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Hsieh CS, Lai MW, Chen CC, Chao HC, Wang CY, Wan YL, Zhou Z, Tsui PH. Quantitative ultrasound envelope statistics imaging as a screening approach for pediatric hepatic steatosis and liver fibrosis: using biomarker and transient elastography as reference standards. Heliyon 2023; 9:e22743. [PMID: 38213577 PMCID: PMC10782159 DOI: 10.1016/j.heliyon.2023.e22743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 11/16/2023] [Accepted: 11/17/2023] [Indexed: 01/13/2024] Open
Abstract
Quantitative ultrasound (QUS) envelope statistics imaging is an emerging technique for the assessment of hepatic steatosis in adults. Blood tests are currently recommended as the screening tool for pediatric hepatic steatosis, a condition that can lead to liver fibrosis in children. This study examined the utility of QUS envelope statistics imaging in grading biomarker-diagnosed hepatic steatosis and detecting liver fibrosis in a pediatric population. A total of 173 subjects was enrolled (Group A) for QUS envelope statistics imaging using two statistical distributions, Nakagami and homodyned K (HK) models, and information entropy. QUS parameter values were compared with the hepatic steatosis index (HSI) and steatosis grade (G0: HSI <30; G1: 30 ≤ HSI <36; G2: 36 ≤ HSI <41.6; G3: ≥41.6). An additional cohort of 63 subjects (Group B) was recruited to undergo both QUS envelope statistics imaging and liver stiffness measurements (LSM) obtained from the transient elastography (Fibroscan), with a cutoff value set at 5 kPa to indicate liver fibrosis. The diagnostic performances were evaluated using the area under the receiver operating characteristic curve (AUROC). QUS envelope statistics imaging generated the AUROC values for steatosis grading at levels ≥ G1, ≥ G2, and ≥ G3 ranged from 0.94 to 0.97, 0.91 to 0.93, and 0.83 to 0.87, respectively, and produced an AUROC range of between 0.82 and 0.84 for identifying liver fibrosis. QUS envelope statistics imaging integrates the benefits of both biomarkers and elastography, enabling the screening of hepatic steatosis and detection of liver fibrosis in a pediatric population.
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Affiliation(s)
- Chiao-Shan Hsieh
- Department of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Ming-Wei Lai
- Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Liver Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Chien-Chang Chen
- Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Hsun-Chin Chao
- Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Chiao-Yin Wang
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Yung-Liang Wan
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Zhuhuang Zhou
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Po-Hsiang Tsui
- Division of Pediatric Gastroenterology, Department of Pediatrics, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Liver Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
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Ozturk A, Kumar V, Pierce TT, Li Q, Baikpour M, Rosado-Mendez I, Wang M, Guo P, Schoen S, Gu Y, Dayavansha S, Grajo JR, Samir AE. The Future Is Beyond Bright: The Evolving Role of Quantitative US for Fatty Liver Disease. Radiology 2023; 309:e223146. [PMID: 37934095 PMCID: PMC10695672 DOI: 10.1148/radiol.223146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a common cause of morbidity and mortality. Nonfocal liver biopsy is the historical reference standard for evaluating NAFLD, but it is limited by invasiveness, high cost, and sampling error. Imaging methods are ideally situated to provide quantifiable results and rule out other anatomic diseases of the liver. MRI and US have shown great promise for the noninvasive evaluation of NAFLD. US is particularly well suited to address the population-level problem of NAFLD because it is lower-cost, more available, and more tolerable to a broader range of patients than MRI. Noninvasive US methods to evaluate liver fibrosis are widely available, and US-based tools to evaluate steatosis and inflammation are gaining traction. US techniques including shear-wave elastography, Doppler spectral imaging, attenuation coefficient, hepatorenal index, speed of sound, and backscatter-based estimation have regulatory clearance and are in clinical use. New methods based on channel and radiofrequency data analysis approaches have shown promise but are mostly experimental. This review discusses the advantages and limitations of clinically available and experimental approaches to sonographic liver tissue characterization for NAFLD diagnosis as well as future applications and strategies to overcome current limitations.
