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Ferraioli G, Barr RG, Berzigotti A, Sporea I, Wong VWS, Reiberger T, Karlas T, Thiele M, Cardoso AC, Ayonrinde OT, Castera L, Dietrich CF, Iijima H, Lee DH, Kemp W, Oliveira CP, Sarin SK. WFUMB Guidelines/Guidance on Liver Multiparametric Ultrasound. Part 2: Guidance on Liver Fat Quantification. ULTRASOUND IN MEDICINE & BIOLOGY 2024; 50:1088-1098. [PMID: 38658207 DOI: 10.1016/j.ultrasmedbio.2024.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/26/2024]
Abstract
The World Federation for Ultrasound in Medicine and Biology (WFUMB) has promoted the development of this document on multiparametric ultrasound. Part 2 is a guidance on the use of the available tools for the quantification of liver fat content with ultrasound. These are attenuation coefficient, backscatter coefficient, and speed of sound. All of them use the raw data of the ultrasound beam to estimate liver fat content. This guidance has the aim of helping the reader in understanding how they work and interpret the results. Confounding factors are discussed and a standardized protocol for measurement acquisition is suggested to mitigate them. The recommendations were based on published studies and experts' opinion but were not formally graded because the body of evidence remained low at the time of drafting this document.
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Affiliation(s)
- Giovanna Ferraioli
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy.
| | - Richard Gary Barr
- Department of Radiology, Northeastern Ohio Medical University, Youngstown, OH, USA
| | - Annalisa Berzigotti
- Department for Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Ioan Sporea
- Department of Internal Medicine II, Division of Gastroenterology and Hepatology, Center for Advanced Research in Gastroenterology and Hepatology, "Victor Babeș" University of Medicine and Pharmacy, Timișoara, Romania
| | - Vincent Wai-Sun Wong
- Department of Medicine and Therapeutics, Medical Data Analytics Centre, The Chinese University of Hong Kong, Hong Kong, China; State Key Laboratory of Digestive Disease, Institute of Digestive Disease, The Chinese University of Hong Kong, Hong Kong, China
| | - Thomas Reiberger
- Division of Gastroenterology and Hepatology, Department of Medicine III, Medical University of Vienna, Vienna, Austria; Christian-Doppler Laboratory for Portal Hypertension and Liver Fibrosis, Medical University of Vienna, Vienna, Austria
| | - Thomas Karlas
- Department of Medicine II, Division of Gastroenterology, Leipzig University Medical Center, Leipzig, Germany
| | - Maja Thiele
- Center for Liver Research, Department of Gastroenterology and Hepatology, Odense University Hospital, Odense, Denmark; Department for Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Ana Carolina Cardoso
- Hepatology Division, School of Medicine, Federal University of Rio de Janeiro, Clementino, Fraga Filho Hospital, Rio de Janeiro, RJ, Brazil
| | - Oyekoya Taiwo Ayonrinde
- Department of Gastroenterology and Hepatology, Fiona Stanley Hospital, Murdoch, WA, Australia; Medical School, The University of Western Australia, Crawley, WA, Australia; Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Laurent Castera
- Université Paris-Cité, Inserm UMR1149, Centre de Recherche sur l'Inflammation, Paris, France; Service d'Hépatologie, Hôpital Beaujon, Assistance-Publique Hôpitaux de Paris, Clichy, France
| | - Christoph Frank Dietrich
- Department Allgemeine Innere Medizin (DAIM), Kliniken Hirslanden Beau Site, Salem and Permancence, Bern, Switzerland
| | - Hiroko Iijima
- Department of Gastroenterology, Division of Hepatobiliary and Pancreatic Disease, Hyogo Medical University, Nishinomiya, Hyogo, Japan; Ultrasound Imaging Center, Hyogo Medical University, Nishinomiya, Hyogo, Japan
| | - Dong Ho Lee
- Department of Radiology, College of Medicine, Seoul National University Hospital, Seoul National University, Seoul, Republic of Korea
| | - William Kemp
- Department of Gastroenterology, Alfred Hospital, Melbourne, Australia; Department of Medicine, Central Clinical School, Monash University, Melbourne, Australia
| | - Claudia P Oliveira
- Gastroenterology Department, Laboratório de Investigação (LIM07), Hospital das Clínicas de São Paulo, HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Shiv Kumar Sarin
- Department of Hepatology, Institute of Liver and Biliary Sciences, New Delhi, India
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Pickhardt PJ, Blake GM, Moeller A, Garrett JW, Summers RM. Post-contrast CT liver attenuation alone is superior to the liver-spleen difference for identifying moderate hepatic steatosis. Eur Radiol 2024:10.1007/s00330-024-10816-2. [PMID: 38834787 DOI: 10.1007/s00330-024-10816-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 04/05/2024] [Accepted: 04/20/2024] [Indexed: 06/06/2024]
Abstract
