2022 Oral oncology

Systematic classification of confocal laser endomicroscopy for the diagnosis of oral cavity carcinoma.

, , , , , , , , , (+2 more)

Oral oncology Vol. 132 : 105978 • Sep 2022

INTRODUCTION: Confocal laser endomicroscopy (CLE) is an optical imaging technique that allows in vivo microscope-like images of the upper aerodigestive tract's mucosa in 1000-fold magnification. The assessment of morphological tissue characteristics for the correct differentiation between healthy and malignoma suspected mucosa requires strict evaluation criteria. This study aims to validate a score for oral cavity squamous cell carcinoma (OCSCC) diagnostic. METHODS: We performed CLE and examined a total of twelve patients. All 95 sequences (778 s, 6224 images) originate from the area of the primary tumor 260 s, 2080 images) and unsuspicious mucosa of the oral cavity (518 s, 4144 images). Specimen were taken at corresponding locations and analyzed histologically in H&E staining as a reference standard. A total of eight examiners (four experienced and four inexperienced) evaluated the sequences based on a scoring system. The primary endpoints are sensitivity, specificity, and accuracy. Secondary endpoints are inter-rater reliability and receiver operator characteristics. RESULTS: Healthy mucosa showed epithelium with uniform size and shape with distinct cytoplasmic membranes and regular vessel architecture. CLE of malignant cells demonstrated a disorganized arrangement of variable cellular morphology. We calculated an accuracy, sensitivity, specificity, PPV, and NPV of 88.7 %, 90.1 %, 87.4 %, 87.5 %, and 90.0 %, respectively, with inter-rater reliability and kappa-value of 0.775, and an area under the curve of 0.935. CONCLUSIONS: The results confirm that this scoring system is applicable in the oral cavity mucosa to classify benign and malignant tissue.

No clinical trial protocols linked to this paper

Clinical trials are automatically linked when NCT numbers are found in the paper's title or abstract.
PICO Elements

No PICO elements extracted yet. Click "Extract PICO" to analyze this paper.

Paper Details
MeSH Terms
Associated Data

No associated datasets or code repositories found for this paper.

Related Papers

Related paper suggestions will be available in future updates.