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

IF 2.7 Q3 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY
Easan Anand, Itai Ghersin, Gita Lingam, Theo Pelly, Daniel Singer, Chris Tomlinson, Robin E J Munro, Rachel Capstick, Anna Antoniou, Ailsa L Hart, Phil Tozer, Kapil Sahnan, Phillip Lung
{"title":"AI-Generated Patient-Friendly MRI Fistula Summaries: A Pilot Randomised Study.","authors":"Easan Anand, Itai Ghersin, Gita Lingam, Theo Pelly, Daniel Singer, Chris Tomlinson, Robin E J Munro, Rachel Capstick, Anna Antoniou, Ailsa L Hart, Phil Tozer, Kapil Sahnan, Phillip Lung","doi":"10.3390/jimaging11090302","DOIUrl":null,"url":null,"abstract":"<p><p>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, <i>p =</i> 0.011), comprehensibility (5 vs. 2, <i>p =</i> 0.007), utility (5 vs. 3, <i>p =</i> 0.014), and overall quality (4.5 vs. 4, <i>p =</i> 0.013), with fewer follow-up questions (3 vs. 4, <i>p =</i> 0.018). Clinicians found AI summaries more readable (mean Flesch-Kincaid 54.6 vs. 32.2, <i>p =</i> 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.</p>","PeriodicalId":37035,"journal":{"name":"Journal of Imaging","volume":"11 9","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12471112/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/jimaging11090302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY","Score":null,"Total":0}
引用次数: 0

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.

人工智能生成的患者友好型MRI瘘总结:一项随机试验研究。
肛周瘘管性克罗恩病(pfCD)影响1 / 5的克罗恩病患者,需要频繁的MRI监测。标准放射学报告是为临床医生编写的,使用的技术语言往往是患者无法理解的,这可能会导致焦虑并阻碍参与。本研究评估了人工智能生成的患者友好型MRI瘘总结的可行性和安全性,以提高患者的理解和共同决策。从愈合到复杂疾病的MRI瘘报告被识别出来,并通过ChatGPT-4生成人工智能患者友好摘要。临床医生评估六份去识别的MRI报告和相应的AI摘要的幻觉和可读性(Flesch-Kincaid评分)。16例肛周瘘管患者被随机分为人工智能摘要或原始报告两组,并使用李克特量表对其可读性、可理解性、实用性、质量、随访问题和可信度进行评分。患者对AI摘要的评价在可读性(中位数为5比2,p = 0.011)、可理解性(中位数为5比2,p = 0.007)、实用性(中位数为5比3,p = 0.014)和整体质量(中位数为4.5比4,p = 0.013)方面显著提高,随访问题较少(中位数为3比4,p = 0.018)。临床医生发现人工智能总结更具可读性(Flesch-Kincaid平均值为54.6比32.2,p = 0.005),并且没有幻觉。未发现有临床意义的不准确。人工智能生成的患者友好型MRI摘要具有增强pfCD患者沟通和临床工作流程的潜力。需要更大规模的研究来验证临床效用、幻觉率和可接受性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Imaging
Journal of Imaging Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.90
自引率
6.20%
发文量
303
审稿时长
7 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信