Multispectral label-free Raman spectroscopy can detect ovarian and endometrial cancer with high accuracy.
Sandryne DavidArthur PlanteFrédérick DallaireJean-Philippe TremblayGuillaume SheehyElizabeth MacdonaldLaura ForrestManijeh DaneshmandDominique TrudelBrian C WilsonLaura HopkinsSangeeta MurugkarBarbara VanderhydenFrédérick DallairePublished in: Journal of biophotonics (2021)
Up to 70% of ovarian cancer patients are diagnosed with advanced-stage disease and the degree of cytoreduction is an important survival prognostic factor. The aim of this study was to evaluate if Raman spectroscopy could detect cancer from different organs within the abdominopelvic region, including the ovaries. A Raman spectroscopy probe was used to interrogate specimens from a cohort of nine patients undergoing cytoreductive surgery, including four ovarian cancer patients and three patients with endometrial cancer. A feature-selection algorithm was developed to determine which spectral bands contributed to cancer detection and a machine-learning model was trained. The model could detect cancer using only eight spectral bands. The receiver-operating-characteristic curve had an area-under-the-curve of 0.96, corresponding to an accuracy, a sensitivity and a specificity of 90%, 93% and 88%, respectively. These results provide evidence multispectral Raman spectroscopy could be developed to detect ovarian cancer intraoperatively.
Keyphrases
- raman spectroscopy
- endometrial cancer
- machine learning
- papillary thyroid
- label free
- squamous cell
- prognostic factors
- minimally invasive
- optical coherence tomography
- magnetic resonance imaging
- lymph node metastasis
- squamous cell carcinoma
- fluorescence imaging
- computed tomography
- acute coronary syndrome
- percutaneous coronary intervention
- photodynamic therapy
- neural network
- atrial fibrillation