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Afrakhteh S, Iacca G, Demi L. A two-dimensional angular interpolation based on radial basis functions for high frame rate ultrafast imaging. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2023; 154:3454-3465. [PMID: 38015029 DOI: 10.1121/10.0022515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023]
Abstract
To solve the problem of reduced image quality in plane wave imaging (PWI), coherent plane wave compounding (CPWC) has been introduced, based on a combination of plane wave images from several directions (i.e., with different angles). However, the number of angles needed to reach a reasonable image quality affects the maximum achievable frame rate in CPWC. In this study, we suggest reducing the tradeoff between the image quality and the frame rate in CPWC by employing two-dimensional (2D) interpolation based on radial basis functions. More specifically, we propose constructing a three-dimensional spatio-angular structure to integrate both spatial and angular information into the reconstruction prior to 2D interpolation. The rationale behind our proposal is to reduce the number of transmissions and then apply the 2D interpolation along the angle dimension to reconstruct the missing information corresponding to the angles not selected for CPWC imaging. To evaluate the proposed technique, we applied it to the PWI challenges in the medical ultrasound database. Results show that we can achieve 3× to 4× improvement in frame rate while maintaining acceptable image quality compared to the case of using all the angles.
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Affiliation(s)
- Sajjad Afrakhteh
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
| | - Giovanni Iacca
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
| | - Libertario Demi
- Department of Information Engineering and Computer Science, University of Trento, Trento, Italy
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Yazdani L, Rafati I, Gesnik M, Nicolet F, Chayer B, Gilbert G, Volniansky A, Olivié D, Giard JM, Sebastiani G, Nguyen BN, Tang A, Cloutier G. Ultrasound Shear Wave Attenuation Imaging for Grading Liver Steatosis in Volunteers and Patients With Non-alcoholic Fatty Liver Disease: A Pilot Study. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2264-2272. [PMID: 37482477 DOI: 10.1016/j.ultrasmedbio.2023.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 07/25/2023]
Abstract
OBJECTIVE The aims of the work described here were to assess shear wave attenuation (SWA) in volunteers and patients with non-alcoholic fatty liver disease (NAFLD) and compare its diagnostic performance with that of shear wave dispersion (SWD), magnetic resonance imaging (MRI) proton density fat fraction (PDFF) and biopsy. METHODS Forty-nine participants (13 volunteers and 36 NAFLD patients) were enrolled. Ultrasound and MRI examinations were performed in all participants. Biopsy was also performed in patients. SWA was used to assess histopathology grades as potential confounders. The areas under curves (AUCs) of SWA, SWD and MRI-PDFF were assessed in different steatosis grades by biopsy. Youden's thresholds of SWA were obtained for steatosis grading while using biopsy or MRI-PDFF as the reference standard. RESULTS Spearman's correlations of SWA with histopathology (steatosis, inflammation, ballooning and fibrosis) were 0.89, 0.73, 0.62 and 0.31, respectively. Multiple linear regressions of SWA confirmed the correlation with steatosis grades (adjusted R2 = 0.77, p < 0.001). The AUCs of MRI-PDFF, SWA and SWD were respectively 0.97, 0.99 and 0.94 for S0 versus ≥S1 (p > 0.05); 0.94, 0.98 and 0.78 for ≤S1 versus ≥S2 (both MRI-PDFF and SWA were higher than SWD, p < 0.05); and 0.90, 0.93 and 0.68 for ≤S2 versus S3 (both SWA and MRI-PDFF were higher than SWD, p < 0.05). SWA's Youden thresholds (Np/m/Hz) (sensitivity, specificity) for S0 versus ≥S1, ≤S1 versus ≥S2 and ≤S2 versus S3 were 1.05 (1.00, 0.92), 1.37 (0.96, 0.96) and 1.51 (0.83, 0.87), respectively. These values were 1.16 (1.00, 0.81), 1.49 (0.91, 0.82) and 1.67 (0.87, 0.92) when considering MRI-PDFF as the reference standard. CONCLUSION In this pilot study, SWA increased with increasing steatosis grades, and its diagnostic performance was higher than that of SWD but equivalent to that of MRI-PDFF.
