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September 10, 2025Journal of Imaging2 citationsOpen Access

AI-Generated Patient-Friendly MRI Fistula Summaries: A Pilot Randomised Study

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EAEasan AnandIGItai GhersinGLGita Lingam

Key Points

  • AI-generated summaries significantly improved readability, with median scores of 5 compared to 2 for original reports.
  • Patients rated AI summaries higher in comprehensibility (5 vs. 2) and utility (5 vs. 3), indicating a profound impact on understanding.
  • Clinicians found AI summaries more readable, scoring an average Flesch-Kincaid readability of 54.6 versus 32.2 for traditional reports.
  • AI-generated patient-friendly MRI summaries may enhance communication and workflow in managing perianal fistulising Crohn’s disease.

Abstract

Perianal fistulising Crohn’s disease (pfCD) affects 1 in 5 Crohn’s patients and requires frequent MRI monitoring. Standard radiology reports are written for clinicians using technical language often inaccessible to patients, which can cause anxiety and hinder engagement. This study evaluates the feasibility and safety of AI-generated patient-friendly MRI fistula summaries to improve patient understanding and shared decision-making. MRI fistula reports spanning healed to complex disease were identified and used to generate AI patient-friendly summaries via ChatGPT-4. Six de-identified MRI reports and corresponding AI summaries were assessed by clinicians for hallucinations and readability (Flesch-Kincaid score). Sixteen patients with perianal fistulas were randomized to review either AI summaries or original reports and rated them on readability, comprehensibility, utility, quality, follow-up questions, and trustworthiness using Likert scales. Patients rated AI summaries significantly higher in readability (median 5 vs. 2, p = 0.011), comprehensibility (5 vs. 2, p = 0.007), utility (5 vs. 3, p = 0.014), and overall quality (4.5 vs. 4, p = 0.013), with fewer follow-up questions (3 vs. 4, p = 0.018). Clinicians found AI summaries more readable (mean Flesch-Kincaid 54.6 vs. 32.2, p = 0.005) and free of hallucinations. No clinically significant inaccuracies were identified. AI-generated patient-friendly MRI summaries have potential to enhance patient communication and clinical workflow in pfCD. Larger studies are needed to validate clinical utility, hallucination rates, and acceptability.

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Cite This Study

Anand et al. (2025) studied this question.

synapsesocial.com/papers/68c189d99b7b07f3a06135e8https://doi.org/10.3390/jimaging11090302
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