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Xie Z, Fan M, Ji N, Ji Z, Xu L, Ma J. Ultrasound wavelet spectra enable direct tissue recognition and full-color visualization. ULTRASONICS 2024; 142:107395. [PMID: 38972175 DOI: 10.1016/j.ultras.2024.107395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/10/2024] [Accepted: 06/27/2024] [Indexed: 07/09/2024]
Abstract
Traditional brightness-mode ultrasound imaging is primarily constrained by the low specificity among tissues and the inconsistency among sonographers. The major cause is the imaging method that represents the amplitude of echoes as brightness and ignores other detailed information, leaving sonographers to interpret based on organ contours that depend highly on specific imaging planes. Other ultrasound imaging modalities, color Doppler imaging or shear wave elastography, overlay motion or stiffness information to brightness-mode images. However, tissue-specific scattering properties and spectral patterns remain unknown in ultrasound imaging. Here we demonstrate that the distribution (size and average distance) of scattering particles leads to characteristic wavelet spectral patterns, which enables tissue recognition and high-contrast ultrasound imaging. Ultrasonic wavelet spectra from similar particle distributions tend to cluster in the eigenspace according to principal component analysis, whereas those with different distributions tend to be distinguishable from one another. For each distribution, a few wavelet spectra are unique and act as a fingerprint to recognize the corresponding tissue. Illumination of specific tissues and organs with designated colors according to the recognition results yields high-contrast ultrasound imaging. The fully-colorized tissue-specific ultrasound imaging potentially simplifies the interpretation and promotes consistency among sonographers, or even enables the applicability for non-professionals.
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Affiliation(s)
- Zhun Xie
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China
| | - Mengzhi Fan
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China
| | - Nan Ji
- Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Zhili Ji
- Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China
| | - Lijun Xu
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China
| | - Jianguo Ma
- School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, 100191, China.
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Li S, Tsui PH, Wu W, Zhou Z, Wu S. Multimodality quantitative ultrasound envelope statistics imaging based support vector machines for characterizing tissue scatterer distribution patterns: Methods and application in detecting microwave-induced thermal lesions. ULTRASONICS SONOCHEMISTRY 2024; 107:106910. [PMID: 38772312 PMCID: PMC11128516 DOI: 10.1016/j.ultsonch.2024.106910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 05/01/2024] [Accepted: 05/13/2024] [Indexed: 05/23/2024]
Abstract
Ultrasound envelope statistics imaging, including ultrasound Nakagami imaging, homodyned-K imaging, and information entropy imaging, is an important group of quantitative ultrasound techniques for characterizing tissue scatterer distribution patterns, such as scatterer concentrations and arrangements. In this study, we proposed a machine learning approach to integrate the strength of multimodality quantitative ultrasound envelope statistics imaging techniques and applied it to detecting microwave ablation induced thermal lesions in porcine liver ex vivo. The quantitative ultrasound parameters included were homodyned-K α which is a scatterer clustering parameter related to the effective scatterer number per resolution cell, Nakagami m which is a shape parameter of the envelope probability density function, and Shannon entropy which is a measure of signal uncertainty or complexity. Specifically, the homodyned-K log10(α), Nakagami-m, and horizontally normalized Shannon entropy parameters were combined as input features to train a support vector machine (SVM) model to classify thermal lesions with higher scatterer concentrations from normal tissues with lower scatterer concentrations. Through heterogeneous phantom simulations based on Field II, the proposed SVM model showed a classification accuracy above 0.90; the area accuracy and Dice score of higher-scatterer-concentration zone identification exceeded 83% and 0.86, respectively, with the Hausdorff distance <26. Microwave ablation experiments of porcine liver ex vivo at 60-80 W, 1-3 min showed that the SVM model achieved a classification accuracy of 0.85; compared with single log10(α),m, or hNSE parametric imaging, the SVM model achieved the highest area accuracy (89.1%) and Dice score (0.77) as well as the smallest Hausdorff distance (46.38) of coagulation zone identification. We concluded that the proposed multimodality quantitative ultrasound envelope statistics imaging based SVM approach can enhance the capability to characterize tissue scatterer distribution patterns and has the potential to detect the thermal lesions induced by microwave ablation.
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Affiliation(s)
- Sinan Li
- Department of Biomedical Engineering, College of Chemistry and Life Sciences, Beijing University of Technology, Beijing, China
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Liver Research Center, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan; Research Center for Radiation Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Weiwei Wu
- College of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Zhuhuang Zhou
- Department of Biomedical Engineering, College of Chemistry and Life Sciences, Beijing University of Technology, Beijing, China.
| | - Shuicai Wu
- Department of Biomedical Engineering, College of Chemistry and Life Sciences, Beijing University of Technology, Beijing, China.
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3
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Bosio G, Destrempes F, Roy Cardinal MH, Cloutier G. Effect of rt-PA on Shear Wave Mechanical Assessment and Quantitative Ultrasound Properties of Blood Clot Kinetics In Vitro. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024; 43:829-840. [PMID: 38205972 DOI: 10.1002/jum.16411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/21/2023] [Accepted: 12/26/2023] [Indexed: 01/12/2024]
Abstract
OBJECTIVE The consequences associated with blood clots are numerous and are responsible for many deaths worldwide. The assessment of treatment efficacy is necessary for patient follow-up and to detect treatment-resistant patients. The aim of this study was to characterize the effect of treatment on blood clots in vitro using quantitative ultrasound parameters. METHODS Blood from 10 pigs was collected to form three clots per pig in gelatin phantoms. Clots were subjected to 1) no treatment, 2) rt-PA (recombinant tissue plasminogen activator) treatment after 20 minutes of clotting, and 3) rt-PA treatment after 60 minutes of clotting. Clots were weighted before and after the experiment to assess the treatment effect by the mass loss. The clot kinetics was studied over 100 minutes using elastography (Young's modulus, shear wave dispersion, and shear wave attenuation). Homodyne K-distribution (HKD) parameters derived from speckle statistics were also studied during clot formation and dissolving (diffuse-to-total signal power ratio and intensity parameters). RESULTS Treated clots loosed significantly more mass than non-treated ones (P < .005). A significant increase in Young's modulus was observed over time (P < .001), and significant reductions were seen for treated clots at 20 or 60 minutes compared with untreated ones (P < .001). The shear wave dispersion differed for treated clots at 60 minutes versus no treatments (P < .001). The shear wave attenuation decreased over time (P < .001), and was different for clots treated at 20 minutes versus no treatments (P < .031). The HKD intensity parameter varied over time (P < .032), and was lower for clots treated at 20 and 60 minutes than those untreated (P < .001 and P < .02). CONCLUSION The effect of rt-PA treatment could be confirmed by a decrease in Young's modulus and HKD intensity parameter. The shear wave dispersion and shear wave attenuation were sensitive to late and early treatments, respectively. The Young's modulus, shear wave attenuation, and HKD intensity parameter varied over time despite treatment.
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Affiliation(s)
- Guillaume Bosio
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada
- Institute of Biomedical Engineering, University of Montreal, Montreal, Quebec, Canada
| | - François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada
| | - Marie-Hélène Roy Cardinal
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada
- Institute of Biomedical Engineering, University of Montreal, Montreal, Quebec, Canada
- Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montreal, Quebec, Canada
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Wu X, Lv K, Wu S, Tai DI, Tsui PH, Zhou Z. Parallelized ultrasound homodyned-K imaging based on a generalized artificial neural network estimator. ULTRASONICS 2023; 132:106987. [PMID: 36958066 DOI: 10.1016/j.ultras.2023.106987] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 03/12/2023] [Accepted: 03/15/2023] [Indexed: 05/29/2023]
Abstract
The homodyned-K (HK) distribution model is a generalized backscatter envelope statistical model for ultrasound tissue characterization, whose parameters are of physical meaning. To estimate the HK parameters is an inverse problem, and is quite complicated. Previously, we proposed an artificial neural network (ANN) estimator and an improved ANN (iANN) estimator for estimating the HK parameters, which are fast and flexible. However, a drawback of the conventional ANN and iANN estimators consists in that they use Monte Carlo simulations under known values of HK parameters to generate training samples, and thus the ANN and iANN models have to be re-trained when the size of the test sets (or of the envelope samples to be estimated) varies. In addition, conventional ultrasound HK imaging uses a sliding window technique, which is non-vectorized and does not support parallel computation, so HK image resolution is usually sacrificed to ensure a reasonable computation cost. To this end, we proposed a generalized ANN (gANN) estimator in this paper, which took the theoretical derivations of feature vectors for network training, and thus it is independent from the size of the test sets. Further, we proposed a parallelized HK imaging method that is based on the gANN estimator, which used a block-based parallel computation method, rather than the conventional sliding window technique. The gANN-based parallelized HK imaging method allowed a higher image resolution and a faster computation at the same time. Computer simulation experiments showed that the gANN estimator was generally comparable to the conventional ANN estimator in terms of HK parameter estimation performance. Clinical experiments of hepatic steatosis showed that the gANN-based parallelized HK imaging could be used to visually and quantitatively characterize hepatic steatosis, with similar performance to the conventional ANN-based HK imaging that used the sliding window technique, but the gANN-based parallelized HK imaging was over 3 times faster than the conventional ANN-based HK imaging. The parallelized computation method presented in this work can be easily extended to other quantitative ultrasound imaging applications.
