1
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Zhou Y, Yang K, Xu J, Cai D, Zhou X. Weighted ultrasound entropy imaging for HIFU ablation monitoring with improved sensitivity and contrast. Med Phys 2024. [PMID: 39092910 DOI: 10.1002/mp.17340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2024] [Revised: 07/11/2024] [Accepted: 07/17/2024] [Indexed: 08/04/2024] Open
Abstract
BACKGROUND Although B-mode imaging has been widely used in ultrasound-guided high-intensity focused ultrasound (HIFU) treatment, challenges remain in improving its quality and sensitivity for monitoring the thermal dose. Recently, quantitative ultrasound (QUS) imaging has been recognized with the potential to better sense the changes in the microstructure of ablated tissues. PURPOSE This study proposed to use a QUS method called weighted ultrasound entropy (WUE) imaging to monitor the HIFU ablation. METHODS Based on ex-vivo and in-vivo experiments, WUE images reflecting tissue changes during HIFU treatment under different acoustic power levels (174-308 W) were reconstructed with a newly established imaging framework. The performance of the proposed WUE imaging in the monitoring of HIFU treatment was compared with the corresponding B-mode images in terms of their contrast-to-noise ratios (CNRs) between the focal region and the background. RESULTS It was found that HIFU irradiation with higher power generated larger WUE values in the focal region, and the bright spots grew in size as the acoustic sonication proceeded. Compared with the in-situ B-mode images, the WUE images had higher image quality in indicating lesion formation, with a 39.2%-53.4% improvement in the CNR at different stages. Meanwhile, a correlation (R = 0.84) between the damage area estimated in WUE images and that measured from the dissected ex-vivo tissue samples was found. CONCLUSIONS WUE imaging is more sensitive and accurate than B-mode imaging in monitoring HIFU therapy. These findings suggest that WUE imaging could be a promising technique for assisting ultrasound-guided HIFU ablation.
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Affiliation(s)
- Yingying Zhou
- The State Key Laboratory of Ultrasound Engineering in Medicine, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
| | - Kun Yang
- The School of Microelectronics, Tianjin University, Tianjin, China
| | - Jiahong Xu
- The State Key Laboratory of Ultrasound Engineering in Medicine, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
| | - Dejia Cai
- The State Key Laboratory of Ultrasound Engineering in Medicine, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
| | - Xiaowei Zhou
- The State Key Laboratory of Ultrasound Engineering in Medicine, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China
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2
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Wei X, Wang Y, Wang L, Gao M, He Q, Zhang Y, Luo J. Simultaneous grading diagnosis of liver fibrosis, inflammation, and steatosis using multimodal quantitative ultrasound and artificial intelligence framework. Med Biol Eng Comput 2024:10.1007/s11517-024-03159-z. [PMID: 38990410 DOI: 10.1007/s11517-024-03159-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 06/22/2024] [Indexed: 07/12/2024]
Abstract
Noninvasive, accurate, and simultaneous grading of liver fibrosis, inflammation, and steatosis is valuable for reversing the progression and improving the prognosis quality of chronic liver diseases (CLDs). In this study, we established an artificial intelligence framework for simultaneous grading diagnosis of these three pathological types through fusing multimodal tissue characterization parameters dug by quantitative ultrasound methods derived from ultrasound radiofrequency signals, B-mode images, shear wave elastography images, and clinical ultrasound systems, using the liver biopsy results as the classification criteria. One hundred forty-two patients diagnosed with CLD were enrolled in this study. The results show that for the classification of fibrosis grade ≥ F1, ≥ F2, ≥ F3, and F4, the highest AUCs were respectively 0.69, 0.82, 0.84, and 0.88 with single clinical indicator alone, and were 0.81, 0.83, 0.89, and 0.91 with the proposed method. For the classification of inflammation grade ≥ A2 and A3, the highest AUCs were respectively 0.66 and 0.76 with single clinical indicator alone and were 0.80 and 0.93 with the proposed method. For the classification of steatosis grade ≥ S1 and ≥ S2, the highest AUCs were respectively 0.71 and 0.90 with single clinical indicator alone and were 0.75 and 0.92 with the proposed method. The proposed method can effectively improve the grading diagnosis performance compared with the present clinical indicators and has potential applications for noninvasive, accurate, and simultaneous diagnosis of CLDs.
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Affiliation(s)
- Xingyue Wei
- School of Biomedical Engineering, Tsinghua University, Beijing, China
- Institute for Precision Medicine, Tsinghua University, Beijing, China
| | - Yuanyuan Wang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
| | - Lianshuang Wang
- Department of Ultrasound, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| | - Mengze Gao
- Department of Precision Instrument, Tsinghua University, Beijing, China
| | - Qiong He
- School of Biomedical Engineering, Tsinghua University, Beijing, China
- Institute for Precision Medicine, Tsinghua University, Beijing, China
| | - Yao Zhang
- Department of Ultrasound, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
| | - Jianwen Luo
- School of Biomedical Engineering, Tsinghua University, Beijing, China.
- Institute for Precision Medicine, Tsinghua University, Beijing, China.
