학술논문
Development and validation of an image biomarker to identify metabolic dysfunction associated steatohepatitis: MR-MASH score.
Document Type
Academic Journal
Author
Marti-Aguado D; Digestive Disease Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.; Arnouk J; Division of Gastroenterology, Hepatology and Nutrition, Center for Liver Diseases, Pittsburgh Liver Research Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.; Liang JX; Digestive Diseases Department, CIBERehd, Virgen del Rocio University Hospital, Seville, Spain.; Institute of Biomedicine of Seville (HUVR/CSIC/US), Department of Medicine, University of Seville, Seville, Spain.; Lara-Romero C; Digestive Diseases Department, CIBERehd, Virgen del Rocio University Hospital, Seville, Spain.; Institute of Biomedicine of Seville (HUVR/CSIC/US), Department of Medicine, University of Seville, Seville, Spain.; Behari J; Division of Gastroenterology, Hepatology and Nutrition, Center for Liver Diseases, Pittsburgh Liver Research Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.; Furlan A; Division of Abdominal Imaging, Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.; Jimenez-Pastor A; Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.; Quantitative Imaging Biomarkers in Medicine, QUIBIM SL, Valencia, Spain.; Ten-Esteve A; Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.; Alfaro-Cervello C; Pathology Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Faculty of Medicine, University of Valencia, Valencia, Spain.; Bauza M; Pathology Department, La Fe University and Polytechnic Hospital, Valencia, Spain.; Gallen-Peris A; Digestive Disease Department, Hospital Arnau de Vilanova, Valencia, Spain.; Gimeno-Torres M; Digestive Disease Department, La Fe University and Polytechnic Hospital, Valencia, Spain.; Merino-Murgui V; Digestive Disease Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Perez-Girbes A; Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.; Radiology Department, La Fe University and Polytechnic Hospital, Valencia, Spain.; Benlloch S; Digestive Disease Department, Hospital Arnau de Vilanova, Valencia, Spain.; CIBERehd, Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas, Instituto de Salud Carlos III, Madrid, Spain.; Pérez-Rojas J; Pathology Department, La Fe University and Polytechnic Hospital, Valencia, Spain.; Puglia V; Pathology Department, Hospital Arnau de Vilanova, Valencia, Spain.; Ferrández-Izquierdo A; Pathology Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Faculty of Medicine, University of Valencia, Valencia, Spain.; Aguilera V; CIBERehd, Centro de Investigación Biomédica en Red en Enfermedades Hepáticas y Digestivas, Instituto de Salud Carlos III, Madrid, Spain.; Hepatology and Liver Transplantation Unit, La Fe University and Polytechnic Hospital, Valencia, Spain.; Giesteira B; Radiology Department, Centro Hospitalar Universitário do Porto, Instituto de Ciências Biomédicas de Abel Salazar, University of Porto, Porto, Portugal.; França M; Radiology Department, Centro Hospitalar Universitário do Porto, Instituto de Ciências Biomédicas de Abel Salazar, University of Porto, Porto, Portugal.; Monton C; Digestive Disease Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Escudero-García D; Digestive Disease Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Faculty of Medicine, University of Valencia, Valencia, Spain.; Alberich-Bayarri Á; Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.; Quantitative Imaging Biomarkers in Medicine, QUIBIM SL, Valencia, Spain.; Serra MA; Digestive Disease Department, Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain.; Faculty of Medicine, University of Valencia, Valencia, Spain.; Bataller R; Division of Gastroenterology, Hepatology and Nutrition, Center for Liver Diseases, Pittsburgh Liver Research Center, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA.; Romero-Gomez M; Digestive Diseases Department, CIBERehd, Virgen del Rocio University Hospital, Seville, Spain.; Institute of Biomedicine of Seville (HUVR/CSIC/US), Department of Medicine, University of Seville, Seville, Spain.; University of Seville, Seville, Spain.; Marti-Bonmati L; Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, and Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.; Radiology Department, La Fe University and Polytechnic Hospital, Valencia, Spain.
Source
Publisher: Wiley-Blackwell Country of Publication: United States NLM ID: 101160857 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1478-3231 (Electronic) Linking ISSN: 14783223 NLM ISO Abbreviation: Liver Int Subsets: MEDLINE
Subject
Language
English
Abstract
Background and Aims: Diagnosis of metabolic dysfunction-associated steatohepatitis (MASH) requires histology. In this study, a magnetic resonance imaging (MRI) score was developed and validated to identify MASH in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Secondarily, a screening strategy for MASH diagnosis was investigated.
Methods: This prospective multicentre study included 317 patients with biopsy-proven MASLD and contemporaneous MRI. The discovery cohort (Spain, Portugal) included 194 patients. NAFLD activity score (NAS) and fibrosis were assessed with the NASH-CRN histologic system. MASH was defined by the presence of steatosis, lobular inflammation, and ballooning, with NAS ≥4 with or without fibrosis. An MRI-based composite biomarker of Proton Density Fat Fraction and waist circumference (MR-MASH score) was developed. Findings were afterwards validated in an independent cohort (United States, Spain) with different MRI protocols.
Results: In the derivation cohort, 51% (n = 99) had MASH. The MR-MASH score identified MASH with an AUC = .88 (95% CI .83-.93) and strongly correlated with NAS (r = .69). The MRI score lower cut-off corresponded to 88% sensitivity with 86% NPV, while the upper cut-off corresponded to 92% specificity with 87% PPV. MR-MASH was validated with an AUC = .86 (95% CI .77-.92), 91% sensitivity (lower cut-off) and 87% specificity (upper cut-off). A two-step screening strategy with sequential MR-MASH examination performed in patients with indeterminate-high FIB-4 or transient elastography showed an 83-84% PPV to identify MASH. The AUC of MR-MASH was significantly higher than that of the FAST score (p < .001).
Conclusions: The MR-MASH score has clinical utility in the identification and management of patients with MASH at risk of progression.
(© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)
Methods: This prospective multicentre study included 317 patients with biopsy-proven MASLD and contemporaneous MRI. The discovery cohort (Spain, Portugal) included 194 patients. NAFLD activity score (NAS) and fibrosis were assessed with the NASH-CRN histologic system. MASH was defined by the presence of steatosis, lobular inflammation, and ballooning, with NAS ≥4 with or without fibrosis. An MRI-based composite biomarker of Proton Density Fat Fraction and waist circumference (MR-MASH score) was developed. Findings were afterwards validated in an independent cohort (United States, Spain) with different MRI protocols.
Results: In the derivation cohort, 51% (n = 99) had MASH. The MR-MASH score identified MASH with an AUC = .88 (95% CI .83-.93) and strongly correlated with NAS (r = .69). The MRI score lower cut-off corresponded to 88% sensitivity with 86% NPV, while the upper cut-off corresponded to 92% specificity with 87% PPV. MR-MASH was validated with an AUC = .86 (95% CI .77-.92), 91% sensitivity (lower cut-off) and 87% specificity (upper cut-off). A two-step screening strategy with sequential MR-MASH examination performed in patients with indeterminate-high FIB-4 or transient elastography showed an 83-84% PPV to identify MASH. The AUC of MR-MASH was significantly higher than that of the FAST score (p < .001).
Conclusions: The MR-MASH score has clinical utility in the identification and management of patients with MASH at risk of progression.
(© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)