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Affiliation(s)
- Xining Wu
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ke Lv
- Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuicai Wu
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan; Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Zhuhuang Zhou
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
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Liu Y, He B, Zhang Y, Lang X, Yao R, Pan L. A Study on a Parameter Estimator for the Homodyned K Distribution Based on Table Search for Ultrasound Tissue Characterization. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:970-981. [PMID: 36631331 DOI: 10.1016/j.ultrasmedbio.2022.11.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 11/27/2022] [Accepted: 11/30/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVE The homodyned K (HK) distribution is considered to be the most suitable distribution in the context of tissue characterization; therefore, the search for a rapid and reliable parameter estimator for HK distribution is important. METHODS We propose a novel parameter estimator based on a table search (TS) for HK parameter estimates. The TS estimator can inherit the strength of conventional estimators by integrating various features and taking advantage of the TS method in a rapid and easy operation. Performance of the proposed TS estimator was evaluated and compared with that of XU (the estimation method based on X and U statistics) and artificial neural network (ANN) estimators. DISCUSSION The simulation results revealed that the TS estimator is superior to the XU and ANN estimators in terms of normalized standard deviations and relative root mean squared errors of parameter estimation, and is faster. Clinical experiments found that the area under the receiver operating curve for breast lesion classification using the parameters estimated by the TS estimator could reach 0.871. CONCLUSION The proposed TS estimator is more accurate, reliable and faster than the state-of-the-art XU and ANN estimators and has great potential for ultrasound tissue characterization based on the HK distribution.
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Affiliation(s)
- Yang Liu
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Bingbing He
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China.
| | - Yufeng Zhang
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Xun Lang
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Ruihan Yao
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Lingrui Pan
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
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Zhou Z, Zhang Z, Gao A, Tai DI, Wu S, Tsui PH. Liver Fibrosis Assessment Using Radiomics of Ultrasound Homodyned-K imaging Based on the Artificial Neural Network Estimator. ULTRASONIC IMAGING 2022; 44:229-241. [PMID: 36017590 DOI: 10.1177/01617346221120070] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The homodyned-K distribution is an important ultrasound backscatter envelope statistics model of physical meaning, and the parametric imaging of the model parameters has been explored for quantitative ultrasound tissue characterization. In this paper, we proposed a new method for liver fibrosis characterization by using radiomics of ultrasound backscatter homodyned-K imaging based on an improved artificial neural network (iANN) estimator. The iANN estimator was used to estimate the ultrasound homodyned-K distribution parameters k and α from the backscattered radiofrequency (RF) signals of clinical liver fibrosis (n = 237), collected with a 3-MHz convex array transducer. The RF data were divided into two groups: Group I corresponded to liver fibrosis with no hepatic steatosis (n = 94), and Group II corresponded to liver fibrosis with mild to severe hepatic steatosis (n = 143). The estimated homodyned-K parameter values were then used to construct k and α parametric images using the sliding window technique. Radiomics features of k and α parametric images were extracted, and feature selection was conducted. Logistic regression classification models based on the selected radiomics features were built for staging liver fibrosis. Experimental results showed that the proposed method is overall superior to the radiomics method of uncompressed envelope images when assessing liver fibrosis. Regardless of hepatic steatosis, the proposed method achieved the best performance in staging liver fibrosis ≥F1, ≥F4, and the area under the receiver operating characteristic curve was 0.88, 0.85 (Group I), and 0.85, 0.86 (Group II), respectively. Radiomics has improved the ability of ultrasound backscatter statistical parametric imaging to assess liver fibrosis, and is expected to become a new quantitative ultrasound method for liver fibrosis characterization.
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Affiliation(s)
- Zhuhuang Zhou
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Zijing Zhang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
- Fan Gongxiu Honors College, Beijing University of Technology, Beijing, China
| | - Anna Gao
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan
| | - Shuicai Wu
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan
- Institute for Radiological Research, Chang Gung University, Taoyuan
- Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan
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Thomson H, Yang S, Cochran S. Machine learning-enabled quantitative ultrasound techniques for tissue differentiation. J Med Ultrason (2001) 2022; 49:517-528. [PMID: 35840774 DOI: 10.1007/s10396-022-01230-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 04/18/2022] [Indexed: 11/24/2022]
Abstract
PURPOSE Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for tissue differentiation. METHODS This study first validated chicken liver and gizzard muscle as suitable acoustic phantoms for human brain and brain tumour tissues via measurement of the speed of sound and acoustic attenuation. A total of thirteen QUS parameters were estimated from twelve samples, each using data obtained with a transducer with a frequency of 5-11 MHz. Spectral parameters, i.e., effective scatterer diameter and acoustic concentration, were calculated from the backscattered power spectrum of the tissue, and echo envelope statistics were estimated by modelling the scattering inside the tissue as a homodyned K-distribution, yielding the scatterer clustering parameter α and the structure parameter κ. Standard deviation and higher-order moments were calculated from the echogenicity value assigned in conventional B-mode images. RESULTS The k-nearest neighbours algorithm was used to combine those parameters, which achieved 94.5% accuracy and 0.933 F1-score. CONCLUSION We were able to generate classification parametric images in near-real-time speed as a potential diagnostic tool in the operating room for the possible use for human brain tissue characterisation.
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Affiliation(s)
- Hannah Thomson
- Centre for Medical and Industrial Ultrasonics, University of Glasgow, University Avenue, Glasgow, UK.
| | - Shufan Yang
- Centre for Medical and Industrial Ultrasonics, University of Glasgow, University Avenue, Glasgow, UK.,School of Computing, Edinburgh Napier University, Merchiston Campus, Edinburgh, UK
| | - Sandy Cochran
- Centre for Medical and Industrial Ultrasonics, University of Glasgow, University Avenue, Glasgow, UK
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Bosio G, Zenati N, Destrempes F, Chayer B, Pernod G, Cloutier G. Shear Wave Elastography and Quantitative Ultrasound as Biomarkers to Characterize Deep Vein Thrombosis In Vivo. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2022; 41:1807-1816. [PMID: 34713918 DOI: 10.1002/jum.15863] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 10/02/2021] [Accepted: 10/11/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVE Investigate shear wave elastography (SWE) and quantitative ultrasound (QUS) parameters in patients hospitalized for lower limb deep vein thrombosis (DVT). METHOD Sixteen patients with DVT were recruited and underwent SWE and radiofrequency data acquisitions for QUS on day 0, day 7, and day 30 after the beginning of symptoms, in both proximal and distal zones of the clot identified on B-mode scan. SWE and QUS features were computed to differentiate between thrombi at day 0, day 7, and day 30 following treatment with heparin or oral anticoagulant. The Young's modulus from SWE was computed, as well as QUS homodyned K-distribution (HKD) parameters reflecting blood clot structure. Median and interquartile range of SWE and QUS parameters within clot were taken as features. RESULTS In the proximal zone of the clot, the HKD ratio of coherent-to-diffuse backscatter median showed a significant decrease from day 7 to day 30 (P = .036), while the HKD ratio of diffuse-to-total backscatter median presented a significant increase from day 7 to day 30 (P = .0491). In the distal zone of the clot, the HKD normalized intensity of the echo envelope median showed a significant increase from day 0 to day 30 (P = .0062). No SWE features showed statistically significant differences over time. Nonetheless, a trend of lower median of Young's modulus within clot for patients who developed a pulmonary embolism was observed. CONCLUSION QUS features may be relevant to characterize clot's evolution over time. Further analysis of their clinical interpretation and validation on a larger dataset would deserve to be studied.
