ROECSG report: Real-world implementation patterns and perceptions of artificial intelligence in radiation oncology

Purpose

While international surveys have examined radiation oncology professionals' attitudes toward artificial intelligence (AI) and documented generally low early utilization, actual implementation patterns and the depth of integration among engaged practitioners remain unclear. This multi-institutional survey aims to characterize current AI implementation, identify critical barriers to optimization, and evaluate the psychological factors driving clinical trust. Methods and materials: A de-identified survey covering six domains was developed by a multi-institutional working group and distributed via a widely subscribed medical physics listserv and at the 2025 American Association of Physicists in Medicine (AAPM) Annual Meeting. The instrument assessed adoption rates, specific workflow applications, and user perceptions (trust and understanding) using 6-point Likert scales to reduce central tendency bias. Quantitative data were analyzed using Pearson correlation coefficients and Welch's two-sample t-tests, while qualitative responses underwent inductive thematic analysis (κ = 0.78).