={10.1177/0954411920944110}, abstractNote={Detection and monitoring of patients with pulmonary hypertension, defined as a mean blood pressure in the main pulmonary artery above 25 mmHg, requires a combination of imaging and hemodynamic measurements. This study demonstrates how to combine imaging data from microcomputed tomography images with hemodynamic pressure and flow waveforms from control and hypertensive mice. Specific attention is devoted to developing a tool that processes computed tomography images, generating subject-specific arterial networks in which one-dimensional fluid dynamics modeling is used to predict blood pressure and flow. Each arterial network is modeled as a directed graph representing vessels along the principal pathway to ensure perfusion of all lobes. The one-dimensional model couples these networks with structured tree boundary conditions representing the small arteries and arterioles. Fluid dynamics equations are solved in this network and compared to measurements of pressure in the main pulmonary artery. Analysis of microcomputed tomography images reveals that the branching ratio is the same in the control and hypertensive animals, but that the vessel length-to-radius ratio is significantly lower in the hypertensive animals. Fluid dynamics predictions show that in addition to changed network geometry, vessel stiffness is higher in the hypertensive animal models than in the control models.}, number={11}, journal={PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE}, publisher={SAGE Publications}, author={Chambers, Megan J. and Colebank, Mitchel J. and Qureshi, M. Umar and Clipp, Rachel and Olufsen, Mette S.}, year={2020}, month={Nov}, pages={1312–1329} }
 @article{randall_billeschou_brinth_mehlsen_olufsen_2019, title={A model-based analysis of autonomic nervous function in response to the Valsalva maneuver}, volume={127}, ISSN={["1522-1601"]}, DOI={10.1152/japplphysiol.00015.2019}, abstractNote={The Valsalva maneuver (VM) is a diagnostic protocol examining sympathetic and parasympathetic activity in patients with autonomic dysfunction (AD) impacting cardiovascular control. Because direct measurement of these signals is costly and invasive, AD is typically assessed indirectly by analyzing heart rate and blood pressure response patterns. This study introduces a mathematical model that can predict sympathetic and parasympathetic dynamics. Our model-based analysis includes two control mechanisms: respiratory sinus arrhythmia (RSA) and the baroreceptor reflex (baroreflex). The RSA submodel integrates an electrocardiogram-derived respiratory signal with intrathoracic pressure, and the baroreflex submodel differentiates aortic and carotid baroreceptor regions. Patient-specific afferent and efferent signals are determined for 34 control subjects and 5 AD patients, estimating parameters fitting the model output to heart rate data. Results show that inclusion of RSA and distinguishing aortic/carotid regions are necessary to model the heart rate response to the VM. Comparing control subjects to patients shows that RSA and baroreflex responses are significantly diminished. This study compares estimated parameter values from the model-based predictions to indices used in clinical practice. Three indices are computed to determine adrenergic function from the slope of the systolic blood pressure in phase II [ α (a new index)], the baroreceptor sensitivity ( β), and the Valsalva ratio ( γ). Results show that these indices can distinguish between normal and abnormal states, but model-based analysis is needed to differentiate pathological signals. In summary, the model simulates various VM responses and, by combining indices and model predictions, we study the pathologies for 5 AD patients. NEW & NOTEWORTHY We introduce a patient-specific model analyzing heart rate and blood pressure during a Valsalva maneuver (VM). The model predicts autonomic function incorporating the baroreflex and respiratory sinus arrhythmia (RSA) control mechanisms. We introduce a novel index ( α) characterizing sympathetic activity, which can distinguish control and abnormal patients. However, we assert that modeling and parameter estimation are necessary to explain pathologies. Finally, we show that aortic baroreceptors contribute significantly to the VM and RSA affects early VM.}, number={5}, journal={JOURNAL OF APPLIED PHYSIOLOGY}, author={Randall, E. Benjamin and Billeschou, Anna and Brinth, Louise S. and Mehlsen, Jesper and Olufsen, Mette S.}, year={2019}, month={Nov}, pages={1386–1402} }
 @article{williams_mehlsen_tran_olufsen_2019, title={An optimal control approach for blood pressure regulation during head-up tilt}, volume={113}, ISSN={["1432-0770"]}, DOI={10.1007/s00422-018-0783-9}, abstractNote={This paper presents an optimal control approach to modeling effects of cardiovascular regulation during head-up tilt (HUT). Many patients who suffer from dizziness or light-headedness are administered a head-up tilt test to explore potential deficits within the autonomic control system, which maintains the cardiovascular system at homeostasis. This system is complex and difficult to study in vivo, and thus we propose to use mathematical modeling to achieve a better understanding of cardiovascular regulation during HUT. In particular, we show the feasibility of using optimal control theory to compute physiological control variables, vascular resistance and cardiac contractility, quantities that cannot be measured directly, but which are useful to assess the state of the cardiovascular system. A non-pulsatile lumped parameter model together with pseudo- and clinical data are utilized in the optimal control problem formulation. Results show that the optimal control approach can predict time-varying quantities regulated by the cardiovascular control system. Our results compare favorable to our previous study using a piecewise linear spline approach, less a priori knowledge is needed, and results were obtained at a significantly lower computational cost.}, number={1-2}, journal={BIOLOGICAL CYBERNETICS}, author={Williams, Nakeya D. and Mehlsen, Jesper and Tran, Hien T. and Olufsen, Mette S.}, year={2019}, month={Apr}, pages={149–159} }
 @article{williams_brady_gilmore_gremaud_tran_ottesen_mehlsen_olufsen_2019, title={Cardiovascular dynamics during head-up tilt assessed via pulsatile and non-pulsatile models}, volume={79}, ISSN={0303-6812 1432-1416}, url={http://dx.doi.org/10.1007/s00285-019-01386-9}, DOI={10.1007/s00285-019-01386-9}, abstractNote={This study develops non-pulsatile and pulsatile models for the prediction of blood flow and pressure during head-up tilt. This test is used to diagnose potential pathologies within the autonomic control system, which acts to keep the cardiovascular system at homeostasis. We show that mathematical modeling can be used to predict changes in cardiac contractility, vascular resistance, and arterial compliance, quantities that cannot be measured but are useful to assess the system's state. These quantities are predicted as time-varying parameters modeled using piecewise linear splines. Having models with various levels of complexity formulated with a common set of parameters, allows us to combine long-term non-pulsatile simulations with pulsatile simulations on a shorter time-scale. We illustrate results for a representative subject tilted head-up from a supine position to a [Formula: see text] angle. The tilt is maintained for 5 min before the subject is tilted back down. Results show that if volume data is available for all vascular compartments three parameters can be identified, cardiovascular resistance, vascular compliance, and ventricular contractility, whereas if model predictions are made against arterial pressure and cardiac output data alone, only two parameters can be estimated either resistance and contractility or resistance and compliance.}, number={3}, journal={Journal of Mathematical Biology}, publisher={Springer Science and Business Media LLC}, author={Williams, Nakeya D. and Brady, Renee and Gilmore, Steven and Gremaud, Pierre and Tran, Hien T. and Ottesen, Johnny T. and Mehlsen, Jesper and Olufsen, Mette S.}, year={2019}, month={May}, pages={987–1014} }
 @article{ciocanel_docken_gasper_dean_carlson_olufsen_2019, title={Cardiovascular regulation in response to multiple hemorrhages: analysis and parameter estimation}, volume={113}, ISSN={["1432-0770"]}, DOI={10.1007/s00422-018-0781-y}, abstractNote={Mathematical models can provide useful insights explaining behavior observed in experimental data; however, rigorous analysis is needed to select a subset of model parameters that can be informed by available data. Here we present a method to estimate an identifiable set of parameters based on baseline left ventricular pressure and volume time series data. From this identifiable subset, we then select, based on current understanding of cardiovascular control, parameters that vary in time in response to blood withdrawal, and estimate these parameters over a series of blood withdrawals. These time-varying parameters are first estimated using piecewise linear splines minimizing the mean squared error between measured and computed left ventricular pressure and volume data over four consecutive blood withdrawals. As a final step, the trends in these splines are fit with empirical functional expressions selected to describe cardiovascular regulation during blood withdrawal. Our analysis at baseline found parameters representing timing of cardiac contraction, systemic vascular resistance, and cardiac contractility to be identifiable. Of these parameters, vascular resistance and cardiac contractility were varied in time. Data used for this study were measured in a control Sprague-Dawley rat. To our knowledge, this is the first study to analyze the response to multiple blood withdrawals both experimentally and theoretically, as most previous studies focus on analyzing the response to one large blood withdrawal. Results show that during each blood withdrawal both systemic vascular resistance and contractility decrease acutely and partially recover, and they decrease chronically across the series of blood withdrawals.}, number={1-2}, journal={BIOLOGICAL CYBERNETICS}, author={Ciocanel, Maria-Veronica and Docken, Steffen S. and Gasper, Rebecca E. and Dean, Caron and Carlson, Brian E. and Olufsen, Mette S.}, year={2019}, month={Apr}, pages={105–120} }
 @article{thomas_olufsen_sepulchre_iglesias_ijspeert_srinivasan_2019, title={Control theory in biology and medicine: Introduction to the special issue}, volume={113}, ISSN={["1432-0770"]}, DOI={10.1007/s00422-018-00791-5}, abstractNote={From September-December 2017, the Mathematical Biosciences Institute at Ohio State University hosted a series of workshops on control theory in biology and medicine, including workshops on control and modulation of neuronal and motor systems, control of cellular and molecular systems, control of disease / personalized medicine across heterogeneous populations, and sensorimotor control of animals and robots. This special issue presents tutorials and research articles by several of the participants in the MBI workshops.}, number={1-2}, journal={BIOLOGICAL CYBERNETICS}, author={Thomas, Peter J. and Olufsen, Mette and Sepulchre, Rodolphe and Iglesias, Pablo A. and Ijspeert, Auke and Srinivasan, Manoj}, year={2019}, month={Apr}, pages={1–6} }
 @article{colebank_paun_qureshi_chesler_husmeier_olufsen_fix_2019, title={Influence of image segmentation on one-dimensional fluid dynamics predictions in the mouse pulmonary arteries}, volume={16}, ISSN={["1742-5662"]}, url={https://doi.org/10.1098/rsif.2019.0284}, DOI={10.1098/rsif.2019.0284}, abstractNote={Computational fluid dynamics (CFD) models are emerging tools for assisting in diagnostic assessment of cardiovascular disease. Recent advances in image segmentation have made subject-specific modelling of the cardiovascular system a feasible task, which is particularly important in the case of pulmonary hypertension, requiring a combination of invasive and non-invasive procedures for diagnosis. Uncertainty in image segmentation propagates to CFD model predictions, making the quantification of segmentation-induced uncertainty crucial for subject-specific models. This study quantifies the variability of one-dimensional CFD predictions by propagating the uncertainty of network geometry and connectivity to blood pressure and flow predictions. We analyse multiple segmentations of a single, excised mouse lung using different pre-segmentation parameters. A custom algorithm extracts vessel length, vessel radii and network connectivity for each segmented pulmonary network. Probability density functions are computed for vessel radius and length and then sampled to propagate uncertainties to haemodynamic predictions in a fixed network. In addition, we compute the uncertainty of model predictions to changes in network size and connectivity. Results show that variation in network connectivity is a larger contributor to haemodynamic uncertainty than vessel radius and length.}, number={159}, journal={JOURNAL OF THE ROYAL SOCIETY INTERFACE}, publisher={The Royal Society}, author={Colebank, Mitchel J. and Paun, L. Mihaela and Qureshi, M. Umar and Chesler, Naomi and Husmeier, Dirk and Olufsen, Mette S. and Fix, Laura Ellwein}, year={2019}, month={Oct} }