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Affiliation(s)
- Arinc Ozturk
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Viksit Kumar
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Theodore T Pierce
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Qian Li
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Masoud Baikpour
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Ivan Rosado-Mendez
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Michael Wang
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Peng Guo
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Scott Schoen
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Yuyang Gu
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Sunethra Dayavansha
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Joseph R Grajo
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
| | - Anthony E Samir
- From the Center for Ultrasound Research & Translation, Department of Radiology, Massachusetts General Hospital, 101 Merrimac St, 3rd Floor, 323G, Boston, MA 02114 (A.O., V.K., T.T.P., Q.L., M.B., P.G., S.S., Y.G., S.D., A.E.S.); Harvard Medical School, Boston, Mass (A.O., V.K., T.T.P, Q.L., A.E.S.); Departments of Medical Physics and Radiology, University of Wisconsin, Madison, Wis (I.R.M.); GE HealthCare, Milwaukee, Wis (M.W.); and Department of Radiology, University of Florida, Gainesville, Fla (J.R.G.)
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Zeng KY, Bao WYG, Wang YH, Liao M, Yang J, Huang JY, Lu Q. Non-invasive evaluation of liver steatosis with imaging modalities: New techniques and applications. World J Gastroenterol 2023; 29:2534-2550. [PMID: 37213404 PMCID: PMC10198053 DOI: 10.3748/wjg.v29.i17.2534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/26/2023] [Accepted: 04/11/2023] [Indexed: 05/23/2023] Open
Abstract
In the world, nonalcoholic fatty liver disease (NAFLD) accounts for majority of diffuse hepatic diseases. Notably, substantial liver fat accumulation can trigger and accelerate hepatic fibrosis, thus contributing to disease progression. Moreover, the presence of NAFLD not only puts adverse influences for liver but is also associated with an increased risk of type 2 diabetes and cardiovascular diseases. Therefore, early detection and quantified measurement of hepatic fat content are of great importance. Liver biopsy is currently the most accurate method for the evaluation of hepatic steatosis. However, liver biopsy has several limitations, namely, its invasiveness, sampling error, high cost and moderate intraobserver and interobserver reproducibility. Recently, various quantitative imaging techniques have been developed for the diagnosis and quantified measurement of hepatic fat content, including ultrasound- or magnetic resonance-based methods. These quantitative imaging techniques can provide objective continuous metrics associated with liver fat content and be recorded for comparison when patients receive check-ups to evaluate changes in liver fat content, which is useful for longitudinal follow-up. In this review, we introduce several imaging techniques and describe their diagnostic performance for the diagnosis and quantified measurement of hepatic fat content.
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Affiliation(s)
- Ke-Yu Zeng
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Wu-Yong-Ga Bao
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Yun-Han Wang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Min Liao
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Jie Yang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Jia-Yan Huang
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
| | - Qiang Lu
- Department of Medical Ultrasound, West China Hospital of Sichuan University, Chengdu 610041, Sichuan Province, China
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Seyedhasani SN, Dorri S, Pournik O, Alamdaran SA, Eslami S. Improving data adequacy of ultrasonography reports for non-alcoholic fatty liver disease (NAFLD) through a national structured template. Acta Radiol 2023; 64:473-478. [PMID: 35538852 DOI: 10.1177/02841851221093141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) is a prevalent disorder that increases due to lifestyle, the rising rate of obesity, and population ages worldwide. Diagnostic ways, including sonography, do not have an explicit reporting structure. PURPOSE To create a structure template for NAFLD reporting, investigate its completeness, and assess the specialist opinions of using it in clinical practice. MATERIAL AND METHODS A structured reporting template (SRT) was designed and implemented in four stages. At first, important features were extracted from a comprehensive literature review and were evaluated by 10 radiologists and gastroenterologists using the Likert scale. Finally, the usefulness of the SRT in comparison with the conventional reporting template (CRT) was judged by 10 gastroenterologists completing the questionnaire. RESULTS Demographic information and sonography of the liver, gallbladder, and spleen organs were the most critical features. The completeness scores of SRT reports were higher than CRT scores for almost all the factors studied. The difference in the scores was significant for most of the parameters. Moreover, the total completeness score increased from 42% in CRT to 92% in SRT. A comparison of the report adequacy of two reports was seen in all items. The SRT obtained more rates from specialists. CONCLUSION Introduction of the SRT for NAFLD significantly enhanced the completeness of reporting to reduce variability in the interpretation of the related reports by clinicians. Nevertheless, more studies are needed to generalize the results in real scales for patients with NAFLD.