OBJECTIVE To assess the diagnostic performance of post-contrast CT for predicting moderate hepatic steatosis in an older adult cohort undergoing a uniform CT protocol, utilizing hepatic and splenic attenuation values. MATERIALS AND METHODS A total of 1676 adults (mean age, 68.4 ± 10.2 years; 1045M/631F) underwent a CT urothelial protocol that included unenhanced, portal venous, and 10-min delayed phases through the liver and spleen. Automated hepatosplenic segmentation for attenuation values (in HU) was performed using a validated deep-learning tool. Unenhanced liver attenuation < 40.0 HU, corresponding to > 15% MRI-based proton density fat, served as the reference standard for moderate steatosis. RESULTS The prevalence of moderate or severe steatosis was 12.9% (216/1676). The diagnostic performance of portal venous liver HU in predicting moderate hepatic steatosis (AUROC = 0.943) was significantly better than the liver-spleen HU difference (AUROC = 0.814) (p < 0.001). Portal venous phase liver thresholds of 80 and 90 HU had a sensitivity/specificity for moderate steatosis of 85.6%/89.6%, and 94.9%/74.7%, respectively, whereas a liver-spleen difference of -40 HU and -10 HU had a sensitivity/specificity of 43.5%/90.0% and 92.1%/52.5%, respectively. Furthermore, livers with moderate-severe steatosis demonstrated significantly less post-contrast enhancement (mean, 35.7 HU vs 47.3 HU; p < 0.001). CONCLUSION Moderate steatosis can be reliably diagnosed on standard portal venous phase CT using liver attenuation values alone. Consideration of splenic attenuation appears to add little value. Moderate steatosis not only has intrinsically lower pre-contrast liver attenuation values (< 40 HU), but also enhances less, typically resulting in post-contrast liver attenuation values of 80 HU or less. CLINICAL RELEVANCE STATEMENT Moderate steatosis can be reliably diagnosed on post-contrast CT using liver attenuation values alone. Livers with at least moderate steatosis enhance less than those with mild or no steatosis, which combines with the lower intrinsic attenuation to improve detection. KEY POINTS The liver-spleen attenuation difference is frequently utilized in routine practice but appears to have performance limitations. The liver-spleen attenuation difference is less effective than liver attenuation for moderate steatosis. Moderate and severe steatosis can be identified on standard portal venous phase CT using liver attenuation alone.
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Affiliation(s)
- Perry J Pickhardt
- The University of Wisconsin School of Medicine & Public Health, Madison, WI, USA.
| | - Glen M Blake
- School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, UK
| | - Alex Moeller
- The University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | - John W Garrett
- The University of Wisconsin School of Medicine & Public Health, Madison, WI, USA
| | - Ronald M Summers
- Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA
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Jhang H, Park SJ, Sul AR, Jang HY, Park SH. Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes. Korean J Radiol 2024; 25:414-425. [PMID: 38627874 PMCID: PMC11058425 DOI: 10.3348/kjr.2023.1281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 01/27/2024] [Accepted: 02/04/2024] [Indexed: 05/01/2024] Open
Abstract
OBJECTIVE This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct value elements offered by AI, with a specific focus on patient-centered outcomes (PCOs). PCOs are distinguished from traditional clinical outcomes and focus on patient-reported experiences and values such as quality of life, functionality, well-being, physical or emotional status, and convenience. MATERIALS AND METHODS We classified the value elements provided by AI into four dimensions: clinical outcomes, economic aspects, organizational aspects, and non-clinical PCOs. The survey comprised three sections: 1) experiences with PCOs in evaluating AI, 2) opinions on the coverage of AI by the National Health Insurance of the Republic of Korea when AI demonstrated benefits across the four value elements, and 3) respondent characteristics. The opinions regarding AI insurance coverage were assessed dichotomously and semi-quantitatively: non-approval (0) vs. approval (on a 1-10 weight scale, with 10 indicating the strongest approval). The survey was conducted from July 4 to 26, 2023, using a web-based method. Responses to PCOs and other value elements were compared. RESULTS Among 200 respondents, 44 (22%) were patients/patient representatives, 64 (32%) were industry/developers, 60 (30%) were medical practitioners/doctors, and 32 (16%) were government health personnel. The level of experience with PCOs regarding AI was low, with only 7% (14/200) having direct experience and 10% (20/200) having any experience (either direct or indirect). The approval rate for insurance coverage for PCOs was 74% (148/200), significantly lower than the corresponding rates for other value elements (82.5%-93.5%; P ≤ 0.034). The approval strength was significantly lower for PCOs, with a mean weight ± standard deviation of 5.1 ± 3.5, compared to other value elements (P ≤ 0.036). CONCLUSION There is currently limited demand for insurance coverage for AI that demonstrates benefits in terms of non-clinical PCOs.
