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.
Highlights
Nonmelanoma skin cancer is by far the most common malignancy worldwide
This study demonstrated the feasibility of detecting biophysical changes between basal cell carcinoma (BCC) and five primary normal structures, but has several limitations: firstly, the number of patients is small; secondly, inflamed dermis was not included in the study, which may be confused with BCC in histopathological diagnosis [6,16]; a more comprehensive analysis is needed to link our biophysical approach with molecular vibrational approaches [24,25]
In this study, we evaluated the accuracy of Raman to discriminate between BCC and normal skin structures in excised micrographic surgery (Mohs) skin sections
Summary
Nonmelanoma skin cancer is by far the most common malignancy worldwide. Among more than 5 million new cases diagnosed annually in the US, approximately 80% are basal cell carcinoma (BCC) [1]. Mohs micrographic surgery (Mohs) is the most effective method for the treatment of BCC. The 5-yr recurrence rate of Mohs (1 – 3% for primary BCC and 5 – 7% for recurrent BCC) is much lower than standard surgical excision (3 – 10% in primary BCC and >17% in recurrent BCC) [2]. Mohs involves iterative excision of surgical margins of each stage, followed by frozen section histopathology. If the histopathological diagnosis indicates tumor still exists, further tissue layers will be removed until the margins are clear
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