CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning.

Journal: Academic radiology
Published Date: Dec 6, 2023

Abstract

RATIONALE AND OBJECTIVES: To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on contrast-enhanced magnetic resonance imaging (CEMRI) and validate its efficiency for predicting microvascular invasion (MVI) and pathological differentiation in hepatocellular carcinoma (HCC).

Authors

  • Hai-Feng Liu
    Department of Health, Liaocheng People's Hospital of Taishan Medical University Liaocheng 252000, Shandong Province, China.
  • Min Wang
    National and Local Joint Engineering Research Center of Ecological Treatment Technology for Urban Water Pollution, Wenzhou University, Wenzhou 325035, China.
  • Yu-Jie Lu
    Department of Radiology, Third Affiliated Hospital of Soochow University, No.185, Juqian ST, Tianning District, Changzhou, 213000, Jiangsu, China (H.-F.L., Y.-J.L., Q.W., Y.L., W.X.).
  • Qing Wang
    School of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610500, China. qwang@163.com.
  • Yang Lu
    Spectral MD, Inc., 2515 McKinney Avenue, Suite 1000, Dallas, Texas 75201, United States.
  • Fei Xing
    School of Aerospace Engineering, Xiamen University, Xiamen, Fujian 361005, China.
  • Wei Xing
    Department of Radiology, Third Affiliated Hospital of Soochow University, Changzhou Jiangsu 213003.

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