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Miranda J, Key Wakate Teruya A, Leão Filho H, Lahan-Martins D, Tamura Sttefano Guimarães C, de Paula Reis Guimarães V, Ide Yamauchi F, Blasbalg R, Velloni FG. Diffuse and focal liver fat: advanced imaging techniques and diagnostic insights. Abdom Radiol (NY) 2024; 49:4437-4462. [PMID: 38896247 DOI: 10.1007/s00261-024-04407-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/21/2024]
Abstract
The fatty liver disease represents a complex, multifaceted challenge, requiring a multidisciplinary approach for effective management and research. This article uses conventional and advanced imaging techniques to explore the etiology, imaging patterns, and quantification methods of hepatic steatosis. Particular emphasis is placed on the challenges and advancements in the imaging diagnostics of fatty liver disease. Techniques such as ultrasound, CT, MRI, and elastography are indispensable for providing deep insights into the liver's fat content. These modalities not only distinguish between diffuse and focal steatosis but also help identify accompanying conditions, such as inflammation and fibrosis, which are critical for accurate diagnosis and management.
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Affiliation(s)
- Joao Miranda
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY, 10065, USA.
- Department of Radiology, University of São Paulo, R. Dr. Ovídio Pires de Campos, 75-Cerqueira César, São Paulo, SP, 05403-010, Brazil.
| | - Alexandre Key Wakate Teruya
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
| | - Hilton Leão Filho
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
| | - Daniel Lahan-Martins
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
- Departament of Radiology-FCM, State University of Campinas (UNICAMP), R. Tessália Vieira de Camargo, 126 Cidade Universitária, Campinas, SP, 13083-887, Brazil
| | - Cássia Tamura Sttefano Guimarães
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
| | - Vivianne de Paula Reis Guimarães
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
| | - Fernando Ide Yamauchi
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
| | - Roberto Blasbalg
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
| | - Fernanda Garozzo Velloni
- Department of Radiology, Diagnósticos da América SA (DASA), Av Juruá 434, Alphaville Industrial, Barueri, São Paulo, SP, 06455-010, Brazil
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Haghshomar M, Antonacci D, Smith AD, Thaker S, Miller FH, Borhani AA. Diagnostic Accuracy of CT for the Detection of Hepatic Steatosis: A Systematic Review and Meta-Analysis. Radiology 2024; 313:e241171. [PMID: 39499183 DOI: 10.1148/radiol.241171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2024]
Abstract
Background CT plays an important role in the opportunistic identification of hepatic steatosis. CT performance for steatosis detection has been inconsistent across various studies, and no clear guidelines on optimum thresholds have been established. Purpose To conduct a systematic review and meta-analysis to assess CT diagnostic accuracy in hepatic steatosis detection and to determine reliable cutoffs for the commonly mentioned measures in the literature. Materials and Methods A systematic search of the PubMed, Embase, and Scopus databases (English-language studies published from September 1977 to January 2024) was performed. Studies evaluating the diagnostic accuracy of noncontrast CT (NCCT), contrast-enhanced (CECT), and dual-energy CT (DECT) for hepatic steatosis detection were included. Reference standards included biopsy, MRI proton density fat fraction (PDFF), or NCCT. In several CECT and DECT studies, NCCT was used as the reference standard, necessitating subgroup analysis. Statistical analysis included a random-effects meta-analysis, assessment of heterogeneity with use of the I2 statistic, and meta-regression to explore potential sources of heterogeneity. When available, mean liver attenuation, liver-spleen attenuation difference, liver to spleen attenuation ratio, and the DECT-derived fat fraction for hepatic steatosis diagnosis were assessed. Results Forty-two studies (14 186 participants) were included. NCCT had a sensitivity and specificity of 72% and 88%, respectively, for steatosis (>5% fat at biopsy) detection and 82% and 94% for at least moderate steatosis (over 20%-33% fat at biopsy) detection. CECT had a sensitivity and specificity of 66% and 90% for steatosis detection and 68% and 93% for at least moderate steatosis detection. DECT had a sensitivity and specificity of 85% and 88% for steatosis detection. In the subgroup analysis, the sensitivity and specificity for detecting steatosis were 80% and 99% for CECT and 84% and 93% for DECT. There was heterogeneity among studies focusing on CECT and DECT. Liver attenuation less than 40-45 HU, liver-spleen attenuation difference less than -5 to 0 HU, and liver to spleen attenuation ratio less than 0.9-1 achieved high specificity for detection of at least moderate steatosis. Conclusion NCCT showed high performance for detection of at least moderate steatosis. © RSNA, 2024 Supplemental material is available for this article.
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Affiliation(s)
- Maryam Haghshomar
- From the Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Arkes Family Pavilion, Ste 800, Chicago, IL 60611 (M.H., D.A., S.T., F.H.M., A.A.B.); and Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (A.D.S.)
| | - Dominic Antonacci
- From the Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Arkes Family Pavilion, Ste 800, Chicago, IL 60611 (M.H., D.A., S.T., F.H.M., A.A.B.); and Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (A.D.S.)
| | - Andrew D Smith
- From the Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Arkes Family Pavilion, Ste 800, Chicago, IL 60611 (M.H., D.A., S.T., F.H.M., A.A.B.); and Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (A.D.S.)
| | - Sarang Thaker
- From the Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Arkes Family Pavilion, Ste 800, Chicago, IL 60611 (M.H., D.A., S.T., F.H.M., A.A.B.); and Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (A.D.S.)
| | - Frank H Miller
- From the Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Arkes Family Pavilion, Ste 800, Chicago, IL 60611 (M.H., D.A., S.T., F.H.M., A.A.B.); and Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (A.D.S.)
| | - Amir A Borhani
- From the Department of Radiology, Northwestern University Feinberg School of Medicine, 676 N St. Clair St, Arkes Family Pavilion, Ste 800, Chicago, IL 60611 (M.H., D.A., S.T., F.H.M., A.A.B.); and Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, Tenn (A.D.S.)
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Hosseini Shabanan S, Martins VF, Wolfson T, Weeks JT, Ceriani L, Behling C, Chernyak V, El Kaffas A, Borhani AA, Han A, Wang K, Fowler KJ, Sirlin CB. MASLD: What We Have Learned and Where We Need to Go-A Call to Action. Radiographics 2024; 44:e240048. [PMID: 39418184 DOI: 10.1148/rg.240048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
Since its introduction in 1980, fatty liver disease (now termed metabolic dysfunction-associated steatotic liver disease [MASLD]) has grown in prevalence significantly, paralleling the rise of obesity worldwide. While MASLD has been the subject of extensive research leading to significant progress in the understanding of its pathophysiology and progression factors, several gaps in knowledge remain. In this pictorial review, the authors present the latest insights into MASLD, covering its recent nomenclature change, spectrum of disease, epidemiology, morbidity, and mortality. The authors also discuss current qualitative and quantitative imaging methods for assessing and monitoring MASLD. Last, they propose six unsolved challenges in MASLD assessment, which they term the proliferation, reproducibility, reporting, needle-in-the-haystack, availability, and knowledge problems. These challenges offer opportunities for the radiology community to proactively contribute to their resolution. The authors conclude with a call to action for the entire radiology community to claim a seat at the table, collaborate with other societies, and commit to advancing the development, validation, dissemination, and accessibility of the imaging technologies required to combat the looming health care crisis of MASLD.
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Affiliation(s)
- Sedighe Hosseini Shabanan
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Vitor F Martins
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Tanya Wolfson
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Jake T Weeks
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Lael Ceriani
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Cynthia Behling
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Victoria Chernyak
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Ahmed El Kaffas
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Amir A Borhani
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Aiguo Han
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Kang Wang
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Kathryn J Fowler
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
| | - Claude B Sirlin
- From the Department of Radiology, UC San Diego Altman Clinical and Translational Research Institute Liver Imaging Group, University of California San Diego, 9452 Medical Center Dr, La Jolla, CA 92037 (S.H.S., V.F.M., T.W., J.T.W., L.C., K.J.F., C.B.S.); Pacific Rim Pathology, San Diego, Calif (C.B.); Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY (V.C.); Department of Radiology, Stanford University School of Medicine, Stanford, Calif (A.E.K.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (A.A.B.); Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, Va (A.H.); and Department of Radiology, University of California San Francisco, Calif (K.W.)
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Hao W, Xu Z, Lin H, Yan F. Using Dual-source Photon-counting Detector CT to Simultaneously Quantify Fat and Iron Content: A Phantom Study. Acad Radiol 2024; 31:4119-4128. [PMID: 38772799 DOI: 10.1016/j.acra.2024.04.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/21/2024] [Accepted: 04/26/2024] [Indexed: 05/23/2024]
Abstract
RATIONALE AND OBJECTIVES To evaluate the feasibility of using photon-counting detector computed tomography (PCD CT) to simultaneously quantify fat and iron content MATERIALS AND METHODS: Phantoms with pure fat, pure iron and fat-iron deposition were scanned by two tube voltages (120 and 140 kV) and two image quality (IQ) settings (80 and 145). Using an iron-specific three-material decomposition algorithm, virtual noniron (VNI) and virtual iron content (VIC) images were generated at quantum iterative reconstruction (QIR) strength levels 1-4. RESULTS Significant linear correlations were observed between known fat content (FC) and VNI for pure fat phantoms (r = 0.981-0.999, p < 0.001) and between known iron content (IC) and VIC for pure iron phantoms (r = 0.897-0.975, p < 0.001). In fat-iron phantoms, the measurement for fat content of 5-30% demonstrated good linearity between FC and VNI (r = 0.919-0.990, p < 0.001), and VNI were not affected by 75, 150, and 225 µmol/g iron overload (p = 0.174-0.519). The measurement for iron demonstrated a linear range of 75-225 µmol/g between IC and VIC (r = 0.961-0.994, p < 0.001) and VIC was not confounded by the coexisting 5%, 20%, and 30% fat deposition (p = 0.943-0.999). The Bland-Altman of fat and iron measurements were not significantly different at varying tube voltages and IQ settings (all p > 0.05). No significant difference in VNI and VIC at QIR 1-4. CONCLUSION PCD CT can accurately and simultaneously quantify fat and iron, including scan parameters with lower radiation dose.
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Affiliation(s)
- Wanting Hao
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China.
| | - Zhihan Xu
- CT Collaboration, Siemens Healthcare Ltd., No. 278 Zhouzhu Road, Shanghai 200025, China.
| | - Huimin Lin
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China.
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No. 197 Ruijin Er Road, Shanghai 200025, China; Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine.
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Wang M, Ma Y, Lan Y, Bai R, Yang L, Hou Y. Association of liver multi-parameter quantitative metrics determined by dual-layer spectral detector computed tomography (SDCT) with coronary plaque scores. Quant Imaging Med Surg 2024; 14:7392-7405. [PMID: 39429605 PMCID: PMC11485365 DOI: 10.21037/qims-24-53] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 08/15/2024] [Indexed: 10/22/2024]
Abstract
Background Hepatic steatosis is closely related to the occurrence and development of coronary plaques. Spectral detector computed tomography (SDCT) can provide more precise multiparameter quantitative parameters for hepatic steatosis. Hence, the purpose of this cross-sectional study was to explore the effect of quantitative liver metrics measured using SDCT on the extent and severity of coronary plaques. Methods In patients who underwent upper abdomen unenhanced SDCT and coronary computed tomography angiography, plaque extent and severity were assessed using segmental involvement score (SIS) and segmental stenosis score (SSS). Liver fat quantification was evaluated by polychromatic and virtual mono-energetic images at 40 and 70 kev, spectral attenuation curve slope, and effective atomic number (CT40 keV, CT70 kev, λHU, and Zeff, respectively). A logistic regression model evaluated the factors influencing high SIS and SSS. Results Enrolled patients (n=644) were divided into groups: low SIS (<5) (n=451), high SIS (≥5) (n=193), low SSS (<5) (n=461), and high SSS (≥5) (n=183). Zeff was more closely correlated with SIS (standard partial regression coefficient =-0.422, P<0.001) and SSS (standard partial regression coefficient =-0.346, P<0.001). Zeff was divided into four groups using interquartile intervals. Compared with the patients in the lowest quartile, those in the second [odds ratio (OR) =2.116, 95% confidence interval (CI): 1.134-3.949, P=0.018], third (OR =2.832, 95% CI: 1.461-5.491, P=0.002), and fourth (OR =3.584, 95% CI: 1.857-6.918, P<0.001) quartiles showed higher risk for high SIS. And correspondingly, the second (OR =1.933, 95% CI: 1.040-3.592, P=0.037), third (OR =2.900, 95% CI: 1.499-5.609, P=0.002), and fourth (OR =3.368, 95% CI: 1.743-6.510, P<0.001) quartiles showed higher risk for high SSS, especially in those who were <60 years old, male and had visceral adipose tissue/subcutaneous adipose tissue <1.18. Conclusions The SDCT-Zeff was an independent factor associated with high SIS and SSS. The quantification of liver fat may be useful for evaluating the risk and prognosis of coronary atherosclerosis.
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Affiliation(s)
- Min Wang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yue Ma
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu Lan
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ruobing Bai
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Linlin Yang
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yang Hou
- Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China
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Ferraioli G, Barr RG. Ultrasound evaluation of chronic liver disease. Abdom Radiol (NY) 2024:10.1007/s00261-024-04568-2. [PMID: 39292280 DOI: 10.1007/s00261-024-04568-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2024] [Revised: 08/30/2024] [Accepted: 08/31/2024] [Indexed: 09/19/2024]
Abstract
Chronic liver disease is a world-wide epidemic. Any etiology that causes inflammation in the liver will lead to chronic liver disease. Presently, the most common inciting factor worldwide is steatotic liver disease. Recent advances in ultrasound imaging provide a multiparametric ultrasound methodology of diagnosing, staging, and monitoring treatment of chronic liver disease. Elastography has become a standard of care technique for the evaluation of liver fibrosis. Quantitative ultrasound allows for determination of the degree of fatty infiltration of the liver. Portal hypertension is the most important factor in determination of liver decompensation. B-mode findings combined with Doppler, and elastography techniques provide qualitative and quantitative methods of determining clinically significant portal hypertension. A newer method using contrast enhanced ultrasound may allow for a non-invasive quantitative estimation of the portal pressures. This paper reviews the use of multiparametric ultrasound in the evaluation of chronic liver disease including conventional B-mode ultrasound, Doppler, elastography and quantitative ultrasound for estimation of liver fat. The recent guidelines are presented and advised protocols reviewed.
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Affiliation(s)
- Giovanna Ferraioli
- Department of Clinical, Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Viale Brambilla 74, 27100, Pavia, Italy.
| | - Richard G Barr
- Department of Radiology, Northeastern Ohio Medical University, Rootstown, OH, USA
- Southwoods Imaging, 7623 Market Street, Youngstown, OH, 44512, USA
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Chen LZ, Jing XB, Chen X, Xie YC, Chen Y, Cai XB. Non-Invasive Serum Markers of Non-Alcoholic Fatty Liver Disease Fibrosis: Potential Tools for Detecting Patients with Cardiovascular Disease. Rev Cardiovasc Med 2024; 25:344. [PMID: 39355605 PMCID: PMC11440407 DOI: 10.31083/j.rcm2509344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Revised: 05/23/2024] [Accepted: 05/28/2024] [Indexed: 10/03/2024] Open
Abstract
Non-alcoholic fatty liver disease (NAFLD), one of the most common chronic liver diseases with a prevalence of 23%-25% globally, is an independent risk factor for cardiovascular diseases (CVDs). Growing evidence indicates that the development of NAFLD, ranging from non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), advanced fibrosis to cirrhosis, and even hepatocellular carcinoma, is at substantial risk for CVDs, which clinically contribute to increased cardiovascular morbidity and mortality. Non-invasive serum markers assessing liver fibrosis, such as fibrosis-4 (FIB-4) score, aspartate transaminase-to-platelet ratio index (APRI), and NAFLD fibrosis score (NFS), are expected to be useful tools for clinical management of patients with CVDs. This review aims to provide an overview of the evidence for the relationship between the progression of NAFLD and CVDs and the clinical application of non-invasive markers of liver fibrosis in managing patients with CVDs.
