保乳手术中漫反射光谱检测阳性切除缘(会议报告)

L. Boer, E. Kho, F. Duijnhoven, M. Peeters, K. Vijver, B. Hendriks, H. Sterenborg, T. Ruers
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引用次数: 2

摘要

在10%至40%接受保乳手术治疗的乳腺癌患者中,导管原位癌(DCIS)或浸润性癌(IC)存在于标本边缘。漫反射光谱(DRS)可以潜在地帮助外科医生在手术中避免这些肿瘤阳性切除边缘。在这里,我们评估DRS用于区分健康乳腺组织和肿瘤的可行性。为此,对71例乳腺标本进行了400-1600nm的DRS测量。在切除标本的切片上放置一个定制的网格,以准确地将DRS测量与组织病理学相关联。为了评估DRS对健康和肿瘤组织类型的区分,开发了一种基于支持向量机的分类算法。共纳入1081个位置,其中236个位置被认为是均匀的(> 95%的脂肪、结缔组织、IC或DCIS), 845个位置由混合组织类型组成。单纯DCIS部位的光谱与单纯IC的光谱相似,提示不能根据其光谱来区分这两种组织类型。在第一次分析中发现,纯脂肪、纯结缔组织和纯肿瘤组织(DCIS和IC)的位置可以区分,准确率分别为0.95、0.95和0.79。混合物位置的分类更具挑战性。肿瘤检测的准确性取决于测量体积中存在的肿瘤数量。这些结果表明,DRS可以潜在地用于肿瘤切除边缘的检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards detection of positive resection margins with diffuse reflectance spectroscopy during breast conserving surgery (Conference Presentation)
In 10 to 40% of breast cancer patients treated with breast conserving surgery, ductal carcinoma in situ (DCIS) or invasive carcinoma (IC) is present at the margin of the specimen. Diffuse Reflectance Spectroscopy (DRS) could potentially help the surgeon during surgery in avoiding these tumor positive resection margins. Here we assess the feasibility of DRS for discriminating healthy breast tissue from tumor. For this purpose, DRS measurements (400-1600nm) were obtained in 71 breast specimens. A custom-made grid was placed on top of a slice of the resection specimen to accurately correlate the DRS measurements with histopathology. To assess DRS for the discrimination between healthy and tumor tissue types, a support vector machine based classification algorithm was developed. A total of 1081 locations were included, of which 236 locations were considered homogenous (> 95% fat, connective tissue, IC, or DCIS) and 845 locations consisted of a mixture of tissue types. The spectra of pure DCIS locations were similar to the spectra of pure IC, suggesting that these tissue types could not be separated based on their spectra. In a first analysis it was found that locations of pure fat, pure connective, and pure tumor tissue (both DCIS and IC) could be discriminated with accuracies of 0.95, 0.95, and 0.79 respectively. Classification of mixture locations was more challenging. The accuracy for tumor detection depends on the amount of tumor present in the measurement volume. These results indicate that DRS can potentially be used for the detection of tumor at the resection margin.
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