Deep learning radiomics of left atrial appendage features for predicting atrial fibrillation recurrence.

Journal: BMC medical imaging
Published Date:

Abstract

BACKGROUND: Structural remodeling of the left atrial appendage (LAA) is characteristic of atrial fibrillation (AF), and LAA morphology impacts radiofrequency catheter ablation (RFCA) outcomes. In this study, we aimed to develop and validate a predictive model for AF ablation outcomes using LAA morphological features, deep learning (DL) radiomics, and clinical variables.

Authors

  • Yanping Yin
    Department of Cardiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Dongdu Road, Linhai, Zhejiang Province, 317000, China.
  • Sixiang Jia
    Department of Heart Center, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, N1 Shangcheng Road, Yiwu 322000, China.
  • Jing Zheng
    Shandong Institute for Food and Drug Control, Jinan 250101, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Ziwen Wang
    Department of Radiology, School of Medicine, The Fourth Affiliated Hospital of Zhejiang University, Yiwu, China.
  • Jiangbo Lin
    Department of Cardiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Dongdu Road, Linhai, Zhejiang Province, 317000, China.
  • Wenting Lin
    Department of Heart Center, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, N1 Shangcheng Road, Yiwu 322000, China.
  • Chao Feng
    Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Shudong Xia
    Department of Heart Center, The Fourth Affiliated Hospital of Zhejiang University School of Medicine, N1 Shangcheng Road, Yiwu 322000, China.
  • Weili Ge
    Department of Cardiology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, Dongdu Road, Linhai, Zhejiang Province, 317000, China. geweili@126.com.