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Affiliation(s)
- Ling-Zi Chen
- Department of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, 515041 Shantou, Guangdong, China
| | - Xu-Bin Jing
- Department of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, 515041 Shantou, Guangdong, China
| | - Xiang Chen
- Department of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, 515041 Shantou, Guangdong, China
| | - Yan-Chun Xie
- Department of Endoscopy Center, Cancer Hospital of Shantou University Medical College, 515041 Shantou, Guangdong, China
| | - Yun Chen
- Department of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, 515041 Shantou, Guangdong, China
| | - Xian-Bin Cai
- Department of Gastroenterology, The First Affiliated Hospital of Shantou University Medical College, 515041 Shantou, Guangdong, China
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Jeon SK, Joo I, Park J, Yoo J. Automated hepatic steatosis assessment on dual-energy CT-derived virtual non-contrast images through fully-automated 3D organ segmentation. LA RADIOLOGIA MEDICA 2024; 129:967-976. [PMID: 38869829 PMCID: PMC11252222 DOI: 10.1007/s11547-024-01833-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 05/30/2024] [Indexed: 06/14/2024]
Abstract
PURPOSE To evaluate the efficacy of volumetric CT attenuation-based parameters obtained through automated 3D organ segmentation on virtual non-contrast (VNC) images from dual-energy CT (DECT) for assessing hepatic steatosis. MATERIALS AND METHODS This retrospective study included living liver donor candidates having liver DECT and MRI-determined proton density fat fraction (PDFF) assessments. Employing a 3D deep learning algorithm, the liver and spleen were automatically segmented from VNC images (derived from contrast-enhanced DECT scans) and true non-contrast (TNC) images, respectively. Mean volumetric CT attenuation values of each segmented liver (L) and spleen (S) were measured, allowing for liver attenuation index (LAI) calculation, defined as L minus S. Agreements of VNC and TNC parameters for hepatic steatosis, i.e., L and LAI, were assessed using intraclass correlation coefficients (ICC). Correlations between VNC parameters and MRI-PDFF values were assessed using the Pearson's correlation coefficient. Their performance to identify MRI-PDFF ≥ 5% and ≥ 10% was evaluated using receiver operating characteristic (ROC) curve analysis. RESULTS Of 252 participants, 56 (22.2%) and 16 (6.3%) had hepatic steatosis with MRI-PDFF ≥ 5% and ≥ 10%, respectively. LVNC and LAIVNC showed excellent agreement with LTNC and LAITNC (ICC = 0.957 and 0.968) and significant correlations with MRI-PDFF values (r = - 0.585 and - 0.588, Ps < 0.001). LVNC and LAIVNC exhibited areas under the ROC curve of 0.795 and 0.806 for MRI-PDFF ≥ 5%; and 0.916 and 0.932, for MRI-PDFF ≥ 10%, respectively. CONCLUSION Volumetric CT attenuation-based parameters from VNC images generated by DECT, via automated 3D segmentation of the liver and spleen, have potential for opportunistic hepatic steatosis screening, as an alternative to TNC images.
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Affiliation(s)
- Sun Kyung Jeon
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea
| | - Ijin Joo
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
- Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea.
- Institute of Radiation Medicine, Seoul National University Medical Research Center Seoul National University Hospital, Seoul, Korea.
| | - Junghoan Park
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea
| | - Jeongin Yoo
- Department of Radiology, Seoul National University Hospital and Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea
- Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea
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9
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Swartz AZ, Robles ME, Park S, Esfandiari H, Bradshaw M, Koethe JR, Silver HJ. Cardiometabolic Characteristics of Obesity Phenotypes in Persons With HIV. Open Forum Infect Dis 2024; 11:ofae376. [PMID: 39035569 PMCID: PMC11259191 DOI: 10.1093/ofid/ofae376] [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: 01/26/2024] [Accepted: 07/02/2024] [Indexed: 07/23/2024] Open
Abstract
Background In the general population, it is established that adipose tissue depots pose various risks for cardiometabolic diseases. The interaction among obesity, HIV, and antiretroviral treatment promotes even greater risk for persons with HIV (PWH). As obesity is a heterogeneous condition, determining the specific obesity phenotypes present and their characteristics is critical to personalize care in PWH. Methods Visceral, sarcopenic, myosteatotic, hepatosteatotic, and metabolically healthy obesity phenotypes were determined by pre-established cut points after segmentation of computed tomography scans at the L3 vertebra. Multivariable linear regression modeling included anthropometrics, clinical biomarkers, and inflammatory factors while controlling for age, sex, race, and body mass index (BMI). Results Of 187 PWH, 86% were male, and the mean ± SD age and BMI were 51.2 ± 12.3 years and 32.6 ± 6.3 kg/m2. Overall, 59% had visceral obesity, 11% sarcopenic obesity, 25% myosteatotic obesity, 9% hepatosteatotic obesity, and 32% metabolically healthy obesity. The strongest predictor of visceral obesity was an elevated triglyceride:high-density lipoprotein (HDL) ratio. Increased subcutaneous fat, waist circumference, and HDL cholesterol were predictors of sarcopenic obesity. Diabetes status and elevated interleukin 6, waist circumference, and HDL cholesterol predicted myosteatotic obesity. An increased CD4+ count and a decreased visceral:subcutaneous adipose tissue ratio predicted hepatosteatotic obesity, though accounting for only 28% of its variability. Participants with metabolically healthy obesity were on average 10 years younger, had higher HDL, lower triglyceride:HDL ratio, and reduced CD4+ counts. Conclusions These findings show that discrete obesity phenotypes are highly prevalent in PWH and convey specific risk factors that measuring BMI alone does not capture. These clinically relevant findings can be used in risk stratification and optimization of personalized treatment regimens. This study is registered at ClinicalTrials.gov (NCT04451980).
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Affiliation(s)
- Alison Z Swartz
- School of Medicine, Vanderbilt University, Nashville, Tennessee, USA
| | - Michelle E Robles
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Seungweon Park
- School of Medicine, Vanderbilt University, Nashville, Tennessee, USA
| | - Helia Esfandiari
- College of Arts and Sciences, University of Tennessee, Knoxville, Tennessee, USA
| | - Marques Bradshaw
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, Tennessee, USA
| | - John R Koethe
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, Tennessee, USA
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Heidi J Silver
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, Tennessee, USA
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Torgersen J, Skanderson M, Kidwai-Khan F, Carbonari DM, Tate JP, Park LS, Bhattacharya D, Lim JK, Taddei TH, Justice AC, Lo Re V. Identification of hepatic steatosis among persons with and without HIV using natural language processing. Hepatol Commun 2024; 8:e0468. [PMID: 38896066 PMCID: PMC11186806 DOI: 10.1097/hc9.0000000000000468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 04/19/2024] [Indexed: 06/21/2024] Open
Abstract
BACKGROUND Steatotic liver disease (SLD) is a growing phenomenon, and our understanding of its determinants has been limited by our ability to identify it clinically. Natural language processing (NLP) can potentially identify hepatic steatosis systematically within large clinical repositories of imaging reports. We validated the performance of an NLP algorithm for the identification of SLD in clinical imaging reports and applied this tool to a large population of people with and without HIV. METHODS Patients were included in the analysis if they enrolled in the Veterans Aging Cohort Study between 2001 and 2017, had an imaging report inclusive of the liver, and had ≥2 years of observation before the imaging study. SLD was considered present when reports contained the terms "fatty," "steatosis," "steatotic," or "steatohepatitis." The performance of the SLD NLP algorithm was compared to a clinical review of 800 reports. We then applied the NLP algorithm to the first eligible imaging study and compared patient characteristics by SLD and HIV status. RESULTS NLP achieved 100% sensitivity and 88.5% positive predictive value for the identification of SLD. When applied to 26,706 eligible Veterans Aging Cohort Study patient imaging reports, SLD was identified in 72.2% and did not significantly differ by HIV status. SLD was associated with a higher prevalence of metabolic comorbidities, alcohol use disorder, and hepatitis B and C, but not HIV infection. CONCLUSIONS While limited to those undergoing radiologic study, the NLP algorithm accurately identified SLD in people with and without HIV and offers a valuable tool to evaluate the determinants and consequences of hepatic steatosis.
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Affiliation(s)
- Jessie Torgersen
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real-world Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Melissa Skanderson
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, VA Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Farah Kidwai-Khan
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, VA Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Dena M. Carbonari
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real-world Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Janet P. Tate
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, VA Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Lesley S. Park
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, California, USA
| | - Debika Bhattacharya
- Department of Medicine, VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Joseph K. Lim
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, VA Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Tamar H. Taddei
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, VA Connecticut Healthcare System, West Haven, Connecticut, USA
| | - Amy C. Justice
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, VA Connecticut Healthcare System, West Haven, Connecticut, USA
- Department of Epidemiology and Public Health, Division of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, USA
| | - Vincent Lo Re
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real-world Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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11
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Savino A, Loglio A, Neri F, Camagni S, Pasulo L, Lucà MG, Trevisan R, Fagiuoli S, Viganò M. Metabolic-Dysfunction-Associated Steatotic Liver Disease (MASLD) after Liver Transplantation: A Narrative Review of an Emerging Issue. J Clin Med 2024; 13:3871. [PMID: 38999436 PMCID: PMC11242808 DOI: 10.3390/jcm13133871] [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: 05/30/2024] [Revised: 06/23/2024] [Accepted: 06/24/2024] [Indexed: 07/14/2024] Open
Abstract
The development of steatotic liver disease after liver transplant (LT) is widely described, and epidemiological data have revealed an increased incidence in recent times. Its evolution runs from simple steatosis to steatohepatitis and, in a small proportion of patients, to significant fibrosis and cirrhosis. Apparently, post-LT steatotic disease has no impact on the recipient's overall survival; however, a higher cardiovascular and malignancy burden has been reported. Many donors' and recipients' risk factors have been associated with this occurrence, although the recipient-related ones seem of greater impact. Particularly, pre- and post-LT metabolic alterations are strictly associated with steatotic graft disease, sharing common pathophysiologic mechanisms that converge on insulin resistance. Other relevant risk factors include genetic variants, sex, age, baseline liver diseases, and immunosuppressive drugs. Diagnostic evaluation relies on liver biopsy, although non-invasive methods are being increasingly used to detect and monitor both steatosis and fibrosis stages. Management requires a multifaceted approach focusing on lifestyle modifications, the optimization of immunosuppressive therapy, and the management of metabolic complications. This review aims to synthesize the current knowledge of post-LT steatotic liver disease, focusing on the recent definition of metabolic-dysfunction-associated steatotic liver disease (MASLD) and its metabolic and multisystemic concerns.
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Affiliation(s)
- Alberto Savino
- Gastroenterology Hepatology and Transplantation Unit, ASST Papa Giovanni XXIII, Piazza OMS 1, 24127 Bergamo, Italy; (A.S.); (S.F.)
- Gastroenterology, Department of Medicine, University of Milan Bicocca, 20126 Milan, Italy
| | - Alessandro Loglio
- Gastroenterology Hepatology and Transplantation Unit, ASST Papa Giovanni XXIII, Piazza OMS 1, 24127 Bergamo, Italy; (A.S.); (S.F.)
| | - Flavia Neri
- Department of Organ Failure and Transplantation, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
| | - Stefania Camagni
- Department of Organ Failure and Transplantation, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
| | - Luisa Pasulo
- Gastroenterology Hepatology and Transplantation Unit, ASST Papa Giovanni XXIII, Piazza OMS 1, 24127 Bergamo, Italy; (A.S.); (S.F.)
| | - Maria Grazia Lucà
- Gastroenterology Hepatology and Transplantation Unit, ASST Papa Giovanni XXIII, Piazza OMS 1, 24127 Bergamo, Italy; (A.S.); (S.F.)
| | - Roberto Trevisan
- Endocrine and Diabetology Unit, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
- Department of Medicine and Surgery, University of Milano Bicocca, 20126 Milan, Italy
| | - Stefano Fagiuoli
- Gastroenterology Hepatology and Transplantation Unit, ASST Papa Giovanni XXIII, Piazza OMS 1, 24127 Bergamo, Italy; (A.S.); (S.F.)
- Gastroenterology, Department of Medicine, University of Milan Bicocca, 20126 Milan, Italy
| | - Mauro Viganò
- Gastroenterology Hepatology and Transplantation Unit, ASST Papa Giovanni XXIII, Piazza OMS 1, 24127 Bergamo, Italy; (A.S.); (S.F.)
- Gastroenterology, Department of Medicine, University of Milan Bicocca, 20126 Milan, Italy
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12
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Yin H, Fan Y, Yu J, Xiong B, Zhou B, Sun Y, Wang L, Zhu Y, Xu H. Quantitative US fat fraction for noninvasive assessment of hepatic steatosis in suspected metabolic-associated fatty liver disease. Insights Imaging 2024; 15:159. [PMID: 38902550 PMCID: PMC11190099 DOI: 10.1186/s13244-024-01728-2] [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: 09/26/2023] [Accepted: 05/19/2024] [Indexed: 06/22/2024] Open
Abstract
OBJECTIVES To evaluate the agreement between quantitative ultrasound system fat fraction (USFF) and proton magnetic resonance spectroscopy (1H-MRS) and the diagnostic value of USFF in assessing metabolic-associated fatty liver disease (MAFLD). METHODS The participants with or suspected of MAFLD were prospectively recruited and underwent 1H-MRS, USFF, and controlled attenuation parameter (CAP) measurements. The correlation between USFF and 1H-MRS was assessed using Pearson correlation coefficients. The USFF diagnostic performance for different grades of steatosis was evaluated using receiver operating characteristic curve analysis (ROC) and was compared with CAP, visual hepatic steatosis grade (VHSG). RESULTS A total of 113 participants (mean age 44.79 years ± 13.56 (SD); 71 males) were enrolled, of whom 98 (86.73%) had hepatic steatosis (1H-MRS ≥ 5.56%). USFF showed a good correlation (Pearson r = 0.76) with 1H-MRS and showed a linear relationship, which was superior to the correlation between CAP and 1H-MRS (Pearson r = 0.61). The USFF provided high diagnostic performance for different grades of hepatic steatosis, with ROC from 0.84 to 0.98, and the diagnostic performance was better than that of the CAP and the VHSG. The cut-off values of the USFF were different for various grades of steatosis, and the cut-off values for S1, S2, and S3 were 12.01%, 19.98%, and 22.22%, respectively. CONCLUSIONS There was a good correlation between USFF and 1H-MRS. Meanwhile, USFF had good diagnostic performance for hepatic steatosis and was superior to CAP and VHSG. USFF represents a superior method for noninvasive quantitative assessment of MAFLD. CRITICAL RELEVANCE STATEMENT Quantitative ultrasound system fat fraction (USFF) accurately assesses liver fat content and has a good correlation with magnetic resonance spectroscopy (1H-MRS) for the assessment of metabolic-associated fatty liver disease (MAFLD), as well as for providing an accurate quantitative assessment of hepatic steatosis. KEY POINTS Current diagnostic and monitoring modalities for metabolic-associated fatty liver disease have limitations. USFF correlated well with 1H-MRS and was superior to the CAP. USFF has good diagnostic performance for steatosis, superior to CAP and VHSG.
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Affiliation(s)
- Haohao Yin
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Yunling Fan
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Jifeng Yu
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Bing Xiong
- Shanghai Institute of Medical Imaging, Fudan University, Shanghai, 200032, China
| | - Boyang Zhou
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Yikang Sun
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Lifan Wang
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China
| | - Yuli Zhu
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China.
| | - Huixiong Xu
- Department of Ultrasound, Zhongshan Hospital, Institute of Ultrasound in Medicine and Engineering, Fudan University, Shanghai, 200032, China.
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Chan WK, Petta S, Noureddin M, Goh GBB, Wong VWS. Diagnosis and non-invasive assessment of MASLD in type 2 diabetes and obesity. Aliment Pharmacol Ther 2024; 59 Suppl 1:S23-S40. [PMID: 38813831 DOI: 10.1111/apt.17866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/24/2023] [Accepted: 12/26/2023] [Indexed: 05/31/2024]
Abstract
BACKGROUND Metabolic dysfunction-associated steatotic liver disease (MASLD) is currently the most common chronic liver disease and an important cause of cirrhosis and hepatocellular carcinoma. It is strongly associated with type 2 diabetes and obesity. Because of the huge number of patients at risk of MASLD, it is imperative to use non-invasive tests appropriately. AIMS To provide a narrative review on the performance and limitations of non-invasive tests, with a special emphasis on the impact of diabetes and obesity. METHODS We searched PubMed and Cochrane databases for articles published from 1990 to August 2023. RESULTS Abdominal ultrasonography remains the primary method to diagnose hepatic steatosis, while magnetic resonance imaging proton density fat fraction is currently the gold standard to quantify steatosis. Simple fibrosis scores such as the Fibrosis-4 index are well suited as initial assessment in primary care and non-hepatology settings to rule out advanced fibrosis and future risk of liver-related complications. However, because of its low positive predictive value, an abnormal test should be followed by specific blood (e.g. Enhanced Liver Fibrosis score) or imaging biomarkers (e.g. vibration-controlled transient elastography and magnetic resonance elastography) of fibrosis. Some non-invasive tests of fibrosis appear to be less accurate in patients with diabetes. Obesity also affects the performance of abdominal ultrasonography and transient elastography, whereas magnetic resonance imaging may not be feasible in some patients with severe obesity. CONCLUSIONS This article highlights issues surrounding the clinical application of non-invasive tests for MASLD in patients with type 2 diabetes and obesity.
