AI Revolutionizes Patient Understanding of CT Reports

Technical University of Munich researchers found that AI-simplified CT reports substantially shortened reading time and improved comprehension and perceived helpfulness for patients with cancer.

In a prospective, controlled trial of 200 patients with cancer, AI-generated simplified report text reduced average reading time from seven minutes to two minutes and produced large increases in ease of understanding and perceived helpfulness.

The research reported a 6% inaccuracy rate in AI-generated findings; outputs were reviewed and corrected by clinicians before release.

However, implementation barriers include integrating simplified outputs with electronic health records, managing consent and data flows, and completing vendor and local model validation. Practical mitigations noted by the investigators and commentators include maintaining audit logs, validating models locally, requiring clinician sign-off on corrections, documenting patient consent, and establishing clear governance—steps that preserve benefits while managing risk.

Key Takeaways:

• A prospective trial of 200 patients showed a marked reduction in patient reading time and large gains in comprehension and perceived helpfulness when CT reports were simplified by AI and reviewed by clinicians.
• Patients with cancer, radiology teams, and cancer care coordinators — simplified reports can be offered as an adjunct immediately after clinician review to improve patient understanding.
• Verification should include documented accuracy checks and corrections, recorded privacy consent, EHR integration with audit logs, and vendor/local model validation to preserve benefits while mitigating risk.