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3
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Li S, Tsui PH, Wu W, Wu S, Zhou Z. Ultrasound k-nearest neighbor entropy imaging: Theory, algorithm, and applications. ULTRASONICS 2024; 138:107256. [PMID: 38325231 DOI: 10.1016/j.ultras.2024.107256] [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: 07/19/2023] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 02/09/2024]
Abstract
Ultrasound information entropy is a flexible approach for analyzing ultrasound backscattering. Shannon entropy imaging based on probability distribution histograms (PDHs) has been implemented as a promising method for tissue characterization and diagnosis. However, the bin number affects the stability of entropy estimation. In this study, we introduced the k-nearest neighbor (KNN) algorithm to estimate entropy values and proposed ultrasound KNN entropy imaging. The proposed KNN estimator leveraged the Euclidean distance between data samples, rather than the histogram bins by conventional PDH estimators. We also proposed cumulative relative entropy (CRE) imaging to analyze time-series radiofrequency signals and applied it to monitor thermal lesions induced by microwave ablation (MWA). Computer simulation phantom experiments were conducted to validate and compare the performance of the proposed KNN entropy imaging, the conventional PDH entropy imaging, and Nakagami-m parametric imaging in detecting the variations of scatterer densities and visualizing inclusions. Clinical data of breast lesions were analyzed, and porcine liver MWA experiments ex vivo were conducted to validate the performance of KNN entropy imaging in classifying benign and malignant breast tumors and monitoring thermal lesions, respectively. Compared with PDH, the entropy estimation based on KNN was less affected by the tuning parameters. KNN entropy imaging was more sensitive to changes in scatterer densities and performed better visualizable capability than typical Shannon entropy (TSE) and Nakagami-m parametric imaging. Among different imaging methods, KNN-based Shannon entropy (KSE) imaging achieved the higher accuracy in classification of benign and malignant breast tumors and KNN-based CRE imaging had larger lesion-to-normal contrast when monitoring the ablated areas during MWA at different powers and treatment durations. Ultrasound KNN entropy imaging is a potential quantitative ultrasound approach for tissue characterization.
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Affiliation(s)
- Sinan Li
- 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, 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
| | - Weiwei Wu
- College of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Shuicai Wu
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
| | - Zhuhuang Zhou
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China.
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Karbalaeisadegh Y, Yao S, Zhu Y, Grimal Q, Muller M. Ultrasound Characterization of Cortical Bone Using Shannon Entropy. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:1824-1829. [PMID: 37244812 DOI: 10.1016/j.ultrasmedbio.2023.04.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/13/2023] [Accepted: 04/19/2023] [Indexed: 05/29/2023]
Abstract
OBJECTIVE Ultrasound backscattered signals encompass information on the microstructure of heterogeneous media such as cortical bone, in which pores act as scatterers and result in the scattering and multiple scattering of ultrasound waves. The objective of this study was to investigate whether Shannon entropy can be exploited to characterize cortical porosity. METHODS In the study described here, to demonstrate proof of concept, Shannon entropy was used as a quantitative ultrasound parameter to experimentally evaluate microstructural changes in samples with controlled scatterer concentrations made of a highly absorbing polydimethylsiloxane matrix (PDMS). Similar assessment was then performed using numerical simulations on cortical bone structures with varying average pore diameter (Ct.Po.Dm.), density (Ct.Po.Dn.) and porosity (Ct.Po.). RESULTS The results suggest that an increase in pore diameter and porosity lead to an increase in entropy, indicating increased levels of randomness in the signals as a result of increased scattering. The entropy-versus-scatterer volume fraction in PDMS samples indicates an initial increasing trend that slows down as the scatterer concentration increases. High levels of attenuation cause the signal amplitudes and corresponding entropy values to decrease drastically. The same trend is observed when porosity of the bone samples is increased above 15%. CONCLUSION Sensitivity of entropy to microstructural changes in highly scattering and absorbing media can potentially be exploited to diagnose and monitor osteoporosis.
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Affiliation(s)
- Yasamin Karbalaeisadegh
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA
| | - Shanshan Yao
- Department of Mechanical Engineering, Stony Brook University, Stony Brook, NY, USA
| | - Yong Zhu
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA
| | - Quentin Grimal
- Laboratory of Biomedical Imaging, Sorbonne University, Paris, France
| | - Marie Muller
- Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, USA.
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5
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Guo HH, Shen HR, Wang LL, Luo ZG, Zhang JL, Zhang HJ, Gao TL, Han YX, Jiang JD. Berberine is a potential alternative for metformin with good regulatory effect on lipids in treating metabolic diseases. Biomed Pharmacother 2023; 163:114754. [PMID: 37094549 DOI: 10.1016/j.biopha.2023.114754] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 04/26/2023] Open
Abstract
Metformin (MTF) and berberine (BBR) share several therapeutic benefits in treating metabolic-related disorders. However, as the two agents have very different chemical structure and bioavailability in oral route, the goal of this study is to learn their characteristics in treating metabolic disorders. The therapeutic efficacy of BBR and MTF was systemically investigated in the high fat diet feeding hamsters and/or ApoE(-/-) mice; in parallel, gut microbiota related mechanisms were studied for both agents. We discovered that, although both two drugs had almost identical effects on reducing fatty liver, inflammation and atherosclerosis, BBR appeared to be superior over MTF in alleviating hyperlipidemia and obesity, but MTF was more effective than BBR for the control of blood glucose. Association analysis revealed that the modulation of intestinal microenvironment played a crucial role in the pharmacodynamics of both drugs, in which their respective superiority on the regulation of gut microbiota composition and intestinal bile acids might contribute to their own merits on lowering glucose or lipids. This study shows that BBR may be a good alternative for MTF in treating diabetic patients, especially for those complicated with dyslipidemia and obesity.