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Affiliation(s)
- Hoyol Jhang
- Division of Healthcare Research, National Evidence-Based Healthcare Collaborating Agency, Seoul, Republic of Korea
| | - So Jin Park
- Division of Healthcare Research, National Evidence-Based Healthcare Collaborating Agency, Seoul, Republic of Korea
| | - Ah-Ram Sul
- Division of Healthcare Research, National Evidence-Based Healthcare Collaborating Agency, Seoul, Republic of Korea.
| | - Hye Young Jang
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Seong Ho Park
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
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Jeon SK, Lee JM. Inter-platform reproducibility of ultrasound-based fat fraction for evaluating hepatic steatosis in nonalcoholic fatty liver disease. Insights Imaging 2024; 15:46. [PMID: 38353856 PMCID: PMC10866839 DOI: 10.1186/s13244-024-01611-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/07/2024] [Indexed: 02/17/2024] Open
Abstract
OBJECTIVES To evaluate the inter-platform reproducibility of ultrasound-based fat fraction examination in nonalcoholic fatty liver disease (NAFLD). METHODS Patients suspected of having NAFLD were prospectively enrolled from January 2023. Ultrasound-based fat fraction examinations were performed using two different platforms (ultrasound-derived fat fraction [UDFF] and quantitative ultrasound-derived estimated fat fraction [USFF]) on the same day. The correlation between UDFF and USFF was assessed using Pearson correlation coefficient. Intraclass correlation coefficient (ICC), Bland-Altman analysis with 95% limits of agreement (LOAs), and the coefficient of variation (CV) were used to assess inter-platform reproducibility. RESULTS A total of 41 patients (21 men and 20 women; mean age, 53.9 ± 12.6 years) were analyzed. Moderate correlation was observed between UDFF and USFF (Pearson's r = 0.748; 95% confidence interval [CI]: 0.572-0.858). On Bland-Altman analysis, the mean difference between UDFF and USFF values was 1.3% with 95% LOAs ranging from -8.0 to 10.6%. The ICC between UDFF and USFF was 0.842 (95% CI: 0.703-0.916), with a CV of 29.9%. CONCLUSION Substantial inter-platform variability was observed among different ultrasound-based fat fraction examinations. Therefore, it is not appropriate to use ultrasound-based fat fraction values obtained from different vendors interchangeably. CRITICAL RELEVANCE STATEMENT Considering the substantial inter-platform variability in ultrasound-based fat fraction assessments, caution is imperative when interpreting and comparing fat fraction values obtained from different ultrasound platforms in clinical practice. KEY POINTS • Inter-platform reproducibility of ultrasound-based fat fraction examinations is important for its clinical application. • Significant variability across different ultrasound-based fat fraction examinations was observed. • Using ultrasound-based fat fraction values from different vendors interchangeably is not advisable.
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Affiliation(s)
- Sun Kyung Jeon
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehangno, Jongno-Gu, Seoul, 03080, South Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehangno, Jongno-Gu, Seoul, 03080, South Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, South Korea.