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Affiliation(s)
- Guillaume Bosio
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Nora Zenati
- UGA UFRM-Université Grenoble Alpes-UFR Médecine, Grenoble, France
| | - François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Boris Chayer
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Gilles Pernod
- UGA UFRM-Université Grenoble Alpes-UFR Médecine, Grenoble, France
- Centre Hospitalier Universitaire de Grenoble, Grenoble, France
- F-CRIN INNOVTE Network, Saint Etienne, France
| | - Guy Cloutier
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
- Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada
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Parker KJ. Power laws prevail in medical ultrasound. Phys Med Biol 2022; 67:10.1088/1361-6560/ac637e. [PMID: 35366658 PMCID: PMC9118335 DOI: 10.1088/1361-6560/ac637e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 04/01/2022] [Indexed: 12/19/2022]
Abstract
Major topics in medical ultrasound rest on the physics of wave propagation through tissue. These include fundamental treatments of backscatter, speed of sound, attenuation, and speckle formation. Each topic has developed its own rich history, lexicography, and particular treatments. However, there is ample evidence to suggest that power law relations are operating at a fundamental level in all the basic phenomena related to medical ultrasound. This review paper develops, from literature over the past 60 years, the accumulating theoretical basis and experimental evidence that point to power law behaviors underlying the most important tissue-wave interactions in ultrasound and in shear waves which are now employed in elastography. The common framework of power laws can be useful as a coherent overview of topics, and as a means for improved tissue characterization.
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Affiliation(s)
- K J Parker
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
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Breast Tumor Classification Using Intratumoral Quantitative Ultrasound Descriptors. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:1633858. [PMID: 35295204 PMCID: PMC8920646 DOI: 10.1155/2022/1633858] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 02/15/2022] [Accepted: 02/23/2022] [Indexed: 12/11/2022]
Abstract
Breast cancer is a global epidemic, responsible for one of the highest mortality rates among women. Ultrasound imaging is becoming a popular tool for breast cancer screening, and quantitative ultrasound (QUS) techniques are being increasingly applied by researchers in an attempt to characterize breast tissue. Several different quantitative descriptors for breast cancer have been explored by researchers. This study proposes a breast tumor classification system using the three major types of intratumoral QUS descriptors which can be extracted from ultrasound radiofrequency (RF) data: spectral features, envelope statistics features, and texture features. A total of 16 features were extracted from ultrasound RF data across two different datasets, of which one is balanced and the other is severely imbalanced. The balanced dataset contains RF data of 100 patients with breast tumors, of which 48 are benign and 52 are malignant. The imbalanced dataset contains RF data of 130 patients with breast tumors, of which 104 are benign and 26 are malignant. Holdout validation was used to split the balanced dataset into 60% training and 40% testing sets. Feature selection was applied on the training set to identify the most relevant subset for the classification of benign and malignant breast tumors, and the performance of the features was evaluated on the test set. A maximum classification accuracy of 95% and an area under the receiver operating characteristic curve (AUC) of 0.968 was obtained on the test set. The performance of the identified relevant features was further validated on the imbalanced dataset, where a hybrid resampling strategy was firstly utilized to create an optimal balance between benign and malignant samples. A maximum classification accuracy of 93.01%, sensitivity of 94.62%, specificity of 91.4%, and AUC of 0.966 were obtained. The results indicate that the identified features are able to distinguish between benign and malignant breast lesions very effectively, and the combination of the features identified in this research has the potential to be a significant tool in the noninvasive rapid and accurate diagnosis of breast cancer.
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Destrempes F, Gesnik M, Chayer B, Roy-Cardinal MH, Olivié D, Giard JM, Sebastiani G, Nguyen BN, Cloutier G, Tang A. Quantitative ultrasound, elastography, and machine learning for assessment of steatosis, inflammation, and fibrosis in chronic liver disease. PLoS One 2022; 17:e0262291. [PMID: 35085294 PMCID: PMC8794185 DOI: 10.1371/journal.pone.0262291] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 12/21/2021] [Indexed: 12/12/2022] Open
Abstract
Objective To develop a quantitative ultrasound (QUS)- and elastography-based model to improve classification of steatosis grade, inflammation grade, and fibrosis stage in patients with chronic liver disease in comparison with shear wave elastography alone, using histopathology as the reference standard. Methods This ancillary study to a prospective institutional review-board approved study included 82 patients with non-alcoholic fatty liver disease, chronic hepatitis B or C virus, or autoimmune hepatitis. Elastography measurements, homodyned K-distribution parametric maps, and total attenuation coefficient slope were recorded. Random forests classification and bootstrapping were used to identify combinations of parameters that provided the highest diagnostic accuracy. Receiver operating characteristic (ROC) curves were computed. Results For classification of steatosis grade S0 vs. S1-3, S0-1 vs. S2-3, S0-2 vs. S3, area under the receiver operating characteristic curve (AUC) were respectively 0.60, 0.63, and 0.62 with elasticity alone, and 0.90, 0.81, and 0.78 with the best tested model combining QUS and elastography features. For classification of inflammation grade A0 vs. A1-3, A0-1 vs. A2-3, A0-2 vs. A3, AUCs were respectively 0.56, 0.62, and 0.64 with elasticity alone, and 0.75, 0.68, and 0.69 with the best model. For classification of liver fibrosis stage F0 vs. F1-4, F0-1 vs. F2-4, F0-2 vs. F3-4, F0-3 vs. F4, AUCs were respectively 0.66, 0.77, 0.72, and 0.74 with elasticity alone, and 0.72, 0.77, 0.77, and 0.75 with the best model. Conclusion Random forest models incorporating QUS and shear wave elastography increased the classification accuracy of liver steatosis, inflammation, and fibrosis when compared to shear wave elastography alone.
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Affiliation(s)
- François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Marc Gesnik
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Boris Chayer
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Marie-Hélène Roy-Cardinal
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Damien Olivié
- Department of Radiology, Radiation oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Radiology, Centre hospitalier de l’Université de Montréal (CHUM), Montréal, Québec, Canada
| | - Jeanne-Marie Giard
- Department of Medicine, Division of Hepatology and Liver Transplantation, Université de Montréal, Montréal, Québec, Canada
| | - Giada Sebastiani
- Department of Medicine, Division of Gastroenterology and Hepatology, McGill University Health Centre (MUHC), Montréal, Québec, Canada
| | - Bich N. Nguyen
- Department of Pathology, Centre hospitalier de l’Université de Montréal (CHUM), Montréal, Québec, Canada
- Department of Pathology and Cellular Biology, Université de Montréal, Montréal, Québec, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
- Department of Radiology, Radiation oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada
- * E-mail: (GC); (AT)
| | - An Tang
- Department of Radiology, Radiation oncology and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Radiology, Centre hospitalier de l’Université de Montréal (CHUM), Montréal, Québec, Canada
- Laboratory of Medical Image Analysis, Centre de recherche du Centre hospitalier de l’Université de Montréal (CRCHUM), Montréal, Québec, Canada
- * E-mail: (GC); (AT)
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12
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Wu K, Lang X, Zhang Y, Li Z, He B, Gao L, Chen J. Ultrasound simulation of blood with different red blood cell aggregations and concentrations. Biomed Mater Eng 2021; 33:235-257. [PMID: 34897078 DOI: 10.3233/bme-211340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Considerable progress of ultrasound simulation on blood has enhanced the characterizing of red blood cell (RBC) aggregation. OBJECTIVE A novel simulation method aims at modeling the blood with different RBC aggregations and concentrations is proposed. METHODS The modeling process is as follows: (i) A three-dimensional scatterer model is first built by a mapping with a Hilbert space-filling curve from the one-dimensional scatterer distribution. (ii) To illustrate the relationship between the model parameters and the RBC aggregation level, a variety of blood samples are prepared and scanned to acquire their radiofrequency signals in-vitro. (iii) The model parameters are determined by matching the Nakagami-distribution characteristics of envelope signals simulated from the model with those measured from the blood samples. RESULTS Nakagami metrics m estimated from 15 kinds of blood samples (hematocrits of 20%, 40%, 60% and plasma concentrations of 15%, 30%, 45%, 60%, 75%) are compared with metrics estimated by their corresponding models (each with different eligible parameters). Results show that for the three hematocrit levels, the mean and standard deviation of the root-mean-squared deviations of m are 0.27 ± 0.0026, 0.16 ± 0.0021, 0.12 ± 0.0018 respectively. CONCLUSION The proposed simulation model provides a viable data source to evaluate the performance of the ultrasound-based methods for quantifying RBC aggregation.
