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3D Pathology Volumetric Technique: A Method for Calculating Breast Tumour Volume from Whole-Mount Serial Section Images

机译:3D病理学体积技术:一种用于从全挂载连续切片图像计算乳腺肿瘤体积的方法

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摘要

Tumour size, most commonly measured by maximum linear extent, remains a strong predictor of survival in breast cancer. Tumour volume, proportional to the number of tumour cells, may be a more accurate surrogate for size. We describe a novel “3D pathology volumetric technique” for lumpectomies and compare it with 2D measurements. Volume renderings and total tumour volume are computed from digitized whole-mount serial sections using custom software tools. Results are presented for two lumpectomy specimens selected for tumour features which may challenge accurate measurement of tumour burden with conventional, sampling-based pathology: (1) an infiltrative pattern admixed with normal breast elements; (2) a localized invasive mass separated from the in situ component by benign tissue. Spatial relationships between key features (tumour foci, close or involved margins) are clearly visualized in volume renderings. Invasive tumour burden can be underestimated using conventional pathology, compared to the volumetric technique (infiltrative pattern: 30% underestimation; localized mass: 3% underestimation for invasive tumour, 44% for in situ component). Tumour volume approximated from 2D measurements (i.e., maximum linear extent), assuming elliptical geometry, was seen to overestimate volume compared to the 3D volumetric calculation (by a factor of 7x for the infiltrative pattern; 1.5x for the localized invasive mass).
机译:肿瘤大小,最通常通过最大线性程度来衡量,仍然是乳腺癌存活率的有力预测指标。与肿瘤细胞数量成正比的肿瘤体积可能是大小的更准确替代。我们描述了一种适用于光谱分析的新型“ 3D病理学体积技术”,并将其与2D测量进行了比较。使用自定义软件工具从数字化的整体安装序列切片中计算体积渲染图和总肿瘤体积。给出了两个针对肿瘤特征选择的肿块切除术标本的结果,这些标本可能挑战以传统的,基于采样的病理学对肿瘤负荷的准确测量:(1)浸润型与正常乳腺成分混合; (2)通过良性组织与原位成分分开的局部浸润性肿块。在体绘制中可以清楚地看到关键特征(肿瘤灶,近缘或受累边缘)之间的空间关系。与容积技术相比,使用常规病理学可以低估浸润性肿瘤的负担(浸润模式:低估30%;局部肿块:浸润性肿瘤低估3%,就地成分低估44%)。与3D体积计算相比,假设为椭圆形几何形状,从2D测量值(即最大线性范围)近似得出的肿瘤体积被高估了体积(对于浸润模式而言为7倍;对于局部浸润性为1.5倍)。

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