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Affiliation(s)
- Hui-Hui Guo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Hao-Ran Shen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Lu-Lu Wang
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zhi-Gang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jin-Lan Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Hong-Juan Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Tian-Le Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| | - Yan-Xing Han
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| | - Jian-Dong Jiang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
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6
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Tsui PH. Information Entropy and Its Applications. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1403:153-167. [PMID: 37495918 DOI: 10.1007/978-3-031-21987-0_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Ultrasound is a first-line diagnostic tool for imaging many disease states. A number of statistical distributions have been proposed to describe ultrasound backscattering measured from tissues having different disease states. As an example, in this chapter we use nonalcoholic fatty liver disease (NAFLD), which is a critical health issue on a global scale, to demonstrate the capabilities of ultrasound to diagnose disease. Ultrasound interaction with the liver is typically characterized by scattering, which is quantified for the purpose of determining the degree of liver steatosis and fibrosis. Information entropy provides an insight into signal uncertainty. This concept allows for the analysis of backscattered statistics without considering the distribution of data or the statistical properties of ultrasound signals. In this chapter, we examined the background of NAFLD and the sources of scattering in the liver. The fundamentals of information entropy and an algorithmic scheme for ultrasound entropy imaging are then presented. Lastly, some examples of using ultrasound entropy imaging to grade hepatic steatosis and evaluate the risk of liver fibrosis in patients with significant hepatic steatosis are presented to illustrate future opportunities for clinical use.
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Affiliation(s)
- Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan.
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7
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Tang YC, Tsui PH, Wang CY, Chien YH, Weng HL, Yang CY, Weng WC. Hepatic Steatosis Assessment as a New Strategy for the Metabolic and Nutritional Management of Duchenne Muscular Dystrophy. Nutrients 2022; 14:nu14040727. [PMID: 35215377 PMCID: PMC8875407 DOI: 10.3390/nu14040727] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 02/04/2023] Open
Abstract
Growing evidence suggests that patients with Duchenne muscular dystrophy (DMD) have an increased risk of obesity and metabolic syndrome (MetS). The aim of this study was to investigate the potential risk factors for MetS and hepatic steatosis in patients with different stages of DMD. A total of 48 patients with DMD were enrolled and classified into three stages according to ambulatory status. Body mass index (BMI), serum fasting glucose, insulin, and lipid profiles including triglycerides (TG) and high-density lipoprotein were measured, and the homeostatic model assessment for insulin resistance (HOMA-IR) index was evaluated. Ultrasound examinations of the liver were performed to assess hepatic steatosis using the Nakagami parameter index (NPI). The results showed that BMI, TG, HOMA-IR, and ultrasound NPI differed significantly among DMD stages (p < 0.05). In contrast to the low rates of conventional MetS indices, including disturbed glucose metabolism (0%), dyslipidemia (14.28%), and insulin resistance (4.76%), a high proportion (40.48%) of the patients had significant hepatic steatosis. The ultrasound NPI increased with DMD progression, and two thirds of the non-ambulatory patients had moderate to severe hepatic steatosis. Steroid treatment was a risk factor for hepatic steatosis in ambulatory patients (p < 0.05). We recommend that DMD patients should undergo ultrasound evaluations for hepatic steatosis for better metabolic and nutritional management.
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Affiliation(s)
- Ya-Chun Tang
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan;
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (P.-H.T.); (C.-Y.W.)
- Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan
| | - Chiao-Yin Wang
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (P.-H.T.); (C.-Y.W.)
| | - Yin-Hsiu Chien
- Department of Pediatrics, National Taiwan University Hospital, Taipei 100225, Taiwan;
- Department of Pediatrics, College of Medicine, National Taiwan University, Taipei 100233, Taiwan
- Department of Medical Genetics, National Taiwan University Hospital, Taipei 100225, Taiwan
| | - Hui-Ling Weng
- Department of Dietetics, National Taiwan University Hospital, Taipei 100225, Taiwan;
- School of Nursing, College of Nursing, National Taipei University of Nursing and Health Sciences, Taipei 112303, Taiwan
| | - Chung-Yi Yang
- School of Medicine, College of Medicine, I-Shou University, Kaohsiung 824005, Taiwan;
- Department of Medical Imaging, E-Da Hospital, Kaohsiung 824410, Taiwan
| | - Wen-Chin Weng
- Department of Pediatrics, National Taiwan University Hospital, Taipei 100225, Taiwan;
- Department of Pediatrics, College of Medicine, National Taiwan University, Taipei 100233, Taiwan
- Department of Pediatric Neurology, National Taiwan University Children’s Hospital, Taipei 100226, Taiwan
- Correspondence: ; Tel.: +886-2-23123456 (ext. 71609)
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8
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Chan HJ, Zhou Z, Fang J, Tai DI, Tseng JH, Lai MW, Hsieh BY, Yamaguchi T, Tsui PH. Ultrasound Sample Entropy Imaging: A New Approach for Evaluating Hepatic Steatosis and Fibrosis. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2021; 9:1800612. [PMID: 34786215 PMCID: PMC8580366 DOI: 10.1109/jtehm.2021.3124937] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 08/20/2021] [Accepted: 10/10/2021] [Indexed: 02/05/2023]
Abstract
Objective: Hepatic steatosis causes nonalcoholic fatty liver disease and may progress to fibrosis. Ultrasound is the first-line approach to examining hepatic steatosis. Fatty droplets in the liver parenchyma alter ultrasound radiofrequency (RF) signal statistical properties. This study proposes using sample entropy, a measure of irregularity in time-series data determined by the dimension [Formula: see text] and tolerance [Formula: see text], for ultrasound parametric imaging of hepatic steatosis and fibrosis. Methods: Liver donors and patients were enrolled, and their hepatic fat fraction (HFF) ([Formula: see text]), steatosis grade ([Formula: see text]), and fibrosis score ([Formula: see text]) were measured to verify the results of sample entropy imaging using sliding-window processing of ultrasound RF data. Results: The sample entropy calculated using [Formula: see text] 4 and [Formula: see text] was highly correlated with the HFF when a small window with a side length of one pulse was used. The areas under the receiver operating characteristic curve for detecting hepatic steatosis that was [Formula: see text]mild, [Formula: see text]moderate, and [Formula: see text]severe were 0.86, 0.90, and 0.88, respectively, and the area was 0.87 for detecting liver fibrosis in individuals with significant steatosis. Discussion/Conclusions: Ultrasound sample entropy imaging enables the identification of time-series patterns in RF signals received from the liver. The algorithmic scheme proposed in this study is compatible with general ultrasound pulse-echo systems, allowing clinical fibrosis risk evaluations of individuals with developing hepatic steatosis.