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Affiliation(s)
- Seyedeh Nahid Seyedhasani
- Department of Health Information Technology, School of Paramedical Sciences, Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran.,Health Sciences Research Center, 435810Torbat Heydariyeh University of Medical Sciences, Torbat Heydariyeh, Iran
| | - Sara Dorri
- Health Information Technology Research Center, 48455Isfahan University of Medical Sciences, Isfahan, Iran
| | - Omid Pournik
- Department of Community Medicine, School of Medicine, 440827Iran University of Medical Sciences, Tehran, Iran
| | | | - Saeid Eslami
- Department of Medical Informatics, School of Medicine, 37552Mashhad University of Medical Sciences, Mashhad, Iran
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Tsui PH. Information Entropy and Its Applications. Adv Exp Med Biol 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] [What about the content of this article? (0)] [Affiliation(s)] [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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Bozic D, Podrug K, Mikolasevic I, Grgurevic I. Ultrasound Methods for the Assessment of Liver Steatosis: A Critical Appraisal. Diagnostics (Basel) 2022; 12:2287. [PMID: 36291976 PMCID: PMC9600709 DOI: 10.3390/diagnostics12102287] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/14/2022] [Accepted: 09/17/2022] [Indexed: 08/10/2023] Open
Abstract
The prevalence of the non-alcoholic fatty liver disease has reached major proportions, being estimated to affect one-quarter of the global population. The reference techniques, which include liver biopsy and the magnetic resonance imaging proton density fat fraction, have objective practical and financial limitations to their routine use in the detection and quantification of liver steatosis. Therefore, there has been a rising necessity for the development of new inexpensive, widely applicable and reliable non-invasive diagnostic tools. The controlled attenuation parameter has been considered the point-of-care technique for the assessment of liver steatosis for a long period of time. Recently, many ultrasound (US) system manufacturers have developed proprietary software solutions for the quantification of liver steatosis. Some of these methods have already been extensively tested with very good performance results reported, while others are still under evaluation. This manuscript reviews the currently available US-based methods for diagnosing and grading liver steatosis, including their classification and performance results, with an appraisal of the importance of this armamentarium in daily clinical practice.