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Affiliation(s)
- Wah-Kheong Chan
- Gastroenterology and Hepatology Unit, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Salvatore Petta
- Sezione di Gastroenterologia, PROMISE, University of Palermo, Palermo, Italy
- Department of Economics and Statistics, University of Palermo, Palermo, Italy
| | - Mazen Noureddin
- Houston Methodist Hospital, Houston Research Institute, Houston, Texas, USA
| | - George Boon Bee Goh
- Department of Gastroenterology and Hepatology, Singapore General Hospital, Singapore
- Medicine Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Vincent Wai-Sun Wong
- Medical Data Analytics Centre, Department of Medicine and Therapeutics, 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
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Yoshino Y, Fujii Y, Chihara K, Nakae A, Enmi JI, Yoshioka Y, Miyawaki I. Non-invasive differentiation of hepatic steatosis and steatohepatitis in a mouse model using nitroxyl radical as an MRI-contrast agent. Toxicol Rep 2024; 12:1-9. [PMID: 38173653 PMCID: PMC10758964 DOI: 10.1016/j.toxrep.2023.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
Drug-induced steatohepatitis is considered more serious than drug-induced hepatic steatosis, so that differentiating between the two is crucial in drug development. In addition, early detection of drug-induced steatohepatitis is considered important since recovery is possible with drug withdrawal. However, no method has been established to differentiate between the two. In the development of drug-induced steatohepatitis, reactive oxygen species (ROS) is excessively generated in the liver. It has been reported that ROS can be monitored with electron spin resonance (ESR) and dynamic nuclear polarization-magnetic resonance imaging (DNP-MRI) by using nitroxyl radicals, which are known to participate in various in vivo redox reactions. The decay/reduction rate, which is an index for monitoring nitroxyl radicals, has been reported to be increased in tissues with excessive ROS levels other than liver, but decreased in methionine choline deficient (MCD) diet-induced steatohepatitis with excess ROS. Therefore, looking to differentiate between drug-induced hepatic steatosis and steatohepatitis, we examined whether the reduction rate decreases in steatohepatitis other than the MCD-diet induced disease and whether the decrease could be detected by MRI. We used STAM™ mice in which hepatic steatosis and steatohepatitis developed sequentially under diabetic conditions. 3-carbamoyl-PROXYL (CmP), one of the nitroxyl radicals, was injected intravenously during the MRI procedure and the reduction rate was calculated. The reduction rate was significantly higher in early steatohepatitis than in hepatic steatosis and the control. Excess ROS in early steatohepatitis was detected by an immunohistochemical marker for ROS. Therefore, it was indicated that the increase or decrease in the reduction rate in steatohepatitis differs depending on the model, and early steatohepatitis could be noninvasively differentiated from hepatic steatosis using CmP in MRI. Since the change in direction of the reduction rate in steatohepatitis in clinical studies could be predicted by confirming the reduction rate in preclinical studies, the present method, which can be used consistently in clinical and preclinical studies, warrants consideration as a candidate monitoring method for differentiating between early drug-induced steatohepatitis and hepatic steatosis in drug development.
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Affiliation(s)
- Yuka Yoshino
- Preclinical Research Unit, Sumitomo Pharma Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-0022, Japan
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita city, Osaka 565-0871, Japan
| | - Yuta Fujii
- Preclinical Research Unit, Sumitomo Pharma Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-0022, Japan
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita city, Osaka 565-0871, Japan
| | - Kazuhiro Chihara
- Preclinical Research Unit, Sumitomo Pharma Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-0022, Japan
| | - Aya Nakae
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita city, Osaka 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Osaka University and National Institute of Information and Communications Technology (NICT), 1-4 Yamadaoka, Suita City, Osaka 565-0871, Japan
| | - Jun-ichiro Enmi
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita city, Osaka 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Osaka University and National Institute of Information and Communications Technology (NICT), 1-4 Yamadaoka, Suita City, Osaka 565-0871, Japan
| | - Yoshichika Yoshioka
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita city, Osaka 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Osaka University and National Institute of Information and Communications Technology (NICT), 1-4 Yamadaoka, Suita City, Osaka 565-0871, Japan
| | - Izuru Miyawaki
- Preclinical Research Unit, Sumitomo Pharma Co., Ltd., 3-1-98 Kasugade-naka, Konohana-ku, Osaka 554-0022, Japan
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Pozzobon FM, Luiz RR, Parente JG, Guarilha TM, Fontes MPRC, de Mello Perez R, Chindamo MC. Is Steatotic Liver Disease Related to Poor Outcome in COVID-19-Hospitalized Patients? J Clin Med 2024; 13:2687. [PMID: 38731216 PMCID: PMC11084585 DOI: 10.3390/jcm13092687] [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: 03/25/2024] [Revised: 04/22/2024] [Accepted: 04/25/2024] [Indexed: 05/13/2024] Open
Abstract
Background: Steatotic liver disease (SLD) has been linked to more exacerbated inflammatory responses in various scenarios. The relationship between SLD and COVID-19 prognosis remains unclear. Our aim was to investigate the impact of SLD on the outcome of COVID-19. Methods: Patients hospitalized with confirmed COVID-19 and who underwent laboratory tests and chest CT scans were included. SLD was assessed by measuring the attenuation coefficient on CT scans. The relationship between SLD, the severity of COVID-19 clinical presentation and in-hospital mortality were assessed. Results: A total of 610 patients were included (mean age 62 ± 16 years, 64% male). The prevalence of SLD was 30%, and the overall in-hospital mortality rate was 19%. Patients with SLD were younger (58 ± 13 vs. 64 ± 16 years, p < 0.001) and had a higher BMI (32 ± 5 vs. 28 ± 4 kg/m2, p = 0.014). Admission AST values were higher in patients with SLD (82 ± 339 vs. 50 ± 37, p = 0.02), while D-dimer (1112 ± 2147 vs. 1959 ± 8509, p = 0.07), C-reactive protein (12 ± 9 vs. 11 ± 8, p = 0.27), ALT (67 ± 163 vs. 47 ± 90, p = 0.11), ALP (83 ± 52 vs. 102 ± 125, p = 0.27), and GGT (123 ± 125 vs. 104 ± 146, p = 0.61) did not significantly differ compared to patients without SLD. No difference was observed regarding lung parenchyma involvement >50% (20% vs. 17%, p = 0.25), hospital length of stay (14 ± 19 vs. 16 ± 23 days, p = 0.20), hemodialysis support (14% vs. 16%, p = 0.57), use of mechanical ventilation (20% vs. 20%, p = 0.96), and in-hospital mortality (17% vs. 20%, p = 0.40) when comparing patients with and without SLD. Conclusions: SLD showed no significant association with morbidity and mortality in patients with COVID-19.
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Affiliation(s)
- Fernanda Manhães Pozzobon
- Barra D’Or Hospital, Rede D’Or São Luiz, Rio de Janeiro 22775-002, RJ, Brazil; (J.G.P.); (T.M.G.); (M.P.R.C.F.); (M.C.C.)
- Health Assistance Division, Federal Fluminense University (UFF), Niterói 24220-900, RJ, Brazil
| | - Ronir Raggio Luiz
- Institute for Collective Health Studies, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21941-598, RJ, Brazil;
| | - Júlia Gomes Parente
- Barra D’Or Hospital, Rede D’Or São Luiz, Rio de Janeiro 22775-002, RJ, Brazil; (J.G.P.); (T.M.G.); (M.P.R.C.F.); (M.C.C.)
| | - Taísa Melo Guarilha
- Barra D’Or Hospital, Rede D’Or São Luiz, Rio de Janeiro 22775-002, RJ, Brazil; (J.G.P.); (T.M.G.); (M.P.R.C.F.); (M.C.C.)
| | | | - Renata de Mello Perez
- D’Or Institute for Research and Education (IDOR), Rio de Janeiro 22281-100, RJ, Brazil;
- School of Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21044-020, RJ, Brazil
| | - Maria Chiara Chindamo
- Barra D’Or Hospital, Rede D’Or São Luiz, Rio de Janeiro 22775-002, RJ, Brazil; (J.G.P.); (T.M.G.); (M.P.R.C.F.); (M.C.C.)
- School of Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro 21044-020, RJ, Brazil
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Dioguardi Burgio M, Castera L, Oufighou M, Rautou PE, Paradis V, Bedossa P, Sartoris R, Ronot M, Bodard S, Garteiser P, Van Beers B, Valla D, Vilgrain V, Correas JM. Prospective Comparison of Attenuation Imaging and Controlled Attenuation Parameter for Liver Steatosis Diagnosis in Patients With Nonalcoholic Fatty Liver Disease and Type 2 Diabetes. Clin Gastroenterol Hepatol 2024; 22:1005-1013.e27. [PMID: 38072287 DOI: 10.1016/j.cgh.2023.11.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/31/2023] [Accepted: 11/26/2023] [Indexed: 01/04/2024]
Abstract
BACKGROUND & AIMS Similarly to the controlled attenuation parameter (CAP), the ultrasound-based attenuation imaging (ATI) can quantify hepatic steatosis. We prospectively compared the performance of ATI and CAP for the diagnosis of hepatic steatosis in patients with type 2 diabetes and nonalcoholic fatty liver disease using histology and magnetic resonance imaging-proton density fat fraction (MRI-PDFF) as references. METHODS Patients underwent ATI and CAP measurement, MRI, and biopsy on the same day. Steatosis was classified as S0, S1, S2, and S3 on histology (<5%, 5%-33%, 33%-66%, and >66%, respectively) while the thresholds of 6.4%, 17.4%, and 22.1%, respectively, were used for MRI-PDFF. The area under the curve (AUC) of ATI and CAP was compared using a DeLong test. RESULTS Steatosis could be evaluated in 191 and 187 patients with MRI-PDFF and liver biopsy, respectively. For MRI-PDFF steatosis, the AUC of ATI and CAP were 0.86 (95% confidence interval [CI], 0.81-0.91) vs 0.69 (95% CI, 0.62-0.75) for S0 vs S1-S3 (P = .02) and 0.71 (95% CI, 0.64-0.77) vs 0.69 (95% CI, 0.61-0.75) for S0-S1 vs S2-S3 (P = .60), respectively. For histological steatosis, the AUC of ATI and CAP were 0.92 (95% CI, 0.87-0.95) vs 0.95 (95% CI, 0.91-0.98) for S0 vs S1-S3 (P = .64) and 0.79 (95% CI, 0.72-0.84) vs 0.76 (95% CI, 0.69-0.82) for S0-S1 vs S2-S3 (P = .61), respectively. CONCLUSION ATI may be used as an alternative to CAP for the diagnosis and quantification of steatosis, in patients with type 2 diabetes and nonalcoholic fatty liver disease.
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Affiliation(s)
- Marco Dioguardi Burgio
- Department of Radiology, Hôpital Beaujon, AP-HP Nord, Clichy, France; Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France.
| | - Laurent Castera
- Departement of Hepatology, Hospital Beaujon, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Mehdi Oufighou
- Department of Radiology, Hôpital Beaujon, AP-HP Nord, Clichy, France
| | - Pierre-Emmanuel Rautou
- Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France; Service d'Hépatologie, AP-HP, Hôpital Beaujon, DMU DIGEST, Centre de Référence des Maladies Vasculaires du Foie, FILFOIE, ERN RARE-LIVER, Clichy, France
| | - Valérie Paradis
- Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France; Department of Pathology, Hôpital Beaujon, AP-HP Nord, Clichy, France
| | - Pierre Bedossa
- Department of Pathology, Hôpital Beaujon, AP-HP Nord, Clichy, France
| | - Riccardo Sartoris
- Department of Radiology, Hôpital Beaujon, AP-HP Nord, Clichy, France
| | - Maxime Ronot
- Department of Radiology, Hôpital Beaujon, AP-HP Nord, Clichy, France; Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France
| | - Sylvain Bodard
- Department of Adult Radiology, Necker University Hospital, AP-HP, Paris, France; Université Paris Cité, Paris, France
| | - Philippe Garteiser
- Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France
| | - Bernard Van Beers
- Department of Radiology, Hôpital Beaujon, AP-HP Nord, Clichy, France; Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France
| | - Dominique Valla
- Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France; Service d'Hépatologie, AP-HP, Hôpital Beaujon, DMU DIGEST, Centre de Référence des Maladies Vasculaires du Foie, FILFOIE, ERN RARE-LIVER, Clichy, France
| | - Valérie Vilgrain
- Department of Radiology, Hôpital Beaujon, AP-HP Nord, Clichy, France; Université Paris Cité, INSERM, Centre de Recherche sur L'inflammation, Paris, France
| | - Jean Michel Correas
- Department of Adult Radiology, Necker University Hospital, AP-HP, Paris, France; Université Paris Cité, Paris, France; Sorbonne Université, CNRS, INSERM Laboratoire d'Imagerie Biomédicale, Paris, France
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Taniguchi H, Ueda M, Sano F, Kobayashi Y, Shima T. Dietary characteristics associated with the risk of non-alcoholic fatty liver disease and metabolic dysfunction-associated steatotic liver disease in non-obese Japanese participants: A cross-sectional study. JGH Open 2024; 8:e13082. [PMID: 38779132 PMCID: PMC11109997 DOI: 10.1002/jgh3.13082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 02/09/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024]
Abstract
Background and Aim Dietary characteristics associated with non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated steatotic liver disease (MASLD) in non-obese patients remain to be elucidated. This study examined the association of NAFLD and MASLD with dietary characteristics according to obesity status. Methods We performed a cross-sectional study of 15 135 participants (n = 7568 men and 7567 women) aged 35-74 years using data of annual health checks between 2008 and 2020. Obesity was defined as BMI ≥ 25 kg/m2. Diagnosis of fatty liver was based on abdominal ultrasonography. Fatty-liver-related dietary characteristics were assessed using a self-administered questionnaire. Results For non-obese participants, NAFLD was found in 31.0% of men and 19.4% of women. Non-obese MASLD was found in 27.6% of men and 18.1% of women. Multivariable-adjusted stepwise logistic regression analysis indicated that, in males, both non-obese NAFLD and non-obese MASLD were significantly and negatively associated with "often eat sesame/nuts", and positively associated with "often eat noodles/rice bowl" and "often eat evening meal" (P < 0.05). For non-obese women, both NAFLD and MASLD were significantly and positively associated with "often eat sweet buns/bread with fillings" (P < 0.05). Adjusted analyses showed that all dietary characteristics were not significantly associated with the risk of NAFLD/MASLD in obese men and women. Conclusion This cross-sectional study indicates the existence of sex and obesity differences in the association of NAFLD and MASLD with dietary characteristics. Our findings suggest that some dietary characteristics are associated with NAFLD and MASLD prevalence in non-obese Japanese participants.
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Affiliation(s)
- Hirokazu Taniguchi
- Division of Applied Life Sciences, Graduate School of Life and Environmental SciencesKyoto Prefectural UniversityKyotoJapan
| | - Miho Ueda
- Center for Health Promotion, Japanese Red Cross Kyoto Daiichi HospitalKyotoJapan
| | - Fumika Sano
- Division of Applied Life Sciences, Graduate School of Life and Environmental SciencesKyoto Prefectural UniversityKyotoJapan
| | - Yukiko Kobayashi
- Division of Applied Life Sciences, Graduate School of Life and Environmental SciencesKyoto Prefectural UniversityKyotoJapan
| | - Takatomo Shima
- Center for Health Promotion, Japanese Red Cross Kyoto Daiichi HospitalKyotoJapan
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Chang YC, Yen KC, Liang PC, Ho MC, Ho CM, Hsiao CY, Hsiao CH, Lu CH, Wu CH. Automated liver volumetry and hepatic steatosis quantification with magnetic resonance imaging proton density fat fraction. J Formos Med Assoc 2024:S0929-6646(24)00212-2. [PMID: 38643056 DOI: 10.1016/j.jfma.2024.04.012] [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: 05/13/2023] [Revised: 04/04/2024] [Accepted: 04/16/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND Preoperative imaging evaluation of liver volume and hepatic steatosis for the donor affects transplantation outcomes. However, computed tomography (CT) for liver volumetry and magnetic resonance spectroscopy (MRS) for hepatic steatosis are time consuming. Therefore, we investigated the correlation of automated 3D-multi-echo-Dixon sequence magnetic resonance imaging (ME-Dixon MRI) and its derived proton density fat fraction (MRI-PDFF) with CT liver volumetry and MRS hepatic steatosis measurements in living liver donors. METHODS This retrospective cross-sectional study was conducted from December 2017 to November 2022. We enrolled donors who received a dynamic CT scan and an MRI exam within 2 days. First, the CT volumetry was processed semiautomatically using commercial software, and ME-Dixon MRI volumetry was automatically measured using an embedded sequence. Next, the signal intensity of MRI-PDFF volumetric data was correlated with MRS as the gold standard. RESULTS We included the 165 living donors. The total liver volume of ME-Dixon MRI was significantly correlated with CT (r = 0.913, p < 0.001). The fat percentage measured using MRI-PDFF revealed a strong correlation between automatic segmental volume and MRS (r = 0.705, p < 0.001). Furthermore, the hepatic steatosis group (MRS ≥5%) had a strong correlation than the non-hepatic steatosis group (MRS <5%) in both volumetric (r = 0.906 vs. r = 0.887) and fat fraction analysis (r = 0.779 vs. r = 0.338). CONCLUSION Automated ME-Dixon MRI liver volumetry and MRI-PDFF were strongly correlated with CT liver volumetry and MRS hepatic steatosis measurements, especially in donors with hepatic steatosis.