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Pickhardt PJ, Blake GM, Kimmel Y, Weinstock E, Shaanan K, Hassid S, Abbas A, Fox MA. Detection of Moderate Hepatic Steatosis on Portal Venous Phase Contrast-Enhanced CT: Evaluation Using an Automated Artificial Intelligence Tool. AJR Am J Roentgenol 2023; 221:748-758. [PMID: 37466185 DOI: 10.2214/ajr.23.29651] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND. Precontrast CT is an established means of evaluating for hepatic steatosis; postcontrast CT has historically been limited for this purpose. OBJECTIVE. The purpose of this study was to evaluate the diagnostic performance of portal venous phase postcontrast CT in detecting at least moderate hepatic steatosis using liver and spleen attenuation measurements determined by an automated artificial intelligence (AI) tool. METHODS. This retrospective study included 2917 patients (1381 men, 1536 women; mean age, 56.8 years) who underwent a CT examination that included at least two series through the liver. Examinations were obtained from an AI vendor's data lake of data from 24 centers in one U.S. health care network and 29 centers in one Israeli health care network. An automated deep learning tool extracted liver and spleen attenuation measurements. The reference for at least moderate steatosis was precontrast liver attenuation of less than 40 HU (i.e., estimated liver fat > 15%). A radiologist manually reviewed examinations with outlier AI results to confirm portal venous timing and identify issues impacting attenuation measurements. RESULTS. After outlier review, analysis included 2777 patients with portal venous phase images. Prevalence of at least moderate steatosis was 13.9% (387/2777). Patients without and with at least moderate steatosis, respectively, had mean postcontrast liver attenuation of 104.5 ± 18.1 (SD) HU and 67.1 ± 18.6 HU (p < .001); a mean difference in postcontrast attenuation between the liver and the spleen (hereafter, postcontrast liver-spleen attenuation difference) of -7.6 ± 16.4 (SD) HU and -31.8 ± 20.3 HU (p < .001); and mean liver enhancement of 49.3 ± 15.9 (SD) HU versus 38.6 ± 13.6 HU (p < .001). Diagnostic performance for the detection of at least moderate steatosis was higher for postcontrast liver attenuation (AUC = 0.938) than for the postcontrast liver-spleen attenuation difference (AUC = 0.832) (p < .001). For detection of at least moderate steatosis, postcontrast liver attenuation had sensitivity and specificity of 77.8% and 93.2%, respectively, at less than 80 HU and 90.5% and 78.4%, respectively, at less than 90 HU; the postcontrast liver-spleen attenuation difference had sensitivity and specificity of 71.4% and 79.3%, respectively, at less than -20 HU and 87.0% and 62.1%, respectively, at less than -10 HU. CONCLUSION. Postcontrast liver attenuation outperformed the postcontrast liver-spleen attenuation difference for detecting at least moderate steatosis in a heterogeneous patient sample, as evaluated using an automated AI tool. Splenic attenuation likely is not needed to assess for at least moderate steatosis on postcontrast images. CLINICAL IMPACT. The technique could promote early detection of clinically significant nonalcoholic fatty liver disease through individualized or large-scale opportunistic evaluation.
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Affiliation(s)
- Perry J Pickhardt
- Department of Radiology, University of Wisconsin School of Medicine & Public Health, E3/311 Clinical Science Center, 600 Highland Ave, Madison, WI 53792-3252
| | - Glen M Blake
- School of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas' Hospital, London, United Kingdom
| | | | | | | | | | - Ahmad Abbas
- Department of Radiology, Barzilai University Medical Center, Ashkelon, Israel
| | - Matthew A Fox
- Nanox-AI, Ltd., Neve Ilan, Israel
- Department of Radiology, Samson Assuta Ashdod University Hospital, Ashdod, Israel
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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] [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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Kaposi PN, Zsombor Z, Rónaszéki AD, Budai BK, Csongrády B, Stollmayer R, Kalina I, Győri G, Bérczi V, Werling K, Maurovich-Horvat P, Folhoffer A, Hagymási K. The Calculation and Evaluation of an Ultrasound-Estimated Fat Fraction in Non-Alcoholic Fatty Liver Disease and Metabolic-Associated Fatty Liver Disease. Diagnostics (Basel) 2023; 13:3353. [PMID: 37958249 PMCID: PMC10648816 DOI: 10.3390/diagnostics13213353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
