Generative artificial intelligence for fundus fluorescein angiography interpretation and human expert evaluation.

Journal: NPJ digital medicine
Published Date: Jul 2, 2025

Abstract

Fundus fluorescein angiography (FFA) is the gold standard for diagnosing chorioretinal diseases, but its interpretation requires significant expertise and time. Despite generative AI's enormous potential in medical report generation, automatic FFA interpretation lacks robust models and sufficient evaluation metrics. This study introduces InterpreFFA, a diagnosis-supervised contrastive learning framework, to emulate ophthalmologists' decision-making process in FFA report generation. Validated on multi-center datasets, InterpreFFA demonstrated superior performance and generalization compared to baseline models. In a simulated clinical setting, two residents used InterpreFFA to diagnose and report FFA cases, with six board-certified ophthalmologists rating the generated reports based on a five-point Likert scale. InterpreFFA significantly improved diagnostic accuracy (85.55 to 90.34%, p < 0.05) and shortened reporting time (153.93 to 108.08 s, p < 0.001). Although AI-generated reports scored slightly lower than manual reports (4.12 vs. 4.38, p < 0.01), InterpreFFA proves to be a promising and cost-effective ancillary tool for enhancing clinical efficiency.

Authors

  • An Shao
    Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, College of Medicine, Hangzhou, 310009, China.
  • Xiaocong Liu
    Eye Center, The Second Affiliated Hospital, Zhejiang University, Zhejiang, China.
  • Wenyue Shen
    Eye Center, The Second Affiliated Hospital, Zhejiang University, Zhejiang, China.
  • Yingyu Li
    Zhejiang University, Eye Center of Second Affiliated Hospital, School of Medicine, China. Zhejiang Provincial Key Laboratory of Ophthalmology. Zhejiang Provincial Clinical Research Center for Eye Diseases. Zhejiang Provincial Engineering Institute on Eye Diseases, Hangzhou, China.
  • Hongkang Wu
    Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Xiangji Pan
    Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, College of Medicine, Hangzhou, 310009, China.
  • Zexin Yang
    College of Economics and Management, China Jiliang University, Hangzhou, China.
  • Yufeng Xu
    Department of Ophthalmology, The Second Affiliated Hospital of Zhejiang University, College of Medicine, Hangzhou, 310009, China.
  • Tiepei Zhu
    Zhejiang University, Eye Center of Second Affiliated Hospital, School of Medicine, China. Zhejiang Provincial Key Laboratory of Ophthalmology. Zhejiang Provincial Clinical Research Center for Eye Diseases. Zhejiang Provincial Engineering Institute on Eye Diseases, Hangzhou, China.
  • Yao Wang
    Department of Gastrointestinal Surgery, Zhongshan People's Hospital, Zhongshan, Guangdong, China.
  • Jie Yang
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.
  • Yih Chung Tham
    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. thamyc@nus.edu.sg.
  • Jian Wu
    Department of Medical Technology, Jiangxi Medical College, Shangrao, Jiangxi, China.
  • Kai Jin
    Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
  • Juan Ye
    Eye Center, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

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