@article{roshankhah_blackwell_yuan_egan_muller_2023, title={Investigating pulmonary edema in rat lungs using separation of multiple scattering and single scattering contribution}, volume={153}, ISSN={["1520-8524"]}, DOI={10.1121/10.0018614}, abstractNote={Lung ultrasound imaging is challenging due to multiple scattering (MS) from alveoli. Conventional B-mode does not provide lung microstructure images. However, MS signals can provide valuable information about structure and alveolar distribution and investigating conditions such as pulmonary edema. Lung edema results in fluid buildup in interstitial spaces and alveoli, affecting density of alveoli. Previously, we demonstrated that changes in the distribution of scatterers due to edema result in changes in the wave diffusion regime and the scattering mean free path was sensitive to lung injury due to induced edema in rodents. In the present study, we introduce a novel way of quantifying MS in lungs by isolating the single scattering (SS) and MS contributions and processing them separately. After inducing different severity of edema using ischemia reperfusion injury in 18 rats, full synthetic aperture transmit sequences were used to acquire backscattered signals. The SS/MS contributions were separated using singular value decomposition. The separated SS/MS intensities were calculated and a new parameter defined as the rate of decay in intensity with depth. To assess edema severity and method validation, ex vivo CT lung images were assigned scores compared with this novel biomarker (R = 0.47, p = 0.021). Lung wet/dry ratio was also compared (R = 0.52, p = 0.009).}, number={3}, journal={JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA}, author={Roshankhah, Roshan and Blackwell, John and Yuan, Hong and Egan, Thomas M. and Muller, Marie}, year={2023}, month={Mar} }
 @article{cole_roshankhah_blackwell_montgomery_egan_muller_2023, title={Random matrix theory to quantify micro-structural changes in rodent lungs due to pulmonary diseases}, volume={153}, ISSN={["1520-8524"]}, DOI={10.1121/10.0018613}, abstractNote={We exploit the random matrix theory to detect changes in rodent lungs exhibiting pulmonary fibrosis and edema. Coherences in the backscattered signals are stronger when single scattering dominates (fibrosis/edema). On the contrary, healthy lungs exhibit more apparent randomness due to multiple scattering. This leads to differences in the distribution of eigenvalues, which can be retrieved using Singular Value Decomposition of the Inter-elementResponse Matrix (IRM). We use features of the eigenvalue distribution (E(x), the expected value, and, the eigenvalue with the highest probability) to quantify changes in lung parenchyma and investigate whether they can improve the specificity of quantitative ultrasound to lung diseases. IRMs were acquired from 51 rat lungs (10 controls, 18 edematous, 17 fibrotic, 6 fibrotic rats, which were treated with Nintedanib) using a 128-element linear array (Verasonics L11-4v, 7.8 MHz). Severity of fibrosis and edema were quantified by histology and the ratio of wet to dry weight. Both parameters showed significant differences between edematous and fibrotic lungs, and between control and fibrotic lungs, which was significantly correlated to both the severity of fibrosis and edema. E(x) was significantly correlated to the severity of fibrosis. This suggests that these parameters could be part of a toolkit for the quantitative assessment of lung diseases.}, number={3}, journal={JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA}, author={Cole, Azadeh D. and Roshankhah, Roshan and Blackwell, John and Montgomery, Stephanie A. and Egan, Thomas M. and Muller, Marie}, year={2023}, month={Mar} }
 @article{roshankhah_blackwell_ali_masuodi_egan_muller_2021, title={Detecting pulmonary nodules by using ultrasound multiple scattering}, volume={150}, ISSN={["1520-8524"]}, DOI={10.1121/10.0006666}, abstractNote={Although X-Ray Computed Tomography (CT) is widely used for detecting pulmonary nodules inside the parenchyma, it cannot be used during video-assisted surgical procedures. Real-time, non-ionizing, ultrasound-based techniques are an attractive alternative for nodule localization to ensure safe resection margins during surgery. Conventional ultrasound B-mode imaging of the lung is challenging due to multiple scattering. However, the multiple scattering contribution can be exploited to detect regions inside the lung containing no scatterers. Pulmonary nodules are homogeneous regions in contrast to the highly scattering parenchyma containing millions of air-filled alveoli. We developed a method relying on mapping the multiple scattering contribution inside the highly scattering lung to detect and localize pulmonary nodules. Impulse response matrices were acquired in ex-vivo pig and dog lungs using a linear array transducer to semi-locally investigate the backscattered field. Extracting the multiple-scattering contribution using singular-value decomposition and combining it with a depression detection algorithm allowed us to detect and localize regions with less multiple scattering, associated with the nodules. The feasibility of this method was demonstrated in five ex-vivo lungs containing a total of 20 artificial nodules. Ninety-five percent of the nodules were detected. Nodule depth and diameter significantly correlated with their ex-vivo CT-estimated counterparts (R = 0.960, 0.563, respectively).