@article{mohanty_karbalaeisadegh_blackwell_ali_masuodi_egan_muller_2020, title={In Vivo Assessment of Pulmonary Fibrosis and Pulmonary Edema in Rodents Using Ultrasound Multiple Scattering}, volume={67}, ISSN={["1525-8955"]}, DOI={10.1109/TUFFC.2020.3023611}, abstractNote={Idiopathic pulmonary fibrosis (IPF) affects 200 000 patients in the United States of America. IPF is responsible for changes in the micro-architecture of the lung parenchyma, such as thickening of the alveolar walls, which reduces compliance and elasticity. In this study, we verify the hypothesis that changes in the microarchitecture of the lung parenchyma can be characterized by exploiting multiple scattering of ultrasound waves by the alveolar structure. Ultrasound propagation in a highly scattering regime follows a diffusion process, which can be characterized using the diffusion constant. We hypothesize that in a fibrotic lung, the thickening of the alveolar wall reduces the amount of air (compared with a healthy lung), thereby minimizing the scattering events. Pulmonary fibrosis is created in Sprague–Dawley rats by instilling bleomycin into the airway. The rats are studied within 3 weeks after bleomycin administration. Using a 128-element linear array transducer operating at 7.8 MHz, in vivo experimental data are obtained from Sprague–Dawley rats and the transport mean free path (L*) and backscatter frequency shift (BFS) are evaluated. Significant differences ( ${p}< 0.05$ ) in the L* values between control and fibrotic rats and in the BFS values between fibrotic and edematous rats showcase the potential of these parameters for diagnosis and monitoring of IPF.}, number={11}, journal={IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL}, author={Mohanty, Kaustav and Karbalaeisadegh, Yasamin and Blackwell, John William and Ali, Mir Hasnain and Masuodi, Behrooz and Egan, Thomas and Muller, Marie}, year={2020}, month={Nov}, pages={2274–2280} }
 @article{mohanty_roshankhah_ulrich_muller_2020, title={Lesion Imaging and Target Detection in Multiple Scattering (LITMUS) Media}, volume={67}, ISSN={["1525-8955"]}, DOI={10.1109/TUFFC.2020.2990704}, abstractNote={We present an ultrasound algorithm [lesion imaging and target detection in multiple scattering (LITMUS)] suited to image lesions (hypoechoic) or targets (hyperechoic) in highly complex structures. In such media, standard ultrasound imaging techniques fail to detect lesions or targets due to aberrations and the loss of linearity between propagation distance and propagation time, caused by multiple scattering of ultrasound waves. The present algorithm (LITMUS) has the capability to predict the location as well as the size of such lesions/targets by using the multiple scattered ultrasound signals to its advantage. In this experimental and computational study, we use an ultrasound linear array. Lesions/targets are embedded at varying depths inside multiple scattering media with varying density of scatterers. In the simulations, plastic scatterers are used as the source of multiple scattering in a propagation medium (water). In the experiments, melamine sponges are used, with air alveoli as the scattering source. For multiple locations along the transducer, the incoherent backscattered intensity of the backscattered signals is extracted and the linear growth of the diffusive halo over time is tracked. Sudden changes in this growth indicate the presence of a region with reduced heterogeneity, indicative of the presence of a lesion/target. This methodology is combined with a depression detection algorithm to predict the size and location of the lesion/targets with high fidelity, despite the presence of strong heterogeneity and multiple scattering.}, number={11}, journal={IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL}, author={Mohanty, Kaustav and Roshankhah, Roshan and Ulrich, Micah and Muller, Marie}, year={2020}, month={Nov}, pages={2281–2290} }
 @article{nandi_mohanty_nellenbach_erb_muller_brown_2020, title={Ultrasound Enhanced Synthetic Platelet Therapy for Augmented Wound Repair}, volume={6}, ISSN={["2373-9878"]}, DOI={10.1021/acsbiomaterials.9b01976}, abstractNote={Native platelets perform a number of functions within the wound healing process, including interacting with fibrin fibers at the wound site to bring about retraction after clot formation. Clot retraction improves clot stability and enhances the function of the fibrin network as a provisional matrix to support cellular infiltration of the wound site, thus facilitating tissue repair and remodeling after hemostasis. In cases of traumatic injury or disease, platelets can become depleted and this process disrupted. To that end, our lab has developed synthetic platelet-like particles (PLPs) that recapitulate the clot retraction abilities of native platelets through a Brownian-wrench driven mechanism that drives fibrin network densification and clot retraction over time, however, this Brownian-motion driven process occurs on a longer time scale than native active actin/myosin-driven platelet-mediated clot retraction. We hypothesized that a combinatorial therapy comprised of ultrasound stimulation of PLP motion within fibrin clots would