 @article{olsen_ottesen_smith_olufsen_2019, title={Parameter subset selection techniques for problems in mathematical biology}, volume={113}, ISSN={["1432-0770"]}, DOI={10.1007/s00422-018-0784-8}, abstractNote={Patient-specific models for diagnostics and treatment planning require reliable parameter estimation and model predictions. Mathematical models of physiological systems are often formulated as systems of nonlinear ordinary differential equations with many parameters and few options for measuring all state variables. Consequently, it can be difficult to determine which parameters can reliably be estimated from available data. This investigation highlights pitfalls associated with practical parameter identifiability and subset selection. The latter refer to the process associated with selecting a subset of parameters that can be identified uniquely by parameter estimation protocols. The methods will be demonstrated using five examples of increasing complexity, as well as with patient-specific model predicting arterial blood pressure. This study demonstrates that methods based on local sensitivities are preferable in terms of computational cost and model fit when good initial parameter values are available, but that global methods should be considered when initial parameter value is not known or poorly understood. For global sensitivity analysis, Morris screening provides results in terms of parameter sensitivity ranking at a much lower computational cost.}, number={1-2}, journal={BIOLOGICAL CYBERNETICS}, author={Olsen, Christian Haargaard and Ottesen, Johnny T. and Smith, Ralph C. and Olufsen, Mette S.}, year={2019}, month={Apr}, pages={121–138} }
 @article{qureshi_colebank_schreier_tabima_haider_chesler_olufsen_2018, title={Characteristic impedance: frequency or time domain approach?}, volume={39}, ISSN={1361-6579}, url={http://dx.doi.org/10.1088/1361-6579/aa9d60}, DOI={10.1088/1361-6579/aa9d60}, abstractNote={Characteristic impedance (Zc) is an important component in the theory of hemodynamics. It is a commonly used metric of proximal arterial stiffness and pulse wave velocity. Calculated using simultaneously measured dynamic pressure and flow data, estimates of characteristic impedance can be obtained using methods based on frequency or time domain analysis. Applications of these methods under different physiological and pathological conditions in species with different body sizes and heart rates show that the two approaches do not always agree. In this study, we have investigated the discrepancies between frequency and time domain estimates accounting for uncertainties associated with experimental processes and physiological conditions.We have used published data measured in different species including humans, dogs, and mice to investigate: (a) the effects of time delay and signal noise in the pressure-flow data, (b) uncertainties about the blood flow conditions, (c) periodicity of the cardiac cycle versus the breathing cycle, on the frequency and time domain estimates of Zc, and (d) if discrepancies observed under different hemodynamic conditions can be eliminated. Main results and Significance: We have shown that the frequency and time domain estimates are not equally sensitive to certain characteristics of hemodynamic signals including phase lag between pressure and flow, signal to noise ratio and the end of systole retrograde flow. The discrepancies between two types of estimates are inherent due to their intrinsically different mathematical expressions and therefore it is impossible to define a criterion to resolve such discrepancies. Considering the interpretation and role of Zc as an important hemodynamic parameter, we suggest that the frequency and time domain estimates should be further assessed as two different hemodynamic parameters in a future study.}, number={1}, journal={Physiological Measurement}, publisher={IOP Publishing}, author={Qureshi, M Umar and Colebank, Mitchel J and Schreier, David A and Tabima, Diana M and Haider, Mansoor A and Chesler, Naomi C and Olufsen, Mette S}, year={2018}, month={Jan}, pages={014004} }
 @article{qureshi_colebank_paun_ellwein fix_chesler_haider_hill_husmeier_olufsen_2018, title={Hemodynamic assessment of pulmonary hypertension in mice: a model-based analysis of the disease mechanism}, volume={18}, ISSN={1617-7959 1617-7940}, url={http://dx.doi.org/10.1007/s10237-018-1078-8}, DOI={10.1007/s10237-018-1078-8}, abstractNote={This study uses a one-dimensional fluid dynamics arterial network model to infer changes in hemodynamic quantities associated with pulmonary hypertension in mice. Data for this study include blood flow and pressure measurements from the main pulmonary artery for 7 control mice with normal pulmonary function and 5 mice with hypoxia-induced pulmonary hypertension. Arterial dimensions for a 21-vessel network are extracted from micro-CT images of lungs from a representative control and hypertensive mouse. Each vessel is represented by its length and radius. Fluid dynamic computations are done assuming that the flow is Newtonian, viscous, laminar, and has no swirl. The system of equations is closed by a constitutive equation relating pressure and area, using a linear model derived from stress–strain deformation in the circumferential direction assuming that the arterial walls are thin, and also an empirical nonlinear model. For each dataset, an inflow waveform is extracted from the data, and nominal parameters specifying the outflow boundary conditions are computed from mean values and characteristic timescales extracted from the data. The model is calibrated for each mouse by estimating parameters that minimize the least squares error between measured and computed waveforms. Optimized parameters are compared across the control and the hypertensive groups to characterize vascular remodeling with disease. Results show that pulmonary hypertension is associated with stiffer and less compliant proximal and distal vasculature with augmented wave reflections, and that elastic nonlinearities are insignificant in the hypertensive animal.}, number={1}, journal={Biomechanics and Modeling in Mechanobiology}, publisher={Springer Nature}, author={Qureshi, M. Umar and Colebank, Mitchel J. and Paun, L. Mihaela and Ellwein Fix, Laura and Chesler, Naomi and Haider, Mansoor A. and Hill, Nicholas A. and Husmeier, Dirk and Olufsen, Mette S.}, year={2018}, month={Oct}, pages={219–243} }
 @article{păun_qureshi_colebank_hill_olufsen_haider_husmeier_2018, title={MCMC methods for inference in a mathematical model of pulmonary circulation}, volume={72}, ISSN={0039-0402}, url={http://dx.doi.org/10.1111/stan.12132}, DOI={10.1111/stan.12132}, abstractNote={This study performs parameter inference in a partial differential equations system of pulmonary circulation. We use a fluid dynamics network model that takes selected parameter values and mimics the behaviour of the pulmonary haemodynamics under normal physiological and pathological conditions. This is of medical interest as it enables tracking the progression of pulmonary hypertension. We show how we make the fluids model tractable by reducing the parameter dimension from a 55D to a 5D problem. The Delayed Rejection Adaptive Metropolis algorithm, coupled with constraint non-linear optimization, is successfully used to learn the parameter values and quantify the uncertainty in the parameter estimates. To accommodate for different magnitudes of the parameter values, we introduce an improved parameter scaling technique in the Delayed Rejection Adaptive Metropolis algorithm. Formal convergence diagnostics are employed to check for convergence of the Markov chains. Additionally, we perform model selection using different information criteria, including Watanabe Akaike Information Criteria.}, number={3}, journal={Statistica Neerlandica}, publisher={Wiley}, author={Păun, L. Mihaela and Qureshi, M. Umar and Colebank, Mitchel and Hill, Nicholas A. and Olufsen, Mette S. and Haider, Mansoor A. and Husmeier, Dirk}, year={2018}, month={Apr}, pages={306–338} }
 @article{brady_frank-ito_tran_janum_møller_brix_ottesen_mehlsen_olufsen_2018, title={Personalized mathematical model of endotoxin-induced inflammatory responses in young men and associated changes in heart rate variability}, volume={13}, ISSN={0973-5348 1760-6101}, url={http://dx.doi.org/10.1051/mmnp/2018031}, DOI={10.1051/mmnp/2018031}, abstractNote={The objective of this study was to develop a personalized inflammatory model and estimate subject-specific parameters that could be related to changes in heart rate variability (HRV), a measure that can be obtained non-invasively in real time. An inflammatory model was developed and calibrated to measurements of interleukin-6 (IL-6), tumor necrosis factor (TNF-alpha), interleukin-8 (IL-8) and interleukin-10 (IL-10) over 8 hours in 20 subjects administered a low dose of lipopolysaccharide. For this model, we estimated 11 subject-specific parameters for all 20 subjects. Estimated parameters were correlated with changes in HRV, computed from ECG measurements using a built-in HRV module available in Labchart. Results revealed that patients could be separated into two groups expressing normal and abnormal responses to endotoxin. Abnormal responders exhibited increased HRV, most likely as a result of increased vagal firing. The observed correlation between the inflammatory response and HRV brings us a step further towards understanding if HRV predictions can be used as a marker for inflammation. Analyzing HRV parameters provides an easy, non-invasively obtained measure that can be used to assess the state of the subject, potentially translating to identifying a non-invasive marker that can be used to detect the onset of sepsis.}, number={5}, journal={Mathematical Modelling of Natural Phenomena}, publisher={EDP Sciences}, author={Brady, R. and Frank-Ito, D.O. and Tran, H.T. and Janum, S. and Møller, K. and Brix, S. and Ottesen, J.T. and Mehlsen, J. and Olufsen, M.S.}, editor={Maruta, K. and Minaev, S. and Il Kim, N. and Im, H. and Gubernov, V.Editors}, year={2018}, pages={42} }
 @article{marquis_arnold_dean-bernhoft_carlson_olufsen_2018, title={Practical identifiability and uncertainty quantification of a pulsatile cardiovascular model}, volume={304}, ISSN={["1879-3134"]}, DOI={10.1016/j.mbs.2018.07.001}, abstractNote={Mathematical models are essential tools to study how the cardiovascular system maintains homeostasis. The utility of such models is limited by the accuracy of their predictions, which can be determined by uncertainty quantification (UQ). A challenge associated with the use of UQ is that many published methods assume that the underlying model is identifiable (e.g. that a one-to-one mapping exists from the parameter space to the model output). In this study we present a novel workflow to calibrate a lumped-parameter model to left ventricular pressure and volume time series data. Key steps include using (1) literature and available data to determine nominal parameter values; (2) sensitivity analysis and subset selection to determine a set of identifiable parameters; (3) optimization to find a point estimate for identifiable parameters; and (4) frequentist and Bayesian UQ calculations to assess the predictive capability of the model. Our results show that it is possible to determine 5 identifiable model parameters that can be estimated to our experimental data from three rats, and that computed UQ intervals capture the measurement and model error.}, journal={MATHEMATICAL BIOSCIENCES}, author={Marquis, Andrew D. and Arnold, Andrea and Dean-Bernhoft, Caron and Carlson, Brian E. and Olufsen, Mette S.}, year={2018}, month={Oct}, pages={9–24} }