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Affiliation(s)
- Hsien-Jung Chan
- Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung UniversityTaoyuan333323Taiwan
| | - Zhuhuang Zhou
- Department of Biomedical EngineeringFaculty of Environment and LifeBeijing University of TechnologyBeijing100124China
| | - Jui Fang
- X-Dimension Center for Medical Research and TranslationChina Medical University HospitalTaichung40447Taiwan
| | - Dar-In Tai
- Department of Gastroenterology and HepatologyChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Jeng-Hwei Tseng
- Department of Medical Imaging and InterventionChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Ming-Wei Lai
- Division of Pediatric GastroenterologyDepartment of PediatricsChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Bao-Yu Hsieh
- Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung UniversityTaoyuan333323Taiwan
- Department of Medical Imaging and InterventionChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
| | - Tadashi Yamaguchi
- Center for Frontier Medical EngineeringChiba UniversityChiba263-8522Japan
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological SciencesCollege of Medicine, Chang Gung UniversityTaoyuan333323Taiwan
- Division of Pediatric GastroenterologyDepartment of PediatricsChang Gung Memorial Hospital at LinkouTaoyuan333423Taiwan
- Institute for Radiological Research, Chang Gung UniversityTaoyuan333323Taiwan
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Sorriento A, Cafarelli A, Valenza G, Ricotti L. Ex-vivo quantitative ultrasound assessment of cartilage degeneration. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:2976-2980. [PMID: 34891870 DOI: 10.1109/embc46164.2021.9630198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Osteoarthritis is a common disease that implies joint degeneration and that strongly affects the quality of life. Conventional radiography remains currently the most used diagnostic method, even if it allows only an indirect assessment of the articular cartilage and employ the use of ionizing radiations. A non-invasive, continuous and reliable diagnosis is crucial to detect impairments and to improve the treatment outcomes.Quantitative ultrasound techniques have proved to be very useful in providing an objective diagnosis of several soft tissues. In this study, we propose quantitative ultrasound parameters, based on the analysis of radiofrequency data derived from both healthy and osteoarthritis-mimicking (through chemical degradation) ex-vivo cartilage samples. Using a transmission frequency typically employed in the clinical practice (7.5-15 MHz) with an external ultrasound probe, we found results in terms of reflection at the cartilage surface and sample thickness comparable to those reported in the literature by exploiting arthroscopic transducers at high frequency (from 20 to 55 MHz). Moreover, for the first time, we introduce an objective metric based on the phase entropy calculation, able to discriminate the healthy cartilage from the degenerated one.Clinical Relevance- This preliminary study proposes a novel and quantitative method to discriminate healthy from degenerated cartilage. The obtained results pave the way to the use of quantitative ultrasound in the diagnosis and monitoring of knee osteoarthritis.
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10
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Two-Dimensional EspEn: A New Approach to Analyze Image Texture by Irregularity. ENTROPY 2021; 23:e23101261. [PMID: 34681985 PMCID: PMC8535151 DOI: 10.3390/e23101261] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 09/15/2021] [Accepted: 09/24/2021] [Indexed: 11/21/2022]
Abstract
Image processing has played a relevant role in various industries, where the main challenge is to extract specific features from images. Specifically, texture characterizes the phenomenon of the occurrence of a pattern along the spatial distribution, taking into account the intensities of the pixels for which it has been applied in classification and segmentation tasks. Therefore, several feature extraction methods have been proposed in recent decades, but few of them rely on entropy, which is a measure of uncertainty. Moreover, entropy algorithms have been little explored in bidimensional data. Nevertheless, there is a growing interest in developing algorithms to solve current limits, since Shannon Entropy does not consider spatial information, and SampEn2D generates unreliable values in small sizes. We introduce a proposed algorithm, EspEn (Espinosa Entropy), to measure the irregularity present in two-dimensional data, where the calculation requires setting the parameters as follows: m (length of square window), r (tolerance threshold), and ρ (percentage of similarity). Three experiments were performed; the first two were on simulated images contaminated with different noise levels. The last experiment was with grayscale images from the Normalized Brodatz Texture database (NBT). First, we compared the performance of EspEn against the entropy of Shannon and SampEn2D. Second, we evaluated the dependence of EspEn on variations of the values of the parameters m, r, and ρ. Third, we evaluated the EspEn algorithm on NBT images. The results revealed that EspEn could discriminate images with different size and degrees of noise. Finally, EspEn provides an alternative algorithm to quantify the irregularity in 2D data; the recommended parameters for better performance are m = 3, r = 20, and ρ = 0.7.
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Sato Y, Tamura K, Mori S, Tai DI, Tsui PH, Yoshida K, Hirata S, Maruyama H, Yamaguchi T. Fatty liver evaluation with double-Nakagami model under low-resolution conditions. JAPANESE JOURNAL OF APPLIED PHYSICS 2021. [DOI: 10.35848/1347-4065/abf07d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Abstract
In previous studies, the double-Nakagami (DN) model has been proposed for fatty liver assessment and applied to in vivo rat livers and clinical data sets. The healthy liver structure filter (HLSF) method, which extracts non-healthy areas using two DN parameters, has also been proposed. In this paper, we first verify the accuracy of the DN model and the HLSF method for acoustic fields at 15 and 5 MHz, which were reproduced using numerical simulation. We then apply the method to clinical data sets of livers observed using a frequency of 3 MHz and investigate the method’s clinical usefulness. A positive correlation (
r
=
0.28
) was found between the ratio of the non-healthy area and fat mass. Although the results were inferior to the results produced using 15 MHz ultrasound (
r
=
0.96
), we found that it was possible to detect the difference between a normal liver and a fatty liver even at a lower frequency.