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Affiliation(s)
- Yuan-Chen Chang
- Department of Medical Imaging and Radiology, National Taiwan University Hospital and College of Medicine, Taiwan
| | - Kuang-Chen Yen
- Department of Medical Imaging and Radiology, National Taiwan University Hospital and College of Medicine, Taiwan
| | - Po-Chin Liang
- Department of Medical Imaging and Radiology, National Taiwan University Hospital and College of Medicine, Taiwan
| | - Ming-Chih Ho
- Departments of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan; Center for Functional Image and Interventional Image, National Taiwan University, Taipei, Taiwan; Department of Surgery, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
| | - Cheng-Maw Ho
- Departments of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chih-Yang Hsiao
- Departments of Surgery, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chiu-Han Hsiao
- Research Center for Information Technology Innovation, Academia Sinica, Taiwan
| | - Chia-Hsun Lu
- Department of Radiology, Wan-Fang Hospital, Taipei Medical University, Taipei, Taiwan
| | - Chih-Horng Wu
- Department of Medical Imaging and Radiology, National Taiwan University Hospital and College of Medicine, Taiwan; Hepatits Research Center, National Taiwan University Hospital, Taipei, Taiwan; Center of Minimal-Invasive Interventional Radiology, National Taiwan University Hospital, Taipei, Taiwan.
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Kostka F, Ittermann T, Groß S, Laqua FC, Bülow R, Völzke H, Dörr M, Kühn JP, Markus MRP, Kromrey ML. Cardiac remodelling in non-alcoholic fatty liver disease in the general population. Liver Int 2024; 44:1032-1041. [PMID: 38293745 DOI: 10.1111/liv.15844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Revised: 01/01/2024] [Accepted: 01/05/2024] [Indexed: 02/01/2024]
Abstract
BACKGROUND AND AIMS Non-alcoholic fatty liver disease (NAFLD) is associated with increased risk for cardiovascular disease. Our study investigates the contribution of NAFLD to changes in cardiac structure and function in a general population. METHODS One thousand ninety-six adults (49.3% female) from the Study of Health in Pomerania underwent magnetic resonance imaging including cardiac and liver imaging. The presence of NAFLD by proton density fat fraction was related to left cardiac structure and function. Results were adjusted for clinical confounders using multivariable linear regression model. RESULTS The prevalence for NAFLD was 35.9%. In adjusted multivariable linear regression models, NAFLD was positively associated with higher left ventricular mass index (β = 0.95; 95% confidence interval (CI): 0.45; 1.45), left ventricular concentricity (β = 0.043; 95% CI: 0.031; 0.056), left ventricular end-diastolic wall thickness (β = 0.29; 95% CI: 0.20; 0.38), left atrial end-diastolic volume index (β = 0.67; 95% CI: 0.01; 1.32) and inversely associated with left ventricular end-diastolic volume index (β = -0.78; 95% CI: -1.51; -0.05). When stratified by sex, we only found significant positive associations of NAFLD with left ventricular mass index, left atrial end-diastolic volume index, left ventricular cardiac output and an inverse association with global longitudinal strain in women. In contrast, men had an inverse association with left ventricular end-diastolic volume index and left ventricular stroke volume. Higher liver fat content was stronger associated with higher left ventricular mass index, left ventricular concentricity and left ventricular end-diastolic wall thickness. CONCLUSION NAFLD is associated with cardiac remodelling in the general population showing sex specific patterns in cardiac structure and function.
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Affiliation(s)
- Frederik Kostka
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Till Ittermann
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Stefan Groß
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Fabian Christopher Laqua
- Department of Diagnostic and Interventional Radiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Henry Völzke
- Department of Study of Health in Pomerania/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Jens Peter Kühn
- Institute and Policlinic for Diagnostic and Interventional Radiology, University Hospital, Carl Gustav Carus University, TU Dresden, Dresden, Germany
| | - Marcello Ricardo Paulista Markus
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
- German Center for Diabetes Research (DZD), Partner Site Greifswald, Greifswald, Germany
| | - Marie-Luise Kromrey
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
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Carmichael OT, Singh M, Bashir A, Russell AM, Bolding M, Redden DT, Storrs J, Willoughby WR, Howard-Claudio C, Hsia DS, Kimberly RP, Gray ME, Ravussin Ph.D E, Denney TS. Harmonized Multisite MRI-Based Quantification of Human Liver Fat and Stiffness: A Pilot Study. J Magn Reson Imaging 2024; 59:1070-1073. [PMID: 37246446 PMCID: PMC11247954 DOI: 10.1002/jmri.28790] [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: 09/29/2022] [Revised: 05/02/2023] [Accepted: 05/04/2023] [Indexed: 05/30/2023] Open
Abstract
BACKGROUND Nonalcoholic fatty liver disease (NAFLD) is a leading cause of end-stage liver disease. NAFLD diagnosis and follow-up relies on a combination of clinical data, liver imaging, and/or liver biopsy. However, intersite imaging differences impede diagnostic consistency and reduce the repeatability of the multisite clinical trials necessary to develop effective treatments. PURPOSE/HYPOTHESIS The goal of this pilot study was to harmonize commercially available 3 T magnetic resonance imaging (MRI) measurements of liver fat and stiffness in human participants across academic sites and MRI vendors. STUDY TYPE Cohort. SUBJECTS Four community-dwelling adults with obesity. FIELD STRENGTH/SEQUENCE 1.5 and 3 T, multiecho 3D imaging, PRESS, and GRE. ASSESSMENT Harmonized proton density fat fraction (PDFF) and magnetic resonance spectroscopy (MRS) protocols were used to quantify the FF of synthetic phantoms and human participants with obesity using standard acquisition parameters at four sites that had four different 3 T MRI instruments. In addition, a harmonized magnetic resonance elastography (MRE) protocol was used to quantify liver stiffness among participants at two different sites at 1.5 and 3 T field strengths. Data were sent to a single data coordinating site for postprocessing. STATISTICAL TESTS Linear regression in MATLAB, ICC analyses using SAS 9.4, one-sided 95% confidence intervals for the ICC. RESULTS PDFF and MRS FF measurements were highly repeatable among sites in both humans and phantoms. MRE measurements of liver stiffness in three individuals at two sites using one 1.5 T and one 3 T instrument showed repeatability that was high although lower than that of MRS and PDFF. CONCLUSIONS We demonstrated harmonization of PDFF, MRS, and MRE-based quantification of liver fat and stiffness through synthetic phantoms, traveling participants, and standardization of postprocessing analysis. Multisite MRI harmonization could contribute to multisite clinical trials assessing the efficacy of interventions and therapy for NAFLD. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 2.
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Affiliation(s)
| | - Maninder Singh
- Pennington Biomedical Research Center, Baton Rouge, Louisiana – 70808
| | - Adil Bashir
- Auburn University, Samuel Ginn College of Engineering, Auburn, Alabama – 36849
| | | | - Mark Bolding
- The University of Alabama, Birmingham, Alabama – 35294
- The University of Alabama Medical Center, Birmingham, Alabama – 35233
| | - David T. Redden
- The University of Alabama, Birmingham, Alabama – 35294
- The University of Alabama, School of Public Health, Birmingham, Alabama – 35233
| | - Judd Storrs
- The University of Mississippi Medical Center, Jackson, Mississippi – 39216
| | - William R. Willoughby
- The University of Alabama, Birmingham, Alabama – 35294
- The University of Alabama Medical Center, Birmingham, Alabama – 35233
| | | | - Daniel S. Hsia
- Pennington Biomedical Research Center, Baton Rouge, Louisiana – 70808
| | - Robert P. Kimberly
- The University of Alabama, Birmingham, Alabama – 35294
- The University of Alabama, School of Medicine, Birmingham, Alabama – 35233
| | - Meagan E. Gray
- The University of Alabama, Birmingham, Alabama – 35294
- The University of Alabama, School of Medicine, Birmingham, Alabama – 35233
- The University of Alabama Hospital, Birmingham, Alabama – 35205
| | - Eric Ravussin Ph.D
- Pennington Biomedical Research Center, Baton Rouge, Louisiana – 70808
- The University of Alabama, Birmingham, Alabama – 35294
| | - Thomas S. Denney
- Auburn University, Samuel Ginn College of Engineering, Auburn, Alabama – 36849
- The University of Alabama, Birmingham, Alabama – 35294
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Yıldız AB, Vehbi S, Copur S, Gurses B, Siriopol D, Karakaya BAD, Hasbal NB, Tekin B, Akyıldız M, van Raalte DH, Cozzolino M, Kanbay M. Kidney and liver fat accumulation: from imaging to clinical consequences. J Nephrol 2024; 37:483-490. [PMID: 38133740 DOI: 10.1007/s40620-023-01824-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/24/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Recent studies indicate that accumulation of adipose tissue in various organs such as liver and kidney may contribute to the pathophysiology of metabolic syndrome. We aim to investigate the association between kidney and liver adipose tissue accumulation, assessed by the magnetic resonance imaging (MRI) proton density fat fraction technique, along with its relation to clinical and biochemical parameters. METHODS We included 51 volunteers with phenotypical features of metabolic syndrome (mean age = 34 years, mean body-mass index = 26.4 kg/m2) in our study in which liver and kidney adipose tissue accumulation was assessed via MRI-proton density fat fraction along with multiple other clinical and biochemical parameters such as estimated glomerular filtration rate (eGFR), urine albumin-to-creatinine ratio, serum lipid profile, liver function tests and body-mass index (BMI). RESULTS Our results from the univariate linear regression analysis indicate that both the kidney and liver scores were positively correlated with markers such as BMI, urine albumin-to-creatinine ratio, triglycerides (p < 0.001) and negatively correlated with eGFR (p < 0.05). In multivariate analysis, urine albumin-to-creatinine ratio (p < 0.05), triglycerides (p < 0.01), eGFR (p < 0.05) and BMI (p < 0.001) were found to be independently associated with kidney and liver fat accumulation, respectively (R2 = 0.64; R2 = 0.89). There was also a positive correlation between kidney and liver fat accumulation. CONCLUSION We have found a significant association between adipose tissue accumulation in liver and kidney and the parameters of metabolic syndrome. Moreover, the presence of a strong association between kidney and liver fat accumulation and kidney function parameters such as urine albumin-to-creatinine ratio and eGFR may be an indicator of the clinical significance of parenchymal fat accumulation.
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Affiliation(s)
- Abdullah B Yıldız
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Sezan Vehbi
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Sidar Copur
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Bengi Gurses
- Department of Radiology, Koc University School of Medicine, Istanbul, Turkey
| | - Dimitrie Siriopol
- Department of Nephrology, "Saint John the New" County Hospital, "Stefan Cel Mare" University of Suceava, Suceava, Romania
| | | | - Nuri B Hasbal
- Division of Nephrology, Department of Medicine, Koc University School of Medicine, 34010, Istanbul, Turkey
| | - Bahar Tekin
- Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Murat Akyıldız
- Division of Gastroenterology, Department of Medicine, Koc University School of Medicine, Istanbul, Turkey
| | - Daniel H van Raalte
- Diabetes Center, Department of Internal Medicine, Amsterdam University Medical Centers, Location VUMC, Amsterdam, The Netherlands
| | - Mario Cozzolino
- Renal Division, Department of Health Sciences, University of Milan, Milan, Italy
| | - Mehmet Kanbay
- Division of Nephrology, Department of Medicine, Koc University School of Medicine, 34010, Istanbul, Turkey.
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Wang M, Tang S, Li G, Huang Z, Mo S, Yang K, Chen J, Du B, Xu J, Ding Z, Dong F. Comparative study of ultrasound attenuation analysis and controlled attenuation parameter in the diagnosis and grading of liver steatosis in non-alcoholic fatty liver disease patients. BMC Gastroenterol 2024; 24:81. [PMID: 38395765 PMCID: PMC10885558 DOI: 10.1186/s12876-024-03160-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024] Open
Abstract
PURPOSE To assess the diagnostic performance of Ultrasound Attenuation Analysis (USAT) in the diagnosis and grading of hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD) using Controlled Attenuation Parameters (CAP) as a reference. MATERIALS AND METHODS From February 13, 2023, to September 26, 2023, participants underwent CAP and USAT examinations on the same day. We used manufacturer-recommended CAP thresholds to categorize the stages of hepatic steatosis: stage 1 (mild) - 240 dB/m, stage 2 (moderate) - 265 dB/m, stage 3 (severe) - 295 dB/m. Receiver Operating Characteristic curves were employed to evaluate the diagnostic accuracy of USAT and determine the thresholds for different levels of hepatic steatosis. RESULTS Using CAP as the reference, we observed that the average USAT value increased with the severity of hepatic steatosis, and the differences in USAT values among the different hepatic steatosis groups were statistically significant (p < 0.05). There was a strong positive correlation between USAT and CAP (r = 0.674, p < 0.0001). When using CAP as the reference, the optimal cut-off values for diagnosing and predicting different levels of hepatic steatosis with USAT were as follows: the cut-off value for excluding the presence of hepatic steatosis was 0.54 dB/cm/MHz (AUC 0.96); for mild hepatic steatosis, it was 0.59 dB/cm/MHz (AUC 0.86); for moderate hepatic steatosis, it was 0.73 dB/cm/MHz (AUC 0.81); and for severe hepatic steatosis, it was 0.87 dB/cm/MHz (AUC 0.87). CONCLUSION USAT exhibits strong diagnostic performance for hepatic steatosis and shows a high correlation with CAP values.
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Affiliation(s)
- Mengyun Wang
- The Second Clinical Medical College, Jinan University, Guangzhou, China
| | - Shuzhen Tang
- The Second Clinical Medical College, Jinan University, Guangzhou, China
| | - Guoqiu Li
- The Second Clinical Medical College, Jinan University, Guangzhou, China
| | - Zhibin Huang
- The Second Clinical Medical College, Jinan University, Guangzhou, China
| | - Sijie Mo
- The Second Clinical Medical College, Jinan University, Guangzhou, China
| | - Keen Yang
- Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Jing Chen
- Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Baishan Du
- Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China
| | - Jinfeng Xu
- Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
| | - Zhimin Ding
- Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
| | - Fajin Dong
- Department of Ultrasound, The Second Clinical Medical College, Jinan University (Shenzhen People's Hospital), Shenzhen, China.
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23
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Md Shah MN, Azman RR, Chan WY, Ng KH. Opportunistic Extraction of Quantitative CT Biomarkers: Turning the Incidental Into Prognostic Information. Can Assoc Radiol J 2024; 75:92-97. [PMID: 37075322 DOI: 10.1177/08465371231171700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023] Open
Abstract
The past two decades have seen a significant increase in the use of CT, with a corresponding rise in the mean population radiation dose. This rise in CT use has caused improved diagnostic certainty in conditions that were not previously routinely evaluated using CT, such as headaches, back pain, and chest pain. Unused data, unrelated to the primary diagnosis, embedded within these scans have the potential to provide organ-specific measurements that can be used to prognosticate or risk-profile patients for a wide variety of conditions. The recent increased availability of computing power, expertise and software for automated segmentation and measurements, assisted by artificial intelligence, provides a conducive environment for the deployment of these analyses into routine use. Data gathering from CT has the potential to add value to examinations and help offset the public perception of harm from radiation exposure. We review the potential for the collection of these data and propose the incorporation of this strategy into routine clinical practice.