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Affiliation(s)
- Ladan Yazdani
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada
| | - Iman Rafati
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada
| | - Marc Gesnik
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Frank Nicolet
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Boris Chayer
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada
| | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare Canada, Markham, ON, Canada; Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada
| | - Anton Volniansky
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada
| | - Damien Olivié
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada
| | | | - Giada Sebastiani
- Division of Gastroenterology and Hepatology, McGill University Health Centre, Montreal, QC, Canada
| | - Bich N Nguyen
- Service of Pathology, Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, QC, Canada
| | - An Tang
- Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, Canada; Laboratory of Clinical Image Processing, CRCHUM, Montréal, QC, Canada
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics (LBUM), Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, Université de Montréal, Montréal, QC, Canada; Department of Radiology, Radiation Oncology and Nuclear Medicine, Université de Montréal, Montréal, QQ, 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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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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Yazdani L, Bhatt M, Rafati I, Tang A, Cloutier G. The Revisited Frequency-Shift Method for Shear Wave Attenuation Computation and Imaging. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2022; 69:2061-2074. [PMID: 35404815 DOI: 10.1109/tuffc.2022.3166448] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Ultrasound (US) shear wave (SW) elastography has been widely studied and implemented on clinical systems to assess the elasticity of living organs. Imaging of SW attenuation reflecting viscous properties of tissues has received less attention. A revisited frequency shift (R-FS) method is proposed to improve the robustness of SW attenuation imaging. Performances are compared with the FS method that we originally proposed and with the two-point frequency shift (2P-FS) and attenuation measuring US SW elastography (AMUSE) methods. In the proposed R-FS method, the shape parameter of the gamma distribution fitting SW spectra is assumed to vary with distance, in contrast to FS. Second, an adaptive random sample consensus (A-RANSAC) line fitting method is used to prevent outlier attenuation values in the presence of noise. Validation was made on ten simulated phantoms with two viscosities (0.5 and 2 Pa [Formula: see text]) and different noise levels (15 to -5 dB), two experimental homogeneous gel phantoms, and six in vivo liver acquisitions on awake ducks (including three normal and three fatty duck livers). According to the conducted experiments, R-FS revealed mean reductions in coefficients of variation (CV) of 62.6% on simulations, 62.5% with phantoms, and 62.3% in vivo compared with FS. Corresponding reductions compared with 2P-FS were 45.4%, 77.1%, and 62.0%, respectively. Reductions in normalized root-mean-square errors for simulations were 63.9% and 48.7% with respect to FS and 2P-FS, respectively.
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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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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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Bhatt M, Yazdani L, Destrempes F, Allard L, Nguyen BN, Tang A, Cloutier G. Multiparametric in vivo ultrasound shear wave viscoelastography on farm-raised fatty duck livers: human radiology imaging applied to food sciences. Poult Sci 2021; 100:100968. [PMID: 33607316 PMCID: PMC7900601 DOI: 10.1016/j.psj.2020.12.065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 12/14/2020] [Accepted: 12/18/2020] [Indexed: 12/19/2022] Open
Abstract
Nine mulard ducks that were being raised for foie gras (steatosis) production went through in vivo shear wave (SW) elastography imaging of their liver during the force-feeding period to investigate changes in liver tissue characteristics. A total of 4 imaging sessions at an interval of 3 to 4 d were conducted at the farm on each animal. Three ducks were sacrificed at the second, third, and fourth imaging sessions for histopathology analysis of all animals at these time points. Six SW elastography parameters were evaluated: SW speed, SW attenuation, SW dispersion, Young's modulus, viscosity, and shear modulus. Shear waves of different frequencies propagate with different phase velocities. Thus, SW speed and other dependent parameters such as Young's modulus, viscosity, and shear modulus were computed at 2 frequencies: 75 and 202 Hz. Each parameter depicted a statistically significant trend along the force-feeding process (P-values between 0.001 and 0.0001). The fat fraction of the liver increased over the 12-day period of feeding. All parameters increased monotonically over time at 75 Hz, whereas modal relations were seen at 202 Hz. Shear wave dispersion measured between 75 and 202 Hz depicted a plateau from day 5. Based on this validation, proposed imaging methods are aimed to be used in the future on naturally fed ducks and geese.
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Affiliation(s)
- Manish Bhatt
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada H2X 0A9
| | - Ladan Yazdani
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada H2X 0A9; Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada H3C 3J7
| | - François Destrempes
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada H2X 0A9
| | - Louise Allard
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada H2X 0A9
| | - Bich N Nguyen
- Service of Pathology, University of Montreal Hospital (CHUM), Montréal, Québec, Canada H2X 0C1
| | - An Tang
- Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada H3C 3J7; Laboratory of Medical Image Analysis, CRCHUM, Montréal, Québec, Canada H2X 0A9; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada H3T 1J4
| | - Guy Cloutier
- Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, Québec, Canada H2X 0A9; Institute of Biomedical Engineering, University of Montreal, Montréal, Québec, Canada H3C 3J7; Department of Radiology, Radio-Oncology and Nuclear Medicine, University of Montreal, Montréal, Québec, Canada H3T 1J4.
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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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Poul SS, Parker KJ. Fat and fibrosis as confounding cofactors in viscoelastic measurements of the liver. Phys Med Biol 2021; 66:045024. [PMID: 33348325 DOI: 10.1088/1361-6560/abd593] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Elastography provides significant information on staging of fibrosis in patients with liver disease and may be of some value in assessing steatosis. However, there remain questions as to the role of steatosis and fibrosis as cofactors influencing the viscoelastic measurements of liver tissues, particularly shear wave speed (SWS) and shear wave attenuation (SWA). In this study, by employing the theory of composite elastic media as well as two independent experimental measurements on oil-in-gelatin phantoms and also finite element simulations, it is consistently shown that fat and fibrosis jointly influence the SWS and SWA measurements. At a constant level of fat, fibrosis stages can influence the SWA by factors of 2-4. Moreover, the rate of increase in SWA with increasing fat is strongly influenced by the stages of fibrosis; softer background cases (low fibrosis stages) have higher rate of SWA increase with fat than those with stiffer moduli (higher fibrosis stages). Meanwhile, SWS results are influenced by the presence of fat, however the degree of variability is more subtle. The results indicate the importance of jointly considering fat and fibrosis as contributors to SWS and SWA measurements in complex liver tissues and in the design and interpretation of clinical trials.
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Affiliation(s)
- S S Poul
- Department of Mechanical Engineering, University of Rochester, 235 Hopeman Building, Box 270132, Rochester, NY, United States of America
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