Physics and Astronomy, Faculty of Environment, Science and Economy, University of Exeter, Exeter, Devon, UK.
Royal Devon University Healthcare NHS Foundation Trust, Exeter, Devon, UK.
Analyst. 2023 Sep 11;148(18):4373-4385. doi: 10.1039/d3an00574g.
Optimal oncological results and patient outcomes are achieved in surgery for early breast cancer with breast conserving surgery (BCS) where this is appropriate. A limitation of BCS occurs when cancer is present at, or close, to the resection margin - termed a 'positive' margin - and re-excision is recommended to reduce recurrence rate. This is occurs in 17% of BCS in the UK and there is therefore a critical need for a way to assess margin status intraoperatively to ensure complete excision with adequate margins at the first operation. This study presents the potential of high wavenumber (HWN) Raman spectroscopy to address this. Freshly excised specimens from thirty patients undergoing surgery for breast cancer were measured using a surface Raman probe, and a multivariate classification model to predict normal tumour was developed from the data. This model achieved 77.1% sensitivity and 90.8% specificity following leave one patient out cross validation, with the defining features being differences in water content and lipid protein content. This demonstrates the feasibility of HWN Raman spectroscopy to facilitate future intraoperative margin assessment at specific locations. Clinical utility of the approach will require further research.
在早期乳腺癌的手术中，保乳手术（BCS）可以实现最佳的肿瘤学结果和患者预后。当癌症位于或接近切除边缘时，BCS 存在局限性，称为“阳性”边缘，建议再次切除以降低复发率。在英国，BCS 中有 17%出现这种情况，因此迫切需要一种方法来评估术中边缘状态，以确保在第一次手术中完全切除并留有足够的边缘。本研究提出了高波数（HWN）拉曼光谱技术的应用潜力。对 30 名接受乳腺癌手术的患者的新鲜切除标本进行了测量，使用表面拉曼探头，并从数据中开发了一个用于预测正常肿瘤的多变量分类模型。在进行一次患者留一交叉验证后，该模型的灵敏度为 77.1%，特异性为 90.8%，其特征是水含量和脂质-蛋白质含量的差异。这证明了 HWN 拉曼光谱技术在特定位置辅助未来术中边缘评估的可行性。该方法的临床实用性需要进一步研究。
