Scoping review of regulatory transparency in AI-based radiology software: analysis of PMDA-approved SaMD products.
Authors
Affiliations (11)
Affiliations (11)
- Department of Radiology, Jichi Medical University, 3311-1, Yakushiji, Shimotsuke-shi, Tochigi, 329-0498, Japan.
- Medical AI Promotion Institute Co., Ltd., Life Science Building, 12-9 Nihonbashi Odemmachi, Chuo-ku, Tokyo, Japan.
- Department of Artificial Intelligence, Graduate School of Medicine, Osaka Metropolitan University, Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan.
- Department of Diagnostic and Interventional Radiology, Graduate School of Medicine, Osaka Metropolitan University, 1-4-3 Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan.
- Smart Data and Knowledge Services Department, German Research Center for Artificial Intelligence (DFKI GmbH), 67663, Kaiserslautern, Germany.
- Department of Innovative BioMedical Visualization, Nagoya University Graduate School of Medicine, Showa-ku, Nagoya, Japan.
- Department of Radiology, Keio University School of Medicine, Shinjukuku, Tokyo, Japan.
- Department of Diagnostic Radiology, Kumamoto University Graduate School of Medicine, Chuo-ku, Kumamoto, Japan.
- Medical AI Promotion Institute Co., Ltd., Life Science Building, 12-9 Nihonbashi Odemmachi, Chuo-ku, Tokyo, Japan. [email protected].
- Department of Artificial Intelligence, Graduate School of Medicine, Osaka Metropolitan University, Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan. [email protected].
- Center for Health Science Innovation, Osaka Metropolitan University, Asahi-machi, Abeno-ku, Osaka, 545-8585, Japan. [email protected].
Abstract
The integration of artificial intelligence (AI) in radiology has accelerated globally, with Japan’s Pharmaceuticals and Medical Devices Agency (PMDA) approving numerous AI-based Software as a Medical Device (SaMD) products. However, the transparency and completeness of clinical evidence available to healthcare providers remain unclear. To systematically evaluate the availability and transparency of clinical evidence in package inserts of PMDA-approved AI-based radiology SaMD products, identifying gaps that may impact clinical implementation. We conducted a scoping review of all PMDA-approved SaMD products as of December 31, 2024. Products were included if they utilized AI technology and were classified for radiology applications. Data extraction focused on product characteristics, study designs, demographic information, and performance metrics. Of 151 approved SaMD products, 40 utilized AI technology, with 20 specifically designed for radiology applications. Critical gaps were identified in demographic reporting, with no products providing complete case demographic data. Performance metrics varied widely, with sensitivity ranging from 67.7% to 100% in standalone studies. Physician-assisted studies consistently demonstrated performance improvements but lacked stratified results by characteristics in all cases. Current package insert requirements provide insufficient transparency for evidence-based clinical implementation of AI-based radiology SaMD. Enhanced regulatory frameworks and industry-led initiatives for comprehensive validation are essential for safe and effective AI deployment in Japanese healthcare.