AI辅助有丝分裂计数提高多种肿瘤类型的可重复性和效率

中文摘要 AI 辅助

有丝分裂计数是多种肿瘤类型中肿瘤分级、诊断和预后评估的重要组成部分，但人工评估耗时且受病理学家间差异影响。为帮助解决这些挑战，我们开发了MitPro，一种AI工具，旨在通过引导病理学家关注预测有丝分裂活性最高的区域并高亮显示有丝分裂图像以供审查，同时保留病理学家对区域选择和最终计数的控制，来提高一致性和效率。我们在一项回顾性、非干预性、配对阅读者研究中评估了其对有丝分裂计数可重复性和效率的影响，该研究包含来自3个国家3个中心的385张全切片图像，涉及7种肿瘤类型，使用3种不同扫描仪。13名病理学家参与，每张切片由3名病理学家在无AI辅助下独立评估，并在至少2周洗脱期后再次在AI辅助下评估。在所有切片中，AI辅助计数将组内相关系数从0.589提高到0.949。病理学家层面的中位评估时间从286.4秒降至127.8秒，相当于每次评估平均节省151.8秒。在使用HALO AP和Sectra图像管理系统的支持性分析以及主要研究人群之外的2种额外肿瘤类型中，也观察到一致性和效率的改善。AI辅助评估与有丝分裂计数和评分向更高值的轻微转变相关，这与识别出更多活跃的有丝分裂热点和更少遗漏的有丝分裂图像一致。无辅助和AI辅助评估之间评分变化的频率与常规计数中病理学家间差异相当。这些发现支持MitPro作为辅助工具，在常规实践中实现更一致和高效的有丝分裂评估。

英文摘要

Mitotic counting is an important component of tumour grading, diagnosis and prognostic assessment across several tumour types, but manual assessment is time-consuming and subject to inter-pathologist variability. To help address these challenges, we developed MitPro, an AI tool designed to improve consistency and efficiency by directing pathologists towards regions with the highest predicted mitotic activity and highlighting mitotic figures for review, while retaining pathologist control over region selection and the final count. We evaluated its effect on the reproducibility and efficiency of mitotic counting in a retrospective, non-interventional, paired reader study comprising 385 whole-slide images from 3 centres in 3 countries and 7 tumour types using 3 different scanners. 13 pathologists participated, with each slide assessed independently by 3 pathologists without AI assistance and again with AI assistance after a minimum 2 week washout period. Across all slides, AI-assisted counting increased the intraclass correlation coefficient from 0.589 to 0.949. Mean pathologist-level median assessment time decreased from 286.4 to 127.8 seconds, corresponding to an average saving of 151.8 seconds per assessment. Improvements in agreement and efficiency were also observed in supporting analyses using HALO AP and Sectra image management systems and in 2 additional tumour types outside the main study population. AI-assisted assessment was associated with a subtle shift towards higher mitotic counts and scores, consistent with identification of more active mitotic hotspots and fewer missed mitotic figures. The frequency of score change between unassisted and AI-assisted assessment was comparable with inter-pathologist variation during routine counting. These findings support the use of MitPro as an assistive tool for more consistent and efficient mitotic assessment in routine practice.

发表机构

• AI-assisted mitotic counting improves reproducibility and efficiency across multiple tumour types（中文机构名）

机构由 AI 辅助整理，请以论文原文为准。