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Affiliation(s)
- Mohammad Nazri Md Shah
- Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Raja Rizal Azman
- Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Wai Yee Chan
- Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Kwan Hoong Ng
- Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
- Faculty of Medicine and Health Sciences, UCSI University, Springhill, Negri Sembilan, Malaysia
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24
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Kizildag B, Baykara M, Yurttutan N, Vicdan H. Correlation between ultrasonography and MR proton density fat fraction techniques in evaluating the severity of liver steatosis. HEPATOLOGY FORUM 2024; 5:37-43. [PMID: 38283269 PMCID: PMC10809335 DOI: 10.14744/hf.2023.2023.0046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/16/2023] [Accepted: 10/18/2023] [Indexed: 01/30/2024]
Abstract
Background and Aim To investigate the relationship between ultrasonography (US) and magnetic resonance (MR) proton density fat fraction (PDFF) techniques, using the modified DIXON method, in determining the severity of liver steatosis. Materials and Methods This study included seventy consecutive patients who underwent upper abdominal MRI for various reasons between June 2016 and January 2017. Fatty liver staging was performed using US as indicated.The liver fat percentage was measured and staged according to PDFF values. Results In the study, of the 70 cases, 36 were male and 34 were female. On US, 18.5% of the cases had stage 0, 32.8% had stage 1, 42.8% had stage 2, and 5.7% had stage 3 liver steatosis. A significant correlation was found between ultrasonographic evaluation and PDFF in determining the percentage of liver fat (r=0.775, p<0.001). When comparing the percentages, MR-evaluated PDFF and ultrasonographic staging were most compatible at grade 3 and least compatible at grade 2. When the PDFF threshold value was set at 8.1%, the sensitivity of US in distinguishing between obvious and indistinct steatosis was 97.1%, and the specificity was 88.9%. Conclusion Ultrasound continues to be a useful tool for detecting fatty liver disease. However, magnetic resonance (MR) proton density fat fraction (PDFF) imaging is essential for accurately determining the severity and prevalence of steatosis. Our study revealed inconsistencies between US and MR PDFF in grading liver steatosis, showing higher agreement in severe cases and lower agreement in moderate cases. Therefore, we recommend classifying steatosis as either uncertain or apparent rather than using a grading system in US.
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Affiliation(s)
- Betul Kizildag
- Department of Radiology, Sutcu Imam University School of Medicine, Kahramanmaras, Turkiye
| | - Murat Baykara
- Department of Radiology, Firat University School of Medicine, Elazig, Turkiye
| | - Nursel Yurttutan
- Department of Radiology, Sutcu Imam University School of Medicine, Kahramanmaras, Turkiye
| | - Halit Vicdan
- Department of Radiology, Sutcu Imam University School of Medicine, Kahramanmaras, Turkiye
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25
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Song I, Thompson EW, Verma A, MacLean MT, Duda J, Elahi A, Tran R, Raghupathy P, Swago S, Hazim M, Bhattaru A, Schneider C, Vujkovic M, Torigian DA, Kahn CE, Gee JC, Borthakur A, Kripke CM, Carson CC, Carr R, Jehangir Q, Ko YA, Litt H, Rosen M, Mankoff DA, Schnall MD, Shou H, Chirinos J, Damrauer SM, Serper M, Chen J, Rader DJ, Witschey WRT, Sagreiya H. Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis. Sci Rep 2024; 14:53. [PMID: 38167550 PMCID: PMC10761858 DOI: 10.1038/s41598-023-49470-x] [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: 05/24/2023] [Accepted: 12/08/2023] [Indexed: 01/05/2024] Open
Abstract
The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis. The patient cohort was stratified by BMI with a threshold of 25 kg/m2 and hepatic steatosis with threshold SHAD ≥ - 1 HU or liver mean attenuation ≤ 40 HU. Patient characteristics, diagnoses, and laboratory results representing metabolism and liver function were investigated. A phenome-wide association study (PheWAS) was performed for the statistical interaction between SHAD and the binary characteristic LEAN. The cohort contained 8914 patients-lean patients with (N = 278, 3.1%) and without (N = 1867, 20.9%) steatosis, and overweight patients with (N = 1863, 20.9%) and without (N = 4906, 55.0%) steatosis. Among all lean patients, those with steatosis had increased rates of cardiovascular disease (41.7 vs 27.8%), hypertension (86.7 vs 49.8%), and type 2 diabetes mellitus (29.1 vs 15.7%) (all p < 0.0001). Ten phenotypes were significant in the PheWAS, including chronic kidney disease, renal failure, and cardiovascular disease. Hepatic steatosis was found to be associated with cardiovascular, kidney, and metabolic conditions, separate from overweight BMI.
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Affiliation(s)
- Isabel Song
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Elizabeth W Thompson
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Anurag Verma
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew T MacLean
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey Duda
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Ameena Elahi
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Richard Tran
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Pavan Raghupathy
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Sophia Swago
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Mohamad Hazim
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Abhijit Bhattaru
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Carolin Schneider
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marijana Vujkovic
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Drew A Torigian
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Charles E Kahn
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - James C Gee
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Arijitt Borthakur
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Colleen M Kripke
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher C Carson
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rotonya Carr
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, School of Medicine, University of Washington, Seattle, WA, USA
| | - Qasim Jehangir
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yi-An Ko
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Harold Litt
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Mark Rosen
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - David A Mankoff
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Mitchell D Schnall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Haochang Shou
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Julio Chirinos
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Scott M Damrauer
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marina Serper
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jinbo Chen
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel J Rader
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Walter R T Witschey
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA
| | - Hersh Sagreiya
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
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26
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Ding KR, Lakshmanan S, Holda M, Kinninger A, Manubolu VS, Joshi T, Golub I, Mao SS, Budoff MJ, Roy SK. Methods and Reproducibility of Liver Fat Measurement Using 3-Dimensional Liver Segmentation From Noncontrast Computed Tomography in EVAPORATE Cohort. J Comput Assist Tomogr 2024; 48:49-54. [PMID: 37531634 DOI: 10.1097/rct.0000000000001521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
OBJECTIVE Nonalcoholic fatty liver disease not only shares multiple risk factors with cardiovascular disease but also independently predicts its increased risk and related outcomes. Here, we evaluate reproducibility of 3-dimensional (3D) liver volume segmentation method to identify fatty liver on noncontrast cardiac computed tomography (CT) and compare measures with previously validated 2-dimensional (2D) segmentation CT criteria for the measurement of liver fat. METHODS The study included 68 participants enrolled in the EVAPORATE trial and underwent serial noncontrast cardiac CT. Liver attenuation < 40 Hounsfield units (HU) was used for diagnosing fatty liver, as done in the MESA study. Two-dimensional and 3D segmentation of the liver were performed by Philips software. Bland-Altman plot analysis was used to assess reproducibility. RESULTS Interreader reproducibility of 3D liver mean HU measurements was 96% in a sample of 111 scans. Reproducibility of 2D and 3D liver mean HU measurements was 93% in a sample of 111 scans. Reproducibility of change in 2D and 3D liver mean HU was 94% in 68 scans. Kappa, a measure of agreement in which the 2D and 3D measures both identified fatty liver, was excellent at 96.4% in 111 scans. CONCLUSIONS Fatty liver can be reliably diagnosed and measured serially in a stable and reproducible way by 3D liver segmentation of noncontrast cardiac CT scans. Future studies need to explore the sensitivity and stability of measures for low liver fat content by 3D segmentation, over the current 2D methodology. This measure can serve as an imaging biomarker to understand mechanistic correlations between atherosclerosis, fatty liver, and cardiovascular disease risk.
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Affiliation(s)
- Kimberly R Ding
- From the Department of Medicine, Harbor-UCLA Medical Center, Torrance, CA
| | - Suvasini Lakshmanan
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Mateusz Holda
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - April Kinninger
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Venkat S Manubolu
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Tej Joshi
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Ilana Golub
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Song S Mao
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Matthew J Budoff
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
| | - Sion K Roy
- Department of Cardiology, Harbor-UCLA Medical Center Lundquist Institute, Torrance, CA
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27
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Orcel T, Chau HT, Turlin B, Chaigneau J, Bannier E, Otal P, Frampas E, Leguen A, Boulic A, Saint-Jalmes H, Aubé C, Boursier J, Bardou-Jacquet E, Gandon Y. Evaluation of proton density fat fraction (PDFF) obtained from a vendor-neutral MRI sequence and MRQuantif software. Eur Radiol 2023; 33:8999-9009. [PMID: 37402003 DOI: 10.1007/s00330-023-09798-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 03/29/2023] [Accepted: 04/21/2023] [Indexed: 07/05/2023]
Abstract
OBJECTIVE To validate the proton density fat fraction (PDFF) obtained by the MRQuantif software from 2D chemical shift encoded MR (CSE-MR) data in comparison with the histological steatosis data. METHODS This study, pooling data from 3 prospective studies spread over time between January 2007 and July 2020, analyzed 445 patients who underwent 2D CSE-MR and liver biopsy. MR derived liver iron concentration (MR-LIC) and PDFF was calculated using the MRQuantif software. The histological standard steatosis score (SS) served as reference. In order to get a value more comparable to PDFF, histomorphometry fat fraction (HFF) were centrally determined for 281 patients. Spearman correlation and the Bland and Altman method were used for comparison. RESULTS Strong correlations were found between PDFF and SS (rs = 0.84, p < 0.001) or HFF (rs = 0.87, p < 0.001). Spearman's coefficients increased to 0.88 (n = 324) and 0.94 (n = 202) when selecting only the patients without liver iron overload. The Bland and Altman analysis between PDFF and HFF found a mean bias of 5.4% ± 5.7 [95% CI 4.7, 6.1]. The mean bias was 4.7% ± 3.7 [95% CI 4.2, 5.3] and 7.1% ± 8.8 [95% CI 5.2, 9.0] for the patients without and with liver iron overload, respectively. CONCLUSION The PDFF obtained by MRQuantif from a 2D CSE-MR sequence is highly correlated with the steatosis score and very close to the fat fraction estimated by histomorphometry. Liver iron overload reduced the performance of steatosis quantification and joint quantification is recommended. This device-independent method can be particularly useful for multicenter studies. CLINICAL RELEVANCE STATEMENT The quantification of liver steatosis using a vendor-neutral 2D chemical-shift MR sequence, processed by MRQuantif, is well correlated to steatosis score and histomorphometric fat fraction obtained from biopsy, whatever the magnetic field and the MR device used. KEY POINTS • The PDFF measured by MRQuantif from 2D CSE-MR sequence data is highly correlated to hepatic steatosis. • Steatosis quantification performance is reduced in case of significant hepatic iron overload. • This vendor-neutral method may allow consistent estimation of PDFF in multicenter studies.
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Affiliation(s)
- T Orcel
- Department of Radiology, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
| | - H T Chau
- Department of Radiology, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
- NUMECAN, INSERM U1099, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
| | - B Turlin
- NUMECAN, INSERM U1099, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
- Department of Pathology, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
| | - J Chaigneau
- HIFIH, UPRES EA3859, Angers University Hospital, 4 Rue Larrey, 49993, Angers, France
| | - E Bannier
- Department of Radiology, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
- EMPENN U746 Unit/Project, INSERM/INRIA, IRISA, University of Rennes, Beaulieu Campus, UMR CNRS 6074, 35042, Rennes, France
| | - P Otal
- Department of Radiology, Toulouse University Hospital, 1 Av Pr J. Poulhes, 31059, Toulouse, France
| | - E Frampas
- Department of Radiology, Nantes University Hospital, 1 Pl. Alexis-Ricordeau, 44000, Nantes, France
| | - A Leguen
- Department of Radiology, Bretagne-Atlantique Hospital, 20 Bd Général Maurice Guillaudot, 56000, Vannes, France
| | - A Boulic
- Department of Radiology, Bretagne Sud Hospital, 5 Avenue de Choiseul, 56322, Lorient, France
| | - H Saint-Jalmes
- INSERM U1099, LTSI, University of Rennes, Beaulieu Campus, 35042, Rennes, France
| | - C Aubé
- HIFIH, UPRES EA3859, Angers University Hospital, 4 Rue Larrey, 49993, Angers, France
- Department of Radiology, Angers University Hospital, 4 Rue Larrey, 49993, Angers, France
| | - J Boursier
- HIFIH, UPRES EA3859, Angers University Hospital, 4 Rue Larrey, 49993, Angers, France
- Department of Hepatology-GastoeEnterology, Angers University Hospital, 4 Rue Larrey, 49993, Angers, France
| | - E Bardou-Jacquet
- NUMECAN, INSERM U1099, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
- Department of Hepatology, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France
| | - Y Gandon
- Department of Radiology, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France.
- NUMECAN, INSERM U1099, Rennes University Hospital, 2 Rue H. Le Guilloux, 35033, Rennes, France.
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28
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Bangaru S, Sundaresh R, Lee A, Prause N, Hao F, Dong TS, Tincopa M, Cholankeril G, Rich NE, Kawamoto J, Bhattacharya D, Han SB, Patel AA, Shaheen M, Benhammou JN. Predictive Algorithm for Hepatic Steatosis Detection Using Elastography Data in the Veterans Affairs Electronic Health Records. Dig Dis Sci 2023; 68:4474-4484. [PMID: 37864738 PMCID: PMC10635943 DOI: 10.1007/s10620-023-08043-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 07/12/2023] [Indexed: 10/23/2023]
Abstract
BACKGROUND AND AIMS Nonalcoholic fatty liver disease (NAFLD) has reached pandemic proportions. Early detection can identify at-risk patients who can be linked to hepatology care. The vibration-controlled transient elastography (VCTE) controlled attenuation parameter (CAP) is biopsy validated to diagnose hepatic steatosis (HS). We aimed to develop a novel clinical predictive algorithm for HS using the CAP score at a Veterans' Affairs hospital. METHODS We identified 403 patients in the Greater Los Angeles VA Healthcare System with valid VCTEs during 1/2018-6/2020. Patients with alcohol-associated liver disease, genotype 3 hepatitis C, any malignancies, or liver transplantation were excluded. Linear regression was used to identify predictors of NAFLD. To identify a CAP threshold for HS detection, receiver operating characteristic analysis was applied using liver biopsy, MRI, and ultrasound as the gold standards. RESULTS The cohort was racially/ethnically diverse (26% Black/African American; 20% Hispanic). Significant positive predictors of elevated CAP score included diabetes, cholesterol, triglycerides, BMI, and self-identifying as Hispanic. Our predictions of CAP scores using this model strongly correlated (r = 0.61, p < 0.001) with actual CAP scores. The NAFLD model was validated in an independent Veteran cohort and yielded a sensitivity of 82% and specificity 83% (p < 0.001, 95% CI 0.46-0.81%). The estimated optimal CAP for our population cut-off was 273.5 dB/m, resulting in AUC = 75.5% (95% CI 70.7-80.3%). CONCLUSION Our HS predictive algorithm can identify at-risk Veterans for NAFLD to further risk stratify them by non-invasive tests and link them to sub-specialty care. Given the biased referral pattern for VCTEs, future work will need to address its applicability in non-specialty clinics. Proposed clinical algorithm to identify patients at-risk for NAFLD prior to fibrosis staging in Veteran.
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Affiliation(s)
- Saroja Bangaru
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Greater Los Angeles Veterans Affairs Healthcare System, Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, CA, 90075, USA
| | - Ram Sundaresh
- David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Anna Lee
- David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Nicole Prause
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Frank Hao
- Department of Radiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Tien S Dong
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Greater Los Angeles Veterans Affairs Healthcare System, Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, CA, 90075, USA
| | - Monica Tincopa
- Liver Center, University of California, San Diego, San Diego, CA, 92093, USA
| | - George Cholankeril
- Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Nicole E Rich
- UT Southwestern Medical Center, Division of Digestive and Liver Diseases and Harold C. Simmons Comprehensive Cancer Center, Dallas, TX, 75390, USA
| | - Jenna Kawamoto
- Greater Los Angeles Veterans Affairs Healthcare System, Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, CA, 90075, USA
| | - Debika Bhattacharya
- Division of Infectious Diseases, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Section of Infectious Diseases, Greater Los Angeles Veterans Affairs Healthcare System, Los Angeles, CA, 90075, USA
| | - Steven B Han
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Greater Los Angeles Veterans Affairs Healthcare System, Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, CA, 90075, USA
| | - Arpan A Patel
- Vatche and Tamar Manoukian Division of Digestive Diseases, David Geffen School of Medicine at the University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Greater Los Angeles Veterans Affairs Healthcare System, Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, CA, 90075, USA
- VA Center for the Study of Healthcare Innovation, Implementation, and Policy (CSHIIP), North Hills, CA, 91343, USA
| | - Magda Shaheen
- College of Medicine, Charles R Drew University, Los Angeles, CA, USA
| | - Jihane N Benhammou
- Greater Los Angeles Veterans Affairs Healthcare System, Gastroenterology, Hepatology and Parenteral Nutrition, Los Angeles, CA, 90075, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Medicine, University of California, Los Angeles, 11301 Wilshire Blvd, Building 113, Room 312, Los Angeles, CA, 90073, USA.
