Comparison of the Diagnostic Reliability of ChatGPT in Letournel-Judet Acetabulum Fracture Classification Based on Judet Radiographs According to Orthopaedic Residents
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 184
- 试验地点
- 1
- 主要终点
- Diagnostic Accuracy of ChatGPT-4o in Acetabular Fracture Classification.
研究概览
简要总结
This study aims to evaluate the diagnostic reliability of the multimodal artificial intelligence model ChatGPT-4o in classifying acetabular fractures using the Letournel-Judet classification system. The study retrospectively analyzed standardized pelvic radiographs (anteroposterior, iliac oblique, and obturator oblique) from 184 patients presenting with pelvic injuries. The diagnostic performance of ChatGPT-4o was compared against the independent assessments of two fourth-year orthopaedic residents and a reference standard established by an experienced trauma surgeon using multiplanar computed tomography (CT) and intraoperative findings. By utilizing a systematic radiographic checklist, the study assesses the AI (artificial intelligence) model's ability to identify key anatomical landmarks and integrate them into a final fracture pattern. This research aims to provide critical data on the current feasibility of using large language models as decision-support tools in complex orthopaedic trauma.
详细描述
This retrospective observational study was conducted at Ankara Bilkent City Hospital to investigate the diagnostic accuracy of ChatGPT-4o in complex acetabular fracture classification. Imaging data included anonymized anteroposterior, iliac oblique, and obturator oblique radiographs from 184 patients.After approval from the Institutional Review Board, the investigators retrospectively analyzed patients presenting with pelvic injuries and undergoing surgical treatment at our center. Patients with pelvic injuries but with non-acetabular fractures, those with incomplete imaging, those with poor radiographic quality or those who had previously undergone pelvic surgery or trauma were excluded.
Assessment Protocol
Imaging from cases presenting with pelvic injuries and undergoing surgical treatment at our center was selected from the institution's radiology archive. Standard anteroposterior pelvic, iliac oblique and obturator oblique radiographs were collected for each case.
The article "Acetabular Fractures: Easier Classification with a Systematic Approach" by Brandser and Marsh was uploaded to Chat GPT. The prompt used when evaluating the cases was as follows: "In these AP pelvic, iliac oblique, and obturator oblique radiographs, identify the acetabulum fracture as defined by Judet, using the systematic approach in the provided article and answering each question on the radiological checklist individually." Each case was evaluated using the same prompt previously defined. Chat GPT was asked to answer each question individually based on the systematic approach defined in the article and ultimately indicate the type of fracture.These questions were designed to evaluate key radiographic landmarks and fracture components including:
Is there a fracture of the obturator ring? Is the ilioischial line disrupted? Is the iliopectineal line disrupted? Is there a fracture of the iliac wing? Is there a fracture of posterior wall? Does the fracture divide the acetabulum into top and bottom halves or front and back halves? Is there a spur sign?
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients older than 18 years old and presenting with pelvic injuries and undergoing surgical treatment.
排除标准
- •Patients with pelvic injuries but with non-acetabular fractures, those with incomplete imaging, those with poor radiographic quality or those who had previously undergone pelvic surgery or trauma were excluded.
研究组 & 干预措施
Acetabular Fracture Cases
Retrospective cohort of 184 patients presenting with pelvic injuries who underwent surgical treatment and had standardized Judet radiographs available for analysis
干预措施: Diagnostic Assessment by ChatGPT-4o (Other)
结局指标
主要结局
Diagnostic Accuracy of ChatGPT-4o in Acetabular Fracture Classification.
时间窗: Through study completion
The diagnostic accuracy is defined as the proportion of correctly classified acetabular fractures by ChatGPT-4o compared to the reference standard (determined by 3D CT and intraoperative findings).
次要结局
- Interobserver Agreement (Cohen's Kappa)(Through study completion)
- Systematic Radiographic Checklist Accuracy(Through study completion)
研究者
muhammed kılıç
Principal Investigator, Orthopaedic Surgery Resident
Ankara City Hospital Bilkent