An imaging-based artificial intelligence model for non-invasive grading of hepatic venous pressure gradient in cirrhotic portal hypertension.

Journal: Cell reports. Medicine
Published Date: Mar 15, 2022

Abstract

The hepatic venous pressure gradient (HVPG) is the gold standard for cirrhotic portal hypertension (PHT), but it is invasive and specialized. Alternative non-invasive techniques are needed to assess the hepatic venous pressure gradient (HVPG). Here, we develop an auto-machine-learning CT radiomics HVPG quantitative model (HVPG), and then we validate the model in internal and external test datasets by the area under the receiver operating characteristic curves (AUCs) for HVPG stages (≥10, ≥12, ≥16, and ≥20 mm Hg) and compare the model with imaging- and serum-based tools. The final HVPG model achieves AUCs over 0.80 and outperforms other non-invasive tools for assessing HVPG. The model shows performance improvement in identifying the severity of PHT, which may help non-invasive HVPG primary prophylaxis when transjugular HVPG measurements are not available.

Authors

  • Qian Yu
    State Key Laboratory of Characteristic Chinese Medicine Resources in Southwest China, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Yifei Huang
    CHESS Center, Institute of Portal Hypertension, First Hospital of Lanzhou University, Lanzhou, China.
  • Xiaoguo Li
    Robotics Research Center, School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, Singapore.
  • Michael Pavlides
    Oxford Centre for Clinical Magnetic Resonance Research, Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, United Kingdom.
  • Dengxiang Liu
    CHESS Working Party, Xingtai People's Hospital, Xingtai, China.
  • Hongwu Luo
    Department of General Surgery, Third Xiangya Hospital of Central South University, Changsha, China.
  • Huiguo Ding
    Department of Gastroenterology and Hepatology, Beijing You'an Hospital, Capital Medical University, Beijing, China.
  • Weimin An
    Department of Radiology, Fifth Medical Center of PLA General Hospital, Beijing, China.
  • Fuquan Liu
    Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
  • Changzeng Zuo
    CHESS Working Party, Xingtai People's Hospital, Xingtai, China.
  • Chunqiang Lu
    Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
  • Tianyu Tang
    Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
  • Yuancheng Wang
    Department of Radiology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, China.
  • Shan Huang
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, 300211 Tianjin, China.
  • Chuan Liu
    Link Sense Laboratory, Nanjing Research Institute of Electronic Technology, Nanjing, China.
  • Tianlei Zheng
    CHESS Center, Institute of Portal Hypertension, First Hospital of Lanzhou University, Lanzhou, China.
  • Ning Kang
    CHESS Center, Institute of Portal Hypertension, First Hospital of Lanzhou University, Lanzhou, China.
  • Changchun Liu
    School of Control Science and Engineering, Shandong University, 17923 Jingshi Road, Jinan, 250061, People's Republic of China. changchunliu@sdu.edu.cn.
  • Jitao Wang
    CHESS Working Party, Xingtai People's Hospital, Xingtai, China.
  • Seray Akçalar
    Department of Radiology, Ankara University School of Medicine, Ankara, Turkey.
  • Emrecan Çelebioğlu
    Department of Radiology, Ankara University School of Medicine, Ankara, Turkey.
  • Evren Üstüner
    Department of Radiology, Ankara University School of Medicine, Ankara, Turkey.
  • Sadık Bilgiç
    Department of Radiology, Ankara University School of Medicine, Ankara, Turkey.
  • Qu Fang
    Shanghai Aitrox Technology Corporation Limited, Shanghai, 200032, P.R. of China.
  • Chi-Cheng Fu
    Howard Hughes Medical Institute, Janelia Research Campus, 19700 Helix Drive, Ashburn, VA 20147, USA Departments of Bioengineering, Electrical Engineering and Computer Science, and Biophysics Graduate Program, University of California, Berkeley, CA 94720, USA.
  • Ruiping Zhang
    State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100050, China.
  • ChengYan Wang
  • Jingwei Wei
    Animal Reproduction Institute, State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Necati Örmeci
  • Zeynep Ellik
    Department of Gastroenterology, Ankara University School of Medicine, Ankara, Turkey.
  • Özgün Ömer Asiller
    Department of Gastroenterology, Ankara University School of Medicine, Ankara, Turkey.
  • Shenghong Ju
  • Xiaolong Qi
    College of Animal Science and Technology, Beijing University of Agriculture, Beijing, China.

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