}, number={6}, journal={JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA}, author={Roshankhah, Roshan and Blackwell, John and Ali, Mir H. and Masuodi, Behrooz and Egan, Thomas and Muller, Marie}, year={2021}, month={Dec}, pages={4095–4102} }
 @article{lye_roshankhah_karbalaeisadegh_montgomery_egan_muller_mamou_2021, title={In vivo assessment of pulmonary fibrosis and edema in rodents using the backscatter coefficient and envelope statisticsa)}, volume={150}, ISSN={["1520-8524"]}, DOI={10.1121/10.0005481}, abstractNote={Quantitative ultrasound methods based on the backscatter coefficient (BSC) and envelope statistics have been used to quantify disease in a wide variety of tissues, such as prostate, lymph nodes, breast, and thyroid. However, to date, these methods have not been investigated in the lung. In this study, lung properties were quantified by BSC and envelope statistical parameters in normal, fibrotic, and edematous rat lungs in vivo. The average and standard deviation of each parameter were calculated for each lung as well as the evolution of each parameter with acoustic propagation time within the lung. The transport mean free path and backscattered frequency shift, two parameters that have been successfully used to assess pulmonary fibrosis and edema in prior work, were evaluated in combination with the BSC and envelope statistical parameters. Multiple BSC and envelope statistical parameters were found to provide contrast between control and diseased lungs. BSC and envelope statistical parameters were also significantly correlated with fibrosis severity using the modified Ashcroft fibrosis score as the histological gold standard. These results demonstrate the potential for BSC and envelope statistical parameters to improve the diagnosis of pulmonary fibrosis and edema as well as monitor pulmonary fibrosis.}, number={1}, journal={JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA}, author={Lye, Theresa H. and Roshankhah, Roshan and Karbalaeisadegh, Yasamin and Montgomery, Stephanie A. and Egan, Thomas M. and Muller, Marie and Mamou, Jonathan}, year={2021}, month={Jul}, pages={183–192} }
 @article{roshankhah_karbalaeisadegh_greer_mento_soldati_smargiassi_inchingolo_torri_perrone_aylward_et al._2021, title={Investigating training-test data splitting strategies for automated segmentation and scoring of COVID-19 lung ultrasound images}, volume={150}, ISSN={["1520-8524"]}, DOI={10.1121/10.0007272}, abstractNote={Ultrasound in point-of-care lung assessment is becoming increasingly relevant. This is further reinforced in the context of the COVID-19 pandemic, where rapid decisions on the lung state must be made for staging and monitoring purposes. The lung structural changes due to severe COVID-19 modify the way ultrasound propagates in the parenchyma. This is reflected by changes in the appearance of the lung ultrasound images. In abnormal lungs, vertical artifacts known as B-lines appear and can evolve into white lung patterns in the more severe cases. Currently, these artifacts are assessed by trained physicians, and the diagnosis is qualitative and operator dependent. In this article, an automatic segmentation method using a convolutional neural network is proposed to automatically stage the progression of the disease. 1863 B-mode images from 203 videos obtained from 14 asymptomatic individual,14 confirmed COVID-19 cases, and 4 suspected COVID-19 cases were used. Signs of lung damage, such as the presence and extent of B-lines and white lung areas, are manually segmented and scored from zero to three (most severe). These manually scored images are considered as ground truth. Different test-training strategies are evaluated in this study. The results shed light on the efficient approaches and common challenges associated with automatic segmentation methods.}, number={6}, journal={JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA}, author={Roshankhah, Roshan and Karbalaeisadegh, Yasamin and Greer, Hastings and Mento, Federico and Soldati, Gino and Smargiassi, Andrea and Inchingolo, Riccardo and Torri, Elena and Perrone, Tiziano and Aylward, Stephen and et al.}, year={2021}, month={Dec}, pages={4118–4127} }
 @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} }