Intraoperative Flow Cytometry for the Rapid Diagnosis and Validation of Surgical Clearance of Non-Melanoma Skin Cancer: A Prospective Clinical Feasibility Study.
Georgios S MarkopoulosEvangeli LampriIoulia TraganiNikolaos KourkoumelisGeorgios VartholomatosKonstantinos SeretisPublished in: Cancers (2024)
Non-melanoma skin cancer (NMSC) is the most prevalent cancer in humans, with a high global incidence. We present a prospective clinical feasibility study on the use of intraoperative flow cytometry (iFC) for the instant diagnosis of NMSC and its complete surgical clearance. Flow cytometry, a laser-based technique, quantifies cell features, which has applications in cancer research. This study aim is to explore the potential applicability of iFC in detecting and characterizing NMSC and its surgical margins. In total, 30 patients who underwent diagnosis for NMSC were recruited. The method demonstrated high sensitivity (95.2%) and specificity (87.1%), with an accuracy of 91.1%, as confirmed with a receiver operating characteristic curve analysis. The results also indicated that most tumors were diploid, with two cases being hypoploid. The average G0/G1 fractions for normal and tumor tissue samples were 96.03 ± 0.30% and 88.03 ± 1.29%, respectively, with the tumor index escalating from 3.89 ± 0.30% to 11.95 ± 1.29% in cancerous cells. These findings underscore iFC's capability for precise intraoperative NMSC characterization and margin evaluation, promising enhanced complete tumor excision rates. Given the technique's successful application in various other malignancies, its implementation in NMSC diagnosis and treatment holds significant promise and warrants further research in clinical trials.
Keyphrases
- quality improvement
- flow cytometry
- skin cancer
- papillary thyroid
- clinical trial
- patients undergoing
- end stage renal disease
- ejection fraction
- induced apoptosis
- newly diagnosed
- risk factors
- stem cells
- single cell
- prognostic factors
- healthcare
- childhood cancer
- lymph node metastasis
- risk assessment
- machine learning
- quantum dots
- climate change
- artificial intelligence
- patient reported outcomes
- endoplasmic reticulum stress
- structural basis
- cell cycle arrest
- phase iii