Tissue-conserving surgery is used increasingly in cancer treatment. However, one of the main challenges in this type of surgery is the detection of tumor margins. Histopathology based on tissue sectioning and staining has been the gold standard for cancer diagnosis for more than a century. However, its use during tissue-conserving surgery is limited by time-consuming tissue preparation steps (1-2 h) and the diagnostic variability inherent in subjective image interpretation. Here, we demonstrate an integrated optical technique based on tissue autofluorescence imaging (high sensitivity and high speed but low specificity) and Raman scattering (high sensitivity and high specificity but low speed) that can overcome these limitations. Automated segmentation of autofluorescence images was used to select and prioritize the sampling points for Raman spectroscopy, which then was used to establish the diagnosis based on a spectral classification model (100% sensitivity, 92% specificity per spectrum). This automated sampling strategy allowed objective diagnosis of basal cell carcinoma in skin tissue samples excised during Mohs micrographic surgery faster than frozen section histopathology, and one or two orders of magnitude faster than previous techniques based on infrared or Raman microscopy. We also show that this technique can diagnose the presence or absence of tumors in unsectioned tissue layers, thus eliminating the need for tissue sectioning. This study demonstrates the potential of this technique to provide a rapid and objective intraoperative method to spare healthy tissue and reduce unnecessary surgery by determining whether tumor cells have been removed.

We investigate the potential of Raman microspectroscopy (RMS) for automated evaluation of excised skin tissue during Mohs micrographic surgery (MMS). The main aim is to develop an automated method for imaging and diagnosis of basal cell carcinoma (BCC) regions. Selected Raman bands responsible for the largest spectral differences between BCC and normal skin regions and linear discriminant analysis (LDA) are used to build a multivariate supervised classification model. The model is based on 329 Raman spectra measured on skin tissue obtained from 20 patients. BCC is discriminated from healthy tissue with 90+/-9% sensitivity and 85+/-9% specificity in a 70% to 30% split cross-validation algorithm. This multivariate model is then applied on tissue sections from new patients to image tumor regions. The RMS images show excellent correlation with the gold standard of histopathology sections, BCC being detected in all positive sections. We demonstrate the potential of RMS as an automated objective method for tumor evaluation during MMS. The replacement of current histopathology during MMS by a "generalization" of the proposed technique may improve the feasibility and efficacy of MMS, leading to a wider use according to clinical need.

Increased collagenase activity in colorectal carcinomas has recently been shown to be associated with increased malignant potential. To determine the tissue distribution of collagenase and its specific inhibitor, tissue inhibitor of metalloproteinases (TIMP), we carried out an immunohistochemical study on colorectal carcinomas (n = 20), adenomas (n = 7) and normal mucosa (n = 6). We found increased staining for collagenase in the connective tissue stroma of carcinomas, as compared with adenomas and normal mucosa. Little evidence of epithelial cell staining for collagenase was seen in any tissue. In carcinomas, both stromal fibroblasts and collagen fibres stained strongly and stromal staining was strongest close to neoplastic glands. Vascular staining was more prominent in neoplastic than normal tissues, perhaps reflecting the increased proteolytic activity during tumour angiogenesis. The pattern of TIMP immunostaining was similar to that of collagenase, although basement membrane staining for TIMP was generally more intense. Another difference was that, unlike TIMP, staining for collagenase was often increased at the invasive edge of carcinomas, perhaps reflecting increased collagenase activity at this location.