GPT-4用于基于临床常规中的放射学请求表单的MRI协议的自动序列级确定
Robert Terzis1, Kenan Kaya2, Thomas Schömig2
1Institute for Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany. robert.terzis@uk-koeln.de.
European radiology
|August 8, 2025
概括
在选择MRI序列方面,GPT-4的准确性与较少经验的住院医生相美,具有很高的临床适用性. 然而,它在各个子专业的表现不同,在心脏和神经放射学方面表现出色,但在肌肉骨成像方面落后.
科学领域:
- 医疗成像中的人工智能
- 放射学工作流的优化 工作流的优化
- 机器学习用于诊断成像.
背景情况:
- 精确的磁共振成像 (MRI) 协议选择对于有效的诊断至关重要,但它耗时且容易出现错误,特别是对于经验较少的放射科医生来说.
- 长时间的MRI采集时间可能会限制患者的访问,强调需要优化协议选择流程.
研究的目的:
- 评估GPT-4在根据放射学请求表格 (RRF) 选择MRI序列时的准确性.
- 为了比较GPT-4在MRI协议选择中的性能,与具有不同经验水平的放射科医生进行对比.
- 评估GPT-4产生的MRI协议的临床适用性和质量.
主要方法:
- 一项回顾性研究涉及100个RRF跨心脏成像,神经放射学,肌肉骨和瘤学子专业.
- GPT-4和两个放射科住院医生 (R1: 2年,R2: 5年MRI经验) 独立选择了MRI序列.
- 五名专业放射科医生通过使用利克特尺度对协议的完整性,质量和实用性进行了评估,主要放射科医生对临床适用性进行了评估.
主要成果:
- 在总体协议质量和实用性方面,GPT-4的得分与R1居民的得分相当,但在总体协议质量和实用性方面却低于R2居民.
- 协议质量因子专业而异:GPT-4在心脏和瘤学中表现相对较好,在神经放射学中没有差异,但在肌肉骨成像中得分较低.
- 基于GPT-4的协议显示出高临床适用性 (95%),类似于居民 (95-96%).
结论:
- GPT-4可以生成具有显著完整性,质量,实用性和临床适用性的MRI协议.
- 大型语言模型显示出作为帮助放射科医生,特别是经验较少的放射科医生,优化MRI协议选择和提高诊断效率的工具的潜力.
- 虽然在标准化子专业有效,但GPT-4在肌肉骨成像中的准确性需要进一步改进.
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