School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK.
Division of Oncology, School of Medicine, University of Nottingham, Nottingham, NG5 1PB, UK.
Breast Cancer Res. 2018 Jul 9;20(1):69. doi: 10.1186/s13058-018-1002-2.
In over 20% of breast conserving operations, postoperative pathological assessment of the excised tissue reveals positive margins, requiring additional surgery. Current techniques for intra-operative assessment of tumor margins are insufficient in accuracy or resolution to reliably detect small tumors. There is a distinct need for a fast technique to accurately identify tumors smaller than 1 mm in large tissue surfaces within 30 min.
Multi-modal spectral histopathology (MSH), a multimodal imaging technique combining tissue auto-fluorescence and Raman spectroscopy was used to detect microscopic residual tumor at the surface of the excised breast tissue. New algorithms were developed to optimally utilize auto-fluorescence images to guide Raman measurements and achieve the required detection accuracy over large tissue surfaces (up to 4 × 6.5 cm). Algorithms were trained on 91 breast tissue samples from 65 patients.
Independent tests on 121 samples from 107 patients - including 51 fresh, whole excision specimens - detected breast carcinoma on the tissue surface with 95% sensitivity and 82% specificity. One surface of each uncut excision specimen was measured in 12-24 min. The combination of high spatial-resolution auto-fluorescence with specific diagnosis by Raman spectroscopy allows reliable detection even for invasive carcinoma or ductal carcinoma in situ smaller than 1 mm.
This study provides evidence that this multimodal approach could provide an objective tool for intra-operative assessment of breast conserving surgery margins, reducing the risk for unnecessary second operations.
在超过 20%的保乳手术中,术后对切除组织的病理评估显示切缘阳性,需要进行额外的手术。目前用于术中评估肿瘤切缘的技术在准确性或分辨率方面都不足以可靠地检测到小肿瘤。因此,迫切需要一种快速的技术,以便在 30 分钟内准确识别大于 1 毫米的大组织表面的小肿瘤。
多模态光谱组织病理学(MSH)是一种结合组织自体荧光和拉曼光谱的多模态成像技术,用于检测切除的乳腺组织表面的微小残留肿瘤。开发了新的算法来最佳地利用自体荧光图像来指导拉曼测量,并实现对大组织表面(最大可达 4×6.5cm)的所需检测精度。算法在 65 名患者的 91 个乳腺组织样本上进行了训练。
对 107 名患者的 121 个样本(包括 51 个新鲜的全切除标本)进行了独立测试,该方法检测到了组织表面的乳腺癌,其敏感性为 95%,特异性为 82%。每个未经切割的切除标本的一个表面在 12-24 分钟内进行了测量。高空间分辨率的自体荧光与拉曼光谱的特异性诊断相结合,即使对于小于 1 毫米的浸润性癌或导管原位癌也能可靠地检测到。
这项研究提供了证据表明,这种多模态方法可以为保乳手术切缘的术中评估提供一种客观的工具,从而降低不必要的二次手术的风险。