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Boeriu A, Dobru D, Fofiu C. Non-Invasive Diagnostic of NAFLD in Type 2 Diabetes Mellitus and Risk Stratification: Strengths and Limitations. Life (Basel) 2023; 13:2262. [PMID: 38137863 PMCID: PMC10744403 DOI: 10.3390/life13122262] [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: 10/07/2023] [Revised: 10/26/2023] [Accepted: 11/25/2023] [Indexed: 12/24/2023] Open
Abstract
The progressive potential of liver damage in type 2 diabetes mellitus (T2DM) towards advanced fibrosis, end-stage liver disease, and hepatocarcinoma has led to increased concern for quantifying liver injury and individual risk assessment. The combination of blood-based markers and imaging techniques is recommended for the initial evaluation in NAFLD and for regular monitoring to evaluate disease progression. Continued development of ultrasonographic and magnetic resonance imaging methods for accurate quantification of liver steatosis and fibrosis, as well as promising tools for the detection of high-risk NASH, have been noted. In this review, we aim to summarize available evidence regarding the usefulness of non-invasive methods for the assessment of NAFLD in T2DM. We focus on the power and limitations of various methods for diagnosis, risk stratification, and patient monitoring that support their implementation in clinical setting or in research field.
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Affiliation(s)
- Alina Boeriu
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Gastroenterology Department, Mures County Clinical Hospital, 540103 Targu Mures, Romania
| | - Daniela Dobru
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Gastroenterology Department, Mures County Clinical Hospital, 540103 Targu Mures, Romania
| | - Crina Fofiu
- Gastroenterology Department, University of Medicine Pharmacy, Sciences, and Technology “George Emil Palade” Targu Mures, 540142 Targu Mures, Romania;
- Internal Medicine Department, Bistrita County Clinical Hospital, 420094 Bistrita, Romania
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30
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López López AP, Tuli S, Lauze M, Becetti I, Pedreira CC, Huber FA, Omeroglu E, Singhal V, Misra M, Bredella MA. Changes in Hepatic Fat Content by CT 1 Year After Sleeve Gastrectomy in Adolescents and Young Adults With Obesity. J Clin Endocrinol Metab 2023; 108:e1489-e1495. [PMID: 37403207 PMCID: PMC10655539 DOI: 10.1210/clinem/dgad390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 06/09/2023] [Accepted: 06/27/2023] [Indexed: 07/06/2023]
Abstract
CONTEXT Obesity is associated with nonalcoholic fatty liver disease (NAFLD). Sleeve gastrectomy (SG) is an effective means of weight loss and improvement of NAFLD in adults; however, data regarding the efficacy of SG in the early stages of pediatric NAFLD are sparse. OBJECTIVE To assess the impact of SG on hepatic fat content 1 year after SG in youth with obesity compared with nonsurgical controls with obesity (NS). DESIGN A 12-month prospective study in 52 participants (mean age, 18.2 ± .36 years) with obesity, comprising 25 subjects who underwent SG (84% female; median body mass index [BMI], 44.6 [42.1-47.9] kg/m2) and 27 who were NS (70% female; median BMI, 42.2 [38.7-47.0] kg/m2). MAIN OUTCOME MEASURES Hepatic fat content by computed tomography (liver/spleen ratio), abdominal fat by magnetic resonance imaging. RESULTS Mean 12-month decrease in BMI was greater in SG vs NS (-12.5 ± .8 vs -.2 ± .5 kg/m2, P < .0001). There was a within-group increase in the liver-to-spleen (L/S) ratio in SG (.13 ± .05, P = .014) but not NS with a trend for a difference between groups (P = .055). All SG participants with an L/S ratio <1.0 (threshold for the diagnosis of NAFLD) before surgery had a ratio of >1.0 a year after surgery, consistent with resolution of NAFLD. Within SG, the 12-month change in L/S ratio was negatively associated with 12-month change in visceral fat (ρ = -.51 P = .016). CONCLUSIONS Hepatic fat content as assessed by noncontrast computed tomography improved after SG over 1 year in youth with obesity with resolution of NAFLD in all subjects. This was associated with decreases in visceral adiposity.
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Affiliation(s)
- Ana Paola López López
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Shubhangi Tuli
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Meghan Lauze
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Imen Becetti
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Division of Pediatric Endocrinology, Massachusetts General Hospital for Children and Harvard Medical School, Boston, MA 02114, USA
| | - Clarissa C Pedreira
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Florian A Huber
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Emre Omeroglu
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Vibha Singhal
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Division of Pediatric Endocrinology, Massachusetts General Hospital for Children and Harvard Medical School, Boston, MA 02114, USA
- Pediatric Program MGH Weight Center, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Madhusmita Misra
- Neuroendocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Division of Pediatric Endocrinology, Massachusetts General Hospital for Children and Harvard Medical School, Boston, MA 02114, USA
| | - Miriam A Bredella
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
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31
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Wang X, Bamber JC, Esquivel-Sirvent R, Ormachea J, Sidhu PS, Thomenius KE, Schoen S, Rosenzweig S, Pierce TT. Ultrasonic Sound Speed Estimation for Liver Fat Quantification: A Review by the AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative. ULTRASOUND IN MEDICINE & BIOLOGY 2023; 49:2327-2335. [PMID: 37550173 DOI: 10.1016/j.ultrasmedbio.2023.06.021] [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: 01/06/2023] [Revised: 06/23/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a significant cause of diffuse liver disease, morbidity and mortality worldwide. Early and accurate diagnosis of NALFD is critical to identify patients at risk of disease progression. Liver biopsy is the current gold standard for diagnosis and prognosis. However, a non-invasive diagnostic tool is desired because of the high cost and risk of complications of tissue sampling. Medical ultrasound is a safe, inexpensive and widely available imaging tool for diagnosing NAFLD. Emerging sonographic tools to quantitatively estimate hepatic fat fraction, such as tissue sound speed estimation, are likely to improve diagnostic accuracy, precision and reproducibility compared with existing qualitative and semi-quantitative techniques. Various pulse-echo ultrasound speed of sound estimation methodologies have been investigated, and some have been recently commercialized. We review state-of-the-art in vivo speed of sound estimation techniques, including their advantages, limitations, technical sources of variability, biological confounders and existing commercial implementations. We report the expected range of hepatic speed of sound as a function of liver steatosis and fibrosis that may be encountered in clinical practice. Ongoing efforts seek to quantify sound speed measurement accuracy and precision to inform threshold development around meaningful differences in fat fraction and between sequential measurements.
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Affiliation(s)
- Xiaohong Wang
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Jeffrey C Bamber
- Joint Department of Physics, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK
| | | | | | - Paul S Sidhu
- Department of Radiology, King's College Hospital, London, UK
| | - Kai E Thomenius
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | - Scott Schoen
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA
| | | | - Theodore T Pierce
- Center for Ultrasound Research and Translation, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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Wang K, Cunha GM, Hasenstab K, Henderson WC, Middleton MS, Cole SA, Umans JG, Ali T, Hsiao A, Sirlin CB. Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data. AJR Am J Roentgenol 2023; 221:620-631. [PMID: 37466189 DOI: 10.2214/ajr.23.29607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Abstract
BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.
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Affiliation(s)
- Kang Wang
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Radiology, Stanford University, 500 Pasteur Dr, Palo Alto, CA 94304
| | | | - Kyle Hasenstab
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA
| | - Walter C Henderson
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Michael S Middleton
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
| | - Shelley A Cole
- Population Health, Texas Biomedical Research Institute, San Antonio, TX
| | - Jason G Umans
- MedStar Health Research Institute, Field Studies Division, Hyattsville, MD
- Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, DC
| | - Tauqeer Ali
- Department of Biostatistics and Epidemiology, Center for American Indian Health Research, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK
| | - Albert Hsiao
- Department of Radiology, Artificial Intelligence and Data Analytic Laboratory, University of California, San Diego, La Jolla, CA
| | - Claude B Sirlin
- Department of Radiology, Liver Imaging Group, University of California, San Diego, La Jolla, CA
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Lee YS, Song SH, Wu TC, Wu SL, Huang CF. Correlation of hepatic transient elastography measurements and abdominal adiposity in children: A cross-sectional study. Pediatr Neonatol 2023; 64:631-636. [PMID: 36967291 DOI: 10.1016/j.pedneo.2022.12.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/16/2022] [Accepted: 12/08/2022] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Transient elastography is a non-invasive assessment of steatosis (measured as the controlled attenuation parameter, [CAP]) and fibrosis (measured as liver stiffness measurement, [LSM]) in patients with pediatric non-alcoholic fatty liver disease (NAFLD). Abdominal adiposity is considered the most important factor for metabolic dysregulation including NAFLD. However, there is lack of a correlation between transient elastography measurements and abdominal adiposity. Accordingly, this study aimed to assess the correlation between transient elastography measurements and abdominal adiposity in children. METHODS This cross-sectional study included 137 children who visited the Taipei Veterans General Hospital. Hepatic steatosis (CAP) and fibrosis (LSM), were assessed by transient elastography. Abdominal adiposity including subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and preperitoneal adipose tissue (PPT) was assessed using abdominal sonography. The correlation between transient elastography measurements and abdominal adiposity was assessed using multiple linear regression. RESULTS In total, 137 children were included in this study. SAT and VAT were significantly associated with CAP, whereas SAT was significantly associated with LSM. An increment of 1 mm in SAT increased CAP and LSM by 5.56 dB/m and 0.06 kPa, respectively. CONCLUSION Certain abdominal adiposities, especially SAT, are significantly associated with CAP and LSM, as determined by transient elastography. Simple abdominal adiposity measured using sonography may be useful for the early detection of pediatric NAFLD.
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Affiliation(s)
- Yii-Shiuan Lee
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Shih-Hsi Song
- Department of Pediatrics, National Yang Ming Chiao Tung University Hospital, Yilan, Taiwan
| | - Tzee-Chung Wu
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Shang-Liang Wu
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ching-Feng Huang
- Division of Pediatric Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Defense Medical Center, Taipei, Taiwan.
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34
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Ali MA, El-Abd E, Morsi M, El Safwany MM, El-Sayed MZ. The effect of hepatic steatosis on 18F-FDG uptake in PET-CT examinations of cancer Egyptian patients. Eur J Hybrid Imaging 2023; 7:19. [PMID: 37840056 PMCID: PMC10577118 DOI: 10.1186/s41824-023-00173-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 07/24/2023] [Indexed: 10/17/2023] Open
Abstract
BACKGROUND Hepatic steatosis is the most common chronic hepatic disease. Imaging diagnosis of hepatic steatosis has been evaluated as an alternative to invasive histological diagnosis. STUDY AIMS The study aimed to assess the effect of hepatic steatosis on Flourine-18 fluorodeoxyglucose (18F-FDG) uptakes in cancer patients. PATIENTS AND METHODS Blood samples were collected from 50 cancer patients and analyzed to calculate fatty liver index and Hepatic steatosis index (HIS). Hepatic steatosis examined using high-resolution ultrasound and positron emission tomography-computed tomography (PET-CT). Linear attenuation coefficient, standardized-uptake value (SUV) mean (SUV mean), and SUV maximum (SUVmax) were measured. Accordingly, patients were divided equally into non-fatty liver, and fatty liver groups. RESULTS A significant increase in SUVmax and SUV mean was observed in the fatty liver group more than in the non-fatty liver group. HSI significantly increased in the fatty liver group compared to the non-fatty liver group. Liver tissue uptake FDG was significantly correlated with HSI values. SUV max significantly correlated with body mass index (BMI) in the non-fatty group only. CONCLUSION Hepatic changes in cancer patients affect the liver metabolic activity and thus the 18 F-FDG uptake. Therefore, further corrections should be considered when the liver is used as a comparator for PET-CT scans of cancer patients.
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Affiliation(s)
- Magdi A Ali
- Faculty of Health Sciences, Gulf Medical University, Ajman, United Arab Emirates.
| | - Eman El-Abd
- Medical Research Institute, Alexandria University, Alexandria, Egypt
| | - Mohamed Morsi
- Medical Research Institute, Alexandria University, Alexandria, Egypt
| | - Mohamed M El Safwany
- Faculty of Applied Health Science Technology, Pharos University in Alexandria, Alexandria, Egypt
| | - Mohamed Z El-Sayed
- Faculty of Applied Health Science Technology, Pharos University in Alexandria, Alexandria, Egypt
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Chouari T, Merali N, La Costa F, Santol J, Chapman S, Horton A, Aroori S, Connell J, Rockall TA, Mole D, Starlinger P, Welsh F, Rees M, Frampton AE. The Role of the Multiparametric MRI LiverMultiScan TM in the Quantitative Assessment of the Liver and Its Predicted Clinical Applications in Patients Undergoing Major Hepatic Resection for Colorectal Liver Metastasis. Cancers (Basel) 2023; 15:4863. [PMID: 37835557 PMCID: PMC10571783 DOI: 10.3390/cancers15194863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 08/05/2023] [Accepted: 10/02/2023] [Indexed: 10/15/2023] Open
Abstract
Liver biopsy remains the gold standard for the histological assessment of the liver. With clear disadvantages and the rise in the incidences of liver disease, the role of neoadjuvant chemotherapy in colorectal liver metastasis (CRLM) and an explosion of surgical management options available, non-invasive serological and imaging markers of liver histopathology have never been more pertinent in order to assess liver health and stratify patients considered for surgical intervention. Liver MRI is a leading modality in the assessment of hepatic malignancy. Recent technological advancements in multiparametric MRI software such as the LiverMultiScanTM offers an attractive non-invasive assay of anatomy and histopathology in the pre-operative setting, especially in the context of CRLM. This narrative review examines the evidence for the LiverMultiScanTM in the assessment of hepatic fibrosis, steatosis/steatohepatitis, and potential applications for chemotherapy-associated hepatic changes. We postulate its future role and the hurdles it must surpass in order to be implemented in the pre-operative management of patients undergoing hepatic resection for colorectal liver metastasis. Such a role likely extends to other hepatic malignancies planned for resection.
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Affiliation(s)
- Tarak Chouari
- MATTU, The Leggett Building, Daphne Jackson Road, Guildford GU2 7WG, UK; (T.C.)
- Department of Hepato-Pancreato-Biliary (HPB) Surgery, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
- Oncology Section, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Science, University of Surrey, Guildford GU2 7WG, UK
| | - Nabeel Merali
- MATTU, The Leggett Building, Daphne Jackson Road, Guildford GU2 7WG, UK; (T.C.)
- Department of Hepato-Pancreato-Biliary (HPB) Surgery, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
- Oncology Section, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Science, University of Surrey, Guildford GU2 7WG, UK
| | - Francesca La Costa
- Department of Hepato-Pancreato-Biliary (HPB) Surgery, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
| | - Jonas Santol
- Department of Surgery, HPB Center, Vienna Health Network, Clinic Favoriten and Sigmund Freud Private University, 1090 Vienna, Austria
- Institute of Vascular Biology and Thrombosis Research, Center of Physiology and Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
| | - Shelley Chapman
- Department of Radiology, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
| | - Alex Horton
- Department of Radiology, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
| | - Somaiah Aroori
- Department of Surgery, Division of Hepatobiliary and Pancreatic Surgery and Transplant Surgery, Derriford Hospital, Plymouth PL6 8DH, UK
| | | | - Timothy A. Rockall
- MATTU, The Leggett Building, Daphne Jackson Road, Guildford GU2 7WG, UK; (T.C.)
- Oncology Section, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Science, University of Surrey, Guildford GU2 7WG, UK
| | - Damian Mole
- Clinical Surgery, Royal Infirmary of Edinburgh, University of Edinburgh, Edinburgh EH10 5HF, UK
- Centre for Inflammation Research, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh EH105HF, UK
| | - Patrick Starlinger
- Department of Surgery, Division of Hepatobiliary and Pancreatic Surgery, Mayo Clinic, Rochester, MN 55902, USA
- Center of Physiology and Pharmacology, Medical University of Vienna, 1090 Vienna, Austria
- Department of Surgery, Medical University of Vienna, General Hospital, 1090 Vienna, Austria
| | - Fenella Welsh
- Hepato-Biliary Unit, Hampshire Hospitals Foundation Trust, Basingstoke, Hampshire RG24 9NA, UK
| | - Myrddin Rees
- Hepato-Biliary Unit, Hampshire Hospitals Foundation Trust, Basingstoke, Hampshire RG24 9NA, UK
| | - Adam E. Frampton
- MATTU, The Leggett Building, Daphne Jackson Road, Guildford GU2 7WG, UK; (T.C.)
