Computerized decision support system for intraoperative analysis of margin status in breast conservation therapy.

ISRN surgery Pub Date : 2012-01-01 Epub Date: 2012-11-25 DOI:10.5402/2012/546721
Manuel E Ruidíaz, Sarah L Blair, Andrew C Kummel, Jessica Wang-Rodriguez
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引用次数: 5

Abstract

Background. Breast conservation therapy (BCT) is the standard treatment for breast cancer; however, 32-63% of procedures have a positive margin leading to secondary procedures. The standard of care to evaluate surgical margins is based on permanent section. Imprint cytology (IC) has been used to evaluate surgical samples but is limited by excessive cauterization thus requiring experienced cytopathologist for interpretation. An automated image screening process has been developed to detect cancerous cells from IC on cauterized margins. Methods. IC was prospectively performed on margins during lumpectomy operations for breast cancer in addition to permanent section on 127 patients. An 8-slide training subset and 8-slide testing subset were culled. H&E IC automated analysis, based on linear discriminant analysis, was compared to manual pathologist interpretation. Results. The most important descriptors, from highest to lowest performance, are nucleus color (23%), cytoplasm color (15%), shape (12%), grey intensity (9%), and local area (5%). There was 100% agreement between automated and manual interpretation of IC slides. Conclusion. Although limited by IC sampling variability, an automated system for accurate IC cancer cell identification system is demonstrated, with high correlation to manual analysis, even in the face of cauterization effects which supplement permanent section analysis.

Abstract Image

Abstract Image

Abstract Image

保乳术中切缘状态分析的计算机决策支持系统。
背景。乳房保护疗法(BCT)是乳腺癌的标准治疗方法;然而,32-63%的手术有导致二次手术的正余量。评估手术切缘的护理标准是基于永久切片。印迹细胞学(IC)已用于评估手术样本,但由于过度烧灼,因此需要经验丰富的细胞病理学家进行解释。一种自动图像筛选过程已开发,以检测癌变细胞从IC烧灼边缘。方法。在127例乳腺癌乳房肿瘤切除手术中,除了永久性切除外,还在边缘处进行了前瞻性的IC。筛选了8张幻灯片的训练子集和8张幻灯片的测试子集。将基于线性判别分析的H&E - IC自动分析与病理学家手工解释进行比较。结果。从最高性能到最低性能,最重要的描述符是细胞核颜色(23%)、细胞质颜色(15%)、形状(12%)、灰色强度(9%)和局部面积(5%)。自动和人工解读IC幻灯片的准确率100%一致。结论。虽然受到IC采样可变性的限制,但证明了一个准确的IC癌细胞识别系统的自动化系统,与人工分析高度相关,即使面对烧灼效应,也可以补充永久切片分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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