计算机辅助息肉特征增强结肠镜检查研究：比较实习医生与无人工智能辅助的专家光学诊断诊断可靠性的前瞻性研究。

The Augmented Colonoscopy With Computer-Aided Polyp Characterization Study: Prospective Study Comparing the Diagnostic Reliability of Optical Diagnosis of Trainees With Experts Without Artificial Intelligence.

作者信息

Bernhofer Sebastian, Prosenz Julian, Duller Christine, Venturi David, Maieron Andreas

机构信息

Gastrointestinal Endoscopy Quality Matters Working Group (GIEQM), Karl Landsteiner University of Health Sciences, Krems, Austria.

Department of Internal Medicine 2 Gastroenterology & Hepatology, University Hospital St. Pölten, St. Pölten, Austria.

出版信息

Am J Gastroenterol. 2025 May 28. doi: 10.14309/ajg.0000000000003558.

DOI:10.14309/ajg.0000000000003558

PMID:40434246

Abstract

INTRODUCTION

Optical diagnosis (OD) is an essential part of a high-quality colonoscopy, but highly experience-dependent. Artificial intelligence (AI) in the form of computer-aided diagnosis (CADx) may bridge the gap between trainee endoscopists and experts. The aim of this study was to evaluate the diagnostic reliability of OD of trainee endoscopists with the help of AI compared with experts.

METHODS

This prospective, observational study included patients undergoing trainee-performed CADx-supported (GI Genius) colonoscopy. Resected polyps were recorded and video-reviewed without CADx information by experts. The primary outcome was the negative predictive value (NPV) for adenomatous histology of diminutive (≤5 mm) rectosigmoid polyps of trainees vs experts and CADx output alone. Secondary outcomes were the NPV for rectosigmoid polyps of any size and sensitivities and specificities of adenomas in the entire colon.

RESULTS

Overall, 630 polyps were resected in 225 patients (48.9% male, mean age 63.8 (SD 12.7) years). In the rectosigmoid, 252 lesions (40%) were found, 223 (88.5%) of which were ≤5 mm. The NPV for diminutive rectosigmoid polyps of trainees using CADx was 90.2% (95% confidence interval [CI] 0.85-0.94), NPV of the experts without CADx was 90.3% (95% CI 0.84-0.94). There was no statistically significant difference in NPV between these 2 groups. The NPV of CADx alone was 93.2% (95% CI 0.88-0.97). The NPV for rectosigmoid polyps of any sizes were 90.1% (95% CI 0.85-0.94) for trainees, 90.4% (95% CI 0.85-0.95) for experts, and 93.4% (95% CI 0.88-0.97) for CADx alone.

DISCUSSION

OD of rectosigmoid polyps by trainee endoscopists with CADx is highly accurate, fulfilling PIVI 2 "diagnose-and-leave" strategy.

摘要

引言

光学诊断（OD）是高质量结肠镜检查的重要组成部分，但高度依赖经验。计算机辅助诊断（CADx）形式的人工智能（AI）可能会弥合实习内镜医师与专家之间的差距。本研究的目的是评估在AI帮助下实习内镜医师与专家相比OD的诊断可靠性。

方法

这项前瞻性观察性研究纳入了接受实习医师进行的CADx支持（GI Genius）结肠镜检查的患者。记录切除的息肉，并由专家在不参考CADx信息的情况下对视频进行复查。主要结局是实习生与专家以及仅CADx输出的微小（≤5mm）直肠乙状结肠息肉腺瘤组织学的阴性预测值（NPV）。次要结局是任何大小的直肠乙状结肠息肉的NPV以及整个结肠腺瘤的敏感性和特异性。

结果

总体而言，225例患者共切除630个息肉（男性占48.9%，平均年龄63.8（标准差12.7）岁）。在直肠乙状结肠中发现252个病变（40%），其中223个（88.5%）≤5mm。使用CADx的实习生微小直肠乙状结肠息肉的NPV为90.2%（95%置信区间[CI]0.85 - 0.94），未使用CADx的专家的NPV为90.3%（95%CI 0.84 - 0.94）。这两组之间的NPV无统计学显著差异。仅CADx的NPV为93.2%（95%CI 0.88 - 0.97）。实习生任何大小直肠乙状结肠息肉的NPV为90.1%（95%CI 0.85 - 0.94），专家为90.4%（95%CI 0.85 - 0.95），仅CADx为93.4%（95%CI 0.88 - 0.97）。