- Department of Hepato-Pancreato-Biliary (HPB) Surgery, Royal Surrey County Hospital, Egerton Road, Guildford GU2 7XX, UK
- Oncology Section, Department of Clinical and Experimental Medicine, Faculty of Health and Medical Science, University of Surrey, Guildford GU2 7WG, UK
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Huang X, Lian YE, Qiu L, Yu X, Miao J, Zhang S, Zhang Z, Zhang X, Chen J, Bai Y, Li L. Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program. J Transl Med 2023; 103:100223. [PMID: 37517702 DOI: 10.1016/j.labinv.2023.100223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 07/17/2023] [Accepted: 07/24/2023] [Indexed: 08/01/2023] Open
Abstract
Nonalcoholic fatty liver disease is rapidly becoming one of the most common causes of chronic liver disease worldwide and is the leading cause of liver-related morbidity and mortality. A quantitative assessment of the degree of steatosis would be more advantageous for diagnostic evaluation and exploring the patterns of disease progression. Here, multiphoton microscopy, based on the second harmonic generation and 2-photon excited fluorescence, was used to label-free image the samples of nonalcoholic fatty liver. Imaging results confirm that multiphoton microscopy is capable of directly visualizing important pathologic features such as normal hepatocytes, hepatic steatosis, Mallory bodies, necrosis, inflammation, collagen deposition, microvessel, and so on and is a reliable auxiliary tool for the diagnosis of nonalcoholic fatty liver disease. Furthermore, we developed an image segmentation algorithm to simultaneously assess hepatic steatosis and fibrotic changes, and quantitative results reveal that there is a correlation between the degree of steatosis and collagen content. We also developed a feature extraction program to precisely display the spatial distribution of hepatocyte steatosis in tissues. These studies may be beneficial for a better clinical understanding of the process of steatosis as well as for exploring possible therapeutic targets.
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Affiliation(s)
- Xingxin Huang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Yuan-E Lian
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Lida Qiu
- College of Physics and Electronic Information Engineering, Minjiang University, Fuzhou, China
| | - XunBin Yu
- Department of Pathology, Fujian Provincial Hospital, Fuzhou, China
| | - Jikui Miao
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Shichao Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Zheng Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Xiong Zhang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Jianxin Chen
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China
| | - Yannan Bai
- Department of Hepatobiliary and Pancreatic Surgery, Fujian Provincial Hospital, Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China.
| | - Lianhuang Li
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Provincial Key Laboratory of Photonics Technology, Fujian Normal University, Fuzhou, China.
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Vitali F, Zundler S, Jesper D, Wildner D, Strobel D, Frulloni L, Neurath MF. Diagnostic Endoscopic Ultrasound in Pancreatology: Focus on Normal Variants and Pancreatic Masses. Visc Med 2023; 39:121-130. [PMID: 37899794 PMCID: PMC10601528 DOI: 10.1159/000533432] [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: 05/19/2023] [Accepted: 08/03/2023] [Indexed: 10/31/2023] Open
Abstract
Background Endoscopic ultrasound (EUS) is a main tool in gastroenterology for both diagnosis and exclusion of pancreatic pathology. It allows minimally invasive assessment of various diseases or anatomic variations affecting the pancreas also with the help of new Doppler technologies, elastography, contrast-enhanced imaging including post hoc image processing with quantification analyses, three-dimensional reconstruction, and artificial intelligence. EUS also allows interventional direct access to the pancreatic parenchyma and the retroperitoneal space, to the pancreatic duct, pancreatic masses, cysts, and vascular structures. Summary This review aimed to summarize new developments of EUS in the field of pancreatology. We highlight the role of EUS in evaluating pancreatic pathology by describing normal anatomic variants like pancreas divisum, pancreatic lipomatosis, pancreatic fibrosis in the elderly and characterizing pancreatic masses, both in the context of chronic pancreatitis and within healthy pancreatic parenchyma. EUS is considered the optimal imaging modality for pancreatic masses of uncertain dignity and allows both cytological diagnosis and histology, which is essential not only for neoplastic conditions but also for tailoring therapy for benign inflammatory conditions. Key Messages EUS plays an indispensable role in pancreatology and the development of new diagnostic and interventional approaches to the retroperitoneal space and the pancreas exponentially increased over the last years. The development of computer-aided diagnosis and artificial intelligence algorithms hold the potential to overcome the obstacles associated with interobserver variability and will most likely support decision-making in the management of pancreatic disease.
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Affiliation(s)
- Francesco Vitali
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Sebastian Zundler
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Daniel Jesper
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Dane Wildner
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Deike Strobel
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
| | - Luca Frulloni
- Department of Medicine, Gastroenterology Unit, Pancreas Center, University of Verona, Verona, Italy
| | - Markus F. Neurath
- Department of Medicine 1, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen, Germany
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Buitinga M, Veeraiah P, Haans F, Schrauwen-Hinderling VB. Ectopic lipid deposition in muscle and liver, quantified by proton magnetic resonance spectroscopy. Obesity (Silver Spring) 2023; 31:2447-2459. [PMID: 37667838 DOI: 10.1002/oby.23865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/09/2023] [Accepted: 05/09/2023] [Indexed: 09/06/2023]
Abstract
Advances in the development of noninvasive imaging techniques have spurred investigations into ectopic lipid deposition in the liver and muscle and its implications in the development of metabolic diseases such as type 2 diabetes. Computed tomography and ultrasound have been applied in the past, though magnetic resonance-based methods are currently considered the gold standard as they allow more accurate quantitative detection of ectopic lipid stores. This review focuses on methodological considerations of magnetic resonance-based methods to image hepatic and muscle fat fractions, and it emphasizes anatomical and morphological aspects and how these may influence data acquisition, analysis, and interpretation.
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Affiliation(s)
- Mijke Buitinga
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
- Department of Nutrition and Movement Sciences (NUTRIM), Maastricht University, Maastricht, The Netherlands
| | - Pandichelvam Veeraiah
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
- Scannexus (Ultra-High Field Imaging Center), Maastricht, The Netherlands
- Faculty of Health Medicine and Life Sciences (FHML), Maastricht, The Netherlands
| | - Florian Haans
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Vera B Schrauwen-Hinderling
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
- Department of Nutrition and Movement Sciences (NUTRIM), Maastricht University, Maastricht, The Netherlands
- Institute for Clinical Diabetology, German Diabetes Center and Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
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Torgersen J, Akers S, Huo Y, Terry JG, Carr JJ, Ruutiainen AT, Skanderson M, Levin W, Lim JK, Taddei TH, So-Armah K, Bhattacharya D, Rentsch CT, Shen L, Carr R, Shinohara RT, McClain M, Freiberg M, Justice AC, Re VL. Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV. Pharmacoepidemiol Drug Saf 2023; 32:1121-1130. [PMID: 37276449 PMCID: PMC10527049 DOI: 10.1002/pds.5648] [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: 11/10/2022] [Revised: 05/06/2023] [Accepted: 05/31/2023] [Indexed: 06/07/2023]
Abstract
PURPOSE Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to evaluate liver fat within digitized images have not been developed. We determined the accuracy of a deep learning algorithm (automatic liver attenuation region-of-interest-based measurement [ALARM]) to identify steatosis within clinically obtained noncontrast abdominal CT images compared to manual radiologist review and evaluated its performance by HIV status. METHODS We performed a cross-sectional study to evaluate the performance of ALARM within noncontrast abdominal CT images from a sample of patients with and without HIV in the US Veterans Health Administration. We evaluated the ability of ALARM to identify moderate-to-severe hepatic steatosis, defined by mean absolute liver attenuation <40 Hounsfield units (HU), compared to manual radiologist assessment. RESULTS Among 120 patients (51 PWH) who underwent noncontrast abdominal CT, moderate-to-severe hepatic steatosis was identified in 15 (12.5%) persons via ALARM and 12 (10%) by radiologist assessment. Percent agreement between ALARM and radiologist assessment of absolute liver attenuation <40 HU was 95.8%. Sensitivity, specificity, positive predictive value, and negative predictive value of ALARM were 91.7% (95%CI, 51.5%-99.8%), 96.3% (95%CI, 90.8%-99.0%), 73.3% (95%CI, 44.9%-92.2%), and 99.0% (95%CI, 94.8%-100%), respectively. No differences in performance were observed by HIV status. CONCLUSIONS ALARM demonstrated excellent accuracy for moderate-to-severe hepatic steatosis regardless of HIV status. Application of ALARM to radiographic repositories could facilitate real-world studies to evaluate medications associated with steatosis and assess differences by HIV status.
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Affiliation(s)
- Jessie Torgersen
- Department of Medicine, Penn Center for AIDS Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real World Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Scott Akers
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Yuankai Huo
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - James G. Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - J. Jeffrey Carr
- Department of Radiology and Radiological Sciences, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Melissa Skanderson
- Department of Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Woody Levin
- Department of Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Joseph K. Lim
- Department of Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Tamar H. Taddei
- Department of Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Kaku So-Armah
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Debika Bhattacharya
- VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Christopher T. Rentsch
- Department of Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Li Shen
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real World Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rotonya Carr
- Department of Medicine, Division of Gastroenterology, University of Washington, Seattle, WA, USA
| | - Russell T. Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real World Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analysis (CBICA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, 19104
| | | | - Matthew Freiberg
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Amy C. Justice
- Department of Medicine, Yale School of Medicine, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
- Division of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA
| | - Vincent Lo Re
- Department of Medicine, Penn Center for AIDS Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Center for Real World Effectiveness and Safety of Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Medellin A, Wilson S. Sonographic evaluation of a surgically created pouch. Abdom Radiol (NY) 2023; 48:2986-2999. [PMID: 37318537 DOI: 10.1007/s00261-023-03941-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 04/24/2023] [Accepted: 04/24/2023] [Indexed: 06/16/2023]
Abstract
This manuscript focuses on a review of the normal and abnormal sonographic appearance of the surgically created pouch as part of an article series on the topic. It includes information regarding sonographic technique, normal anatomy, and commonly encounter diseases and complications.
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Affiliation(s)
- Alexandra Medellin
- Department of Radiology, University of Calgary, Foothills Medical Centre, Calgary, AB, Canada.
| | - Stephanie Wilson
- Division of Gastroenterology, Department of Radiology and Department of Medicine, University of Calgary. Foothills Medical Centre, Calgary, AB, Canada
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Qi YM, Xiao EH. Advances in application of novel magnetic resonance imaging technologies in liver disease diagnosis. World J Gastroenterol 2023; 29:4384-4396. [PMID: 37576700 PMCID: PMC10415971 DOI: 10.3748/wjg.v29.i28.4384] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/03/2023] [Accepted: 07/07/2023] [Indexed: 07/26/2023] Open
Abstract
Liver disease is a major health concern globally, with high morbidity and mor-tality rates. Precise diagnosis and assessment are vital for guiding treatment approaches, predicting outcomes, and improving patient prognosis. Magnetic resonance imaging (MRI) is a non-invasive diagnostic technique that has been widely used for detecting liver disease. Recent advancements in MRI technology, such as diffusion weighted imaging, intravoxel incoherent motion, magnetic resonance elastography, chemical exchange saturation transfer, magnetic resonance spectroscopy, hyperpolarized MR, contrast-enhanced MRI, and ra-diomics, have significantly improved the accuracy and effectiveness of liver disease diagnosis. This review aims to discuss the progress in new MRI technologies for liver diagnosis. By summarizing current research findings, we aim to provide a comprehensive reference for researchers and clinicians to optimize the use of MRI in liver disease diagnosis and improve patient prognosis.
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Affiliation(s)
- Yi-Ming Qi
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha 410000, Hunan Province, China
| | - En-Hua Xiao
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha 410000, Hunan Province, China
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Bulakci M, Ercan CC, Karapinar E, Aksakal MZT, Aliyev S, Bicen F, Sahin AY, Salmaslioglu A. Quantitative evaluation of hepatic steatosis using attenuation imaging in a pediatric population: a prospective study. Pediatr Radiol 2023; 53:1629-1639. [PMID: 36881143 DOI: 10.1007/s00247-023-05615-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 01/23/2023] [Accepted: 01/24/2023] [Indexed: 03/08/2023]
Abstract
BACKGROUND Obesity and fatty-liver disease are increasingly common in children. Hepatic steatosis is becoming the most common cause of chronic liver disease during childhood. There is a need for noninvasive imaging methods that are easily accessible, safe and do not require sedation in the diagnosis and follow-up of the disease. OBJECTIVE In this study, the diagnostic role of ultrasound attenuation imaging (ATI) in the detection and staging of fatty liver in the pediatric age group was investigated using the magnetic resonance imaging (MRI)-proton density fat fraction as the reference. MATERIALS AND METHODS A total of 140 children with both ATI and MRI constituted the study group. Fatty liver was classified as mild (S1, defined as ≥ 5% steatosis), moderate (S2, defined as ≥ 10% steatosis), or severe (S3, defined as ≥ 20% steatosis) according to MRI-proton density fat fraction values. MRI studies were performed on the same 1.5-tesla (T) MR device without sedation and contrast agent. Ultrasound examinations were performed independently by two radiology residents blinded to the MRI data. RESULTS While no steatosis was detected in half of the cases, S1 steatosis was found in 31 patients (22.1%), S2 in 29 patients (20.7%) and S3 in 10 patients (7.1%). A strong correlation was found between attenuation coefficient and MRI-proton density fat fraction values (r = 0.88, 95% CI 0.84-0.92; P < 0.001). The area under the receiver operating characteristic curve values of ATI were calculated as 0.944 for S > 0, 0.976 for S > 1 and 0.970 for S > 2, based on 0.65, 0.74 and 0.91 dB/cm/MHz cut-off values, respectively. The intraclass correlation coefficient values for the inter-observer agreement and test-retest reproducibility were calculated as 0.90 and 0.91, respectively. CONCLUSION Ultrasound attenuation imaging is a promising noninvasive method for the quantitative evaluation of fatty liver disease.
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Affiliation(s)
- Mesut Bulakci
- Department of Radiology, Istanbul Faculty of Medicine, Istanbul University, Topkapi Mahallesi, Turgut Ozal Caddesi, No:118, 34093, Fatih, Istanbul, Turkey.
| | - Celal Caner Ercan
- Department of Radiology, Istanbul Faculty of Medicine, Istanbul University, Topkapi Mahallesi, Turgut Ozal Caddesi, No:118, 34093, Fatih, Istanbul, Turkey
| | - Edanur Karapinar
- Department of Radiology, Istanbul Faculty of Medicine, Istanbul University, Topkapi Mahallesi, Turgut Ozal Caddesi, No:118, 34093, Fatih, Istanbul, Turkey
| | | | - Shamil Aliyev
- Department of Radiology, Faculty of Medicine, Istinye University, Istanbul, Turkey
| | - Fuat Bicen
- Department of Radiology and Neuroradiology, Klinikum Barnim GmbH, Werner Forssmann Hospital, Eberswalde, Germany
| | - Aylin Yetim Sahin
- Department of Pediatrics, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
| | - Artur Salmaslioglu
- Department of Radiology, Istanbul Faculty of Medicine, Istanbul University, Topkapi Mahallesi, Turgut Ozal Caddesi, No:118, 34093, Fatih, Istanbul, Turkey
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Jang W, Song JS. Non-Invasive Imaging Methods to Evaluate Non-Alcoholic Fatty Liver Disease with Fat Quantification: A Review. Diagnostics (Basel) 2023; 13:diagnostics13111852. [PMID: 37296703 DOI: 10.3390/diagnostics13111852] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 05/17/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023] Open
Abstract
Hepatic steatosis without specific causes (e.g., viral infection, alcohol abuse, etc.) is called non-alcoholic fatty liver disease (NAFLD), which ranges from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), fibrosis, and NASH-related cirrhosis. Despite the usefulness of the standard grading system, liver biopsy has several limitations. In addition, patient acceptability and intra- and inter-observer reproducibility are also concerns. Due to the prevalence of NAFLD and limitations of liver biopsies, non-invasive imaging methods such as ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) that can reliably diagnose hepatic steatosis have developed rapidly. US is widely available and radiation-free but cannot examine the entire liver. CT is readily available and helpful for detection and risk classification, significantly when analyzed using artificial intelligence; however, it exposes users to radiation. Although expensive and time-consuming, MRI can measure liver fat percentage with magnetic resonance imaging proton density fat fraction (MRI-PDFF). Specifically, chemical shift-encoded (CSE)-MRI is the best imaging indicator for early liver fat detection. The purpose of this review is to provide an overview of each imaging modality with an emphasis on the recent progress and current status of liver fat quantification.