We aimed to develop a non-linear regression model that could predict the fat fraction of the liver (UEFF), similar to magnetic resonance imaging proton density fat fraction (MRI-PDFF), based on quantitative ultrasound (QUS) parameters. We measured and retrospectively collected the ultrasound attenuation coefficient (AC), backscatter-distribution coefficient (BSC-D), and liver stiffness (LS) using shear wave elastography (SWE) in 90 patients with clinically suspected non-alcoholic fatty liver disease (NAFLD), and 51 patients with clinically suspected metabolic-associated fatty liver disease (MAFLD). The MRI-PDFF was also measured in all patients within a month of the ultrasound scan. In the linear regression analysis, only AC and BSC-D showed a significant association with MRI-PDFF. Therefore, we developed prediction models using non-linear least squares analysis to estimate MRI-PDFF based on the AC and BSC-D parameters. We fitted the models on the NAFLD dataset and evaluated their performance in three-fold cross-validation repeated five times. We decided to use the model based on both parameters to calculate UEFF. The correlation between UEFF and MRI-PDFF was strong in NAFLD and very strong in MAFLD. According to a receiver operating characteristics (ROC) analysis, UEFF could differentiate between <5% vs. ≥5% and <10% vs. ≥10% MRI-PDFF steatosis with excellent, 0.97 and 0.91 area under the curve (AUC), accuracy in the NAFLD and with AUCs of 0.99 and 0.96 in the MAFLD groups. In conclusion, UEFF calculated from QUS parameters is an accurate method to quantify liver fat fraction and to diagnose ≥5% and ≥10% steatosis in both NAFLD and MAFLD. Therefore, UEFF can be an ideal non-invasive screening tool for patients with NAFLD and MAFLD risk factors.
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Affiliation(s)
- Pál Novák Kaposi
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Zita Zsombor
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Aladár D. Rónaszéki
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Bettina K. Budai
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Barbara Csongrády
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Róbert Stollmayer
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Ildikó Kalina
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Gabriella Győri
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Viktor Bérczi
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Klára Werling
- Department of Surgery, Transplantation and Gastroenterology, Faculty of Medicine, Semmelweis University, Üllői út 78., 1082 Budapest, Hungary; (K.W.); (K.H.)
| | - Pál Maurovich-Horvat
- Department of Radiology, Medical Imaging Center, Faculty of Medicine, Semmelweis University, Korányi S. u. 2., 1083 Budapest, Hungary; (Z.Z.); (A.D.R.); (B.K.B.); (B.C.); (R.S.); (I.K.); (G.G.); (V.B.); (P.M.-H.)
| | - Anikó Folhoffer
- Department of Internal Medicine and Oncology, Faculty of Medicine, Semmelweis University, Korányi S. u. 2/A., 1083 Budapest, Hungary;
| | - Krisztina Hagymási
- Department of Surgery, Transplantation and Gastroenterology, Faculty of Medicine, Semmelweis University, Üllői út 78., 1082 Budapest, Hungary; (K.W.); (K.H.)
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Harrison AP, Li B, Hsu TH, Chen CJ, Yu WT, Tai J, Lu L, Tai DI. Steatosis Quantification on Ultrasound Images by a Deep Learning Algorithm on Patients Undergoing Weight Changes. Diagnostics (Basel) 2023; 13:3225. [PMID: 37892046 PMCID: PMC10605714 DOI: 10.3390/diagnostics13203225] [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: 09/05/2023] [Revised: 09/30/2023] [Accepted: 10/11/2023] [Indexed: 10/29/2023] Open
Abstract
INTRODUCTION A deep learning algorithm to quantify steatosis from ultrasound images may change a subjective diagnosis to objective quantification. We evaluate this algorithm in patients with weight changes. MATERIALS AND METHODS Patients (N = 101) who experienced weight changes ≥ 5% were selected for the study, using serial ultrasound studies retrospectively collected from 2013 to 2021. After applying our exclusion criteria, 74 patients from 239 studies were included. We classified images into four scanning views and applied the algorithm. Mean values from 3-5 images in each group were used for the results and correlated against weight changes. RESULTS Images from the left lobe (G1) in 45 patients, right intercostal view (G2) in 67 patients, and subcostal view (G4) in 46 patients were collected. In a head-to-head comparison, G1 versus G2 or G2 versus G4 views showed identical steatosis scores (R2 > 0.86, p < 0.001). The body weight and steatosis scores were significantly correlated (R2 = 0.62, p < 0.001). Significant differences in steatosis scores between the highest and lowest body weight timepoints were found (p < 0.001). Men showed a higher liver steatosis/BMI ratio than women (p = 0.026). CONCLUSIONS The best scanning conditions are 3-5 images from the right intercostal view. The algorithm objectively quantified liver steatosis, which correlated with body weight changes and gender.
