人工智能辅助胃肠道内窥镜活检组织学诊断日常质量控制系统:一年的经验。

Seung-Yeon Yoo, Yuri Hwang, Seokju Yun, Ok Hee Lee, Jiwook Jang, Youngjin Park, Tae Young Cho, Young Sin Ko
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引用次数: 0

摘要

背景Seegene 医疗基金会是韩国主要的临床实验室之一,它开发了基于人工智能(AI)的分析后日常质量控制(QC)系统 SeeDP,该系统可重新评估所有胃肠道(GI)内窥镜活检(EB)切片的错误诊断:回顾 SeeDP 自 2022 年 3 月启动以来的运行记录和临床影响:检索了2022年3月1日至2023年2月28日期间SeeDP的运行记录。在 40 个工作日(2022 年 3 月 10 日至 2022 年 5 月 4 日)内扫描的病例中,对 2 名病理学家遇到的所有不一致病例进行了审查。收集 SeeDP 辅助修订诊断的病例,并与使用传统方法确认的病例进行比较:扫描仪偶发故障和各种类型的异常错误影响了质控覆盖率,导致提交的所有 EB 切片中仅有 67.7%(844 906 张中的 572 254 张)被扫描,0.8% 的扫描切片被进一步排除在人工智能分析之外。在人工智能模型成功评估的 557 672 张胃肠道 EB 病理切片中,有 42 760 张(7.7%)的人工智能预测与病理学家的诊断存在差异;然而,对不一致病理切片的详细审查显示,真正的误诊仅占不一致病理切片的 5.5%(454 张中的 25 张)。与传统的错误识别方法相比,SeeDP 在更短的时间内(平均 3.6 天对 38.7 天;P < .001)发现了更多的误诊(7 例对 14 例),其中包括 1 例最初诊断为胃炎的印戒细胞癌:基于人工智能的日常质控系统能够快速检测和纠正误诊,是保证高质量病理诊断的可行解决方案。
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Artificial Intelligence-Assisted Daily Quality Control System for the Histologic Diagnosis of Gastrointestinal Endoscopic Biopsies: A 1-Year Experience.

Context.—: Seegene Medical Foundation, one of the major clinical laboratories in South Korea, developed SeeDP, an artificial intelligence (AI)-based postanalytic daily quality control (QC) system that reassesses all gastrointestinal (GI) endoscopic biopsy (EB) slides for incorrect diagnoses.

Objective.—: To review the operational records and clinical impact of SeeDP since its launch in March 2022.

Design.—: Operational records of SeeDP were retrieved for the period of March 1, 2022, to February 28, 2023. Among cases scanned during 40 working days (March 10, 2022, to May 4, 2022), all discordant cases encountered by 2 pathologists were reviewed. Cases of SeeDP-assisted revised diagnoses were collected and compared with cases recognized using conventional methods.

Results.—: Occasional scanner failures and various types of aberrant errors compromised QC coverage, resulting in the scanning of only 67.7% (572 254 of 844 906) of all EB slides submitted and 0.8% of the scanned slides being further excluded from the AI analysis. The AI predictions differed from the pathologists' diagnoses in 42 760 of the 557 672 gastrointestinal EB slides (7.7%) successfully assessed by the AI models; however, a detailed review of discordant slides revealed that true misdiagnosis accounted for only 5.5% (25 of 454) of the disagreements. Compared with conventional error recognition methods, SeeDP detected more misdiagnoses (7 versus 14) within a significantly shorter time (average, 3.6 versus 38.7 days; P < .001), including 1 signet ring cell carcinoma initially diagnosed as gastritis.

Conclusions.—: AI-based daily QC systems are plausible solutions to guarantee high-quality pathologic diagnosis by enabling rapid detection and correction of misdiagnosis.

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