Background Technological advances constantly provide cutting-edge tools that enhance the progress of diagnostic capabilities. Gastrointestinal stromal tumors belong to a family of mesenchymal tumors where patient triaging is still based on traditional criteria such as mitotic count, tumor size, and tumor location. Limitations of the human eye and randomness in choice of area for mitotic figure counting compel us to seek more objective solutions such as digital image analysis. Presently, the labelling of proliferative activity is becoming a routine task amidst many cancers. The purpose of the present study was to compare the traditional method of prediction based on mitotic ratio with digital image analysis of cell cycle-dependent proteins. Methods Fifty-seven eligible cases were enrolled. Furthermore, a digital analysis of previously performed whole tissue section immunohistochemical assays was executed. Digital labelling covered both hotspots and not-hotspots equally. Results We noted a significant diversity of proliferative activities, and consequently, the results pointed to 6.5% of Ki-67, counted in hotspots, as the optimal cut-off for low–high-grade GIST. ROC analysis (AUC = 0.913; 95% CI: 0.828–0.997, p < 0.00001) and odds ratio (OR = 40.0, 95% CI: 6.7–237.3, p < 0.0001) pointed to Ki-67 16% as the cut-off for very high-grade (groups 5–6) cases. With help of a tumor digital map, we revealed possible errors resulting from a wrong choice of field for analysis. We confirmed that Ki-67 scores are in line with the level of intracellular metabolism that could be used as the additional biomarker. Conclusions Tumor digital masking is very promising solution for repeatable and objective labelling. Software adjustments of nuclear shape, outlines, size, etc. are helpful to omit other Ki-67-positive cells especially small lymphocytes. Our results pointed to Ki-67 as a good biomarker in GIST, but concurrently, we noted significant differences in used digital approaches which could lead to unequivocal results.

中文翻译：

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肿瘤数字掩蔽允许精确的患者分类：基于胃肠道间质瘤中 Ki-67 评分的研究

背景技术进步不断提供尖端工具来增强诊断能力的进步。胃肠道间质瘤属于间充质肿瘤家族，其中患者分类仍基于传统标准，如有丝分裂计数、肿瘤大小和肿瘤位置。人眼的局限性和有丝分裂计数区域选择的随机性迫使我们寻求更客观的解决方案，例如数字图像分析。目前，增殖活动的标记正在成为许多癌症中的常规任务。本研究的目的是将基于有丝分裂率的传统预测方法与细胞周期依赖性蛋白的数字图像分析进行比较。方法纳入57例符合条件的病例。此外，对先前进行的全组织切片免疫组织化学测定进行了数字分析。数字标签同样覆盖了热点和非热点。结果我们注意到增殖活动的显着多样性，因此，结果指出，在热点中计数的 Ki-67 的 6.5% 作为低-高级别 GIST 的最佳截止值。ROC 分析 (AUC = 0.913; 95% CI: 0.828–0.997, p < 0.00001) 和优势比 (OR = 40.0, 95% CI: 6.7–237.3, p < 0.0001) 指出 Ki-67 16% 作为切点非常高级别（第 5-6 组）病例关闭。在肿瘤数字地图的帮助下，我们揭示了由于选择错误的分析领域而可能导致的错误。我们证实 Ki-67 评分与可用作额外生物标志物的细胞内代谢水平一致。结论 肿瘤数字掩蔽是可重复和客观标记的非常有前景的解决方案。核形状、轮廓、大小等的软件调整有助于省略其他 Ki-67 阳性细胞，尤其是小淋巴细胞。我们的结果表明 Ki-67 在 GIST 中是一个很好的生物标志物，但同时，我们注意到使用的数字方法存在显着差异，这可能导致明确的结果。