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12
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Chang TY, Chang SH, Lin YH, Ho WC, Wang CY, Jeng WJ, Wan YL, Tsui PH. Utility of quantitative ultrasound in community screening for hepatic steatosis. ULTRASONICS 2021; 111:106329. [PMID: 33338730 DOI: 10.1016/j.ultras.2020.106329] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 11/10/2020] [Accepted: 12/01/2020] [Indexed: 06/12/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. Quantitative ultrasound facilitates clinical grading of hepatic steatosis (the early stage of NAFLD). However, the utility of quantitative ultrasound as a first-line method for community screening of hepatic steatosis remains unclear. Therefore, this study aimed to investigate the utility of quantitative ultrasound to screen for hepatic steatosis and for metabolic evaluation at the community level. In total, 278 participants enrolled from a community satisfied the study criteria. Each subject underwent anthropometric and biochemical examinations, and abdominal ultrasound imaging was performed to measure the controlled attenuation (CAP), integrated backscatter (IB), and information Shannon entropy (ISE). The assessment outcomes were compared with the fatty liver index (FLI), hepatic steatosis index (HSI), metabolic syndrome (MetS), and insulin resistance to evaluate the screening performance through the area under the receiver operating characteristic curve (AUROC) and Delong's test. Ultrasound ISE, CAP, and IB were effective in screening hepatic steatosis, MetS, and insulin resistance. In screening for hepatic steatosis, the AUROCs of ISE, CAP, and IB were 0.85, 0.83, and 0.80 (the cutoff FLI = 60), respectively, and 0.84, 0.75, 0.77 (the cutoff HSI = 36), respectively, and those for the evaluation of MetS and insulin resistance were 0.79, 0.75, 0.79, respectively, and 0.83, 0.76, 0.78, respectively. Delong's test revealed that ISE outperformed CAP and IB for the detection of hepatic steatosis and insulin resistance (P < .05). Based on the present results, ultrasound ISE is a potential imaging biomarker during first-line community screening of hepatic steatosis and insulin resistance.
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Affiliation(s)
- Tu-Yung Chang
- Department of Anatomic Pathology, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Shu-Hung Chang
- Graduate Institute of Gerontology and Health Care Management, Chang Gung University of Science and Technology, Taoyuan, Taiwan; Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Ying-Hsiu Lin
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Wen-Chao Ho
- Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan; Department of Nursing & Graduate Institute of Nursing, Asia University, Taichung, Taiwan
| | - Chiao-Yin Wang
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Wen-Juei Jeng
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, 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; Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, 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; Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
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13
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Ballestri S, Tana C, Di Girolamo M, Fontana MC, Capitelli M, Lonardo A, Cioni G. Semi-Quantitative Ultrasonographic Evaluation of NAFLD. Curr Pharm Des 2021; 26:3915-3927. [PMID: 32303161 DOI: 10.2174/1381612826666200417142444] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 03/20/2020] [Indexed: 02/07/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) embraces histopathological entities ranging from the relatively benign simple steatosis to the progressive form nonalcoholic steatohepatitis (NASH), which is associated with fibrosis and an increased risk of progression to cirrhosis and hepatocellular carcinoma. NAFLD is the most common liver disease and is associated with extrahepatic comorbidities including a major cardiovascular disease burden. The non-invasive diagnosis of NAFLD and the identification of subjects at risk of progressive liver disease and cardio-metabolic complications are key in implementing personalized treatment schedules and follow-up strategies. In this review, we highlight the potential role of ultrasound semiquantitative scores for detecting and assessing steatosis severity, progression of NAFLD, and cardio-metabolic risk. Ultrasonographic scores of fatty liver severity act as sensors of cardio-metabolic health and may assist in selecting patients to submit to second-line non-invasive imaging techniques and/or liver biopsy.
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Affiliation(s)
- Stefano Ballestri
- Internal Medicine Unit, Pavullo Hospital, Azienda USL, Modena, Italy
| | - Claudio Tana
- Internal Medicine Unit, Pavullo Hospital, Azienda USL, Modena, Italy
| | - Maria Di Girolamo
- Internal Medicine Unit, Pavullo Hospital, Azienda USL, Modena, Italy
| | | | - Mariano Capitelli
- Internal Medicine Unit, Pavullo Hospital, Azienda USL, Modena, Italy
| | - Amedeo Lonardo
- Internal Medicine Unit, Pavullo Hospital, Azienda USL, Modena, Italy
| | - Giorgio Cioni
- Internal Medicine Unit, Pavullo Hospital, Azienda USL, Modena, Italy
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14
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Sorriento A, Poliziani A, Cafarelli A, Valenza G, Ricotti L. A novel quantitative and reference-free ultrasound analysis to discriminate different concentrations of bone mineral content. Sci Rep 2021; 11:301. [PMID: 33432022 PMCID: PMC7801603 DOI: 10.1038/s41598-020-79365-0] [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: 07/10/2020] [Accepted: 12/07/2020] [Indexed: 12/19/2022] Open
Abstract
Bone fracture is a continuous process, during which bone mineral matrix evolves leading to an increase in hydroxyapatite and calcium carbonate content. Currently, no gold standard methods are available for a quantitative assessment of bone fracture healing. Moreover, the available tools do not provide information on bone composition. Whereby, there is a need for objective and non-invasive methods to monitor the evolution of bone mineral content. In general, ultrasound can guarantee a quantitative characterization of tissues. However, previous studies required measurements on reference samples. In this paper we propose a novel and reference-free parameter, based on the entropy of the phase signal calculated from the backscattered data in combination with amplitude information, to also consider absorption and scattering phenomena. The proposed metric was effective in discriminating different hydroxyapatite (from 10 to 50% w/v) and calcium carbonate (from 2 to 6% w/v) concentrations in bone-mimicking phantoms without the need for reference measurements, paving the way to their translational use for the diagnosis of tissue healing. To the best of our knowledge this is the first time that the phase entropy of the backscattered ultrasound signals is exploited for monitoring changes in the mineral content of bone-like materials.