 @article{mandi_nikolic_birch_olufsen_panerai_simpson_payne_2017, title={Increased blood pressure variability upon standing up improves reproducibility of cerebral autoregulation indices}, volume={47}, ISSN={["1873-4030"]}, DOI={10.1016/j.medengphy.2017.06.006}, abstractNote={Dynamic cerebral autoregulation, that is the transient response of cerebral blood flow to changes in arterial blood pressure, is currently assessed using a variety of different time series methods and data collection protocols. In the continuing absence of a gold standard for the study of cerebral autoregulation it is unclear to what extent does the assessment depend on the choice of a computational method and protocol. We use continuous measurements of blood pressure and cerebral blood flow velocity in the middle cerebral artery from the cohorts of 18 normotensive subjects performing sit-to-stand manoeuvre. We estimate cerebral autoregulation using a wide variety of black-box approaches (including the following six autoregulation indices ARI, Mx, Sx, Dx, FIR and ARX) and compare them in the context of reproducibility and variability. For all autoregulation indices, considered here, the intra-class correlation was greater during the standing protocol, however, it was significantly greater (Fisher's Z-test) for Mx (p < 0.03), Sx (p < 0.003) and Dx (p < 0.03). In the specific case of the sit-to-stand manoeuvre, measurements taken immediately after standing up greatly improve the reproducibility of the autoregulation coefficients. This is generally coupled with an increase of the within-group spread of the estimates.}, journal={MEDICAL ENGINEERING & PHYSICS}, author={Mandi, Adam and Nikolic, Dragana and Birch, Anthony A. and Olufsen, Mette S. and Panerai, Ronney B. and Simpson, David M. and Payne, Stephen J.}, year={2017}, month={Sep}, pages={151–158} }
 @article{bangsgaard_hjorth_olufsen_mehlsen_ottesen_2017, title={Integrated Inflammatory Stress (ITIS) Model}, volume={79}, ISSN={["1522-9602"]}, DOI={10.1007/s11538-017-0293-2}, abstractNote={During the last decade, there has been an increasing interest in the coupling between the acute inflammatory response and the Hypothalamic-Pituitary-Adrenal (HPA) axis. The inflammatory response is activated acutely by pathogen- or damage-related molecular patterns, whereas the HPA axis maintains a long-term level of the stress hormone cortisol which is also anti-inflammatory. A new integrated model of the interaction between these two subsystems of the inflammatory system is proposed and coined the integrated inflammatory stress (ITIS) model. The coupling mechanisms describing the interactions between the subsystems in the ITIS model are formulated based on biological reasoning and its ability to describe clinical data. The ITIS model is calibrated and validated by simulating various scenarios related to endotoxin (LPS) exposure. The model is capable of reproducing human data of tumor necrosis factor alpha, adrenocorticotropic hormone (ACTH) and cortisol and suggests that repeated LPS injections lead to a deficient response. The ITIS model predicts that the most extensive response to an LPS injection in ACTH and cortisol concentrations is observed in the early hours of the day. A constant activation results in elevated levels of the variables in the model while a prolonged change of the oscillations in ACTH and cortisol concentrations is the most pronounced result of different LPS doses predicted by the model.}, number={7}, journal={BULLETIN OF MATHEMATICAL BIOLOGY}, author={Bangsgaard, Elisabeth O. and Hjorth, Poul G. and Olufsen, Mette S. and Mehlsen, Jesper and Ottesen, Johnny T.}, year={2017}, month={Jul}, pages={1487–1509} }
 @article{sturdy_ottesen_olufsen_2017, title={Modeling the differentiation of A- and C-type baroreceptor firing patterns}, volume={42}, ISSN={["1573-6873"]}, DOI={10.1007/s10827-016-0624-6}, abstractNote={The baroreceptor neurons serve as the primary transducers of blood pressure for the autonomic nervous system and are thus critical in enabling the body to respond effectively to changes in blood pressure. These neurons can be separated into two types (A and C) based on the myelination of their axons and their distinct firing patterns elicited in response to specific pressure stimuli. This study has developed a comprehensive model of the afferent baroreceptor discharge built on physiological knowledge of arterial wall mechanics, firing rate responses to controlled pressure stimuli, and ion channel dynamics within the baroreceptor neurons. With this model, we were able to predict firing rates observed in previously published experiments in both A- and C-type neurons. These results were obtained by adjusting model parameters determining the maximal ion-channel conductances. The observed variation in the model parameters are hypothesized to correspond to physiological differences between A- and C-type neurons. In agreement with published experimental observations, our simulations suggest that a twofold lower potassium conductance in C-type neurons is responsible for the observed sustained basal firing, where as a tenfold higher mechanosensitive conductance is responsible for the greater firing rate observed in A-type neurons. A better understanding of the difference between the two neuron types can potentially be used to gain more insight about pathophysiology and treatment of diseases related to baroreflex function, e.g. in patients with autonomic failure, a syndrome that is difficult to diagnose in terms of its pathophysiology.}, number={1}, journal={JOURNAL OF COMPUTATIONAL NEUROSCIENCE}, author={Sturdy, Jacob and Ottesen, Johnny T. and Olufsen, Mette S.}, year={2017}, month={Feb}, pages={11–30} }
 @article{arnold_battista_bia_german_armentano_tran_olufsen_2017, title={Uncertainty Quantification in a Patient-Specific One-Dimensional Arterial Network Model: EnKF-Based Inflow Estimator}, volume={2}, ISSN={2377-2158}, url={http://dx.doi.org/10.1115/1.4035918}, DOI={10.1115/1.4035918}, abstractNote={Successful clinical use of patient-specific models for cardiovascular dynamics depends on the reliability of the model output in the presence of input uncertainties. For 1D fluid dynamics models of arterial networks, input uncertainties associated with the model output are related to the specification of vessel and network geometry, parameters within the fluid and wall equations, and parameters used to specify inlet and outlet boundary conditions. This study investigates how uncertainty in the flow profile applied at the inlet boundary of a 1D model affects area and pressure predictions at the center of a single vessel. More specifically, this study develops an iterative scheme based on the ensemble Kalman filter (EnKF) to estimate the temporal inflow profile from a prior distribution of curves. The EnKF-based inflow estimator provides a measure of uncertainty in the size and shape of the estimated inflow, which is propagated through the model to determine the corresponding uncertainty in model predictions of area and pressure. Model predictions are compared to ex vivo area and blood pressure measurements in the ascending aorta, the carotid artery, and the femoral artery of a healthy male Merino sheep. Results discuss dynamics obtained using a linear and a nonlinear viscoelastic wall model.}, number={1}, journal={Journal of Verification, Validation and Uncertainty Quantification}, publisher={ASME International}, author={Arnold, Andrea and Battista, Christina and Bia, Daniel and German, Yanina Zócalo and Armentano, Ricardo L. and Tran, Hien and Olufsen, Mette S.}, year={2017}, month={Feb}, pages={011002} }
 @article{lee_carlson_chesler_olufsen_qureshi_smith_sochi_beard_2016, title={Heterogeneous mechanics of the mouse pulmonary arterial network}, volume={15}, ISSN={["1617-7940"]}, DOI={10.1007/s10237-015-0757-y}, abstractNote={Individualized modeling and simulation of blood flow mechanics find applications in both animal research and patient care. Individual animal or patient models for blood vessel mechanics are based on combining measured vascular geometry with a fluid structure model coupling formulations describing dynamics of the fluid and mechanics of the wall. For example, one-dimensional fluid flow modeling requires a constitutive law relating vessel cross-sectional deformation to pressure in the lumen. To investigate means of identifying appropriate constitutive relationships, an automated segmentation algorithm was applied to micro-computerized tomography images from a mouse lung obtained at four different static pressures to identify the static pressure-radius relationship for four generations of vessels in the pulmonary arterial network. A shape-fitting function was parameterized for each vessel in the network to characterize the nonlinear and heterogeneous nature of vessel distensibility in the pulmonary arteries. These data on morphometric and mechanical properties were used to simulate pressure and flow velocity propagation in the network using one-dimensional representations of fluid and vessel wall mechanics. Moreover, wave intensity analysis was used to study effects of wall mechanics on generation and propagation of pressure wave reflections. Simulations were conducted to investigate the role of linear versus nonlinear formulations of wall elasticity and homogeneous versus heterogeneous treatments of vessel wall properties. Accounting for heterogeneity, by parameterizing the pressure/distention equation of state individually for each vessel segment, was found to have little effect on the predicted pressure profiles and wave propagation compared to a homogeneous parameterization based on average behavior. However, substantially different results were obtained using a linear elastic thin-shell model than were obtained using a nonlinear model that has a more physiologically realistic pressure versus radius relationship.}, number={5}, journal={BIOMECHANICS AND MODELING IN MECHANOBIOLOGY}, author={Lee, Pilhwa and Carlson, Brian E. and Chesler, Naomi and Olufsen, Mette S. and Qureshi, M. Umar and Smith, Nicolas P. and Sochi, Taha and Beard, Daniel A.}, year={2016}, month={Oct}, pages={1245–1261} }
 @article{battista_bia_germán_armentano_haider_olufsen_2016, title={Wave propagation in a 1D fluid dynamics model using pressure-area measurements from ovine arteries}, volume={16}, ISSN={0219-5194 1793-6810}, url={http://dx.doi.org/10.1142/s021951941650007x}, DOI={10.1142/s021951941650007x}, abstractNote={This study considers a 1D fluid dynamics arterial network model with 14 vessels developed to assimilate ex vivo 0D temporal data for pressure-area dynamics in individual vessel segments from 11 male Merino sheep. A 0D model was used to estimate vessel wall parameters in a two-parameter elastic model and a four-parameter Kelvin viscoelastic model. This was done using nonlinear optimization minimizing the least squares error between model predictions and measured cross-sectional areas. Subsequently, estimated values for elastic stiffness and unstressed area were related to construct a nonlinear relationship. This relation was used in the network model. A 1D single vessel model of the aorta was then developed and used to estimate the inflow profile and parameters for total resistance and compliance for the downstream network and to demonstrate effects of incorporating viscoelasticity in the arterial wall. Lastly, the extent to which vessel wall parameters estimated from ex vivo data can be used to realistically simulate pressure and area in a vessel network was evaluated. Elastic wall parameters in the network simulations were found to yield pressure-area relationships across all vessel locations and sheep that were in ranges comparable to those in the ex vivo data.}, number={02}, journal={Journal of Mechanics in Medicine and Biology}, publisher={World Scientific Pub Co Pte Lt}, author={Battista, Christina and Bia, Daniel and Germán, Yanina Zócalo and Armentano, Ricardo L. and Haider, Mansoor A. and Olufsen, Mette S.}, year={2016}, month={Mar}, pages={1650007} }
