How study design choices inflate AI performance in prostate MRI cancer detection

Apparent near-perfect AI performance for prostate cancer detection on MRI may stem from study design flaws—spectrum bias, pathway bias, imperfect reference standards—rather than genuine technical progress, a structured appraisal warns.

• Six appraisal domains defined: limits of predictability, reference standard quality, cohort design, benchmark validity, clinical deployment, and AI terminology.
• Spectrum bias (cancer prevalence), pathway bias (patient selection), and imperfect reference standards can falsely elevate reported accuracy.
• Adopt structured criteria from PI-RADS Steering Committee to distinguish tools with real-world generalizability from those whose performance is inflated by design.

Automated summary

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