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利用拉曼光谱法评估皮肤癌切缘的生物物理基础。

Biophysical basis of skin cancer margin assessment using Raman spectroscopy.

作者信息

Feng Xu, Fox Matthew C, Reichenberg Jason S, Lopes Fabiana C P S, Sebastian Katherine R, Markey Mia K, Tunnell James W

机构信息

Department of Biomedical Engineering, The University of Texas at Austin, 107 W. Dean Keeton Street C0800, Austin, TX 78712, USA.

Department of Internal Medicine, Dell Medical School, The University of Texas at Austin, 1701 Trinity Street Z0900, Austin, TX 78712, USA.

出版信息

Biomed Opt Express. 2018 Dec 7;10(1):104-118. doi: 10.1364/BOE.10.000104. eCollection 2019 Jan 1.

Abstract

Achieving adequate margins during tumor margin resection is critical to minimize the recurrence rate and maximize positive patient outcomes during skin cancer surgery. Although Mohs micrographic surgery is by far the most effective method to treat nonmelanoma skin cancer, it can be limited by its inherent required infrastructure, including time-consuming and expensive on-site histopathology. Previous studies have demonstrated that Raman spectroscopy can accurately detect basal cell carcinoma (BCC) from surrounding normal tissue; however, the biophysical basis of the detection remained unclear. Therefore, we aim to explore the relevant Raman biomarkers to guide BCC margin resection. Raman imaging was performed on skin tissue samples from 30 patients undergoing Mohs surgery. High correlations were found between the histopathology and Raman images for BCC and primary normal structures (including epidermis, dermis, inflamed dermis, hair follicle, hair shaft, sebaceous gland and fat). A previously developed model was used to extract the biochemical changes associated with malignancy. Our results showed that BCC had a significantly different concentration of nucleus, keratin, collagen, triolein and ceramide compared to normal structures. The nucleus accounted for most of the discriminant power (90% sensitivity, 92% specificity - balanced approach). Our findings suggest that Raman spectroscopy is a promising surgical guidance tool for identifying tumors in the resection margins.

摘要

在皮肤癌手术中,实现肿瘤边缘切除时的足够切缘对于降低复发率和最大化患者的积极预后至关重要。尽管莫氏显微外科手术是目前治疗非黑色素瘤皮肤癌最有效的方法,但它可能受到其固有的所需基础设施的限制,包括耗时且昂贵的现场组织病理学检查。先前的研究表明,拉曼光谱能够从周围正常组织中准确检测出基底细胞癌(BCC);然而,检测的生物物理基础仍不清楚。因此,我们旨在探索相关的拉曼生物标志物以指导BCC边缘切除。对30例行莫氏手术患者的皮肤组织样本进行了拉曼成像。在BCC与主要正常结构(包括表皮、真皮、炎症真皮、毛囊、毛干、皮脂腺和脂肪)的组织病理学和拉曼图像之间发现了高度相关性。使用先前开发的模型来提取与恶性肿瘤相关的生化变化。我们的结果表明,与正常结构相比,BCC的细胞核、角蛋白、胶原蛋白、甘油三油酸酯和神经酰胺浓度存在显著差异。细胞核在判别能力中占大部分(90%的敏感性,92%的特异性——平衡方法)。我们的研究结果表明,拉曼光谱是一种用于识别切除边缘肿瘤的有前景的手术指导工具。

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