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Affiliation(s)
- Weon Jang
- Department of Radiology, Jeonbuk National University Medical School and Hospital, 20 Geonji-ro, Deokjin-gu, Jeonju 54907, Jeonbuk, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Jeonbuk, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Jeonbuk, Republic of Korea
| | - Ji Soo Song
- Department of Radiology, Jeonbuk National University Medical School and Hospital, 20 Geonji-ro, Deokjin-gu, Jeonju 54907, Jeonbuk, Republic of Korea
- Research Institute of Clinical Medicine, Jeonbuk National University, Jeonju 54907, Jeonbuk, Republic of Korea
- Biomedical Research Institute, Jeonbuk National University Hospital, Jeonju 54907, Jeonbuk, Republic of Korea
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Shah UA, Ballinger TJ, Bhandari R, Dieli-Conwright CM, Guertin KA, Hibler EA, Kalam F, Lohmann AE, Ippolito JE. Imaging modalities for measuring body composition in patients with cancer: opportunities and challenges. J Natl Cancer Inst Monogr 2023; 2023:56-67. [PMID: 37139984 PMCID: PMC10157788 DOI: 10.1093/jncimonographs/lgad001] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 12/15/2022] [Accepted: 12/30/2022] [Indexed: 05/05/2023] Open
Abstract
Body composition assessment (ie, the measurement of muscle and adiposity) impacts several cancer-related outcomes including treatment-related toxicities, treatment responses, complications, and prognosis. Traditional modalities for body composition measurement include body mass index, body circumference, skinfold thickness, and bioelectrical impedance analysis; advanced imaging modalities include dual energy x-ray absorptiometry, computerized tomography, magnetic resonance imaging, and positron emission tomography. Each modality has its advantages and disadvantages, thus requiring an individualized approach in identifying the most appropriate measure for specific clinical or research situations. Advancements in imaging approaches have led to an abundance of available data, however, the lack of standardized thresholds for classification of abnormal muscle mass or adiposity has been a barrier to adopting these measurements widely in research and clinical care. In this review, we discuss the different modalities in detail and provide guidance on their unique opportunities and challenges.
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Affiliation(s)
- Urvi A Shah
- Department of Medicine, Myeloma Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Tarah J Ballinger
- Department of Medicine, Indiana University Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Rusha Bhandari
- Department of Pediatrics, City of Hope, Duarte, CA, USA
- Department of Population Science, City of Hope, Duarte, CA, USA
| | - Christina M Dieli-Conwright
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Kristin A Guertin
- Department of Public Health Sciences, University of Connecticut Health, Farmington, CT, USA
| | - Elizabeth A Hibler
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Faiza Kalam
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ana Elisa Lohmann
- Department of Medical Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Joseph E Ippolito
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St Louis, MO, USA
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Lee SJ, Kim YR, Lee YH, Yoon KH. US Attenuation Imaging for the Evaluation and Diagnosis of Fatty Liver Disease. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2023; 84:666-675. [PMID: 37324990 PMCID: PMC10265227 DOI: 10.3348/jksr.2022.0053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 06/30/2022] [Accepted: 10/14/2022] [Indexed: 06/17/2023]
Abstract
Purpose This study aimed to determine whether the attenuation coefficient (AC) from attenuation imaging (ATI) was correlated with visual US assessment in patients with hepatic steatosis. Moreover, it aimed to assess whether the patient's blood chemistry results and CT attenuation were correlated with AC. Materials and Methods Patients who underwent abdominal US with ATI between April 2018 and December 2018 were included in this study. Patients with chronic liver disease or cirrhosis were excluded. The correlation between AC and other parameters, such as visual US assessment, blood chemistry results, liver attenuation, and liver-to-spleen (L/S) ratio, were analyzed. AC values according to visual US assessment grades were compared using analysis of variance. Results A total of 161 patients were included in this study. The correlation coefficient between US assessment and AC was 0.814 (p < 0.001). The mean AC values for the normal, mild, moderate, and severe grades were 0.56, 0.66, 0.74, and 0.85, respectively (p < 0.001). Alanine aminotransferase levels were significantly correlated with AC (r = 0.317, p < 0.001). The correlation coefficients between liver attenuation and AC and between L/S ratio and AC were -0.702 and -0.626, respectively (p < 0.001). Conclusion Visual US assessment and AC showed a strong positive correlation with the discriminative value between the groups. Computed tomography attenuation and AC showed a strong negative correlation.
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Klepper C, Crimmins NA, Orkin S, Sun Q, Fei L, Xanthakos S, Mouzaki M. Nonalcoholic Fatty Liver Disease in Young Children with Obesity. Child Obes 2023; 19:179-185. [PMID: 35639419 PMCID: PMC10122212 DOI: 10.1089/chi.2022.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Background: To evaluate the prevalence of suspected nonalcoholic fatty liver disease (NAFLD) in young children with obesity and determine associated risk factors. Methods: Retrospective single-center study of children with obesity, ages 2-6 years. Suspected NAFLD was defined as an alanine aminotransferase (ALT) >30 U/L. Multivariable analyses were performed to determine predictors of elevated ALT. Results: Among 237 children 2-6 years old, 35% had elevated ALT. Multivariable analysis showed that higher BMI z score [odds ratio (OR): 1.5 confidence interval (95% CI: 1.04-1.92)] and higher gamma-glutamyl transferase (GGT) [OR: 21.3 (95% CI: 3.7-121.1)] predicted elevated ALT. Of those with ≥2 ALT levels, 38% (n = 33/86) had a persistently elevated ALT (median ALT >30 U/L). Only 7% of patients with ALT >30 U/L underwent further testing to evaluate for alternative causes of liver disease. Conclusion: Suspected NAFLD is common in young children with obesity and predicted by obesity severity and GGT. Other cardiometabolic markers were equivalent between those with normal vs. elevated ALT, suggesting NAFLD onset may precede development of comorbidities. Earlier screening will enable prompt diagnosis and intervention, which may prevent or delay the onset of cardiometabolic diseases commonly associated with NAFLD in adolescence and adulthood.
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Affiliation(s)
- Corie Klepper
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Nancy A. Crimmins
- Division of Endocrinology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Sarah Orkin
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Qin Sun
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Lin Fei
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Stavra Xanthakos
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Marialena Mouzaki
- Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
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Rajesh S, Arunachalam VK, Periaswamy G, Kalyan G, Renganathan R, SM G, Cherian M. Accuracy of Evaluation of Fatty Liver with Third-Generation Unenhanced Dual-Energy CT and MRI: Prospective Comparison with MR Spectroscopy. JOURNAL OF GASTROINTESTINAL AND ABDOMINAL RADIOLOGY 2023. [DOI: 10.1055/s-0043-1763483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/31/2023] Open
Abstract
Abstract
Background and Objectives The purpose of this study is to evaluate and establish the accuracy of noninvasive methods, including third-generation dual-source dual-energy computed tomography (DECT) and proton density fat (PDF) fraction on magnetic resonance imaging (MRI) using three-dimensional multiecho multipoint chemical shift-encoded spoiled gradient echo (q-Dixon) sequence in the quantification of hepatic steatosis; with H1-MR spectroscopy (MRS) as the reference standard.
Materials and Methods A total of 47 patients were included in this prospective study. We studied the accuracy of fatty liver detection using third-generation DECT using mixed set images (MSIs), virtual monochromatic images (VMIs), and MRI q-Dixon. The results were compared with H1-MRS. Data were analyzed using linear regression for each technique compared with MRS.
Results Our study's correlation and linear regression analysis showed a good correlation between PDF values obtained by H1-MRS and MR q-Dixon methods (r = 0.821, r
2 = 0.674, p < 0.001). On MSI, H1-MRS showed a low correlation with average liver attenuation (r
2 = 0.379, p < 0.001) and a moderate correlation with liver attenuation index (r
2 = 0.508, p < 0.001) noted. There was a moderate correlation between H1-MRS and average liver attenuation and liver attenuation index on VMI at 80 to 120 keV with r
2 = 0.434, p < 0.001, and r
2 = 0.485, p < 0.001, respectively.
Conclusion MRI q-Dixon is the method of choice for evaluating fat quantification in the absence of H1 MRS. Among DECT images, VMI is valuable in the evaluation of hepatic fat as compared with the mixed set of images.
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48
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Ultrasound-based hepatic fat quantification: current status and future directions. Clin Radiol 2023; 78:187-200. [PMID: 36411088 DOI: 10.1016/j.crad.2022.10.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 09/22/2022] [Accepted: 10/06/2022] [Indexed: 11/19/2022]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a spectrum of disease from fatty accumulation (steatosis), necro-inflammation though to fibrosis. It is of increasing global prevalence as a hepatic manifestation of the metabolic syndrome. Although accurate histopathology and magnetic resonance imaging techniques for hepatic fat quantification exist, these are limited by invasiveness and availability, respectively. Ultrasonography is potentially ideal for assessing and monitoring hepatic steatosis given the examination is rapid and readily available. Traditional ultrasound methods include qualitative B-mode for imaging markers, such as increased hepatic parenchymal echogenicity compared to adjacent renal cortex are commonplace; however, there is acknowledged significant interobserver variability and they are suboptimal for detecting mild steatosis. Recently quantitative ultrasound metrics have been investigated as biomarkers for hepatic steatosis. These methods rely on changes in backscatter, attenuation, and speed of sound differences encountered in a steatotic liver. Prospective studies using quantitative ultrasound parameters show good diagnostic performance even at low steatosis grades and in NAFLD. This review aims to define the clinical need for ultrasound-based assessments of liver steatosis, to describe briefly the physics that underpins the various techniques available, and to assess the evidence base for the effectiveness of the techniques that are available commercially from various ultrasound vendors.
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Wu Y, Liu Q, Wang Y, Li F, Chan LWC, Wen Y, Yang F, Xiang Y, Duan Q, Luo P, Lei P. Diagnostic efficiency on ultrasound shear wave elastography in evaluation of steatosis severity for non-alcoholic fatty liver disease: a rat model. Eur J Med Res 2023; 28:75. [PMID: 36774529 PMCID: PMC9921353 DOI: 10.1186/s40001-023-01042-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Accepted: 02/03/2023] [Indexed: 02/13/2023] Open
Abstract
BACKGROUND The pathological feature of steatosis affects the elasticity values measured by shear wave elastography (SWE) is still controversial in non-alcoholic fatty liver disease (NAFLD). The aim of this study is to demonstrate the influence of steatosis on liver stiffness measured by SWE on a rat model with NAFLD and analyze feasibility of SWE for grading steatosis in absence of fibrosis. METHODS Sixty-six rats were fed with methionine choline deficient diet or standard diet to produce various stages of steatosis; 48 rats were available for final analysis. Rats underwent abdominal ultrasound SWE examination and pathological assessment. Liver histopathology was analyzed to assess the degree of steatosis, inflammation, ballooning, and fibrosis according to the non-alcoholic fatty liver disease activity score. The diagnostic performance of SWE for differentiating steatosis stages was estimated according to the receiver operating characteristic (ROC) curve. Decision curve analysis (DCA) was conducted to determine clinical usefulness and the areas under DCA (AUDCAs) calculated. RESULTS In multivariate analysis, steatosis was an independent factor affecting the mean elastic modules (B = 1.558, P < 0.001), but not inflammation (B = - 0.031, P = 0.920) and ballooning (B = 0.216, P = 0.458). After adjusting for inflammation and ballooning, the AUROC of the mean elasticity for identifying S ≥ S1 was 0.956 (95%CI: 0.872-0.998) and the AUDCA, 0.621. The AUROC for distinguishing S ≥ S2 and S = S3 was 0.987 (95%CI: 0.951-1.000) and 0.920 (95%CI: 0.816-0.986) and the AUDCA was 0.506 and 0.256, respectively. CONCLUSIONS Steatosis is associated with liver stiffness and SWE may have the feasibility to be introduced as an assistive technology in grading steatosis for patients with NAFLD in absence of fibrosis.
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Affiliation(s)
- Yuhui Wu
- grid.452244.1Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004 Guizhou China
| | - Qianjiao Liu
- grid.452244.1Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004 Guizhou China
| | - Yan Wang
- grid.452244.1Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004 Guizhou China
| | - Fangyan Li
- grid.452244.1Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004 Guizhou China
| | - Lawrence Wing-Chi Chan
- grid.16890.360000 0004 1764 6123Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, SAR China
| | - Yong Wen
- grid.452244.1Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004 Guizhou China
| | - Fan Yang
- grid.413458.f0000 0000 9330 9891School of Biology & Engineering, Guizhou Medical University, Guiyang,, Guizhou China
| | - Yining Xiang
- grid.452244.1Department of Pathology, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou China
| | - Qinghong Duan
- grid.452244.1Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004 Guizhou China
| | - Peng Luo
- grid.413458.f0000 0000 9330 9891School of Public Health, Guizhou Medical University, Guiyang, Guizhou China
| | - Pinggui Lei
- Department of Radiology, the Affiliated Hospital of Guizhou Medical University, No. 28 Guiyi Street, Yunyan District, Guiyang, 550004, Guizhou, China. .,School of Public Health, Guizhou Medical University, Guiyang, Guizhou, China. .,Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, SAR, China.
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50
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Bisaccia G, Ricci F, Khanji MY, Sorella A, Melchiorre E, Iannetti G, Galanti K, Mantini C, Pizzi AD, Tana C, Renda G, Fedorowski A, De Caterina R, Gallina S. Cardiovascular Morbidity and Mortality Related to Non-alcoholic Fatty Liver Disease: A Systematic Review and Meta-analysis. Curr Probl Cardiol 2023; 48:101643. [PMID: 36773944 DOI: 10.1016/j.cpcardiol.2023.101643] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 02/04/2023] [Indexed: 02/12/2023]
Abstract
Whether non-alcoholic fatty liver disease (NAFLD) is a cardiovascular (CV) risk factor is debated. We performed a systematic review and meta-analysis to assess the CV morbidity and mortality related to NAFLD in the general population, and to determine whether CV risk is comparable between lean and non-lean NAFLD phenotypes. We searched multiple databases, including PubMed, Embase, and the Cochrane Library, for observational studies published through 2022 that reported the risk of CV events and mortality. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for all-cause mortality, CV mortality, myocardial infarction (MI), stroke, atrial fibrillation (AF), and major adverse cardiovascular and cerebrovascular events (MACCE) were assessed through random-effect meta-analysis. We identified 33 studies and a total study population of 10,592,851 individuals (mean age 53±8; male sex 50%; NAFLD 2, 9%). Mean follow-up was 10±6 years. Pooled ORs for all-cause and CV mortality were respectively 1.14 (95% CI, 0.78-1.67) and 1.13 (95% CI, 0.57-2.23), indicating no significant association between NAFLD and mortality. NAFLD was associated with increased risk of MI (OR 1.6; 95% CI, 1.5-1.7), stroke (OR: 1.6; 95% CI, 1.2-2.1), atrial fibrillation (OR: 1.7; 95% CI, 1.2-2.3), and MACCE (OR: 2.3; 95% CI, 1.3-4.2). Compared with non-lean NAFLD, lean NAFLD was associated with increased CV mortality (OR: 1.50; 95% CI, 1.1-2.0), but similar all-cause mortality and risk of MACCE. While NAFLD may not be a risk factor for total and CV mortality, it is associated with excess risk of non-fatal CV events. Lean and non-lean NAFLD phenotypes exhibit distinct prognostic profiles and should receive equitable clinical care.
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Affiliation(s)
- Giandomenico Bisaccia
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Ricci
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Department of Clinical Sciences, Lund University, Malmö, Sweden; Fondazione VillaSerena per la Ricerca, Città Sant'Angelo, Pescara, Italy.
| | - Mohammed Y Khanji
- Newham University Hospital, Barts Health NHS Trust, London; Barts Heart Centre, Barts Health NHS Trust, London; NIHR Barts Biomedical Research Centre, William Harvey Research Institute, Queen Mary University, London
| | - Anna Sorella
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Eugenia Melchiorre
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Giovanni Iannetti
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Kristian Galanti
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Cesare Mantini
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Andrea Delli Pizzi
- Department of Innovative Technologies in Medicine and Dentistry, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Claudio Tana
- Center of Excellence on Headache, Geriatrics and COVID-19 Clinic, SS Annunziata Hospital of Chieti, Chieti, Italy
| | - Giulia Renda
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Artur Fedorowski
- Department of Clinical Sciences, Lund University, Malmö, Sweden; Department of Cardiology, Karolinska University Hospital, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Raffaele De Caterina
- Fondazione VillaSerena per la Ricerca, Città Sant'Angelo, Pescara, Italy; Cardiology Division, Pisa University Hospital and University of Pisa, Pisa, Italy
| | - Sabina Gallina
- Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University of Chieti-Pescara, Chieti, Italy
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