Phospholipid Detection From Surgical Smoke Distinguishes Basal Cell Carcinoma: A Proof-of-Principle Study

Abstract

Background: Basal cell carcinoma (BCC) is a nonmelanocytic skin cancer and the most common malignancy in Caucasians. Diagnostics and treatment of BCC cause significant health-related stress for many patients and costs for public health care systems. Differential mobility spectrometry (DMS) is a sensitive method for detection of gaseous molecules. The DMS-derived automatic tissue analysis system (ATAS) utilises diathermy-generated surgical smoke to distinguish cancerous tissue from normal tissue based on lipid profiling between the tissues. Objectives: The aim of this study was to create a surrogate porcine model to test the feasibility of the ATAS in lipid detection of skin. Another objective was to determine whether BCC of human skin could be identified from healthy skin using lipid profiling. Methods: Porcine ear skin was used to establish a three-group porcine model for lipid profile detection. Lecithin was chosen as a marker to demonstrate elevated phospholipid levels in one of the groups. We also recruited five BCC patients to collect BCC tumour biopsies and healthy skin biopsies to test the model in human samples. In both models, all samples were processed with the ATAS to test the accuracy of lipid profiling and resolution between the groups. Results: In the porcine model, the classification accuracy was 74.5% for three groups (unprocessed porcine skin, fine-grained porcine skin, and lecithin-marked fine-grained porcine skin) and 91.8% for two groups (unprocessed porcine skin and fine-grained porcine skin combined into one group in comparison to lecithin-marked fine-grained porcine skin). The support vector machine (SVM) classifier model trained on porcine surrogate samples was then used to analyse a small number of human BCC and healthy skin samples with 95% accuracy. Conclusion: DMS-based differentiation of porcine skin samples based on surgical smoke is possible. This study is a step towards a method to distinguish human BCC from healthy skin from surgical smoke by the ATAS. The presented skin identification of DMS analysis of surgical smoke opens the possibility to research the method in a larger sample number of human BCC and healthy skin samples as well as develop the method and ATAS towards a clinical tool for margin assessment.