Chemo-radiotherapy induced oral mucositis during IMRT for head and neck cancer - An assessment.

BACKGROUND: This study is conducted mainly to evaluate the changes in quality and quantity of oral epithelial cells during the course of IMRT. MATERIAL AND METHODS: 30 Patients undergoing chemo-radiotherapy were followed through course of treatment. They were compared with a group of age- and sex-matched healthy individuals. The procedure involved WHO clinical scoring, collection of oral washings and preparation of buccal smears from both study group and control group. The changes occurred were recorded as a way of assessing the severity of oral mucositis. RESULTS: revealed a significant occurrence of oral mucositis in almost all patients during weekly follow up. There was a significant increase in percentage of viable buccal epithelial cells in study group when compared to normal controls (P<0.005) during and at the end of chemo-radiotherapy. CONCLUSIONS: quantification of oral mucositis can be done at cellular level by determining the oral mucosal cell viability and their maturation during IMRT.

Bimodal multispectral imaging system with cloud-based machine learning algorithm for real-time screening and detection of oral potentially malignant lesions and biopsy guidance.

SIGNIFICANCE: Screening and early detection of oral potentially malignant lesions (OPMLs) are of great significance in reducing the mortality rates associated with head and neck malignancies. Intra-oral multispectral optical imaging of tissues in conjunction with cloud-based machine learning (CBML) can be used to detect oral precancers at the point-of-care (POC) and guide the clinician to the most malignant site for biopsy. AIM: Develop a bimodal multispectral imaging system (BMIS) combining tissue autofluorescence and diffuse reflectance (DR) for mapping changes in oxygenated hemoglobin (HbO2) absorption in the oral mucosa, quantifying tissue abnormalities, and guiding biopsies. APPROACH: The hand-held widefield BMIS consisting of LEDs emitting at 405, 545, 575, and 610 nm, 5MPx monochrome camera, and proprietary Windows-based software was developed for image capture, processing, and analytics. The DR image ratio (R610/R545) was compared with pathologic classification to develop a CBML algorithm for real-time assessment of tissue status at the POC. RESULTS: Sensitivity of 97.5% and specificity of 92.5% were achieved for discrimination of OPML from patient normal in 40 sites, whereas 82% sensitivity and 96.6% specificity were obtained for discrimination of abnormal (OPML + SCC) in 89 sites. Site-specific algorithms derived for buccal mucosa (27 sites) showed improved sensitivity and specificity of 96.3% for discrimination of OPML from normal. CONCLUSIONS: Assessment of oral cancer risk is possible by mapping of HbO2 absorption in tissues, and the BMIS system developed appears to be suitable for biopsy guidance and early detection of oral cancers.