 @article{matzuka_mehlsen_tran_olufsen_2015, title={Using Kalman Filtering to Predict Time-Varying Parameters in a Model Predicting Baroreflex Regulation During Head-Up Tilt}, volume={62}, ISSN={0018-9294 1558-2531}, url={http://dx.doi.org/10.1109/TBME.2015.2409211}, DOI={10.1109/tbme.2015.2409211}, abstractNote={The cardiovascular control system is continuously engaged to maintain homeostasis, but it is known to fail in a large cohort of patients suffering from orthostatic intolerance. Numerous clinical studies have been put forward to understand how the system fails, yet noninvasive clinical data are sparse, typical studies only include measurements of heart rate and blood pressure, as a result it is difficult to determine what mechanisms that are impaired. It is known, that blood pressure regulation is mediated by changes in heart rate, vascular resistance, cardiac contractility, and a number of other factors. Given that numerous factors contribute to changing these quantities, it is difficult to devise a physiological model describing how they change in time. One way is to build a model that allows these controlled quantities to change and to compare dynamics between subject groups. To do so, it requires more knowledge of how these quantities change for healthy subjects. This study compares two methods predicting time-varying changes in cardiac contractility and vascular resistance during head-up tilt. Similar to the study by Williams et al.[51], the first method uses piecewise linear splines, while the second uses the ensemble transform Kalman filter (ETKF) [1] , [11], [12], [33]. In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained with the ETKF. While the spline method is easier to set up, this study shows that the ETKF has a significantly shorter computational time. Moreover, while uncertainty of predictions can be augmented to spline predictions using DRAM, these are readily available with the ETKF.}, number={8}, journal={IEEE Transactions on Biomedical Engineering}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Matzuka, Brett and Mehlsen, Jesper and Tran, Hien and Olufsen, Mette Sofie}, year={2015}, month={Aug}, pages={1992–2000} }
 @article{pontrelli_olufsen_ottesen_2014, title={Mathematical methods and models in system biomedicine}, volume={257}, ISSN={0025-5564}, url={http://dx.doi.org/10.1016/J.MBS.2014.09.012}, DOI={10.1016/J.MBS.2014.09.012}, abstractNote={A particular case of the famous quasispecies model — the Crow–Kimura model with a permutation invariant fitness landscape — is investigated. Using the fact that the mutation matrix in the case of a permutation invariant fitness landscape has a special tridiagonal form, a change of the basis is suggested such that in the new coordinates a number of analytical results can be obtained. In particular, using the eigenvectors of the mutation matrix as the new basis, we show that the quasispecies distribution approaches a binomial one and give simple estimates for the speed of convergence. Another consequence of the suggested approach is a parametric solution to the system of equations determining the quasispecies. Using this parametric solution we show that our approach leads to exact asymptotic results in some cases, which are not covered by the existing methods. In particular, we are able to present not only the limit behavior of the leading eigenvalue (mean population fitness), but also the exact formulas for the limit quasispecies eigenvector for special cases. For instance, this eigenvector has a geometric distribution in the case of the classical single peaked fitness landscape. On the biological side, we propose a mathematical definition, based on the closeness of the quasispecies to the binomial distribution, which can be used as an operational definition of the notorious error threshold. Using this definition, we suggest two approximate formulas to estimate the critical mutation rate after which the quasispecies delocalization occurs.}, journal={Mathematical Biosciences}, publisher={Elsevier BV}, author={Pontrelli, Giuseppe and Olufsen, Mette S. and Ottesen, Johnny T.}, year={2014}, month={Nov}, pages={1} }
 @article{mader_olufsen_mahdi_2014, title={Modeling Cerebral Blood Flow Velocity During Orthostatic Stress}, volume={43}, ISSN={0090-6964 1573-9686}, url={http://dx.doi.org/10.1007/s10439-014-1220-4}, DOI={10.1007/s10439-014-1220-4}, number={8}, journal={Annals of Biomedical Engineering}, publisher={Springer Science and Business Media LLC}, author={Mader, Greg and Olufsen, Mette and Mahdi, Adam}, year={2014}, month={Dec}, pages={1748–1758} }
 @article{qureshi_vaughan_sainsbury_johnson_peskin_olufsen_hill_2014, title={Numerical simulation of blood flow and pressure drop in the pulmonary arterial and venous circulation}, volume={13}, ISSN={["1617-7940"]}, DOI={10.1007/s10237-014-0563-y}, abstractNote={A novel multiscale mathematical and computational model of the pulmonary circulation is presented and used to analyse both arterial and venous pressure and flow. This work is a major advance over previous studies by Olufsen et al. (Ann Biomed Eng 28:1281–1299, 2012) which only considered the arterial circulation. For the first three generations of vessels within the pulmonary circulation, geometry is specified from patient-specific measurements obtained using magnetic resonance imaging (MRI). Blood flow and pressure in the larger arteries and veins are predicted using a nonlinear, cross-sectional-area-averaged system of equations for a Newtonian fluid in an elastic tube. Inflow into the main pulmonary artery is obtained from MRI measurements, while pressure entering the left atrium from the main pulmonary vein is kept constant at the normal mean value of 2 mmHg. Each terminal vessel in the network of ‘large’ arteries is connected to its corresponding terminal vein via a network of vessels representing the vascular bed of smaller arteries and veins. We develop and implement an algorithm to calculate the admittance of each vascular bed, using bifurcating structured trees and recursion. The structured-tree models take into account the geometry and material properties of the ‘smaller’ arteries and veins of radii $$\ge $$ 50 $$\upmu $$ m. We study the effects on flow and pressure associated with three classes of pulmonary hypertension expressed via stiffening of larger and smaller vessels, and vascular rarefaction. The results of simulating these pathological conditions are in agreement with clinical observations, showing that the model has potential for assisting with diagnosis and treatment for circulatory diseases within the lung.}, number={5}, journal={BIOMECHANICS AND MODELING IN MECHANOBIOLOGY}, author={Qureshi, M. Umar and Vaughan, Gareth D. A. and Sainsbury, Christopher and Johnson, Martin and Peskin, Charles S. and Olufsen, Mette S. and Hill, N. A.}, year={2014}, month={Oct}, pages={1137–1154} }
 @article{williams_wind-willassen_wright_program_mehlsen_ottesen_olufsen_2014, title={Patient-specific modelling of head-up tilt}, volume={31}, ISSN={["1477-8602"]}, DOI={10.1093/imammb/dqt004}, abstractNote={Short-term cardiovascular responses to head-up tilt (HUT) involve complex cardiovascular regulation in order to maintain blood pressure at homoeostatic levels. This manuscript presents a patient-specific model that uses heart rate as an input to fit the dynamic changes in arterial blood pressure data during HUT. The model contains five compartments representing arteries and veins in the upper and lower body of the systemic circulation, as well as the left ventricle facilitating pumping of the heart. A physiologically based submodel describes gravitational pooling of the blood into the lower extremities during HUT, and a cardiovascular regulation model adjusts cardiac contractility and vascular resistance to the blood pressure changes. Nominal parameter values are computed from patient-specific data and literature estimates. The model is rendered patient specific via the use of parameter estimation techniques. This process involves sensitivity analysis, prediction of a subset of identifiable parameters, and non-linear optimization. The approach proposed here was applied to the analysis of aortic and carotid HUT data from five healthy young subjects. Results showed that it is possible to identify a subset of model parameters that can be estimated allowing the model to fit changes in arterial blood pressure observed at the level of the carotid bifurcation. Moreover, the model estimates physiologically reasonable values for arterial and venous blood pressures, blood volumes and cardiac output for which data are not available.}, number={4}, journal={MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA}, author={Williams, Nakeya D. and Wind-Willassen, Oistein and Wright, Andrew A. and Program, Reu and Mehlsen, Jesper and Ottesen, Johnny T. and Olufsen, Mette S.}, year={2014}, month={Dec}, pages={365–392} }
 @article{ottesen_mehlsen_olufsen_2014, title={Structural correlation method for model reduction and practical estimation of patient specific parameters illustrated on heart rate regulation}, volume={257}, ISSN={["1879-3134"]}, DOI={10.1016/j.mbs.2014.07.003}, abstractNote={We consider the inverse and patient specific problem of short term (seconds to minutes) heart rate regulation specified by a system of nonlinear ODEs and corresponding data. We show how a recent method termed the structural correlation method (SCM) can be used for model reduction and for obtaining a set of practically identifiable parameters. The structural correlation method includes two steps: sensitivity and correlation analysis. When combined with an optimization step, it is possible to estimate model parameters, enabling the model to fit dynamics observed in data. This method is illustrated in detail on a model predicting baroreflex regulation of heart rate and applied to analysis of data from a rat and healthy humans. Numerous mathematical models have been proposed for prediction of baroreflex regulation of heart rate, yet most of these have been designed to provide qualitative predictions of the phenomena though some recent models have been developed to fit observed data. In this study we show that the model put forward by Bugenhagen et al. [2] can be simplified without loss of its ability to predict measured data and to be interpreted physiologically. Moreover, we show that with minimal changes in nominal parameter values the simplified model can be adapted to predict observations from both rats and humans. The use of these methods make the model suitable for estimation of parameters from individuals, allowing it to be adopted for diagnostic procedures.}, journal={MATHEMATICAL BIOSCIENCES}, author={Ottesen, Johnny T. and Mehlsen, Jesper and Olufsen, Mette S.}, year={2014}, month={Nov}, pages={50–59} }
 @article{olufsen_ottesen_2013, title={A practical approach to parameter estimation applied to model predicting heart rate regulation}, volume={67}, ISSN={["1432-1416"]}, DOI={10.1007/s00285-012-0535-8}, abstractNote={Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities. Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse. However, it may be possible to estimate a subset of model parameters reducing the complexity of the problem. In this study, we compare three methods that allow identification of parameter subsets that can be estimated given a model and a set of data. These methods will be used to estimate patient specific parameters in a model predicting baroreceptor feedback regulation of heart rate during head-up tilt. The three methods include: structured analysis of the correlation matrix, analysis via singular value decomposition followed by QR factorization, and identification of the subspace closest to the one spanned by eigenvectors of the model Hessian. Results showed that all three methods facilitate identification of a parameter subset. The “best” subset was obtained using the structured correlation method, though this method was also the most computationally intensive. Subsets obtained using the other two methods were easier to compute, but analysis revealed that the final subsets contained correlated parameters. In conclusion, to avoid lengthy computations, these three methods may be combined for efficient identification of parameter subsets.}, number={1}, journal={JOURNAL OF MATHEMATICAL BIOLOGY}, author={Olufsen, Mette S. and Ottesen, Johnny T.}, year={2013}, month={Jul}, pages={39–68} }
