Nationwide survey of the status of artificial intelligence-based intracranial aneurysm detection systems

IF 4.4 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Intelligent medicine Pub Date : 2025-02-01 DOI:10.1016/j.imed.2024.11.001

Xinran Wang , Zhao Shi , Xiaoqian Ji , Bin Hu , Sui Chen , Longjiang Zhang

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引用次数: 0

Abstract

Objective

Intracranial aneurysm imaging artificial intelligence (AI) products have entered the clinical implementation phase, but the application status of them in Chinese hospitals remains unclear. A nationwide survey was conducted to explore the current status of intracranial aneurysm imaging AI products in hospitals across China.

Methods

Delphi method was used to develop a questionnaire, which was then distributed to the radiologists across China between September 3rd and 10th, 2023. Independent predictors of the adoption of these AI products, radiologists' attitudes, concerns and knowledge about these AI products were evaluated using logistic regression. Participants were categorized into seven groups based on Chinese geographical regions to compare the performance of these AI products in different geographical regions.

Results

After 3 rounds of Delphi discussion by 29 radiologists, the questionnaire was derived. A total of 961 radiologists from 777 different hospitals in 31 provinces across China completed the questionnaire. Among these hospitals, 45.4% (353/777) had introduced intracranial aneurysm imaging AI products. The most commonly reported concern with these AI products was poor specificity (265/446, 59.4%). The majority of respondents had basic (310/961, 42.0%) or intermediate (331/961, 44.9%) knowledge of AI products and they held positive attitudes (913/961, 95.0%) towards using them. Those who had received AI training were more likely to possess a higher level of knowledge about AI (odds ratio (OR) = 1.80, P = 0.04). For regional comparison, respondents in Central China and East China gave the highest ratings to the accuracy (OR = 2.41, P = 0.048 vs. OR=2.36, P = 0.02) and specificity (OR = 2.34, P = 0.046 vs. OR = 2.37, P = 0.02) of these AI products.