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Affiliation(s)
- Keyan Wu
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Xun Lang
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Yufeng Zhang
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Zhiyao Li
- The Third Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Bingbing He
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Lian Gao
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
| | - Jianhua Chen
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, Yunnan, China
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13
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Destrempes F, Cloutier G. Statistical modeling of ultrasound signals related to the packing factor of wave scattering phenomena for structural characterization. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2021; 150:3544. [PMID: 34852623 DOI: 10.1121/10.0007047] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 10/13/2021] [Indexed: 06/13/2023]
Abstract
The two-dimensional homodyned K-distribution has been widely used to model the echo envelope of ultrasound radio frequency (RF) signals in the field of medical ultrasonics. The main contribution of this work is to present a theoretical framework for supporting this model of the echo envelope and statistical models of the RF signals and their Hilbert transform in the case in which the scatterers' positions may be dependent. In doing so, the law of large numbers, Lyapounov's central limit theorem, and the Berry-Esseen theorem are being used. In particular, the proposed theoretical framework supports a previous conjecture relating the scatterer clustering parameter of the homodyned K-distribution to the packing factor W, which is related to the spatial organization of the scatterers, appearing in statistical physics or backscatter coefficient modeling. Simulations showed that the proposed modeling is valid for a number of scatterers and packing factors varying by steps of 2 from 1 to 21 and 1 to 11, respectively. The proposed framework allows, in principle, the detection of the structural information taking place at a scale smaller than the wavelength based solely on the statistical analysis of the RF signals or their echo envelope, although this goal was previously achieved based on the spectral analysis of ultrasound signals.
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Affiliation(s)
- François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Centre (CRCHUM), 900 St-Denis (suite R11.720), Montreal, Quebec, H2X 0A9, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Centre (CRCHUM), 900 St-Denis (suite R11.720), Montreal, Quebec, H2X 0A9, Canada
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14
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Cloutier G, Destrempes F, Yu F, Tang A. Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists. Insights Imaging 2021; 12:127. [PMID: 34499249 PMCID: PMC8429541 DOI: 10.1186/s13244-021-01071-w] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 08/07/2021] [Indexed: 12/26/2022] Open
Abstract
Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.
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Affiliation(s)
- Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 St-Denis, Montréal, Québec, H2X 0A9, Canada.
- Department of Radiology, Radio-oncology, and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada.
- Institute of Biomedical Engineering, Université de Montréal, Montréal, Québec, Canada.
| | - François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 St-Denis, Montréal, Québec, H2X 0A9, Canada
| | - François Yu
- Department of Radiology, Radio-oncology, and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada
- Institute of Biomedical Engineering, Université de Montréal, Montréal, Québec, Canada
- Microbubble Theranostics Laboratory, CRCHUM, Montréal, Québec, Canada
| | - An Tang
- Department of Radiology, Radio-oncology, and Nuclear Medicine, Université de Montréal, Montréal, Québec, Canada
- Department of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada
- Laboratory of Medical Image Analysis, Montréal, CRCHUM, Canada
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15
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Zhou Z, Gao A, Wu W, Tai DI, Tseng JH, Wu S, Tsui PH. Parameter estimation of the homodyned K distribution based on an artificial neural network for ultrasound tissue characterization. ULTRASONICS 2021; 111:106308. [PMID: 33290957 DOI: 10.1016/j.ultras.2020.106308] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 09/19/2020] [Accepted: 11/17/2020] [Indexed: 02/07/2023]
Abstract
The homodyned K (HK) distribution allows a general description of ultrasound backscatter envelope statistics with specific physical meanings. In this study, we proposed a new artificial neural network (ANN) based parameter estimation method of the HK distribution. The proposed ANN estimator took advantages of ANNs in learning and function approximation and inherited the strengths of conventional estimators through extracting five feature parameters from backscatter envelope signals as the input of the ANN: the signal-to-noise ratio (SNR), skewness, kurtosis, as well as X- and U-statistics. Computer simulations and clinical data of hepatic steatosis were used for validations of the proposed ANN estimator. The ANN estimator was compared with the RSK (the level-curve method that uses SNR, skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on X- and U-statistics) estimators. Computer simulation results showed that the relative bias was best for the XU estimator, whilst the normalized standard deviation was overall best for the ANN estimator. The ANN estimator was almost one order of magnitude faster than the RSK and XU estimators. The ANN estimator also yielded comparable diagnostic performance to state-of-the-art HK estimators in the assessment of hepatic steatosis. The proposed ANN estimator has great potential in ultrasound tissue characterization based on the HK distribution.
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Affiliation(s)
- Zhuhuang Zhou
- Department of Biomedical Engineering, Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing, China
| | - Anna Gao
- Department of Biomedical Engineering, Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing, China
| | - Weiwei Wu
- College of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan
| | - Jeng-Hwei Tseng
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Shuicai Wu
- Department of Biomedical Engineering, Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing, China.
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
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16
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Tehrani AKZ, Amiri M, Rosado-Mendez IM, Hall TJ, Rivaz H. A Pilot Study on Scatterer Density Classification of Ultrasound Images Using Deep Neural Networks. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:2059-2062. [PMID: 33018410 DOI: 10.1109/embc44109.2020.9175806] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Quantitative ultrasound estimates different intrinsic tissue properties, which can be used for tissue characterization. Among different tissue properties, the effective number of scatterers per resolution cell is an important parameter, which can be estimated by the echo envelope. Assuming the signal is stationary and coherent, if the number of scatterers per resolution cell is above approximately 10, envelope signal is considered to be fully developed speckle (FDS) and otherwise they are from low scatterer number density (LSND). Two statistical parameters named R and S are often calculated from envelope intensity to classify FDS from LSND. The main problem is that limited data from small patches often renders this classification inaccurate. Herein, we propose two techniques based on neural networks to estimate the effective number of scatterers. The first network is a multi-layer perceptron (MLP) that uses the hand-crafted features of R and S for classification. The second network is a convolutional neural network (CNN) that does not need hand-crafted features and instead utilizes spectrum and the envelope intensity directly. We show that the proposed MLP works very well for large patches wherein a reliable estimation of R and S can be made. However, its classification becomes inaccurate for small patches, where the proposed CNN provides accurate classifications.
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17
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Gesnik M, Bhatt M, Roy Cardinal MH, Destrempes F, Allard L, Nguyen BN, Alquier T, Giroux JF, Tang A, Cloutier G. In vivo Ultrafast Quantitative Ultrasound and Shear Wave Elastography Imaging on Farm-Raised Duck Livers during Force Feeding. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:1715-1726. [PMID: 32381381 DOI: 10.1016/j.ultrasmedbio.2020.03.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 02/05/2020] [Accepted: 03/10/2020] [Indexed: 06/11/2023]
Abstract
Shear wave elastography (speed and dispersion), local attenuation coefficient slope and homodyned-K parametric imaging were used for liver steatosis grading. These ultrasound biomarkers rely on physical interactions between shear and compression waves with tissues at both macroscopic and microscopic scales. These techniques were applied in a context not yet studied with ultrasound imaging, that is, monitoring steatosis of force-fed duck livers from pre-force-fed to foie gras stages. Each estimated feature presented a statistically significant trend along the feeding process (p values <10-3). However, whereas a monotonic increase in the shear wave speed was observed along the process, most quantitative ultrasound features exhibited an absolute maximum value halfway through the process. As the liver fat fraction in foie gras is much higher than that seen clinically, we hypothesized that a change in the ultrasound scattering regime is encountered for high-fat fractions, and consequently, care has to be taken when applying ultrasound biomarkers to grading of severe states of steatosis.