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Affiliation(s)
- Dorotea Bozic
- Department of Gastroenterology and Hepatology, University Hospital Center Split, Spinčićeva 1, 21 000 Split, Croatia
| | - Kristian Podrug
- Department of Gastroenterology and Hepatology, University Hospital Center Split, Spinčićeva 1, 21 000 Split, Croatia
| | - Ivana Mikolasevic
- Department of Gastroenterology and Hepatology, University Hospital Center Rijeka, Krešimirova 42, 51 000 Rijeka, Croatia
| | - Ivica Grgurevic
- Department of Gastroenterology, Hepatology and Clinical Nutrition, University Hospital Dubrava, Avenija Gojka Šuška 6, 10 000 Zagreb, Croatia
- School of Medicine, University of Zagreb, Šalata 2, 10 000 Zagreb, Croatia
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Guan X, Chen YC, Xu HX. New horizon of ultrasound for screening and surveillance of non-alcoholic fatty liver disease spectrum. Eur J Radiol 2022; 154:110450. [PMID: 35917757 DOI: 10.1016/j.ejrad.2022.110450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 07/01/2022] [Accepted: 07/19/2022] [Indexed: 12/07/2022]
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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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 J Transl Eng Health Med 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] [What about the content of this article? (0)] [Affiliation(s)] [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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10
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Abstract
A framework is developed for estimating the volume fraction of fat in steatotic livers from viscoelastic measures of shear wave speed and attenuation. These measures are emerging on clinical ultrasound systems' elastography options so this approach can become widely available for assessing and monitoring steatosis. The framework assumes a distribution of fat vesicles as spherical inhomogeneities within the liver and uses a composite rheological model (Christensen 1969J. Mech. Phys. Solids1723-41) to determine the shear modulus as a function of increasing volume of fat within the liver. We show that accurate measurements of shear wave speed and attenuation provide the necessary and sufficient information to solve for the unknown fat volume and the underlying liver stiffness. Extension of the framework to compression wave measurements is also possible. Data from viscoelastic phantoms, human liver studies, and steatotic animal livers are shown to provide reasonable estimates of the volume fraction of fat.
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Affiliation(s)
- K J Parker
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
| | - J Ormachea
- Department of Electrical and Computer Engineering, University of Rochester, 724 Computer Studies Building, Box 270231, Rochester, NY 14627, United States of America
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11
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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 Med Biol 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] [What about the content of this article? (0)] [Affiliation(s)] [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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12
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Baek J, Poul SS, Swanson TA, Tuthill T, Parker KJ. Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification. Ultrasound Med Biol 2020; 46:3379-3392. [PMID: 32917469 PMCID: PMC9386788 DOI: 10.1016/j.ultrasmedbio.2020.08.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 07/30/2020] [Accepted: 08/06/2020] [Indexed: 05/14/2023]
Abstract
Fifty years of research on the nature of backscatter from tissues has resulted in a number of promising diagnostic parameters. We recently introduced two analyses tied directly to the biophysics of ultrasound scattering: the H-scan, based on a matched filter approach to distinguishing scattering transfer functions, and the Burr distribution for quantification of speckle patterns. Together, these analyses can produce at least five parameters that are directly linked to the mathematics of ultrasound in tissue. These have been measured in vivo in 35 rat livers under normal conditions and after exposure to compounds that induce inflammation, fibrosis, and steatosis in varying combinations. A classification technique, the support vector machine, is employed to determine clusters of the five parameters that are signatures of the different liver conditions. With the multiparametric measurement approach and determination of clusters, the different types of liver pathology can be discriminated with 94.6% accuracy.
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Affiliation(s)
- Jihye Baek
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York, USA
| | - Sedigheh S Poul
- Department of Mechanical Engineering, University of Rochester, Rochester, New York, USA
| | | | | | - Kevin J Parker
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York, USA.