 @article{ottesen_novak_olufsen_2013, title={Development of Patient Specific Cardiovascular Models Predicting Dynamics in Response to Orthostatic Stress Challenges}, volume={2064}, ISBN={["978-3-642-32881-7"]}, ISSN={["1617-9692"]}, DOI={10.1007/978-3-642-32882-4_10}, abstractNote={Physiological realistic models of the controlled cardiovascular system are constructed and validated against clinical data. Special attention is paid to the control of blood pressure, cerebral blood flow velocity, and heart rate during postural challenges, including sit-to-stand and head-up tilt. This study describes development of patient specific models, and how sensitivity analysis and nonlinear optimization methods can be used to predict patient specific characteristics when analyzed using experimental data. Finally, we discuss how a given model can be used to understand physiological changes between groups of individuals and how to use modeling to identify biomarkers.}, journal={MATHEMATICAL MODELING AND VALIDATION IN PHYSIOLOGY: APPLICATIONS TO THE CARDIOVASCULAR AND RESPIRATORY SYSTEMS}, author={Ottesen, Johnny T. and Novak, Vera and Olufsen, Mette S.}, year={2013}, pages={177–213} }
 @article{mahdi_sturdy_ottesen_olufsen_2013, title={Modeling the Afferent Dynamics of the Baroreflex Control System}, volume={9}, ISSN={1553-7358}, url={http://dx.doi.org/10.1371/journal.pcbi.1003384}, DOI={10.1371/journal.pcbi.1003384}, abstractNote={In this study we develop a modeling framework for predicting baroreceptor firing rate as a function of blood pressure. We test models within this framework both quantitatively and qualitatively using data from rats. The models describe three components: arterial wall deformation, stimulation of mechanoreceptors located in the BR nerve-endings, and modulation of the action potential frequency. The three sub-systems are modeled individually following well-established biological principles. The first submodel, predicting arterial wall deformation, uses blood pressure as an input and outputs circumferential strain. The mechanoreceptor stimulation model, uses circumferential strain as an input, predicting receptor deformation as an output. Finally, the neural model takes receptor deformation as an input predicting the BR firing rate as an output. Our results show that nonlinear dependence of firing rate on pressure can be accounted for by taking into account the nonlinear elastic properties of the artery wall. This was observed when testing the models using multiple experiments with a single set of parameters. We find that to model the response to a square pressure stimulus, giving rise to post-excitatory depression, it is necessary to include an integrate-and-fire model, which allows the firing rate to cease when the stimulus falls below a given threshold. We show that our modeling framework in combination with sensitivity analysis and parameter estimation can be used to test and compare models. Finally, we demonstrate that our preferred model can exhibit all known dynamics and that it is advantageous to combine qualitative and quantitative analysis methods.}, number={12}, journal={PLoS Computational Biology}, publisher={Public Library of Science (PLoS)}, author={Mahdi, Adam and Sturdy, Jacob and Ottesen, Johnny T. and Olufsen, Mette S.}, editor={Arciero, Julia C.Editor}, year={2013}, month={Dec}, pages={e1003384} }
 @article{ellwein_pope_xie_batzel_kelley_olufsen_2013, title={Patient-specific modeling of cardiovascular and respiratory dynamics during hypercapnia}, volume={241}, ISSN={0025-5564}, url={http://dx.doi.org/10.1016/j.mbs.2012.09.003}, DOI={10.1016/j.mbs.2012.09.003}, abstractNote={This study develops a lumped cardiovascular–respiratory system-level model that incorporates patient-specific data to predict cardiorespiratory response to hypercapnia (increased CO2 partial pressure) for a patient with congestive heart failure (CHF). In particular, the study focuses on predicting cerebral CO2 reactivity, which can be defined as the ability of vessels in the cerebral vasculature to expand or contract in response CO2 induced challenges. It is difficult to characterize cerebral CO2 reactivity directly from measurements, since no methods exist to dynamically measure vasomotion of vessels in the cerebral vasculature. In this study we show how mathematical modeling can be combined with available data to predict cerebral CO2 reactivity via dynamic predictions of cerebral vascular resistance, which can be directly related to vasomotion of vessels in the cerebral vasculature. To this end we have developed a coupled cardiovascular and respiratory model that predicts blood pressure, flow, and concentration of gasses (CO2 and O2) in the systemic, cerebral, and pulmonary arteries and veins. Cerebral vascular resistance is incorporated via a model parameter separating cerebral arteries and veins. The model was adapted to a specific patient using parameter estimation combined with sensitivity analysis and subset selection. These techniques allowed estimation of cerebral vascular resistance along with other cardiovascular and respiratory parameters. Parameter estimation was carried out during eucapnia (breathing room air), first for the cardiovascular model and then for the respiratory model. Then, hypercapnia was introduced by increasing inspired CO2 partial pressure. During eucapnia, seven cardiovascular parameters and four respiratory parameters was be identified and estimated, including cerebral and systemic resistance. During the transition from eucapnia to hypercapnia, the model predicted a drop in cerebral vascular resistance consistent with cerebral vasodilation.}, number={1}, journal={Mathematical Biosciences}, publisher={Elsevier BV}, author={Ellwein, L.M. and Pope, S.R. and Xie, A. and Batzel, J.J. and Kelley, C.T. and Olufsen, M.S.}, year={2013}, month={Jan}, pages={56–74} }
 @article{aoi_hu_lo_selim_olufsen_novak_2012, title={Impaired Cerebral Autoregulation Is Associated with Brain Atrophy and Worse Functional Status in Chronic Ischemic Stroke}, volume={7}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0046794}, abstractNote={Dynamic cerebral autoregulation (dCA) is impaired following stroke. However, the relationship between dCA, brain atrophy, and functional outcomes following stroke remains unclear. In this study, we aimed to determine whether impairment of dCA is associated with atrophy in specific regions or globally, thereby affecting daily functions in stroke patients.We performed a retrospective analysis of 33 subjects with chronic infarctions in the middle cerebral artery territory, and 109 age-matched non-stroke subjects. dCA was assessed via the phase relationship between arterial blood pressure and cerebral blood flow velocity. Brain tissue volumes were quantified from MRI. Functional status was assessed by gait speed, instrumental activities of daily living (IADL), modified Rankin Scale, and NIH Stroke Score.Compared to the non-stroke group, stroke subjects showed degraded dCA bilaterally, and showed gray matter atrophy in the frontal, parietal and temporal lobes ipsilateral to infarct. In stroke subjects, better dCA was associated with less temporal lobe gray matter atrophy on the infracted side ([Formula: see text] = 0.029), faster gait speed ([Formula: see text] = 0.018) and lower IADL score ([Formula: see text]0.002). Our results indicate that better dynamic cerebral perfusion regulation is associated with less atrophy and better long-term functional status in older adults with chronic ischemic infarctions.}, number={10}, journal={PLOS ONE}, author={Aoi, Mikio C. and Hu, Kun and Lo, Men-Tzung and Selim, Magdy and Olufsen, Mette S. and Novak, Vera}, year={2012}, month={Oct} }
 @article{olufsen_hill_vaughan_sainsbury_johnson_2012, title={Rarefaction and blood pressure in systemic and pulmonary arteries}, volume={705}, ISSN={["1469-7645"]}, DOI={10.1017/jfm.2012.220}, abstractNote={The effects of vascular rarefaction (the loss of small arteries) on the circulation of blood are studied using a multiscale mathematical model that can predict blood flow and pressure in the systemic and pulmonary arteries. We augmented a model originally developed for the systemic arteries (Olufsen et al. 1998, 1999, 2000, 2004) to (a) predict flow and pressure in the pulmonary arteries, and (b) predict pressure propagation along the small arteries in the vascular beds. The systemic and pulmonary arteries are modelled as separate, bifurcating trees of compliant and tapering vessels. Each tree is divided into two parts representing the `large' and `small' arteries. Blood flow and pressure in the large arteries are predicted using a nonlinear cross-sectional area-averaged model for a Newtonian fluid in an elastic tube with inflow obtained from magnetic resonance measurements. Each terminal vessel within the network of the large arteries is coupled to a vascular bed of small `resistance' arteries, which are modelled as asymmetric structured trees with specified area and asymmetry ratios between the parent and daughter arteries. For the systemic circulation, each structured tree represents a specific vascular bed corresponding to major organs and limbs. For the pulmonary circulation, there are four vascular beds supplied by the interlobar arteries. This manuscript presents the first theoretical calculations of the propagation of the pressure and flow waves along systemic and pulmonary large and small arteries. Results for all networks were in agreement with published observations. Two studies were done with this model. First, we showed how rarefaction can be modelled by pruning the tree of arteries in the microvascular system. This was done by modulating parameters used for designing the structured trees. Results showed that rarefaction leads to increased mean and decreased pulse pressure in the large arteries. Second, we investigated the impact of decreasing vessel compliance in both large and small arteries. Results showed, that the effects of decreased compliance in the large arteries far outweigh the effects observed when decreasing the compliance of the small arteries. We further showed that a decrease of compliance in the large arteries results in pressure increases consistent with observations of isolated systolic hypertension, as occurs in ageing.}, journal={JOURNAL OF FLUID MECHANICS}, author={Olufsen, Mette S. and Hill, N. A. and Vaughan, Gareth D. A. and Sainsbury, Christopher and Johnson, Martin}, year={2012}, month={Aug}, pages={280–305} }
 @article{ottesen_olufsen_2011, title={Functionality of the baroreceptor nerves in heart rate regulation}, volume={101}, ISSN={["1872-7565"]}, DOI={10.1016/j.cmpb.2010.10.012}, abstractNote={Two models describing the afferent baroreceptor firing are analyzed, a basic model predicting firing using a single nonlinear differential equation, and an extended model, coupling K nonlinear responses. Both models respond to the the rate (derivative) and the rate history of the carotid sinus arterial pressure. As a result both the rate and the relative level of the carotid sinus arterial pressure is sensed. Simulations with these models show that responses to step changes in pressure follow from the rate sensitivity as observed in experimental studies. Adaptation and asymmetric responses are a consequence of the memory encapsulated by the models, and the nonlinearity gives rise to sigmoidal response curves. The nonlinear afferent baroreceptor models are coupled with an effector model, and the coupled model has been used to predict baroreceptor feedback regulation of heart rate during postural change from sitting to standing and during head-up tilt. The efferent model couples the afferent nerve paths to the sympathetic and parasympathetic outflow, and subsequently predicts the build up of an action potential at the sinus knot of the heart. In this paper, we analyze the nonlinear afferent model and show that the coupled model is able to predict heart rate regulation using blood pressure data as an input.}, number={2}, journal={COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE}, author={Ottesen, J. T. and Olufsen, M. S.}, year={2011}, month={Feb}, pages={208–219} }