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Affiliation(s)
- Marc Gesnik
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada
| | - Manish Bhatt
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada
| | - Marie-Hélène Roy Cardinal
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada
| | - François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada
| | - Louise Allard
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada
| | - Bich N Nguyen
- Service of Pathology, University of Montreal Hospital (CHUM), Montréal, QC, Canada
| | - Thierry Alquier
- CRCHUM and Montreal Diabetes Research Center, Montréal, QC, Canada; Department of Medicine, University of Montreal, Montréal, QC, Canada
| | - Jean-François Giroux
- Department of Biological Sciences, University of Quebec in Montreal, Montréal, QC, Canada
| | - An Tang
- Service of Radiology, University of Montreal Hospital (CHUM), Montréal, QC, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, QC, Canada; Laboratory of Medical Image Analysis, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, University of Montreal, Montréal, QC, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, QC, Canada; Institute of Biomedical Engineering, University of Montreal, Montréal, QC, Canada.
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18
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Nasr R, Falou O, Shahin A, Hysi E, Wirtzfeld LA, Berndl ESL, Kolios MC. Mean Scatterer Spacing Estimation Using Cepstrum-Based Continuous Wavelet Transform. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2020; 67:1118-1126. [PMID: 31905136 DOI: 10.1109/tuffc.2020.2963955] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The goal of this study was to develop an ultrasound (US) scatterer spacing estimation method using an enhanced cepstral analysis based on continuous wavelet transforms (CWTs). Simulations of backscattering media containing periodic and quasi-periodic scatterers were carried out to test the developed algorithm. Experimental data from HT-29 pellets and in vivo PC3 tumors were then used to estimate the mean scatterer spacing. For simulated media containing quasi-periodic scatterers at 1-mm and 100- [Formula: see text] spacing with 5% positional variation, the developed algorithm yielded a spacing estimation error of ~1% for 25- and 55-MHz US pulses. The mean scatterer spacing of HT-29 cell pellets (31.97 [Formula: see text]) was within 3% of the spacing obtained from histology and agreed with the predicted spacing from simulations based on the same pellets for both frequencies. The agreement extended to in vivo PC3 tumors estimation of the spacing with a variance of 1.68% between the spacing derived from the tumor histology and the application of the CWT to the experimental results. The developed technique outperformed the traditional cepstral methods as it can detect nonprominent peaks from quasi-random scatterer configurations. This work can be potentially used to detect morphological tissue changes during normal development or disease treatment.
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19
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Cristea A, Collier N, Franceschini E, Mamou J, Cachard C, Basset O. Quantitative assessment of media concentration using the Homodyned K distribution. ULTRASONICS 2020; 101:105986. [PMID: 31539763 DOI: 10.1016/j.ultras.2019.105986] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 05/04/2019] [Accepted: 08/22/2019] [Indexed: 06/10/2023]
Abstract
The Homodyned K distribution has been used successfully as a tool in the ultrasound characterization of sparse media, where the scatterer clustering parameter α accurately discriminates between media with different numbers of scatterers per resolution cell. However, as the number of scatterers increases and the corresponding amplitude statistics become Rician, the reliability of the α estimates decreases rapidly. In the present study, we assess the usefulness of α for the characterization of both sparse and concentrated media, using simulated independent and identically distributed (i.i.d.) samples from Homodyned K distributions, ultrasound images of media with up to 68 scatterers per resolution cell and ultrasound signals acquired from particle phantoms with up to 101 scatterers per resolution cell. All parameter estimates are obtained using the XU estimator (Destrempes et al., 2013). Results suggest that the parameter α can be used to distinguish between media with up to 40 scatterers per resolution cell at 22 MHz, provided that parameter estimation can be performed on very large sample sizes (i.e., >10,000 i.i.d. samples).
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Affiliation(s)
- Anca Cristea
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway; Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, Lyon, France.
| | - Nicolas Collier
- Aix-Marseille Univ., CNRS, Centrale Marseille, LMA, Marseille, France
| | | | - Jonathan Mamou
- F.L. Lizzi Center for Biomedical Engineering, Riverside Research, New York, NY, USA
| | - Christian Cachard
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, Lyon, France
| | - Olivier Basset
- Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, Lyon, France
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20
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Destrempes F, Trop I, Allard L, Chayer B, Garcia-Duitama J, El Khoury M, Lalonde L, Cloutier G. Added Value of Quantitative Ultrasound and Machine Learning in BI-RADS 4-5 Assessment of Solid Breast Lesions. ULTRASOUND IN MEDICINE & BIOLOGY 2020; 46:436-444. [PMID: 31785840 DOI: 10.1016/j.ultrasmedbio.2019.10.024] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 09/17/2019] [Accepted: 10/25/2019] [Indexed: 06/10/2023]
Abstract
The purpose of this study was to evaluate various combinations of 13 features based on shear wave elasticity (SWE), statistical and spectral backscatter properties of tissues, along with the Breast Imaging Reporting and Data System (BI-RADS), for classification of solid breast lesions at ultrasonography by means of random forests. One hundred and three women with 103 suspicious solid breast lesions (BI-RADS categories 4-5) were enrolled. Before biopsy, additional SWE images and a cine sequence of ultrasound images were obtained. The contours of lesions were delineated, and parametric maps of the homodyned-K distribution were computed on three regions: intra-tumoral, supra-tumoral and infra-tumoral zones. Maximum elasticity and total attenuation coefficient were also extracted. Random forests yielded receiver operating characteristic (ROC) curves for various combinations of features. Adding BI-RADS category improved the classification performance of other features. The best result was an area under the ROC curve of 0.97, with 75.9% specificity at 98% sensitivity.
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Affiliation(s)
- François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Isabelle Trop
- Department of Radiology, Breast Imaging Center, University of Montreal Hospital (CHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada
| | - Louise Allard
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Boris Chayer
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Julian Garcia-Duitama
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Mona El Khoury
- Department of Radiology, Breast Imaging Center, University of Montreal Hospital (CHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada
| | - Lucie Lalonde
- Department of Radiology, Breast Imaging Center, University of Montreal Hospital (CHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada; Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada.
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21
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Zhou Z, Fang J, Cristea A, Lin YH, Tsai YW, Wan YL, Yeow KM, Ho MC, Tsui PH. Value of homodyned K distribution in ultrasound parametric imaging of hepatic steatosis: An animal study. ULTRASONICS 2020; 101:106001. [PMID: 31505328 DOI: 10.1016/j.ultras.2019.106001] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 08/26/2019] [Accepted: 08/30/2019] [Indexed: 06/10/2023]
Abstract
Ultrasound is the first-line tool for screening hepatic steatosis. Statistical distributions can be used to model the backscattered signals for liver characterization. The Nakagami distribution is the most frequently adopted model; however, the homodyned K (HK) distribution has received attention due to its link to physical meaning and improved parameter estimation through X- and U-statistics (termed "XU"). To assess hepatic steatosis, we proposed HK parametric imaging based on the α parameter (a measure of the number of scatterers per resolution cell) calculated using the XU estimator. Using a commercial system equipped with a 7-MHz linear array transducer, phantom experiments were performed to suggest an appropriate window size for α imaging using the sliding window technique, which was further applied to measuring the livers of rats (n = 66) with hepatic steatosis induced by feeding the rats a methionine- and choline-deficient diet. The relationships between the α parameter, the stage of hepatic steatosis, and histological features were verified by the correlation coefficient r, one-way analysis of variance, and regression analysis. The phantom results showed that the window side length corresponding to five times the pulse length supported a reliable α imaging. The α parameter showed a promising performance for grading hepatic steatosis (p < 0.05; r2 = 0.68). Compared with conventional Nakagami imaging, α parametric imaging provided significant information associated with fat droplet size (p < 0.05; r2 = 0.53), enabling further analysis and evaluation of severe hepatic steatosis.
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Affiliation(s)
- Zhuhuang Zhou
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
| | - Jui Fang
- 3D Printing Medical Research Center, China Medical University Hospital, China Medical University, Taichung, Taiwan
| | - Anca Cristea
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Ying-Hsiu Lin
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yu-Wei Tsai
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yung-Liang Wan
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Kee-Min Yeow
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Ming-Chih Ho
- Department of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan.
