Clinical use of artificial intelligence in radiology departments in the Netherlands: a survey

K. van Leeuwen, M. Rutten, S. Schalekamp, M. de Rooij and B. van Ginneken

European Congress of Radiology 2021.

Purpose: There are over 150 artificial intelligence (AI) products for radiology offered, but little is known about their current clinical use. We investigated actual clinical use of AI software in radiology departments in the Netherlands.

Materials and Methods: We consulted the radiology department of each hospital organization in the Netherlands (n=70) about their current AI implementations and plans from February-March 2020. A representative of the department was asked to fill in a questionnaire about their knowledge, experience, research and/or clinical use of commercially available CE-certified AI products for radiology (n=93). Responses for these familiarity-levels were analysed to create an overview with quantitative metrics.

Results: The response rate of the consulted hospitals was 43/70: 38/62 for general hospitals, 5/7 for academic medical centers, and 0/1 for children’s hospitals. Of the respondents 30 (70%) were radiologists, 5 (12%) application or information managers, and 8 (19%), among others, clinical physicists and managers. A third (14) of the participating organizations had one to three AI applications in clinical use, with a total of 19 implementations. These implementations involved eight different vendors of which four were from the Netherlands. Most commonly used was software for bone age prediction and stroke detection. Respondents were most familiar with products aimed at neurology and cardiology. MR, CT and mammography were the most familiar modalities for AI. Most interest for clinical implementation was shown in software to triage exams. Eleven organizations (26%) had a dedicated budget for AI, either from the hospital or the department.

Conclusion: Even though the supply of AI software is extensive, clinical use remains limited showing that we are still in the initial stages of integrating AI in clinical practice in the Netherlands.

Limitations: Results may be influenced by a nonresponse bias.