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Affiliation(s)
- A Sorriento
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy.
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy.
| | - A Poliziani
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
| | - A Cafarelli
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
| | - G Valenza
- Bioengineerring and Robotics Research Centre E Piaggio, University of Pisa, 56122, Pisa, Italy
- Department of Information Engineering, University of Pisa, 56123, Pisa, Italy
| | - L Ricotti
- The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, 56127, Pisa, Italy
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15
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Tsai YW, Zhou Z, Gong CSA, Tai DI, Cristea A, Lin YC, Tang YC, Tsui PH. Ultrasound Detection of Liver Fibrosis in Individuals with Hepatic Steatosis Using the Homodyned K Distribution. ULTRASOUND IN MEDICINE & BIOLOGY 2021; 47:84-94. [PMID: 33109381 DOI: 10.1016/j.ultrasmedbio.2020.09.021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 08/15/2020] [Accepted: 09/13/2020] [Indexed: 02/07/2023]
Abstract
Acoustic structure quantification (ASQ) based on the analysis of ultrasound backscattered statistics has been reported to detect liver fibrosis without significant hepatic steatosis. This study proposed using ultrasound parametric imaging based on the parameter α of the homodyned K (HK) distribution for staging liver fibrosis in patients with significant hepatic steatosis. Raw ultrasound image data were acquired from patients (n = 237) to construct B-mode and HK α parametric images, which were compared with the focal disturbance (FD) ratio obtained from ASQ on the basis of histologic evidence (METAVIR fibrosis score and hepatic steatosis severity). The data were divided into group I (n = 173; normal to mild hepatic steatosis) and group II (n = 64; with moderate to severe hepatic steatosis) for statistical analysis through one-way analysis of variance and receiver operating characteristic (ROC) curve analysis. The results showed that the HK α parameter monotonically decreased as the liver fibrosis stage increased (p < .05); concurrently, the FD ratio increased (p < .05). For group I, the areas under the ROC (AUROCs) obtained using the FD ratio and the α parameter (AUROCFD and AUROCα) were, respectively, 0.56 and 0.55, 0.68 and 0.68, 0.64 and 0.64 and 0.62 and 0.62 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. The values of AUROCFD and AUROCα for group II were, respectively, 0.88 and 0.91, 0.81 and 0.81, 0.77 and 0.76 and 0.78 and 0.73 for diagnosing liver fibrosis ≥F1, ≥F2, ≥F3 and ≥F4. As opposed to previous studies, ASQ was found to fail in characterizing liver fibrosis in group I; however, it was workable for identifying liver fibrosis in patients with significant hepatic steatosis (group II). Compared with ASQ, HK imaging provided improved diagnostic performance in the early detection of liver fibrosis coexisting with moderate to severe hepatic steatosis. Ultrasound HK imaging is recommended as a strategy to evaluate early fibrosis risk in patients with significant hepatic steatosis.
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Affiliation(s)
- Yu-Wei Tsai
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Zhuhuang Zhou
- College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
| | - Cihun-Siyong Alex Gong
- Department of Electrical Engineering, College of Engineering, Chang Gung University, Taoyuan, Taiwan; Department of Ophthalmology, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan, Taiwan
| | - Anca Cristea
- Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Yu-Ching Lin
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, at Keelung and Chang Gung University, Taiwan
| | - Ya-Chun Tang
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, 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; Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan.
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16
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Chen JR, Chao YP, Tsai YW, Chan HJ, Wan YL, Tai DI, Tsui PH. Clinical Value of Information Entropy Compared with Deep Learning for Ultrasound Grading of Hepatic Steatosis. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E1006. [PMID: 33286775 PMCID: PMC7597079 DOI: 10.3390/e22091006] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 08/31/2020] [Accepted: 09/07/2020] [Indexed: 02/07/2023]
Abstract
Entropy is a quantitative measure of signal uncertainty and has been widely applied to ultrasound tissue characterization. Ultrasound assessment of hepatic steatosis typically involves a backscattered statistical analysis of signals based on information entropy. Deep learning extracts features for classification without any physical assumptions or considerations in acoustics. In this study, we assessed clinical values of information entropy and deep learning in the grading of hepatic steatosis. A total of 205 participants underwent ultrasound examinations. The image raw data were used for Shannon entropy imaging and for training and testing by the pretrained VGG-16 model, which has been employed for medical data analysis. The entropy imaging and VGG-16 model predictions were compared with histological examinations. The diagnostic performances in grading hepatic steatosis were evaluated using receiver operating characteristic (ROC) curve analysis and the DeLong test. The areas under the ROC curves when using the VGG-16 model to grade mild, moderate, and severe hepatic steatosis were 0.71, 0.75, and 0.88, respectively; those for entropy imaging were 0.68, 0.85, and 0.9, respectively. Ultrasound entropy, which varies with fatty infiltration in the liver, outperformed VGG-16 in identifying participants with moderate or severe hepatic steatosis (p < 0.05). The results indicated that physics-based information entropy for backscattering statistics analysis can be recommended for ultrasound diagnosis of hepatic steatosis, providing not only improved performance in grading but also clinical interpretations of hepatic steatosis.