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
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Zhou Z, Zhang Q, Wu W, Lin YH, Tai DI, Tseng JH, Lin YR, Wu S, Tsui PH. Hepatic steatosis assessment using ultrasound homodyned-K parametric imaging: the effects of estimators. Quant Imaging Med Surg 2019; 9:1932-1947. [PMID: 31929966 PMCID: PMC6942974 DOI: 10.21037/qims.2019.08.03] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND The homodyned-K (HK) distribution is an important statistical model for describing ultrasound backscatter envelope statistics. HK parametric imaging has shown potential for characterizing hepatic steatosis. However, the feasibility of HK parametric imaging in assessing human hepatic steatosis in vivo remains unclear. METHODS In this paper, ultrasound HK μ parametric imaging was proposed for assessing human hepatic steatosis in vivo. Two recent estimators for the HK model, RSK (the level-curve method that uses the signal-to-noise ratio (SNR), skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on the first moment of the intensity and two log-moments, namely X- and U-statistics), were investigated. Liver donors (n=72) and patients (n=204) were recruited to evaluate hepatic fat fractions (HFFs) using magnetic resonance spectroscopy and to evaluate the stages of fatty liver disease (normal, mild, moderate, and severe) using liver biopsy with histopathology. Livers were scanned using a 3-MHz ultrasound to construct μ RSK and μ XU images to correlate with HFF analyses and fatty liver stages. The μ RSK and μ XU parametric images were constructed using the sliding window technique with the window side length (WSL) =1-9 pulse lengths (PLs). The diagnostic values of the μ RSK and μ XU parametric imaging methods were evaluated using receiver operating characteristic (ROC) curves. RESULTS For the 72 participants in Group A, the μ RSK parametric imaging with WSL =2-9 PLs exhibited similar correlation with log10(HFF), and the μ RSK parametric imaging with WSL = 3 PLs had the highest correlation with log10(HFF) (r=0.592); the μ XU parametric imaging with WSL =1-9 PLs exhibited similar correlation with log10(HFF), and the μ XU parametric imaging with WSL =1 PL had the highest correlation with log10(HFF) (r=0.628). For the 204 patients in Group B, the areas under the ROC (AUROCs) obtained using μ RSK for fatty stages ≥ mild (AUROC1), ≥ moderate (AUROC2), and ≥ severe (AUROC3) were (AUROC1, AUROC2, AUROC3) = (0.56, 0.57, 0.53), (0.68, 0.72, 0.75), (0.73, 0.78, 0.80), (0.74, 0.77, 0.79), (0.74, 0.78, 0.79), (0.75, 0.80, 0.82), (0.74, 0.77, 0.83), (0.74, 0.78, 0.84) and (0.73, 0.76, 0.83) for WSL =1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. The AUROCs obtained using μ XU for fatty stages ≥ mild, ≥ moderate, and ≥ severe were (AUROC1, AUROC2, AUROC3) = (0.75, 0.83, 0.81), (0.74, 0.80, 0.80), (0.76, 0.82, 0.82), (0.74, 0.80, 0.84), (0.76, 0.80, 0.83), (0.75, 0.80, 0.84), (0.75, 0.79, 0.85), (0.75, 0.80, 0.85) and (0.73, 0.77, 0.83) for WSL = 1, 2, 3, 4, 5, 6, 7, 8 and 9 PLs, respectively. CONCLUSIONS Both the μ RSK and μ XU parametric images are feasible for evaluating human hepatic steatosis. The WSL exhibits little impact on the diagnosing performance of the μ RSK and μ XU parametric imaging. The μ XU parametric imaging provided improved performance compared to the μ RSK parametric imaging in characterizing human hepatic steatosis in vivo.
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Affiliation(s)
- Zhuhuang Zhou
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China
| | - Qiyu Zhang
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China
| | - Weiwei Wu
- College of Biomedical Engineering, Capital Medical University, Beijing 100069, China
| | - Ying-Hsiu Lin
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan 33302, Taiwan
| | - Jeng-Hwei Tseng
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
| | - Yi-Ru Lin
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
| | - Shuicai Wu
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing 100124, China
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
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Validation of differences in backscatter coefficients among four ultrasound scanners with different beamforming methods. J Med Ultrason (2001) 2019; 47:35-46. [PMID: 31679096 DOI: 10.1007/s10396-019-00984-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Accepted: 09/11/2019] [Indexed: 12/17/2022]
Abstract
PURPOSE The backscatter coefficient (BSC) indicates the absolute scatterer property of a material, independently of clinicians and system settings. Our study verified that the BSC differed among the scanners, transducers, and beamforming methods used for quantitative ultrasound analyses of biological tissues. METHODS Measurements were performed on four tissue-mimicking homogeneous phantoms containing spherical scatterers with mean diameters of 20 and 30 µm prepared at concentrations of 0.5 and 2.0 wt%, respectively. The BSCs in the different systems were compared using ultrasound scanners with two single-element transducers and five linear high- or low-frequency probes. The beamforming methods were line-by-line formation using focused imaging (FI) and parallel beam formation using plane wave imaging (PWI). The BSC of each system was calculated by the reference phantom method. The mean deviation from the theoretical BSC computed by the Faran model was analyzed as the benchmark validation of the calculated BSC. RESULTS The BSCs calculated in systems with different properties and beamforming methods well concurred with the theoretical BSC. The mean deviation was below ± 2.8 dB on average, and within the approximate standard deviation (± 2.2 dB at most) in all cases. These variations agreed with a previous study in which the largest error among four different scanners with FI beamforming was 3.5 dB. CONCLUSION The BSC in PWI was equivalent to those in the other systems and to those of FI beamforming. This result indicates the possibility of ultra-high frame-rate BSC analysis using PWI.
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Bureau NJ, Destrempes F, Acid S, Lungu E, Moser T, Michaud J, Cloutier G. Diagnostic Accuracy of Echo Envelope Statistical Modeling Compared to B-Mode and Power Doppler Ultrasound Imaging in Patients With Clinically Diagnosed Lateral Epicondylosis of the Elbow. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2019; 38:2631-2641. [PMID: 30729545 DOI: 10.1002/jum.14964] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Revised: 01/22/2019] [Accepted: 01/23/2019] [Indexed: 06/09/2023]
Abstract
OBJECTIVES To compare the accuracy of homodyned K quantitative ultrasound (QUS) with that of B-mode and Doppler ultrasound imaging for discriminating between lateral epicondylosis (LE) and asymptomatic elbows. METHODS This prospective study received Institutional Review Board approval, and participants provided written informed consent. Between February 2015 and March 2017, 30 LE elbows in 27 patients and 24 asymptomatic elbows in 13 volunteers underwent B-mode, Doppler, and radiofrequency ultrasound imaging of the common extensor tendon (CET) and radial collateral ligament (RCL). Two readers classified the elbows independently on the basis of a review of B-mode and Doppler images. The global and local estimates of QUS parameters (μ n , 1/α, and k) were computed in the CET and CET-RCL regions, respectively, and the area of each region was calculated. A random-forest classifier identified the most discriminating 3-parameter combination: CET global estimate of 1/α, CET-RCL area, and local estimate of k. RESULTS The patients with LE had a mean age of 50 years (range, 31-66 years), and the volunteers had a mean age of 50 years (range, 37-57 years). The area under the receiver operating characteristic curve, sensitivity, and specificity of reader 1, reader 2, and the QUS-based model were 0.80 (95% confidence interval [CI], 0.66-0.95), 0.72 (95% CI, 0.56-0.89), and 0.88 (95% CI, 0.72-1.04); 0.79 (95% CI, 0.66-0.93), 0.65 (95% CI, 0.47-0.82), and 0.84 (95% CI, 0.67-1.01); and 0.82 (95% CI, 0.80-0.85), 0.73, and 0.79, respectively. CONCLUSIONS An automated, computer-based QUS technique diagnosed LE with accuracy of 0.82. This technique could provide quantitative biomarkers for the characterization of LE disease.