 @article{valdez-jasso_bia_zocalo_armentano_haider_olufsen_2011, title={Linear and Nonlinear Viscoelastic Modeling of Aorta and Carotid Pressure-Area Dynamics Under In Vivo and Ex Vivo Conditions}, volume={39}, ISSN={["1573-9686"]}, DOI={10.1007/s10439-010-0236-7}, abstractNote={A better understanding of the biomechanical properties of the arterial wall provides important insight into arterial vascular biology under normal (healthy) and pathological conditions. This insight has potential to improve tracking of disease progression and to aid in vascular graft design and implementation. In this study, we use linear and nonlinear viscoelastic models to predict biomechanical properties of the thoracic descending aorta and the carotid artery under ex vivo and in vivo conditions in ovine and human arteries. Models analyzed include a four-parameter (linear) Kelvin viscoelastic model and two five-parameter nonlinear viscoelastic models (an arctangent and a sigmoid model) that relate changes in arterial blood pressure to the vessel cross-sectional area (via estimation of vessel strain). These models were developed using the framework of Quasilinear Viscoelasticity (QLV) theory and were validated using measurements from the thoracic descending aorta and the carotid artery obtained from human and ovine arteries. In vivo measurements were obtained from 10 ovine aortas and 10 human carotid arteries. Ex vivo measurements (from both locations) were made in 11 male Merino sheep. Biomechanical properties were obtained through constrained estimation of model parameters. To further investigate the parameter estimates, we computed standard errors and confidence intervals and we used analysis of variance to compare results within and between groups. Overall, our results indicate that optimal model selection depends on the artery type. Results showed that for the thoracic descending aorta (under both experimental conditions), the best predictions were obtained with the nonlinear sigmoid model, while under healthy physiological pressure loading the carotid arteries nonlinear stiffening with increasing pressure is negligible, and consequently, the linear (Kelvin) viscoelastic model better describes the pressure–area dynamics in this vessel. Results comparing biomechanical properties show that the Kelvin and sigmoid models were able to predict the zero-pressure vessel radius; that under ex vivo conditions vessels are more rigid, and comparatively, that the carotid artery is stiffer than the thoracic descending aorta; and that the viscoelastic gain and relaxation parameters do not differ significantly between vessels or experimental conditions. In conclusion, our study demonstrates that the proposed models can predict pressure–area dynamics and that model parameters can be extracted for further interpretation of biomechanical properties.}, number={5}, journal={ANNALS OF BIOMEDICAL ENGINEERING}, author={Valdez-Jasso, Daniela and Bia, Daniel and Zocalo, Yanina and Armentano, Ricardo L. and Haider, Mansoor A. and Olufsen, Mette S.}, year={2011}, month={May}, pages={1438–1456} }
 @article{steele_valdez-jasso_haider_olufsen_2011, title={PREDICTING ARTERIAL FLOW AND PRESSURE DYNAMICS USING A 1D FLUID DYNAMICS MODEL WITH A VISCOELASTIC WALL}, volume={71}, ISSN={["1095-712X"]}, DOI={10.1137/100810186}, abstractNote={This paper combines a generalized viscoelastic model with a one-dimensional (1D) fluid dynamics model for the prediction of blood flow, pressure, and vessel area in systemic arteries. The 1D fluid dynamics model is derived from the Navier–Stokes equations for an incompressible Newtonian flow through a network of cylindrical vessels. This model predicts pressure and flow and is combined with a viscoelastic constitutive equation derived using the quasilinear viscoelasticity theory that relates pressure and vessel area. This formulation allows for inclusion of an elastic response as well as an appropriate creep function allowing for the description of the viscoelastic deformation of the arterial wall. Three constitutive models were investigated: a linear elastic model and two viscoelastic models. The Kelvin and sigmoidal viscoelastic models provide linear and nonlinear elastic responses, respectively. For the fluid domain, the model assumes that a given flow profile is prescribed at the inlet, that flow is conserved and pressure is continuous across vessel junctions, and that it incorporates a multiscale boundary condition (a three element Windkessel model) at each outlet. This outlet boundary condition allows prediction of the overall impact on the flow and pressure generated by the downstream vasculature. The coupled fluid structure interaction model is solved using a finite element method that is adapted to account for time history of the viscoelastic model. Results of this study demonstrate that incorporation of a viscoelastic wall model allows more physiologic prediction of arterial blood pressure and vessel deformation, which often is overestimated with the simple elastic wall models, while blood flow does not differ significantly between models.}, number={4}, journal={SIAM JOURNAL ON APPLIED MATHEMATICS}, author={Steele, Brooke N. and Valdez-Jasso, Daniela and Haider, Mansoor A. and Olufsen, Mette S.}, year={2011}, pages={1123–1143} }
 @inproceedings{olufsen_smith_mehlsen_ottesen_2011, title={The impact of gravity during head-up tilt}, DOI={10.1109/iembs.2011.6090669}, abstractNote={The impact of gravity during head-up tilt, a test often used in the clinic to diagnose patients who suffer from dizziness or frequent episodes of syncope, is not well described. This study uses mathematical modeling to analyze experimental blood pressure data measured at the level of the aorta and the carotid sinuses in a healthy volunteer. During head-up tilt the head is lifted above the heart stimulating gravitational pooling of blood in the lower extremities. This shift in volume is followed by an increase in blood pressure in the lower body, while the pressure in the head decreases, while the pressure at the level of the heart is either constant or increases. At the same time, the normal response to head-up tilt is an increase in heart rate. The change in posture, and subsequent change in heart rate, is believed to be mediated via baroreflex inhibition. Traditional understanding of the baroreceptor system is that inhibition is a result of a blood pressure drop. However, only the carotid sinus blood pressure is decreased during head-up tilt, suggesting that the receptors at this location are more prominent than the receptors in the aortic arch. To explore this hypothesis further, we developed a model predicting hydrostatic height between the two locations. Results from this model were compared with measurements. Furthermore, we show, using a differential equations model predicting blood pressure, that it is possible to predict blood pressure measured at the level of the carotid sinuses using heart rate as an input. Finally, we discuss our results in relation to measurements obtained at the two locations.}, booktitle={2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, author={Olufsen, M. S. and Smith, B. and Mehlsen, J. and Ottesen, J.}, year={2011}, pages={2399–2402} }
 @inproceedings{aoi_matzuka_olufsen_2011, title={Toward online, noninvasive, nonlinear assessment of cerebral autoregulation}, DOI={10.1109/iembs.2011.6090671}, abstractNote={Online estimation of cerebral autoregulation (CA) may be advantageous in neurosurgical and neurointensive care units. Data from transcranial Doppler, and continuous arterial blood pressure are readily available at high temporal resolution and may be used to assess CA. There are currently no methods for nonlinear, noninvasive, online assessment of CA. We frame the assessment of CA as a parameter estimation problem, in which we estimate the parameters of a nonlinear mathematical model of CA using the ensemble Kalman filter (EnKF). In this simulation study, we use the EnKF to estimate the parameters of a model of cerebral hemodynamics which predicts intracranial pressure and cerebral blood flow velocity, generated from real patient arterial blood pressure measurements. We examine the flexibility and appropriateness of the EnKF for CA assessment.}, booktitle={2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, author={Aoi, M. C. and Matzuka, B. J. and Olufsen, M. S.}, year={2011}, pages={2410–2413} }
 @article{valdez-jasso_bia_haider_zocalo_armentano_olufsen_2010, title={Linear and Nonlinear Viscoelastic Modeling of Ovine Aortic Biomechanical Properties under in vivo and ex vivo Conditions}, ISSN={["1557-170X"]}, DOI={10.1109/iembs.2010.5626563}, abstractNote={This study uses linear and nonlinear viscoelastic models to describe the dynamic distention of the aorta induced by time-varying arterial blood pressure. We employ an inverse mathematical modeling approach on a four-parameter (linear) Kelvin viscoelastic model and two five-parameter nonlinear viscoelastic models (arctangent and sigmoid) to infer vascular biomechanical properties under in vivo and ex vivo experimental conditions in ten and eleven male Merino sheep, respectively. We used the Akaike Information Criterion (AIC) as a goodness-of-fit measure. Results show that under both experimental conditions, the nonlinear models generally outperform the linear Kelvin model, as judged by the AIC. Furthermore, the sigmoid nonlinear viscoelastic model consistently achieves the lowest AIC and also matches the zero-stress vessel radii measured ex vivo. Based on these observations, we conclude that the sigmoid nonlinear viscoelastic model best describes the biomechanical properties of ovine large arteries under both experimental conditions considered in this study.}, journal={2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)}, author={Valdez-Jasso, D. and Bia, D. and Haider, M. A. and Zocalo, Y. and Armentano, R. L. and Olufsen, M. S.}, year={2010}, pages={2634–2637} }
 @article{valdez-jasso_haider_banks_santana_german_armentano_olufsen_2009, title={Analysis of Viscoelastic Wall Properties in Ovine Arteries}, volume={56}, ISSN={["1558-2531"]}, DOI={10.1109/TBME.2008.2003093}, abstractNote={In this paper, we analyze how elastic and viscoelastic properties differ across seven locations along the large arteries in 11 sheep. We employ a two-parameter elastic model and a four-parameter Kelvin viscoelastic model to analyze experimental measurements of vessel diameter and blood pressure obtained <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vitro</i> at conditions mimicking <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vivo</i> dynamics. Elastic and viscoelastic wall properties were assessed via solutions to the associated inverse problem. We use sensitivity analysis to rank the model parameters from the most to the least sensitive, as well as to compute standard errors and confidence intervals. Results reveal that elastic properties in both models (including Young's modulus and the viscoelastic relaxation parameters) vary across locations (smaller arteries are stiffer than larger arteries). We also show that for all locations, the inclusion of viscoelastic behavior is important to capture pressure-area dynamics.}, number={2}, journal={IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING}, author={Valdez-Jasso, Daniela and Haider, Mansoor A. and Banks, H. T. and Santana, Daniel Bia and German, Yanina Zocalo and Armentano, Ricardo L. and Olufsen, Mette S.}, year={2009}, month={Feb}, pages={210–219} }
 @article{pope_ellwein_zapata_novak_kelley_olufsen_2009, title={ESTIMATION AND IDENTIFICATION OF PARAMETERS IN A LUMPED CEREBROVASCULAR MODEL}, volume={6}, ISSN={["1551-0018"]}, DOI={10.3934/mbe.2009.6.93}, abstractNote={This study shows how sensitivity analysis and subset selection can be employed in a cardiovascular model to estimate total systemic resistance, cerebrovascular resistance, arterial compliance, and time for peak systolic ventricular pressure for healthy young and elderly subjects. These quantities are parameters in a simple lumped parameter model that predicts pressure and flow in the systemic circulation. The model is combined with experimental measurements of blood flow velocity from the middle cerebral artery and arterial finger blood pressure. To estimate the model parameters we use nonlinear optimization combined with sensitivity analysis and subset selection. Sensitivity analysis allows us to rank model parameters from the most to the least sensitive with respect to the output states (cerebral blood flow velocity and arterial blood pressure). Subset selection allows us to identify a set of independent candidate parameters that can be estimated given limited data. Analyses of output from both methods allow us to identify five independent sensitive parameters that can be estimated given the data. Results show that with the advance of age total systemic and cerebral resistances increase, that time for peak systolic ventricular pressure is increases, and that arterial compliance is reduced. Thus, the method discussed in this study provides a new methodology to extract clinical markers that cannot easily be assessed noninvasively.}, number={1}, journal={MATHEMATICAL BIOSCIENCES AND ENGINEERING}, author={Pope, Scott R. and Ellwein, Laura M. and Zapata, Cheryl L. and Novak, Vera and Kelley, C. T. and Olufsen, Mette S.}, year={2009}, month={Jan}, pages={93–115} }
