LLM-Generated Lay Summaries for Brain MRI Reports (CLEAR-HEAD)

The goal of this clinical trial is to learn if a summary written by artificial intelligence (AI) helps adults understand brain MRI reports for headaches. The main question it aims to answer is: "Does adding a simple summary help readers correctly understand if a cause for the headache was found in the report?" Researchers will compare standard MRI reports to reports that include an AI-generated explanation to see if the extra summary improves understanding.

Participants will:

Read 6 fictional brain MRI reports online. Answer questions to check if they understood the results. Rate their satisfaction and if they feel they would need to ask a doctor for help.

Study Overview

• Status: Completed
• Conditions: Headache
• Intervention / Treatment: Other: LLM-generated lay summary

Detailed Description

Background Headaches account for approximately 2% to 4% of emergency department visits, representing about 450,000 consultations annually in France. While 95% of these cases are benign primary headaches, identifying secondary causes requiring urgent management is critical, often leading to increased use of neuroimaging such as MRI. However, radiology reports often contain complex medical jargon that can be difficult for patients and non-specialist physicians to understand, potentially causing confusion or anxiety. Large Language Models (LLMs) have demonstrated the potential to simplify complex medical text. While commercial models exist, open-weights models (which can be deployed locally to ensure data security) offer a promising avenue for clinical integration. This study aims to evaluate the efficacy of an AI-generated plain-language summary in improving patient understanding of brain MRI reports.

Study Design This is a randomized, controlled, single-blind trial nested within the COMPARE e-cohort. The study uses a parallel-group design with a 1:1 allocation ratio. The entire study is conducted remotely via secure online forms.

Participants The study recruits adult volunteers already enrolled in the COMPARE e-cohort. Participants must have sufficient proficiency in written French to read the reports and complete the questionnaires. No specific medical condition is required for inclusion, as the study uses fictional case scenarios.

Intervention and Procedures Participants are randomized to one of two groups via a minimization procedure balancing history of brain MRI and known neurological pathology. Each participant is asked to read six fictional brain MRI reports simulating common emergency headache scenarios. The six reports cover three clinical situations: two with normal results, two with incidental findings not explaining the headache, and two with abnormalities explaining the headache. In the experimental group, participants receive the standard MRI report enriched with a structured summary paragraph generated by an open-weights LLM, inserted under the section Synthesis for the patient and non-radiologist physician. In the control group, participants receive the standard MRI report in its native version without the AI-generated summary.

Outcome Measures Immediately after reading each report, participants complete a standardized questionnaire. The primary outcome is the comprehension of the report, measured by the accuracy of the response to the binary question: Is a probable explanation for the headache found in this report? Secondary outcomes include participant satisfaction measured on a Likert scale, perceived need for professional clarification, perceived ability to explain results to a relative, and projected anxiety levels.

Statistical Analysis The primary analysis will compare the proportion of correct responses between groups using a mixed logistic regression model. This model will include the intervention group as a fixed effect and account for crossed random effects (participant and report) to manage intra-individual correlation and variability between clinical cases. The sample size is calculated to be 412 participants (206 per group) to detect a 10% difference in understanding with 95% power.

• Study Type: Interventional
• Enrollment (Actual): 2727
• Phase: Not Applicable

Contacts and Locations

Study Locations

• France
  • Lille, France, 59000
    • Lille University Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Participants of the COMPARE e-cohort

Exclusion Criteria:

• None

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Original MRI reports
Experimental: LLM-generated summaries in addition to the original reports	Other: LLM-generated lay summary; Participants assigned to this group read fictional brain MRI reports that include an additional summary paragraph generated by an artificial intelligence tool. Specifically, an open-weights Large Language Model (LLM) with fewer than 100 billion parameters is used, hosted locally on a secure server to ensure data privacy. This model generates a short synthesis designed to be clear and structured for non-medical readers. This summary is inserted into the report under the heading Synthesis intended for the patient and non-radiologist physician. The intervention consists solely of this added text; the standard medical content of the report remains unchanged.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Objective understanding of the report	Assessment of the participant's ability to correctly understand the medical findings. After reading each of the six fictional brain MRI reports, participants answer the binary question: "Is a probable explanation for the headache found in this report?" (Yes/No). The outcome is calculated as the proportion of correct responses compared to the ground truth of the specific clinical scenario (normal, incidental finding, or explanatory abnormality).	Through completion of each response, an average of 5 minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Self-reported understanding score	Participants rate the the clarity of the MRI report using a 5-point Likert scale (ranging from 1 to 5), where higher scores indicate higher satisfaction.	Through completion of each response, an average of 5 minutes
Perceived need for professional clarification	Participants respond to a binary question asking if they would feel the need to contact a healthcare professional to better understand the report: "Would you like to ask a healthcare professional questions to better understand this report?" (Yes/No).	Through completion of each response, an average of 5 minutes
Perceived ability to explain results to a relative	Participants rate their perceived ability to rephrase and explain the medical results to a close relative using a 5-point Likert scale (ranging from 1 to 5), where higher scores indicate a higher perceived capability.	Through completion of each response, an average of 5 minutes

Collaborators and Investigators

• Sponsor: University Hospital, Lille
• Collaborators: Direction Générale de l'Offre de Soins

Study record dates

Study Major Dates

• Study Start (Actual): March 25, 2026
• Primary Completion (Actual): April 30, 2026
• Study Completion (Actual): April 30, 2026

Study Registration Dates

• First Submitted: November 28, 2025
• First Submitted That Met QC Criteria: December 15, 2025
• First Posted (Actual): December 30, 2025

Study Record Updates

• Last Update Posted (Actual): May 13, 2026
• Last Update Submitted That Met QC Criteria: May 12, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: MRI; headache; LLM; Large Language Model; lay summary
• Additional Relevant MeSH Terms: Pain; Neurologic Manifestations; Pathological Conditions, Signs and Symptoms; Signs and Symptoms; Headache
• Other Study ID Numbers: 2025-3783

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No