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Affiliation(s)
- Nathalie J Bureau
- Departments of Radiology, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
- Departments of Research Center, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
| | - François Destrempes
- Departments of Research Center, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
| | - Souad Acid
- Department of Radiology, Cliniques Universitaires Saint-Luc-Université Catholique de Louvain, Brussels, Belgium
| | - Eugen Lungu
- Departments of Radiology, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
| | - Thomas Moser
- Departments of Radiology, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
- Departments of Research Center, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
| | - Johan Michaud
- Departments of Medicine, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
| | - Guy Cloutier
- Departments of Research Center, Centre Hospitalier de l'Université de Montréal, Montreal, Quebec, Canada
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Strohm EM, Gnyawali V, Sebastian JA, Ngunjiri R, Moore MJ, Tsai SSH, Kolios MC. Sizing biological cells using a microfluidic acoustic flow cytometer. Sci Rep 2019; 9:4775. [PMID: 30886171 PMCID: PMC6423196 DOI: 10.1038/s41598-019-40895-x] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Accepted: 02/25/2019] [Indexed: 12/19/2022] Open
Abstract
We describe a new technique that combines ultrasound and microfluidics to rapidly size and count cells in a high-throughput and label-free fashion. Using 3D hydrodynamic flow focusing, cells are streamed single file through an ultrasound beam where ultrasound scattering events from each individual cell are acquired. The ultrasound operates at a center frequency of 375 MHz with a wavelength of 4 μm; when the ultrasound wavelength is similar to the size of a scatterer, the power spectra of the backscattered ultrasound waves have distinct features at specific frequencies that are directly related to the cell size. Our approach determines cell sizes through a comparison of these distinct spectral features with established theoretical models. We perform an analysis of two types of cells: acute myeloid leukemia cells, where 2,390 measurements resulted in a mean size of 10.0 ± 1.7 μm, and HT29 colorectal cancer cells, where 1,955 measurements resulted in a mean size of 15.0 ± 2.3 μm. These results and histogram distributions agree very well with those measured from a Coulter Counter Multisizer 4. Our technique is the first to combine ultrasound and microfluidics to determine the cell size with the potential for multi-parameter cellular characterization using fluorescence, light scattering and quantitative photoacoustic techniques.
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Affiliation(s)
- Eric M Strohm
- Department of Physics, Ryerson University, 350 Victoria St, Toronto, Canada
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada
| | - Vaskar Gnyawali
- Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria St, Toronto, Canada
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada
| | - Joseph A Sebastian
- Department of Physics, Ryerson University, 350 Victoria St, Toronto, Canada
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada
| | - Robert Ngunjiri
- Department of Physics, Ryerson University, 350 Victoria St, Toronto, Canada
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada
| | - Michael J Moore
- Department of Physics, Ryerson University, 350 Victoria St, Toronto, Canada
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada
| | - Scott S H Tsai
- Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria St, Toronto, Canada
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada
| | - Michael C Kolios
- Department of Physics, Ryerson University, 350 Victoria St, Toronto, Canada.
- Institute for Biomedical Engineering and Science Technology, a partnership between Ryerson University and St. Michael's Hospital, M5B 1W8, Toronto, Canada.
- Keenan Research Center for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital, M5B 1W8, Toronto, Canada.
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Roy-Cardinal MH, Destrempes F, Soulez G, Cloutier G. Assessment of Carotid Artery Plaque Components With Machine Learning Classification Using Homodyned-K Parametric Maps and Elastograms. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2019; 66:493-504. [PMID: 29994706 DOI: 10.1109/tuffc.2018.2851846] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Quantitative ultrasound (QUS) imaging methods, including elastography, echogenicity analysis, and speckle statistical modeling, are available from a single ultrasound (US) radio-frequency data acquisition. Since these US imaging methods provide complementary quantitative tissue information, characterization of carotid artery plaques may gain from their combination. Sixty-six patients with symptomatic ( n = 26 ) and asymptomatic ( n = 40 ) carotid atherosclerotic plaques were included in the study. Of these, 31 underwent magnetic resonance imaging (MRI) to characterize plaque vulnerability and quantify plaque components. US radio-frequency data sequence acquisitions were performed on all patients and were used to compute noninvasive vascular US elastography and other QUS features. Additional QUS features were computed from three types of images: homodyned-K (HK) parametric maps, Nakagami parametric maps, and log-compressed B-mode images. The following six classification tasks were performed: detection of 1) a small area of lipid; 2) a large area of lipid; 3) a large area of calcification; 4) the presence of a ruptured fibrous cap; 5) differentiation of MRI-based classification of nonvulnerable carotid plaques from neovascularized or vulnerable ones; and 6) confirmation of symptomatic versus asymptomatic patients. Feature selection was first applied to reduce the number of QUS parameters to a maximum of three per classification task. A random forest machine learning algorithm was then used to perform classifications. Areas under receiver-operating curves (AUCs) were computed with a bootstrap method. For all tasks, statistically significant higher AUCs were achieved with features based on elastography, HK parametric maps, and B-mode gray levels, when compared to elastography alone or other QUS alone ( ). For detection of a large area of lipid, the combination yielding the highest AUC (0.90, 95% CI 0.80-0.92, ) was based on elastography, HK, and B-mode gray-level features. To detect a large area of calcification, the highest AUC (0.95, 95% CI 0.94-0.96, ) was based on HK and B-mode gray level features. For other tasks, AUCs varied between 0.79 and 0.97. None of the best combinations contained Nakagami features. This study shows the added value of combining different features computed from a single US acquisition with machine learning to characterize carotid artery plaques.
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Hepatic Steatosis Assessment Using Quantitative Ultrasound Parametric Imaging Based on Backscatter Envelope Statistics. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9040661] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Hepatic steatosis is a key manifestation of non-alcoholic fatty liver disease (NAFLD). Early detection of hepatic steatosis is of critical importance. Currently, liver biopsy is the clinical golden standard for hepatic steatosis assessment. However, liver biopsy is invasive and associated with sampling errors. Ultrasound has been recommended as a first-line diagnostic test for the management of NAFLD. However, B-mode ultrasound is qualitative and can be affected by factors including image post-processing parameters. Quantitative ultrasound (QUS) aims to extract quantified acoustic parameters from the ultrasound backscattered signals for ultrasound tissue characterization and can be a complement to conventional B-mode ultrasound. QUS envelope statistics techniques, both statistical model-based and non-model-based, have shown potential for hepatic steatosis characterization. However, a state-of-the-art review of hepatic steatosis assessment using envelope statistics techniques is still lacking. In this paper, envelope statistics-based QUS parametric imaging techniques for characterizing hepatic steatosis are reviewed and discussed. The reviewed ultrasound envelope statistics parametric imaging techniques include acoustic structure quantification imaging, ultrasound Nakagami imaging, homodyned-K imaging, kurtosis imaging, and entropy imaging. Future developments are suggested.
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Tang A, Destrempes F, Kazemirad S, Garcia-Duitama J, Nguyen BN, Cloutier G. Quantitative ultrasound and machine learning for assessment of steatohepatitis in a rat model. Eur Radiol 2018; 29:2175-2184. [DOI: 10.1007/s00330-018-5915-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 10/29/2018] [Accepted: 11/23/2018] [Indexed: 12/13/2022]
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Sikdar S, Diao G, Turo D, Stanley CJ, Sharma A, Chambliss A, Laughrey L, Aralar A, Damiano DL. Quantification of Muscle Tissue Properties by Modeling the Statistics of Ultrasound Image Intensities Using a Mixture of Gamma Distributions in Children With and Without Cerebral Palsy. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2018; 37:2157-2169. [PMID: 29460971 PMCID: PMC6102099 DOI: 10.1002/jum.14566] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Revised: 06/19/2017] [Accepted: 12/09/2017] [Indexed: 06/08/2023]
Abstract
OBJECTIVES To investigate whether quantitative ultrasound (US) imaging, based on the envelope statistics of the backscattered US signal, can describe muscle properties in typically developing children and those with cerebral palsy (CP). METHODS Radiofrequency US data were acquired from the rectus femoris muscle of children with CP (n = 22) and an age-matched cohort without CP (n = 14) at rest and during maximal voluntary isometric contraction. A mixture of gamma distributions was used to model the histogram of the echo intensities within a region of interest in the muscle. RESULTS Muscle in CP had a heterogeneous echo texture that was significantly different from that in healthy controls (P < .001), with larger deviations from Rayleigh scattering. A mixture of 2 gamma distributions showed an excellent fit to the US intensity, and the shape and rate parameters were significantly different between CP and control groups (P < .05). The rate parameters for both the single gamma distribution and mixture of gamma distributions were significantly higher for contracted muscles compared to resting muscles, but there was no significant interaction between these factors (CP and muscle contraction) for a mixed-model analysis of variance. CONCLUSIONS Ultrasound tissue characterization indicates a more disorganized architecture and increased echogenicity in muscles in CP, consistent with previously documented increases in fibrous infiltration and connective tissue changes in this population. Our results indicate that quantitative US can be used to objectively differentiate muscle architecture and tissue properties.