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Affiliation(s)
- Jheng-Ru Chen
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (J.-R.C.); (Y.-W.T.); (H.-J.C.); (Y.-L.W.)
| | - Yi-Ping Chao
- Department of Computer Science and Information Engineering, College of Engineering, Chang Gung University, Taoyuan 333323, Taiwan;
- Graduate Institute of Biomedical Engineering, Chang Gung University, College of Engineering, Taoyuan 333323, Taiwan
- Department of Neurology, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan
| | - Yu-Wei Tsai
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (J.-R.C.); (Y.-W.T.); (H.-J.C.); (Y.-L.W.)
| | - Hsien-Jung Chan
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (J.-R.C.); (Y.-W.T.); (H.-J.C.); (Y.-L.W.)
| | - Yung-Liang Wan
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (J.-R.C.); (Y.-W.T.); (H.-J.C.); (Y.-L.W.)
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan
- Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan 333423, Taiwan
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 333323, Taiwan; (J.-R.C.); (Y.-W.T.); (H.-J.C.); (Y.-L.W.)
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan
- Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 333423, Taiwan
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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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Lin YH, Wan YL, Tai DI, Tseng JH, Wang CY, Tsai YW, Lin YR, Chang TY, Tsui PH. Considerations of Ultrasound Scanning Approaches in Non-alcoholic Fatty Liver Disease Assessment through Acoustic Structure Quantification. ULTRASOUND IN MEDICINE & BIOLOGY 2019; 45:1955-1969. [PMID: 31130411 DOI: 10.1016/j.ultrasmedbio.2019.04.018] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 04/10/2019] [Accepted: 04/12/2019] [Indexed: 02/07/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a risk factor for hepatic fibrosis and cirrhosis. Acoustic structure quantification (ASQ), based on statistical analysis of ultrasound echoes, is an emerging technique for hepatic steatosis diagnosis. A standardized measurement protocol for ASQ analysis was suggested previously; however, an optimal ultrasound scanning approach has not been concluded thus far. In this study, the suitability of scanning approaches for the ASQ-based evaluation of hepatic steatosis was investigated. Hepatic fat fractions (HFFs; liver segments VIII, III and VI) of 70 living liver donors were assessed with magnetic resonance spectroscopy. A clinical ultrasound machine equipped with a 3-MHz convex transducer was used to scan each participant using the intercostal, epigastric and subcostal planes to acquire raw data for estimating two ASQ parameters (Cm2 and focal disturbance [FD] ratio) of segments VIII, III and VI, respectively. The parameters were plotted as functions of the HFF for calculating the values of the correlation coefficient (r) and probability value (p). The diagnostic performance of the parameters in discriminating between the normal and steatotic (≥5 and ≥10%) groups was also compared using receiver operating characteristic (ROC) curves. The Cm2 and FD ratio values measured using the epigastric and subcostal planes did not correlate with the severity of hepatic steatosis. However, intercostal imaging exhibited a higher correlation between the ASQ parameters and HFF (r = -0.64, p < 0.001). The diagnostic performance of Cm2 and FD ratio in detecting hepatic steatosis using intercostal imaging was also satisfactory (areas under ROC curves >0.8). Intercostal imaging is an appropriate scanning approach for ASQ analysis of the liver.
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Affiliation(s)
- Ying-Hsiu Lin
- 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; 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
| | - 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
| | - Chiao-Yin Wang
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Graduate Institute of Clinical Medical 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
| | - Yi-Ru Lin
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Tu-Yung Chang
- Department of Public Health, College of Public Health, China Medical University, Taichung, 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 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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19
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Chiou HJ, Yeh CK, Hwang HE, Liao YY. Efficacy of Quantitative Muscle Ultrasound Using Texture-Feature Parametric Imaging in Detecting Pompe Disease in Children. ENTROPY 2019; 21:e21070714. [PMID: 33267428 PMCID: PMC7515229 DOI: 10.3390/e21070714] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 07/18/2019] [Accepted: 07/21/2019] [Indexed: 12/12/2022]
Abstract
Pompe disease is a hereditary neuromuscular disorder attributed to acid α-glucosidase deficiency, and accurately identifying this disease is essential. Our aim was to discriminate normal muscles from neuropathic muscles in children affected by Pompe disease using a texture-feature parametric imaging method that simultaneously considers microstructure and macrostructure. The study included 22 children aged 0.02-54 months with Pompe disease and six healthy children aged 2-12 months with normal muscles. For each subject, transverse ultrasound images of the bilateral rectus femoris and sartorius muscles were obtained. Gray-level co-occurrence matrix-based Haralick's features were used for constructing parametric images and identifying neuropathic muscles: autocorrelation (AUT), contrast, energy (ENE), entropy (ENT), maximum probability (MAXP), variance (VAR), and cluster prominence (CPR). Stepwise regression was used in feature selection. The Fisher linear discriminant analysis was used for combination of the selected features to distinguish between normal and pathological muscles. The VAR and CPR were the optimal feature set for classifying normal and pathological rectus femoris muscles, whereas the ENE, VAR, and CPR were the optimal feature set for distinguishing between normal and pathological sartorius muscles. The two feature sets were combined to discriminate between children with and without neuropathic muscles affected by Pompe disease, achieving an accuracy of 94.6%, a specificity of 100%, a sensitivity of 93.2%, and an area under the receiver operating characteristic curve of 0.98 ± 0.02. The CPR for the rectus femoris muscles and the AUT, ENT, MAXP, and VAR for the sartorius muscles exhibited statistically significant differences in distinguishing between the infantile-onset Pompe disease and late-onset Pompe disease groups (p < 0.05). Texture-feature parametric imaging can be used to quantify and map tissue structures in skeletal muscles and distinguish between pathological and normal muscles in children or newborns.