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13
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Chuang YH, Hsieh CS, Lai MW, Chen CC, Chao HC, Yeh HY, Lai HH, Tsui PH. Detection of pediatric hepatic steatosis through ultrasound backscattering analysis. Eur Radiol 2021; 31:3216-25. [PMID: 33123795 DOI: 10.1007/s00330-020-07391-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 08/25/2020] [Accepted: 10/08/2020] [Indexed: 01/19/2023]
Abstract
OBJECTIVES Hepatic steatosis has become a considerable concern in the pediatric population. The objective of this study was to evaluate the feasibility of using ultrasound Nakagami imaging to produce a parametric image for analyzing the echo amplitude distribution to assess pediatric hepatic steatosis. METHODS A total of 68 pediatric participants were enrolled in healthy control (n = 26) and study groups (n = 42). Raw data from ultrasound imaging were acquired for each participant analysis using AmCAD-US, a software approved by the US Food and Drug Administration for ultrasound Nakagami imaging. The Nakagami parameters were compared with the hepatic steatosis index (HSI) and the steatosis grade (G0: HSI < 30; G1: 30 ≤ HSI < 36; G2: 36 ≤ HSI < 41.6; G3: 41.6 ≤ HSI < 43; G4: HSI ≥ 43) using correlation analysis, one-way analysis of variance (ANOVA), and receiver operating characteristic (ROC) curve analysis. RESULTS The Nakagami parameter increased from 0.53 ± 0.13 to 0.82 ± 0.05 with increasing severity of hepatic steatosis from G0 to G4 and were significantly different between the different grades of hepatic steatosis (p < .05). The areas under the ROC curves were 0.96, 0.92, 0.85, and 0.82 for diagnosing hepatic steatosis ≥ G1, ≥ G2, ≥ G3, and ≥ G4, respectively. CONCLUSIONS The Nakagami parameter value quantifies changes in the echo amplitude distribution of ultrasound backscattered signals caused by fatty infiltration, providing a novel, noninvasive, and effective data analysis technique to detect pediatric hepatic steatosis. KEY POINTS • Ultrasound Nakagami imaging enabled quantification of the echo amplitude distribution for tissue characterization. • The Nakagami parameter increased with the increasing severity of pediatric hepatic steatosis. • The Nakagami parameter demonstrated promising diagnostic performance in evaluating pediatric hepatic steatosis.
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14
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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) 2020; 22:e22091006. [PMID: 33286775 PMCID: PMC7597079 DOI: 10.3390/e22091006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [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
- Correspondence: (D.-I.T.); (P.-H.T.)
| | - 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
- Correspondence: (D.-I.T.); (P.-H.T.)
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15
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Fang F, Fang J, Li Q, Tai DI, Wan YL, Tamura K, Yamaguchi T, Tsui PH. Ultrasound Assessment of Hepatic Steatosis by Using the Double Nakagami Distribution: A Feasibility Study. Diagnostics (Basel) 2020; 10:diagnostics10080557. [PMID: 32759867 PMCID: PMC7459679 DOI: 10.3390/diagnostics10080557] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 07/28/2020] [Accepted: 08/01/2020] [Indexed: 02/07/2023] Open
Abstract
Ultrasound imaging is a first-line assessment tool for hepatic steatosis. Properties of tissue microstructures correlate with the statistical distribution of ultrasound backscattered signals, which can be described by the Nakagami distribution (a widely adopted approximation of backscattered statistics). The double Nakagami distribution (DND) model, which combines two Nakagami distributions, was recently proposed for using high-frequency ultrasound to analyze backscattered statistics corresponding to lipid droplets in the fat-infiltrated liver. This study evaluated the clinical feasibility of the DND model in ultrasound parametric imaging of hepatic steatosis by conducting clinical experiments using low-frequency ultrasound dedicated to general abdominal examinations. A total of 204 patients were recruited, and ultrasound image raw data were acquired using a 3.5 MHz array transducer for DND parametric imaging using the sliding window technique. The DND parameters were compared with hepatic steatosis grades identified histologically. A receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance. The results indicated that DND parametric imaging constructed using a sliding window with the side length of five times the pulse length of the transducer provided stable and reliable DND parameter estimations and visualized changes in the backscattered statistics caused by hepatic steatosis. The DND parameter increased with the hepatic steatosis grade. The areas under the ROC curve for identifying hepatic steatosis were 0.76 (≥mild), 0.81 (≥moderate), and 0.82 (≥severe). When using low-frequency ultrasound, DND imaging allows the clinical detection of hepatic steatosis and reflects information associated with lipid droplets in the fat-infiltrated liver.
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Affiliation(s)
- Feng Fang
- School of Microelectronics, Tianjin University, Tianjin 300072, China; (F.F.); (Q.L.)
| | - Jui Fang
- x-Dimension Center for Medical Research and Translation, China Medical University Hospital, Taichung 404332, Taiwan;
| | - Qiang Li
- School of Microelectronics, Tianjin University, Tianjin 300072, China; (F.F.); (Q.L.)
