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病理学家对肿瘤细胞分数的计算机辅助诊断评分:瑞士国家研究。

Pathologist Computer-Aided Diagnostic Scoring of Tumor Cell Fraction: A Swiss National Study.

机构信息

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

Institute for Tissue Medicine and Pathology, University of Bern, Bern, Switzerland.

出版信息

Mod Pathol. 2023 Dec;36(12):100335. doi: 10.1016/j.modpat.2023.100335. Epub 2023 Sep 22.

Abstract

Tumor cell fraction (TCF) estimation is a common clinical task with well-established large interobserver variability. It thus provides an ideal test bed to evaluate potential impacts of employing a tumor cell fraction computer-aided diagnostic (TCFCAD) tool to support pathologists' evaluation. During a National Slide Seminar event, pathologists (n = 69) were asked to visually estimate TCF in 10 regions of interest (ROIs) from hematoxylin and eosin colorectal cancer images intentionally curated for diverse tissue compositions, cellularity, and stain intensities. Next, they re-evaluated the same ROIs while being provided a TCFCAD-created overlay highlighting predicted tumor vs nontumor cells, together with the corresponding TCF percentage. Participants also reported confidence levels in their assessments using a 5-tier scale, indicating no confidence to high confidence, respectively. The TCF ground truth (GT) was defined by manual cell-counting by experts. When assisted, interobserver variability significantly decreased, showing estimates converging to the GT. This improvement remained even when TCFCAD predictions deviated slightly from the GT. The standard deviation (SD) of the estimated TCF to the GT across ROIs was 9.9% vs 5.8% with TCFCAD (P < .0001). The intraclass correlation coefficient increased from 0.8 to 0.93 (95% CI, 0.65-0.93 vs 0.86-0.98), and pathologists stated feeling more confident when aided (3.67 ± 0.81 vs 4.17 ± 0.82 with the computer-aided diagnostic [CAD] tool). TCFCAD estimation support demonstrated improved scoring accuracy, interpathologist agreement, and scoring confidence. Interestingly, pathologists also expressed more willingness to use such a CAD tool at the end of the survey, highlighting the importance of training/education to increase adoption of CAD systems.

摘要

肿瘤细胞分数 (TCF) 估计是一项常见的临床任务,观察者间差异很大。因此,它为评估使用肿瘤细胞分数计算机辅助诊断 (TCFCAD) 工具辅助病理学家评估的潜在影响提供了一个理想的测试平台。在一次全国幻灯片研讨会上,病理学家(n=69)被要求在 10 个感兴趣区域 (ROI) 中通过视觉评估苏木精和伊红结直肠癌图像的 TCF,这些 ROI 是为了具有不同的组织成分、细胞密度和染色强度而精心挑选的。接下来,他们在提供 TCFCAD 创建的叠加层的情况下重新评估相同的 ROI,该叠加层突出显示预测的肿瘤与非肿瘤细胞,以及相应的 TCF 百分比。参与者还使用 5 级量表报告他们评估的置信度,分别表示无置信度到高置信度。TCF 地面实况 (GT) 通过专家手动细胞计数定义。当辅助时,观察者间差异显著减小,估计值收敛到 GT。即使 TCFCAD 预测与 GT 略有偏差,这种改进仍然存在。ROI 之间估计的 TCF 与 GT 的标准偏差 (SD) 为 9.9% 与 TCFCAD(P<0.0001)。TCFCAD 时,组内相关系数从 0.8 增加到 0.93(95%CI,0.65-0.93 与 0.86-0.98),并且当辅助时,病理学家表示更有信心(使用计算机辅助诊断 [CAD] 工具时为 3.67±0.81 与 4.17±0.82)。TCFCAD 估计支持提高了评分准确性、病理学家间一致性和评分信心。有趣的是,在调查结束时,病理学家也表示更愿意使用这种 CAD 工具,这突显了培训/教育的重要性,以增加 CAD 系统的采用。

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