 @article{valdez-jasso_banks_haider_bia_zocalo_armentano_olufsen_2009, title={Viscoelastic models for passive arterial wall dynamics}, volume={1}, number={2}, journal={Advances in Applied Mathematics & Mechanics}, author={Valdez-Jasso, D. and Banks, H. T. and Haider, M. A. and Bia, D. and Zocalo, Y. and Armentano, R. L. and Olufsen, M. S.}, year={2009}, pages={151–165} }
 @article{devault_gremaud_novak_olufsen_vernieres_zhao_2008, title={BLOOD FLOW IN THE CIRCLE OF WILLIS: MODELING AND CALIBRATION}, volume={7}, ISSN={["1540-3467"]}, DOI={10.1137/07070231X}, abstractNote={A numerical model based on one-dimensional balance laws and ad hoc zero-dimensional boundary conditions is tested against experimental data. The study concentrates on the circle of Willis, a vital subnetwork of the cerebral vasculature. The main goal is to obtain efficient and reliable numerical tools with predictive capabilities. The flow is assumed to obey the Navier-Stokes equations, while the mechanical reactions of the arterial walls follow a viscoelastic model. Like many previous studies, a dimension reduction is performed through averaging. Unlike most previous work, the resulting model is both calibrated and validated against in vivo data, more precisely transcranial Doppler data of cerebral blood velocity. The network considered has three inflow vessels and six outflow vessels. Inflow conditions come from the data, while outflow conditions are modeled. Parameters in the outflow conditions are calibrated using a subset of the data through ensemble Kalman filtering techniques. The rest of the data is used for validation. The results demonstrate the viability of the proposed approach.}, number={2}, journal={MULTISCALE MODELING & SIMULATION}, author={Devault, Kristen and Gremaud, Pierre A. and Novak, Vera and Olufsen, Mette S. and Vernieres, Guillaume and Zhao, Peng}, year={2008}, pages={888–909} }
 @article{batzel_novak_kappel_olufsen_tran_2008, title={Introduction to the special issues: Short-term cardiovascular-respiratory control mechanisms}, volume={8}, ISSN={["1567-8822"]}, DOI={10.1007/s10558-007-9053-5}, abstractNote={This and the following issue of Cardiovascular Engineering are special issues reflecting research discussed during an interdisciplinary focused workshop entitled Short-term Cardiovascular–Respiratory Control Mechanisms. The workshop was organized by Mette Olufsen and Hien Tran at the Department of Mathematics at North Carolina State University, Jerry Batzel and Franz Kappel at the Institute for Mathematics and Scientific Computing, University of Graz, and Vera Novak at the Department of Gerontology at Harvard Medical School, and hosted by the American Institute of Mathematics (AIM), Palo Alto, California, October 9–13, 2006. The workshop was co-sponsored by AIM and the National Science Foundation.}, number={1}, journal={CARDIOVASCULAR ENGINEERING}, author={Batzel, Jerry J. and Novak, Vera and Kappel, Franz and Olufsen, Mette S. and Tran, Hien T.}, year={2008}, month={Mar}, pages={1–4} }
 @article{vaughan_olufsen_hill_sainsbury_2008, title={Mathematical Modelling of the Systemic Circulation: investigating pressure and flow throughout the microcirculation}, volume={2}, ISSN={1872-9312}, url={http://dx.doi.org/10.1016/j.artres.2008.08.391}, DOI={10.1016/j.artres.2008.08.391}, number={3}, journal={Artery Research}, publisher={Atlantis Press}, author={Vaughan, G.A. and Olufsen, M.S. and Hill, N.A. and Sainsbury, C.A.}, year={2008}, month={Aug}, pages={112} }
 @article{olufsen_alston_tran_ottesen_novak_2008, title={Modeling heart rate regulation - Part I: Sit-to-stand versus head-up tilt}, volume={8}, ISSN={["1573-6806"]}, DOI={10.1007/s10558-007-9050-8}, abstractNote={In this study we describe a model predicting heart rate regulation during postural change from sitting to standing and during head-up tilt in five healthy elderly adults. The model uses blood pressure as an input to predict baroreflex firing-rate, which in turn is used to predict efferent parasympathetic and sympathetic outflows. The model also includes the combined effects of vestibular and central command stimulation of muscle sympathetic nerve activity, which is increased at the onset of postural change. Concentrations of acetylcholine and noradrenaline, predicted as functions of sympathetic and parasympathetic outflow, are then used to estimate the heart rate response. Dynamics of the heart rate and the baroreflex firing rate are modeled using a system of coupled ordinary delay differential equations with 17 parameters. We have derived sensitivity equations and ranked sensitivities of all parameters with respect to all state variables in our model. Using this model we show that during head-up tilt, the baseline firing-rate is larger than during sit-to-stand and that the combined effect of vestibular and central command stimulation of muscle sympathetic nerve activity is less pronounced during head-up tilt than during sit-to-stand.}, number={2}, journal={CARDIOVASCULAR ENGINEERING}, author={Olufsen, Mette S. and Alston, April V. and Tran, Hien T. and Ottesen, Johnny T. and Novak, Vera}, year={2008}, month={Jun}, pages={73–87} }
 @article{fowler_gray_olufsen_2008, title={Modeling heart rate regulation - Part II: Parameter identification and analysis}, volume={8}, ISSN={["1573-6806"]}, DOI={10.1007/s10558-007-9048-2}, number={2}, journal={CARDIOVASCULAR ENGINEERING}, author={Fowler, K. R. and Gray, G. A. and Olufsen, M. S.}, year={2008}, month={Jun}, pages={109–119} }
 @article{ellwein_tran_zapata_novak_olufsen_2008, title={Sensitivity analysis and model assessment: Mathematical models for arterial blood flow and blood pressure}, volume={8}, ISSN={["1573-6806"]}, DOI={10.1007/s10558-007-9047-3}, number={2}, journal={CARDIOVASCULAR ENGINEERING}, author={Ellwein, Laura M. and Tran, Hien T. and Zapata, Cheryl and Novak, Vera and Olufsen, Mette S.}, year={2008}, month={Jun}, pages={94–108} }
 @article{steele_olufsen_taylor_2007, title={Fractal network model for simulating abdominal and lower extremity blood flow during resting and exercise conditions}, volume={10}, ISSN={1025-5842 1476-8259}, url={http://dx.doi.org/10.1080/10255840601068638}, DOI={10.1080/10255840601068638}, abstractNote={We present a one-dimensional (1D) fluid dynamic model that can predict blood flow and blood pressure during exercise using data collected at rest. To facilitate accurate prediction of blood flow, we developed an impedance boundary condition using morphologically derived structured trees. Our model was validated by computing blood flow through a model of large arteries extending from the thoracic aorta to the profunda arteries. The computed flow was compared against measured flow in the infrarenal (IR) aorta at rest and during exercise. Phase contrast-magnetic resonance imaging (PC-MRI) data was collected from 11 healthy volunteers at rest and during steady exercise. For each subject, an allometrically-scaled geometry of the large vessels was created. This geometry extends from the thoracic aorta to the femoral arteries and includes the celiac, superior mesenteric, renal, inferior mesenteric, internal iliac and profunda arteries. During rest, flow was simulated using measured supraceliac (SC) flow at the inlet and a uniform set of impedance boundary conditions at the 11 outlets. To simulate exercise, boundary conditions were modified. Inflow data collected during steady exercise was specified at the inlet and the outlet boundaries were adjusted as follows. The geometry of the structured trees used to compute impedance was scaled to simulate the effective change in the cross-sectional area of resistance vessels and capillaries due to exercise. The resulting computed flow through the IR aorta was compared to measured flow. This method produces good results with a mean difference between paired data to be 1.1 ± 7 cm3 s− 1 at rest and 4.0 ± 15 cm3 s− 1 at exercise. While future work will improve on these results, this method provides groundwork with which to predict the flow distributions in a network due to physiologic regulation.}, number={1}, journal={Computer Methods in Biomechanics and Biomedical Engineering}, publisher={Informa UK Limited}, author={Steele, Brooke N. and Olufsen, Mette S. and Taylor, Charles A.}, year={2007}, month={Feb}, pages={39–51} }
 @article{bai_banks_dediu_govan_last_lloyd_nguyen_olufsen_rempala_slenning_2007, title={Stochastic and deterministic models for agricultural production networks}, volume={4}, url={https://publons.com/publon/12886434/}, DOI={10.3934/mbe.2007.4.373}, abstractNote={An approach to modeling the impact of disturbances in an agricultural production network is presented. A stochastic model and its approximate deterministic model for averages over sample paths of the stochastic system are developed. Simulations, sensitivity and generalized sensitivity analyses are given. Finally, it is shown how diseases may be introduced into the network and corresponding simulations are discussed.}, number={3}, journal={Mathematical Biosciences and Engineering}, author={Bai, P. and Banks, H. T. and Dediu, S. and Govan, A. Y. and Last, M. and Lloyd, Alun and Nguyen, H. K. and Olufsen, M. S. and Rempala, G. and Slenning, B. D.}, year={2007}, pages={373–402} }
 @article{vaughan_johnson_mark_connell_olufsen_hill_sainsbury_2007, title={The Disparate Effects of Microvascular Rarefaction and Reduced Compliance on Proximal Haemodynamics: Investigation with a Mathematical and Computational Model of the Circulation}, volume={1}, ISSN={1872-9312}, url={http://dx.doi.org/10.1016/j.artres.2007.07.029}, DOI={10.1016/j.artres.2007.07.029}, number={2}, journal={Artery Research}, publisher={Atlantis Press}, author={Vaughan, G.A. and Johnson, M.K. and Mark, P.B. and Connell, J.M.C. and Olufsen, M.S. and Hill, N.A. and Sainsbury, C.A.R.}, year={2007}, month={Sep}, pages={74} }
 @article{justice_trussell_olufsen_2006, title={Analysis of blood flow velocity and pressure signals using the multipulse method}, volume={3}, DOI={10.3934/mbe.2006.3.419}, abstractNote={This paper shows how the multipulse method from digital signal processing can be used to accurately synthesize signals obtained from blood pressure and blood flow velocity sensors during posture change from sitting to standing. The multipulse method can be used to analyze signals that are composed of pulses of varying amplitudes. One of the advantages of the multipulse method is that it is able to produce an accurate and efficient representation of the signals at high resolution. The signals are represented as a set of input impulses passed through an autoregressive (AR) filter. The parameters that define the AR filter can be used to distinguish different conditions. In addition, the AR coefficients can be transformed to tube radii associated with digital wave guides, as well as pole-zero representation. Analysis of the dynamics of the model parameters have potential to provide better insight and understanding of the underlying physiological control mechanisms. For example, our data indicate that the tube radii may be related to the diameter of the blood vessels.}, number={2}, journal={Mathematical Biosciences and Engineering}, author={Justice, D. H. and Trussell, H. J. and Olufsen, M. S.}, year={2006}, pages={419–440} }
 @inbook{larsen_andreasen_larsen_olufsen_ottesen_2006, place={London}, title={Cardiovascular modeling at IMFUFA, in The way through science and philosophy}, volume={4}, booktitle={Tributes}, publisher={College Publications}, author={Larsen, J.K. and Andreasen, V. and Larsen, H. and Olufsen, M.S. and Ottesen, J.T.}, editor={Andersen, H.B. and Christiansen, F.V. and Jorgensen, K.F. and Hendricks, V.F.Editors}, year={2006}, pages={87–96} }