facilitate a faster induction of clot retraction on a more platelet-mimetic time scale and at a lower dosage than required for PLPs acting alone. We found that application of ultrasound in combination with a subtherapeutic dosage of PLPs resulted in increased clot density and stiffness, improved fibroblast migration in vitro and increased epidermal thickness and angiogenesis in vivo, indicating that this combination therapy has potential to facilitate multiphase pro-healing outcomes. Additionally, while these particular studies focus on the role of ultrasound in enhancing specific interactions between fibrin-binding synthetic PLPs embedded within fibrin networks, these studies have wide applicability in understanding the role of ultrasound stimulation in enhancing multi-scale colloidal interactions within fibrillar matrices.}, number={5}, journal={ACS BIOMATERIALS SCIENCE & ENGINEERING}, author={Nandi, Seema and Mohanty, Kaustav and Nellenbach, Kimberly and Erb, Mary and Muller, Marie and Brown, Ashley C.}, year={2020}, month={May}, pages={3026–3036} }
 @article{mohanty_yousefian_karbalaeisadegh_ulrich_grimal_muller_2019, title={Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study}, volume={114}, ISBN={1879-0534}, DOI={10.1016/j.compbiomed.2019.103457}, abstractNote={The goal of this study is to estimate micro-architectural parameters of cortical porosity such as pore diameter (φ), pore density (ρ) and porosity (ν) of cortical bone from ultrasound frequency dependent attenuation using an artificial neural network (ANN). First, heterogeneous structures with controlled pore diameters and pore densities (mono-disperse) were generated, to mimic simplified structure of cortical bone. Then, more realistic structures were obtained from high resolution CT scans of human cortical bone. 2-D finite-difference time-domain simulations were conducted to calculate the frequency-dependent attenuation in the 1-8 MHz range. An ANN was then trained with the ultrasonic attenuation at different frequencies as the input feature vectors while the output was set as the micro-architectural parameters (pore diameter, pore density and porosity). The ANN is composed of three fully connected dense layers with 24, 12 and 6 neurons, connected to the output layer. The dataset was trained over 6000 epochs with a batch size of 16. The trained ANN exhibits the ability to predict the micro-architectural parameters with high accuracy and low losses. ANN approaches could potentially be used as a tool to help inform physics-based modelling of ultrasound propagation in complex media such as cortical bone. This will lead to the solution of inverse-problems to retrieve bone micro-architectural parameters from ultrasound measurements for the non-invasive diagnosis and monitoring osteoporosis.}, journal={COMPUTERS IN BIOLOGY AND MEDICINE}, author={Mohanty, Kaustav and Yousefian, Omid and Karbalaeisadegh, Yasamin and Ulrich, Micah and Grimal, Quentin and Muller, Marie}, year={2019}, month={Nov} }
 @article{mohanty_yousefian_karbalaeisadegh_ulrich_muller_2019, title={Predicting Structural Properties of Cortical Bone by Combining Ultrasonic Attenuation and an Artificial Neural Network (ANN): 2-D FDTD Study}, volume={11662}, ISBN={["978-3-030-27201-2"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-030-27202-9_37}, abstractNote={The goal of this paper is to predict the micro-architectural parameters of cortical bone such as pore diameter (ϕ) and porosity (ν) from ultrasound attenuation measurements using an artificial neural network (ANN). Slices from a 3-D CT scan of human femur are obtained. The micro-architectural parameters of porosity such as average pore size and porosity are calculated using image processing. When ultrasound waves propagate in porous structures, attenuation is observed due to scattering. Two-dimensional finite-difference time-domain simulations are carried out to obtain frequency dependent attenuation in those 2D structures. An artificial neural network (ANN) is then trained with the input feature vector as the frequency dependent attenuation and output as pore diameter (ϕ) and porosity (ν). The ANN is composed of one input layer, 3 hidden layers and one output layer, all of which are fully connected. 340 attenuation data sets were acquired and trained over 2000 epochs with a batch size of 32. Data was split into train, validation and test. It was observed that the ANN predicted the micro-architectural parameters of the cortical bone with high accuracies and low losses with a minimum R2 (goodness of fit) value of 0.95. ANN approaches could potentially help inform the solution of inverse-problems to retrieve bone porosity from ultrasound measurements. Ultimately, those inverse-problems could be used for the non-invasive diagnosis and monitoring of osteoporosis.}, journal={IMAGE ANALYSIS AND RECOGNITION, ICIAR 2019, PT I}, author={Mohanty, Kaustav and Yousefian, Omid and Karbalaeisadegh, Yasamin and Ulrich, Micah and Muller, Marie}, year={2019}, pages={407–417} }
