Liver fibrosis progression analyzed with AI predicts renal decline
Dan-Qin Sun,
Jia-Qi Shen,
Xiao-Fei Tong,
Ya-Yun Ren,
Hai-Yang Yuan,
Yang-Yang Li,
Xin-Lei Wang,
Sui-Dan Chen,
Pei-Wu Zhu,
Xiao-Dong Wang,
Christopher D. Byrne,
Giovanni Targher,
Lai Wei,
Vincent W.S. Wong,
Dean Tai,
Arun J. Sanyal,
Hong You,
Ming-Hua Zheng
Affiliations
Dan-Qin Sun
Department of Nephrology, Jiangnan University Medical Center, Wuxi, China; Affiliated Wuxi Clinical College of Nantong University, Wuxi, China; Wuxi No. 2 People's Hospital, Wuxi, China
Jia-Qi Shen
Department of Nephrology, Jiangnan University Medical Center, Wuxi, China; Affiliated Wuxi Clinical College of Nantong University, Wuxi, China; Wuxi No. 2 People's Hospital, Wuxi, China
Xiao-Fei Tong
Liver Research Center, Beijing Friendship Hospital, Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, National Clinical Research Center of Digestive Diseases, Capital Medical University, Beijing, China
Ya-Yun Ren
HistoIndex Pte Ltd, Singapore
Hai-Yang Yuan
MAFLD Research Center, Department of Hepatology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou, China; Institute of Hepatology, Wenzhou Medical University, Wenzhou, China
Yang-Yang Li
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
Xin-Lei Wang
HistoIndex Pte Ltd, Singapore
Sui-Dan Chen
Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
Pei-Wu Zhu
MAFLD Research Center, Department of Hepatology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
Xiao-Dong Wang
Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou, China
Christopher D. Byrne
Southampton National Institute for Health and Care Research Biomedical Research Centre, University Hospital Southampton and University of Southampton, Southampton General Hospital, Southampton, UK
Giovanni Targher
Department of Medicine, University of Verona, Verona, Italy; Metabolic Diseases Research Unit, IRCCS Sacro Cuore-Don Calabria Hospital, Negrar di Valpolicella, Italy
Lai Wei
Hepatopancreatobiliary Center, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China
Vincent W.S. Wong
Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong Special Administrative Region of China
Dean Tai
HistoIndex Pte Ltd, Singapore
Arun J. Sanyal
Stravitz-Sanyal Institute for Liver Disease and Metabolic Health, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Hong You
Liver Research Center, Beijing Friendship Hospital, Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, National Clinical Research Center of Digestive Diseases, Capital Medical University, Beijing, China; Corresponding authors. Addresses: MAFLD Research Center, Department of Hepatology, the First Affiliated Hospital of Wenzhou Medical University; No. 2 Fuxue Lane, Wenzhou 325000, China, Tel.: +86-577-55579611; fax: +86-577-55578522 (M-H. Zheng); Liver Research Center, Beijing Friendship Hospital, Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, National Clinical Research Center of Digestive Diseases, Capital Medical University, Beijing 100050, China, Tel.: +86-10-63139019 (H. You).
Ming-Hua Zheng
MAFLD Research Center, Department of Hepatology, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; Key Laboratory of Diagnosis and Treatment for the Development of Chronic Liver Disease in Zhejiang Province, Wenzhou, China; Institute of Hepatology, Wenzhou Medical University, Wenzhou, China; Corresponding authors. Addresses: MAFLD Research Center, Department of Hepatology, the First Affiliated Hospital of Wenzhou Medical University; No. 2 Fuxue Lane, Wenzhou 325000, China, Tel.: +86-577-55579611; fax: +86-577-55578522 (M-H. Zheng); Liver Research Center, Beijing Friendship Hospital, Beijing Key Laboratory of Translational Medicine on Liver Cirrhosis, National Clinical Research Center of Digestive Diseases, Capital Medical University, Beijing 100050, China, Tel.: +86-10-63139019 (H. You).
Background & Aims: The relationship between biopsy-proven liver fibrosis progression and renal function decline in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) has not been fully elucidated. We used an automated quantitative liver fibrosis assessment (qFibrosis) technique to investigate the temporal changes in regional liver fibrosis. Methods: This retrospective longitudinal study included 68 MASLD patients and their paired formalin-fixed sections of liver biopsies. One hundred eighty-four fibrosis parameters were quantified in five different hepatic regions, including portal tract, peri-portal, zone 2, peri-central and central vein regions, and qFibrosis continuous values were calculated for all samples based on 10 fibrosis parameters using qFibrosis assessment. Liver fibrosis progression (QLF+, n = 18) and regression (QLF-, n = 23) was defined as at least a 20% relative change in qFibrosis over a 23-month follow-up. Renal function decline was assessed by estimated glomerular filtration rate (eGFR) changes. Results: The eGFR decline was greater in the QLF+ group (106.53 ± 13.71 ml/min/1.73 m2 vs. 105.28 ± 12.46 ml/min/1.73 m2) than in the QLF- group (110.87 ± 14.58 ml/min/1.73 m2 vs. 114.18 ± 14.81 ml/min/1.73 m2). In addition, liver fibrosis changes in the central vein and pericentral regions were more strongly associated with eGFR decline than in periportal, zone 2 and portal tract regions. We combined these parameters to construct a prediction model, which better differentiated eGFR decline (a cut-off value of qFibrosis combined index = 0.52, p <0.001). Conclusions: A decline in renal function is significantly related to liver fibrosis progression in MASLD. Regional qFibrosis assessment may efficiently predict eGFR decline, thus highlighting the importance of assessing renal function in patients with MASLD with worsening liver fibrosis. Impact and implications: The study shows that liver fibrosis progression assessed by qFibrosis may be associated with renal function decline, which provides a new perspective for understanding complex pathological processes. A combination of artificial intelligence and digital pathology may earlier and more precisely quantify the progression of regional liver fibrosis, thus better identifying changes in renal function. This opens the possibility of early interventions, which are essential to improve patients’ outcomes.