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Affiliation(s)
- Hong-Jen Chiou
- Division of Ultrasound and Breast Imaging, Department of Radiology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
- School of Medicine, National Yang Ming University, Taipei 11221, Taiwan
- National Defense Medical Center, Taipei 11490, Taiwan
| | - Chih-Kuang Yeh
- Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan
| | - Hsuen-En Hwang
- Department of Radiology, Taipei Veterans General Hospital, Taipei 11217, Taiwan
| | - Yin-Yin Liao
- Department of Biomedical Engineering, Hungkuang University, Taichung 43302, Taiwan
- Correspondence: ; Tel.: +886-4-26318652
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20
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Liao YY, Yeh CK, Huang KC, Tsui PH, Yang KC. Metabolic Characteristics of a Novel Ultrasound Quantitative Diagnostic Index for Nonalcoholic Fatty Liver Disease. Sci Rep 2019; 9:7922. [PMID: 31138858 PMCID: PMC6538602 DOI: 10.1038/s41598-019-44453-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Accepted: 05/14/2019] [Indexed: 02/06/2023] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is an emerging epidemic worldwide and is regarded as a hepatic manifestation of metabolic syndrome (MetS). Only a few studies have discussed the biological features associated with quantitative assessment of ultrasound for characterizing NAFLD. Our aim was to delineate relevant metabolic characteristics using a new quantitative tool, the ultrasound quantitative diagnostic index (QDI). A total of 394 ultrasound data were analyzed to extract texture-feature parameters, the signal-to-noise ratio (SNR), and the slope of the center frequency downshift (CFDS) for determining the QDI. The texture index, SNR, and CFDS slope were all negatively correlated with high-density lipoprotein and positively correlated with other anthropometric indices and metabolic factors (all P < 0.05). The SNR had the greatest contribution to anthropometric and biochemical factors, followed by the texture index and CFDS slope. An increase in 1 unit of QDI score engendered a 9% higher risk of MetS, reflecting that the tool is feasible for use in identifying MetS (area under the receiver operating characteristic curve: 0.89). The QDI was correlated with metabolic factors and an independent predictor for MetS. Thus, this QDI might be a feasible method for use in clinical surveillance, epidemiology research, and metabolic function evaluations in patients with NAFLD.
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Affiliation(s)
- Yin-Yin Liao
- Department of Biomedical Engineering, Hungkuang University, Taichung, Taiwan
| | - Chih-Kuang Yeh
- Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan
| | - Kuo-Chin Huang
- Department of Family Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Family Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Department of Family Medicine, National Taiwan University Hospital, BeiHu Branch, Taipei, Taiwan
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
- 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
| | - Kuen-Cheh Yang
- Department of Family Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
- Department of Family Medicine, National Taiwan University Hospital, BeiHu Branch, Taipei, Taiwan.
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Sparavigna AC. Entropy in Image Analysis. ENTROPY 2019; 21:e21050502. [PMID: 33267216 PMCID: PMC7514991 DOI: 10.3390/e21050502] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 05/15/2019] [Indexed: 12/15/2022]
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Local-Entropy Based Approach for X-Ray Image Segmentation and Fracture Detection. ENTROPY 2019; 21:e21040338. [PMID: 33267052 PMCID: PMC7514822 DOI: 10.3390/e21040338] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/23/2019] [Revised: 03/20/2019] [Accepted: 03/26/2019] [Indexed: 11/17/2022]
Abstract
The paper proposes a segmentation and classification technique for fracture detection in X-ray images. This novel rotation-invariant method introduces the concept of local entropy for de-noising and removing tissue from the analysed X-ray images, followed by an improved procedure for image segmentation and the detection of regions of interest. The proposed local Shannon entropy was calculated for each image pixel using a sliding 2D window. An initial image segmentation was performed on the entropy representation of the original image. Next, a graph theory-based technique was implemented for the purpose of removing false bone contours and improving the edge detection of long bones. Finally, the paper introduces a classification and localisation procedure for fracture detection by tracking the difference between the extracted contour and the estimation of an ideal healthy one. The proposed hybrid method excels at detecting small fractures (which are hard to detect visually by a radiologist) in the ulna and radius bones—common injuries in children. Therefore, it is imperative that a radiologist inspecting the X-ray image receives a warning from the computerised X-ray analysis system, in order to prevent false-negative diagnoses. The proposed method was applied to a data-set containing 860 X-ray images of child radius and ulna bones (642 fracture-free images and 218 images containing fractures). The obtained results showed the efficiency and robustness of the proposed approach, in terms of segmentation quality and classification accuracy and precision (up to 91.16% and 86.22%, respectively).
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On Structural Entropy and Spatial Filling Factor Analysis of Colonoscopy Pictures. ENTROPY 2019; 21:e21030256. [PMID: 33266971 PMCID: PMC7514738 DOI: 10.3390/e21030256] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Revised: 02/19/2019] [Accepted: 02/27/2019] [Indexed: 12/21/2022]
Abstract
Colonoscopy is the standard device for diagnosing colorectal cancer, which develops from little lesions on the bowel wall called polyps. The Rényi entropies-based structural entropy and spatial filling factor are two scale- and resolution-independent quantities that characterize the shape of a probability distribution with the help of characteristic curves of the structural entropy–spatial filling factor map. This alternative definition of structural entropy is easy to calculate, independent of the image resolution, and does not require the calculation of neighbor statistics, unlike the other graph-based structural entropies.The distant goal of this study was to help computer aided diagnosis in finding colorectal polyps by making the Rényi entropy based structural entropy more understood. The direct goal was to determine characteristic curves that can differentiate between polyps and other structure on the picture. After analyzing the distribution of colonoscopy picture color channels, the typical structures were modeled with simple geometrical functions and the structural entropy–spatial filling factor characteristic curves were determined for these model structures for various parameter sets. A colonoscopy image analying method, i.e., the line- or column-wise scanning of the picture, was also tested, with satisfactory matching of the characteristic curve and the image.
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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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