 @article{mohanty_papadopoulou_newsome_shelton_dayton_muller_2019, title={Ultrasound multiple scattering with microbubbles can differentiate between tumor and healthy tissue in vivo}, volume={64}, ISSN={["1361-6560"]}, url={https://europepmc.org/articles/PMC6876296}, DOI={10.1088/1361-6560/ab1a44}, abstractNote={Most solid tumors are characterized by highly dense, isotropic vessel networks. Characterization of such features has shown promise for early cancer diagnosis. Ultrasound diffusion has been used to characterize the micro-architecture of complex media, such as bone and the lungs. In this work, we examine a non-invasive diffusion-based ultrasound technique to assess neo-vascularization. Because the diffusion constant reflects the density of scatterers in heterogeneous media, we hypothesize that by injecting microbubbles into the vasculature, ultrasound diffusivity can reflect vascular density (VD), thus differentiating the microvascular patterns between tumors and healthy tissue. The diffusion constant and its anisotropy are shown to be significantly different between fibrosarcoma tumors (n  =  16) and control tissue (n  =  18) in a rat animal model in vivo. The diffusion constant values for control and tumor were found to be 1.38  ±  0.51 mm2 µs−1 and 0.65  ±  0.27 mm2 µs−1, respectively. These results are corroborated with VD from acoustic angiography (AA) data, confirming increased vessel density in tumors compared to controls. The diffusion constant offers a promising way to quantitatively assess vascular networks when combined with contrast agents, which may allow early tumor detection and characterization.}, number={11}, journal={PHYSICS IN MEDICINE AND BIOLOGY}, author={Mohanty, Kaustav and Papadopoulou, Virginie and Newsome, Isabel G. and Shelton, Sarah and Dayton, Paul A. and Muller, Marie}, year={2019}, month={Jun} }
 @article{mohanty_blackwell_egan_muller_2017, title={CHARACTERIZATION OF THE LUNG PARENCHYMA USING ULTRASOUND MULTIPLE SCATTERING}, volume={43}, ISSN={["1879-291X"]}, DOI={10.1016/j.ultrasmedbio.2017.01.011}, abstractNote={The purpose of the study described here was to showcase the application of ultrasound to quantitative characterization of the micro-architecture of the lung parenchyma to predict the extent of pulmonary edema. The lung parenchyma is a highly complex and diffusive medium for which ultrasound techniques have remained qualitative. The approach presented here is based on ultrasound multiple scattering and exploits the complexity of ultrasound propagation in the lung structure. The experimental setup consisted of a linear transducer array with an 8-MHz central frequency placed in contact with the lung surface. The diffusion constant D and transport mean free path L* of the lung parenchyma were estimated by separating the incoherent and coherent intensities in the near field and measuring the growth of the incoherent diffusive halo over time. Significant differences were observed between the L* values obtained in healthy and edematous rat lungs in vivo. In the control rat lung, L* was found to be 332 μm (±48.8 μm), whereas in the edematous lung, it was 1040 μm (±90 μm). The reproducibility of the measurements of L* and D was tested in vivo and in phantoms made of melamine sponge with varying air volume fractions. Two-dimensional finite difference time domain numerical simulations were carried out on rabbit lung histology images with varying degrees of lung collapse. Significant correlations were observed between air volume fraction and L* in simulation (r = -0.9542, p < 0.0117) and sponge phantom (r = -0.9932, p < 0.0068) experiments. Ex vivo measurements of a rat lung in which edema was simulated by adding phosphate-buffered saline revealed a linear relationship between the fluid volume fraction and L*. These results illustrate the potential of methods based on ultrasound multiple scattering for the quantitative characterization of the lung parenchyma.}, number={5}, journal={ULTRASOUND IN MEDICINE AND BIOLOGY}, author={Mohanty, Kaustav and Blackwell, John and Egan, Thomas and Muller, Marie}, year={2017}, month={May}, pages={993–1003} }
 @article{du_mohanty_mullera_2017, title={Microstructural characterization of trabecular bone using ultrasonic backscattering and diffusion parameters}, volume={141}, ISSN={["1520-8524"]}, DOI={10.1121/1.4982824}, abstractNote={Finite differences time domain methods were utilized to simulate ultrasound propagation and scattering in anisotropic trabecular bone structures obtained from high resolution Computed Tomography (CT). The backscattered signals were collected and the incoherent contribution was extracted. The diffusion constant was calculated for propagations along and across the main direction of anisotropy, and was used to characterize the anisotropy of the trabecular microstructures. In anisotropic structures, the diffusion constant was significantly different in both directions, and the anisotropy of the diffusion constant was strongly correlated to the structural anisotropy measured on the CT images. These results indicate that metrics based on diffusion can be used to quantify the anisotropy of complex structures such as trabecular bone.}, number={5}, journal={JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA}, author={Du, Hualong and Mohanty, Kaustav and Mullera, Marie}, year={2017}, month={May}, pages={EL445–EL451} }