 @article{olufsen_tran_ottesen_lipsitz_novak_2006, title={Modeling baroreflex regulation of heart rate during orthostatic stress}, volume={291}, ISSN={["1522-1490"]}, DOI={10.1152/ajpregu.00205.2006}, abstractNote={During orthostatic stress, arterial and cardiopulmonary baroreflexes play a key role in maintaining arterial pressure by regulating heart rate. This study presents a mathematical model that can predict the dynamics of heart rate regulation in response to postural change from sitting to standing. The model uses blood pressure measured in the finger as an input to model heart rate dynamics in response to changes in baroreceptor nerve firing rate, sympathetic and parasympathetic responses, vestibulo-sympathetic reflex, and concentrations of norepinephrine and acetylcholine. We formulate an inverse least squares problem for parameter estimation and successfully demonstrate that our mathematical model can accurately predict heart rate dynamics observed in data obtained from healthy young, healthy elderly, and hypertensive elderly subjects. One of our key findings indicates that, to successfully validate our model against clinical data, it is necessary to include the vestibulo-sympathetic reflex. Furthermore, our model reveals that the transfer between the nerve firing and blood pressure is nonlinear and follows a hysteresis curve. In healthy young people, the hysteresis loop is wide, whereas, in healthy and hypertensive elderly people, the hysteresis loop shifts to higher blood pressure values, and its area is diminished. Finally, for hypertensive elderly people, the hysteresis loop is generally not closed, indicating that, during postural change from sitting to standing, baroreflex modulation does not return to steady state during the first minute of standing.}, number={5}, journal={AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY}, author={Olufsen, Mette S. and Tran, Hien T. and Ottesen, Johnny T. and Lipsitz, Lewis A. and Novak, Vera}, year={2006}, month={Nov}, pages={R1355–R1368} }
 @article{olufsen_ottesen_tran_ellwein_lipsitz_novak_2005, title={Blood pressure and blood flow variation during postural change from sitting to standing: model development and validation}, volume={99}, ISSN={["1522-1601"]}, DOI={10.1152/japplphysiol.00177.2005}, abstractNote={Short-term cardiovascular responses to postural change from sitting to standing involve complex interactions between the autonomic nervous system, which regulates blood pressure, and cerebral autoregulation, which maintains cerebral perfusion. We present a mathematical model that can predict dynamic changes in beat-to-beat arterial blood pressure and middle cerebral artery blood flow velocity during postural change from sitting to standing. Our cardiovascular model utilizes 11 compartments to describe blood pressure, blood flow, compliance, and resistance in the heart and systemic circulation. To include dynamics due to the pulsatile nature of blood pressure and blood flow, resistances in the large systemic arteries are modeled using nonlinear functions of pressure. A physiologically based submodel is used to describe effects of gravity on venous blood pooling during postural change. Two types of control mechanisms are included: 1) autonomic regulation mediated by sympathetic and parasympathetic responses, which affect heart rate, cardiac contractility, resistance, and compliance, and 2) autoregulation mediated by responses to local changes in myogenic tone, metabolic demand, and CO(2) concentration, which affect cerebrovascular resistance. Finally, we formulate an inverse least-squares problem to estimate parameters and demonstrate that our mathematical model is in agreement with physiological data from a young subject during postural change from sitting to standing.}, number={4}, journal={JOURNAL OF APPLIED PHYSIOLOGY}, author={Olufsen, MS and Ottesen, JT and Tran, HT and Ellwein, LM and Lipsitz, LA and Novak, V}, year={2005}, month={Oct}, pages={1523–1537} }
 @book{ottesen_olufsen_larsen_2004, title={Applied Mathematical Models in Human Physiology}, ISBN={9780898715392 9780898718287}, url={http://dx.doi.org/10.1137/1.9780898718287}, DOI={10.1137/1.9780898718287}, abstractNote={Preface 1. Introduction 2. Cardiovascular and pulmonary physiology and anatomy 3. Blood flow in the heart 4. The ejection effect of the pumping heart 5. Modeling flow and pressure in the systemic arteries 6. A cardiovascular model 7. A baroreceptor model 8. Respiration Appendices Bibliography Index.}, publisher={Society for Industrial and Applied Mathematics}, author={Ottesen, Johnny T. and Olufsen, Mette S. and Larsen, Jesper K.}, year={2004}, month={Jan} }
 @article{olufsen_tran_ottesen_2004, title={Modeling Cerebral Blood Flow Control During Posture Change from Sitting to Standing}, volume={4}, ISSN={1567-8822}, url={http://dx.doi.org/10.1023/b:care.0000025122.46013.1a}, DOI={10.1023/b:care.0000025122.46013.1a}, abstractNote={Hypertension, decreased cerebral blood flow, and diminished cerebral blood flow velocity regulation, are among the first signs indicating the presence of cerebral vascular disease. In this paper, we will present a mathematical model that can predict blood flow and pressure during posture change from sitting to standing. The mathematical model uses a compartmental approach to describe pulsatile blood flow velocity and pressure in a number of compartments representing the systemic circulation. Our model includes compartments representing the trunk and upper extremities, the lower extremities, the brain, and the heart. We use physiologically based control mechanisms to describe the regulation of cerebral blood flow velocity and arterial pressure in response to orthostatic hypotension resulting from postural change. To justify the fidelity of our mathematical model and control mechanisms development, we will show validation results of our model against experimental data from a young subject.}, number={1}, journal={Cardiovascular Engineering}, publisher={Springer Nature}, author={Olufsen, Mette and Tran, Hien and Ottesen, Johnny}, year={2004}, month={Mar}, pages={47–58} }
 @article{olufsen_nadim_2004, title={On deriving lumped models for blood flow and pressure in the systemic arteries}, volume={1}, ISSN={["1551-0018"]}, DOI={10.3934/mbe.2004.1.61}, abstractNote={Windkessel and similar lumped models are often used to represent blood flow and pressure in systemic arteries. The windkessel model was originally developed by Stephen Hales (1733) and Otto Frank (1899) who used it to describe blood flow in the heart. In this paper we start with the one-dimensional axisymmetric Navier-Stokes equations for time-dependent blood flow in a rigid vessel to derive lumped models relating flow and pressure. This is done through Laplace transform and its inversion via residue theory. Upon keeping contributions from one, two, or more residues, we derive lumped models of successively higher order. We focus on zeroth, first and second order models and relate them to electrical circuit analogs, in which current is equivalent to flow and voltage to pressure. By incorporating e ffects of compliance through addition of capacitors, windkessel and related lumped models are obtained. Our results show that given the radius of a blood vessel, it is possible to determine the order of the model that would be appropriate for analyzing the flow and pressure in that vessel. For instance, in small rigid vessels ($R <$ 0.2 cm) it is adequate to use Poiseuille's law to express the relation between flow and pressure, whereas for large vessels it might be necessary to incorporate spatial dependence by using a one-dimensional model accounting for axial variations.}, number={1}, journal={MATHEMATICAL BIOSCIENCES AND ENGINEERING}, author={Olufsen, MS and Nadim, A}, year={2004}, month={Jun}, pages={61–80} }
 @article{olufsen_whittington_camperi_kopell_2003, title={New roles for the gamma rhythm: Population tuning and preprocessing for the beta rhythm}, volume={14}, ISSN={["0929-5313"]}, DOI={10.1023/A:1021124317706}, number={1}, journal={JOURNAL OF COMPUTATIONAL NEUROSCIENCE}, author={Olufsen, MS and Whittington, MA and Camperi, M and Kopell, N}, year={2003}, pages={33–54} }
 @article{olufsen_nadim_lipsitz_2002, title={Dynamics of cerebral blood flow regulation explained using a lumped parameter model}, volume={282}, ISSN={["1522-1490"]}, DOI={10.1152/ajpregu.00285.2001}, abstractNote={The dynamic cerebral blood flow response to sudden hypotension during posture change is poorly understood. To better understand the cardiovascular response to hypotension, we used a windkessel model with two resistors and a capacitor to reproduce beat-to-beat changes in middle cerebral artery blood flow velocity (transcranial Doppler measurements) in response to arterial pressure changes measured in the finger (Finapres). The resistors represent lumped systemic and peripheral resistances in the cerebral vasculature, whereas the capacitor represents a lumped systemic compliance. Ten healthy young subjects were studied during posture change from sitting to standing. Dynamic variations of the peripheral and systemic resistances were extracted from the data on a beat-to-beat basis. The model shows an initial increase, followed approximately 10 s later by a decline in cerebrovascular resistance. The model also suggests that the initial increase in cerebrovascular resistance can explain the widening of the cerebral blood flow pulse observed in young subjects. This biphasic change in cerebrovascular resistance is consistent with an initial vasoconstriction, followed by cerebral autoregulatory vasodilation.}, number={2}, journal={AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY}, author={Olufsen, MS and Nadim, A and Lipsitz, LA}, year={2002}, month={Feb}, pages={R611–R622} }
 @inbook{olufsen_2001, title={A One-Dimensional Fluid Dynamic Model of the Systemic Arteries}, ISBN={9781461265399 9781461301516}, ISSN={0940-6573}, url={http://dx.doi.org/10.1007/978-1-4613-0151-6_9}, DOI={10.1007/978-1-4613-0151-6_9}, booktitle={Computational Modeling in Biological Fluid Dynamics}, publisher={Springer New York}, author={Olufsen, Mette S.}, year={2001}, pages={167–187} }
 @article{olufsen_lipsitz_nadim_2001, title={A lumped parameter model for cerebral blood flow regulation}, volume={51}, journal={Advances in Bioengineering}, author={Olufsen, M.S. and Lipsitz, L.A. and Nadim, A.}, year={2001}, pages={277–278} }
 @inbook{olufsen_2000, place={Washington, D.C.}, series={Studies in health technology and informatics}, title={A one-dimensional fluid dynamic model of the systemic arteries}, ISBN={9781586030261}, DOI={10.3233/978-1-60750-915-8-79}, booktitle={Mathematical modelling in medicine}, publisher={IOS Press}, author={Olufsen, M.S.}, editor={Ottesen, Johnny T. and Danielsen, M.Editors}, year={2000}, pages={79–97}, collection={Studies in health technology and informatics} }
 @article{olufsen_peskin_kim_pedersen_nadim_larsen_2000, title={Numerical Simulation and Experimental Validation of Blood Flow in Arteries with Structured-Tree Outflow Conditions}, volume={28}, ISSN={0090-6964}, url={http://dx.doi.org/10.1114/1.1326031}, DOI={10.1114/1.1326031}, number={11}, journal={Annals of Biomedical Engineering}, publisher={Springer Nature}, author={Olufsen, Mette S. and Peskin, Charles S. and Kim, Won Yong and Pedersen, Erik M. and Nadim, Ali and Larsen, Jesper}, year={2000}, month={Nov}, pages={1281–1299} }
 @article{olufsen_1999, title={Structured tree outflow condition for blood flow  in larger systemic arteries}, volume={276}, ISSN={0363-6135 1522-1539}, url={http://dx.doi.org/10.1152/ajpheart.1999.276.1.h257}, DOI={10.1152/ajpheart.1999.276.1.h257}, abstractNote={A central problem in modeling blood flow and pressure in the larger systemic arteries is determining a physiologically based boundary condition so that the arterial tree can be truncated after a few generations. We have used a structured tree attached to the terminal branches of the truncated arterial tree in which the root impedance is estimated using a semianalytical approach based on a linearization of the viscous axisymmetric Navier-Stokes equations. This provides a dynamic boundary condition that maintains the phase lag between blood flow and pressure as well as the high-frequency oscillations present in the impedance spectra. Furthermore, it accommodates the wave propagation effects for the entire systemic arterial tree. The result is a model that is physiologically adequate as well as computationally feasible. For validation, we have compared the structured tree model with a pure resistance and a windkessel model as well as with measured data.}, number={1}, journal={American Journal of Physiology-Heart and Circulatory Physiology}, publisher={American Physiological Society}, author={Olufsen, Mette S.}, year={1999}, month={Jan}, pages={H257–H268} }