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Affiliation(s)
- Adam P. Harrison
- Research Division, Riverain Technologies, Miamisburg, OH 45342, USA;
| | - Bowen Li
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 20818, USA;
| | - Tse-Hwa Hsu
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan; (T.-H.H.); (C.-J.C.); (W.-T.Y.); (J.T.)
| | - Cheng-Jen Chen
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan; (T.-H.H.); (C.-J.C.); (W.-T.Y.); (J.T.)
| | - Wan-Ting Yu
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan; (T.-H.H.); (C.-J.C.); (W.-T.Y.); (J.T.)
| | - Jennifer Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan; (T.-H.H.); (C.-J.C.); (W.-T.Y.); (J.T.)
| | - Le Lu
- DAMO Academy, Alibaba Group, New York, NY 94085, USA;
| | - Dar-In Tai
- Department of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan 33305, Taiwan; (T.-H.H.); (C.-J.C.); (W.-T.Y.); (J.T.)
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Jeon SK, Lee JM, Cho SJ, Byun YH, Jee JH, Kang M. Development and validation of multivariable quantitative ultrasound for diagnosing hepatic steatosis. Sci Rep 2023; 13:15235. [PMID: 37709827 PMCID: PMC10502048 DOI: 10.1038/s41598-023-42463-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 09/11/2023] [Indexed: 09/16/2023] Open
Abstract
This study developed and validated multivariable quantitative ultrasound (QUS) model for diagnosing hepatic steatosis. Retrospective secondary analysis of prospectively collected QUS data was performed. Participants underwent QUS examinations and magnetic resonance imaging proton density fat fraction (MRI-PDFF; reference standard). A multivariable regression model for estimating hepatic fat fraction was determined using two QUS parameters from one tertiary hospital (development set). Correlation between QUS-derived estimated fat fraction(USFF) and MRI-PDFF and diagnostic performance of USFF for hepatic steatosis (MRI-PDFF ≥ 5%) were assessed, and validated in an independent data set from the other health screening center(validation set). Development set included 173 participants with suspected NAFLD with 126 (72.8%) having hepatic steatosis; and validation set included 452 health screening participants with 237 (52.4%) having hepatic steatosis. USFF was correlated with MRI-PDFF (Pearson r = 0.799 and 0.824; development and validation set). The model demonstrated high diagnostic performance, with areas under the receiver operating characteristic curves of 0.943 and 0.924 for development and validation set, respectively. Using cutoff of 6.0% from development set, USFF showed sensitivity, specificity, positive predictive value, and negative predictive value of 87.8%, 78.6%, 81.9%, and 85.4% for diagnosing hepatic steatosis in validation set. In conclusion, multivariable QUS parameters-derived estimated fat fraction showed high diagnostic performance for detecting hepatic steatosis.
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Affiliation(s)
- Sun Kyung Jeon
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehangno, Jongno-gu, Seoul, 03080, Korea
| | - Jeong Min Lee
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehangno, Jongno-gu, Seoul, 03080, Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.
| | - Soo Jin Cho
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-Gu, Seoul, 06351, Korea.
| | - Young-Hye Byun
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Jae Hwan Jee
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-Gu, Seoul, 06351, Korea
| | - Mira Kang
- Center for Health Promotion, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-Gu, Seoul, 06351, Korea
- Department of Digital Health, Samsung Advanced Institute of Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, Korea
- Digital Innovation Center, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
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Pickhardt PJ. Abdominal Imaging in the Coming Decades: Better, Faster, Safer, and Cheaper? Radiology 2023; 307:e222551. [PMID: 36916892 DOI: 10.1148/radiol.223087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Affiliation(s)
- Perry J Pickhardt
- From the Department of Radiology, University of Wisconsin School of Medicine & Public Health, 600 Highland Ave, E3/311 Clinical Science Center, Madison, WI 53792-3252
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