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan 33305, Taiwan;
| | - Yung-Liang Wan
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan;
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
| | - Kazuki Tamura
- Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, Shizuoka 431-3192, Japan;
| | - Tadashi Yamaguchi
- Center for Frontier Medical Engineering, Chiba University, Chiba 263-8522, Japan
- Correspondence: (T.Y.); (P.-H.T.)
| | - Po-Hsiang Tsui
- Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan 33302, Taiwan;
- Medical Imaging Research Center, Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 33305, Taiwan
- Correspondence: (T.Y.); (P.-H.T.)
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16
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Han A, Zhang YN, Boehringer AS, Montes V, Andre MP, Erdman JW, Loomba R, Valasek MA, Sirlin CB, O'Brien WD. Assessment of Hepatic Steatosis in Nonalcoholic Fatty Liver Disease by Using Quantitative US. Radiology 2020; 295:106-113. [PMID: 32013792 DOI: 10.1148/radiol.2020191152] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background Advanced confounder-corrected chemical shift-encoded MRI-derived proton density fat fraction (PDFF) is a leading parameter for fat fraction quantification in nonalcoholic fatty liver disease (NAFLD). Because of the limited availability of this MRI technique, there is a need to develop and validate alternative parameters to assess liver fat. Purpose To assess relationship of quantitative US parameters to MRI PDFF and to develop multivariable quantitative US models to detect hepatic steatosis and quantify hepatic fat. Materials and Methods Adults with known NAFLD or who were suspected of having NAFLD were prospectively recruited between August 2015 and February 2019. Participants underwent quantitative US and chemical shift-encoded MRI liver examinations. Liver biopsies were performed if clinically indicated. The correlation between seven quantitative US parameters and MRI PDFF was evaluated. By using leave-one-out cross validation, two quantitative US multivariable models were evaluated: a classifier to differentiate participants with NAFLD versus participants without NAFLD and a fat fraction estimator. Classifier performance was summarized by area under the receiver operating characteristic curve and area under the precision-recall curve. Fat fraction estimator performance was evaluated by correlation, linearity, and bias. Results Included were 102 participants (mean age, 52 years ± 13 [standard deviation]; 53 women), 78 with NAFLD (MRI PDFF ≥ 5%). A two-variable classifier yielded a cross-validated area under the receiver operating characteristic curve of 0.89 (95% confidence interval: 0.82, 0.96) and an area under the precision-recall curve of 0.96 (95% confidence interval: 0.93, 0.99). The cross-validated fat fraction predicted by a two-variable fat fraction estimator was correlated with MRI PDFF (Spearman ρ = 0.82 [P < .001]; Pearson r = 0.76 [P < .001]). The mean bias was 0.02% (P = .97), and 95% limits of agreement were ±12.0%. The predicted fat fraction was linear with MRI PDFF (R 2 = 0.63; slope, 0.69; intercept, 4.3%) for MRI PDFF of 34% or less. Conclusion A multivariable quantitative US approach yielded excellent correlation with MRI proton density fat fraction for hepatic steatosis assessment in nonalcoholic fatty liver disease. © RSNA, 2020 Online supplemental material is available for this article.
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Affiliation(s)
- Aiguo Han
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Yingzhen N Zhang
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Andrew S Boehringer
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Vivian Montes
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Michael P Andre
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - John W Erdman
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Rohit Loomba
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Mark A Valasek
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - Claude B Sirlin
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
| | - William D O'Brien
- From the Bioacoustics Research Laboratory, Department of Electrical and Computer Engineering (A.H., W.D.O.), and Department of Food Science and Human Nutrition (J.W.E.), University of Illinois at Urbana-Champaign, 306 N Wright St, Urbana, IL 61801; Liver Imaging Group, Department of Radiology (Y.N.Z., A.S.B., V.M., C.B.S.), Department of Radiology (M.P.A.); NAFLD Research Center, Division of Gastroenterology, Department of Medicine (R.L.), and Department of Pathology (M.A.V.), University of California, San Diego, La Jolla, Calif
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