G.R. Harrison Spectroscopy Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Cancer Res. 2013 Jun 1;73(11):3206-15. doi: 10.1158/0008-5472.CAN-12-2313.
Microcalcifications are a feature of diagnostic significance on a mammogram and a target for stereotactic breast needle biopsy. Here, we report development of a Raman spectroscopy technique to simultaneously identify microcalcification status and diagnose the underlying breast lesion, in real-time, during stereotactic core needle biopsy procedures. Raman spectra were obtained ex vivo from 146 tissue sites from fresh stereotactic breast needle biopsy tissue cores from 33 patients, including 50 normal tissue sites, 77 lesions with microcalcifications, and 19 lesions without microcalcifications, using a compact clinical system. The Raman spectra were modeled on the basis of the breast tissue components, and a support vector machine framework was used to develop a single-step diagnostic algorithm to distinguish normal tissue, fibrocystic change (FCC), fibroadenoma, and breast cancer, in the absence and presence of microcalcifications. This algorithm was subjected to leave-one-site-out cross-validation, yielding a positive predictive value, negative predictive value, sensitivity, and specificity of 100%, 95.6%, 62.5%, and 100% for diagnosis of breast cancer (with or without microcalcifications) and an overall accuracy of 82.2% for classification into specific categories of normal tissue, FCC, fibroadenoma, or breast cancer (with and without microcalcifications). Notably, the majority of breast cancers diagnosed are ductal carcinoma in situ (DCIS), the most common lesion associated with microcalcifications, which could not be diagnosed using previous Raman algorithm(s). Our study shows the potential of Raman spectroscopy to concomitantly detect microcalcifications and diagnose associated lesions, including DCIS, and thus provide real-time feedback to radiologists during such biopsy procedures, reducing nondiagnostic and false-negative biopsies.
微钙化是乳房 X 线摄影中的一个有诊断意义的特征,也是立体定向乳腺针活检的一个目标。在这里,我们报告了一种拉曼光谱技术的发展,该技术能够在立体定向核心针活检过程中实时同时识别微钙化状态并诊断潜在的乳腺病变。使用紧凑型临床系统,从 33 名患者的新鲜立体定向乳腺针活检组织芯中 146 个组织部位获得了拉曼光谱,包括 50 个正常组织部位、77 个有微钙化的病变部位和 19 个无微钙化的病变部位。该拉曼光谱基于乳腺组织成分进行建模,并使用支持向量机框架开发了一种单步诊断算法,以区分正常组织、纤维囊性改变(FCC)、纤维腺瘤和乳腺癌,无论是否存在微钙化。该算法经过了一次留一站点的交叉验证,对乳腺癌(有或无微钙化)的诊断具有 100%的阳性预测值、95.6%的阴性预测值、62.5%的敏感性和 100%的特异性,对特定的正常组织、FCC、纤维腺瘤或乳腺癌(有或无微钙化)的分类具有 82.2%的总体准确性。值得注意的是,诊断出的大多数乳腺癌是导管原位癌(DCIS),这是最常见的与微钙化相关的病变,这是以前的拉曼算法无法诊断的。我们的研究表明,拉曼光谱技术有可能同时检测微钙化并诊断相关病变,包括 DCIS,从而在活检过程中为放射科医生提供实时反馈,减少非诊断性和假阴性活检。