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Affiliation(s)
- Siddhartha Sikdar
- Department of Bioengineering, George Mason University, Fairfax, Virginia, USA
| | - Guoqing Diao
- Department of Statistics, George Mason University, Fairfax, Virginia, USA
| | - Diego Turo
- Department of Mechanical Engineering, Catholic University of America, Washington, DC, USA
| | - Christopher J Stanley
- Functional and Applied Biomechanics, National Institutes of Health, Bethesda, Maryland USA
| | - Abhinav Sharma
- Functional and Applied Biomechanics, National Institutes of Health, Bethesda, Maryland USA
| | - Amy Chambliss
- George Washington University School of Medicine, Washington, DC, USA
| | - Loretta Laughrey
- Department of Physics, George Mason University, Fairfax, Virginia, USA
| | - April Aralar
- Department of Bioengineering, George Mason University, Fairfax, Virginia, USA
| | - Diane L Damiano
- Functional and Applied Biomechanics, National Institutes of Health, Bethesda, Maryland USA
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Gyawali P, Ziegler D, Cailhier JF, Denault A, Cloutier G. Quantitative Measurement of Erythrocyte Aggregation as a Systemic Inflammatory Marker by Ultrasound Imaging: A Systematic Review. ULTRASOUND IN MEDICINE & BIOLOGY 2018; 44:1303-1317. [PMID: 29661483 DOI: 10.1016/j.ultrasmedbio.2018.02.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Revised: 02/21/2018] [Accepted: 02/28/2018] [Indexed: 06/08/2023]
Abstract
This systematic review is aimed at answering two questions: (i) Is erythrocyte aggregation a useful biomarker in assessing systemic inflammation? (ii) Does quantitative ultrasound imaging provide the non-invasive option to measure erythrocyte aggregation in real time? The search was executed through bibliographic electronic databases CINAHL, EMB Review, EMBASE, MEDLINE, PubMed and the grey literature. The majority of studies correlated elevated erythrocyte aggregation with inflammatory blood markers for several pathologic states. Some studies used "erythrocyte aggregation" as an established marker of systemic inflammation. There were limited but promising articles regarding the use of quantitative ultrasound spectroscopy to monitor erythrocyte aggregation. Similarly, there were limited studies that used other ultrasound techniques to measure systemic inflammation. The quantitative measurement of erythrocyte aggregation has the potential to be a routine clinical marker of inflammation as it can reflect the cumulative inflammatory dynamics in vivo, is relatively simple to measure, is cost-effective and has a rapid turnaround time. Technologies like quantitative ultrasound spectroscopy that can measure erythrocyte aggregation non-invasively and in real time may offer the advantage of continuous monitoring of the inflammation state and, thus, may help in rapid decision making in a critical care setup.
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Affiliation(s)
- Prajwal Gyawali
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada
| | - Daniela Ziegler
- Documentation Center, University of Montreal Hospital, Montréal, Québec, Canada
| | - Jean-François Cailhier
- University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada; Department of Medicine, University of Montreal, Montréal, Québec, Canada
| | - André Denault
- University of Montreal Hospital, Montreal, Québec, Canada; Montreal Heart Institute, Montreal, Québec, Canada; Department of Anesthesiology, University of Montreal, Montréal, Québec, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada; Department of Radiology, Radio-Oncology and Nuclear Medicine, Montréal, Québec, Canada; Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada.
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Zhou Z, Wu S, Lin MY, Fang J, Liu HL, Tsui PH. Three-dimensional Visualization of Ultrasound Backscatter Statistics by Window-modulated Compounding Nakagami Imaging. ULTRASONIC IMAGING 2018; 40:171-189. [PMID: 29506441 DOI: 10.1177/0161734618756101] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In this study, the window-modulated compounding (WMC) technique was integrated into three-dimensional (3D) ultrasound Nakagami imaging for improving the spatial visualization of backscatter statistics. A 3D WMC Nakagami image was produced by summing and averaging a number of 3D Nakagami images (number of frames denoted as N) formed using sliding cubes with varying side lengths ranging from 1 to N times the transducer pulse. To evaluate the performance of the proposed 3D WMC Nakagami imaging method, agar phantoms with scatterer concentrations ranging from 2 to 64 scatterers/mm3 were made, and six stages of fatty liver (zero, one, two, four, six, and eight weeks) were induced in rats by methionine-choline-deficient diets (three rats for each stage, total n = 18). A mechanical scanning system with a 5-MHz focused single-element transducer was used for ultrasound radiofrequency data acquisition. The experimental results showed that 3D WMC Nakagami imaging was able to characterize different scatterer concentrations. Backscatter statistics were visualized with various numbers of frames; N = 5 reduced the estimation error of 3D WMC Nakagami imaging in visualizing the backscatter statistics. Compared with conventional 3D Nakagami imaging, 3D WMC Nakagami imaging improved the image smoothness without significant image resolution degradation, and it can thus be used for describing different stages of fatty liver in rats.
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Affiliation(s)
- Zhuhuang Zhou
- 1 College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
- 2 Faculty of Information Technology, Beijing University of Technology, Beijing, China
| | - Shuicai Wu
- 1 College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
| | - Man-Yen Lin
- 3 Department of Electrical Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Jui Fang
- 4 PhD Program in Biomedical Engineering, College of Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Hao-Li Liu
- 3 Department of Electrical Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Po-Hsiang Tsui
- 5 Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- 6 Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
- 7 Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
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Garcia-Duitama J, Chayer B, Garcia D, Goussard Y, Cloutier G. Protocol for Robust In Vivo Measurements of Erythrocyte Aggregation Using Ultrasound Spectroscopy. ULTRASOUND IN MEDICINE & BIOLOGY 2017; 43:2871-2881. [PMID: 28893425 DOI: 10.1016/j.ultrasmedbio.2017.08.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Revised: 07/19/2017] [Accepted: 08/08/2017] [Indexed: 06/07/2023]
Abstract
Erythrocyte aggregation is a non-specific marker of acute and chronic inflammation. Although it is usual to evaluate this phenomenon from blood samples analyzed in laboratory instruments, in vivo real-time assessment of aggregation is possible with spectral ultrasound techniques. However, variable blood flow can affect the interpretation of acoustic measures. Therefore, flow standardization is required. Two techniques of flow standardization were evaluated with porcine and equine blood samples in Couette flow. These techniques consisted in either stopping the flow or reducing it. Then, the sensibility and repeatability of the retained method were evaluated in 11 human volunteers. We observed that stopping the flow compromised interpretation and repeatability. Conversely, maintaining a low flow provided repeatable measures and could distinguish between normal and high extents of erythrocyte aggregation. Agreement was observed between in vivo and ex vivo measures of the phenomenon (R2 = 82.7%, p value < 0.0001). These results support the feasibility of assessing in vivo erythrocyte aggregation in humans by quantitative ultrasound means.
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Affiliation(s)
- Julian Garcia-Duitama
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada
| | - Boris Chayer
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada
| | - Damien Garcia
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada; Research Unit of Biomechanics and Imaging in Cardiology, CRCHUM, Montreal, Quebec, Canada; Department of Radiology, Radio-oncology and Nuclear Medicine, University of Montreal, Montreal, Quebec, Canada; Institute of Biomedical Engineering, University of Montreal, Montreal, Quebec, Canada
| | - Yves Goussard
- Department of Electrical Engineering, École Polytechnique of Montreal, Montreal, Quebec, Canada; Institute of Biomedical Engineering, École Polytechnique of Montreal, Montreal, Quebec, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montreal, Quebec, Canada; Department of Radiology, Radio-oncology and Nuclear Medicine, University of Montreal, Montreal, Quebec, Canada; Institute of Biomedical Engineering, University of Montreal, Montreal, Quebec, Canada.
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