Optical coherence tomography for classification of oral mucosal lesions

  • Witjes M
  • Renting M
  • Roodenburg J
  • et al.
N/ACitations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Introduction: Not having to take a biopsy of oral mucosal lesions can be a great relief for patients. Optical coherence tomography (OCT) allows non-invasive imaging of epithelial layers and subsequently of epithelial lesions. The aim of this study is to establish whether OCT can aid in clinical diagnosis and in the decision of taking a biopsy or not. Methods: Patients with a lesion of the oral mucosa were selected for this study. Before taking biopsies an OCT image (Niris, Imalux, USA) as well as a white light image was made. The spot was marked with a felt pen, which was biopsied. Histolopathology was the gold standard. Uninformed on the diagnosis, two independent observers graded the OCT image and clinical white light image. Results: 36 biopsies were taken in 22 patients. Three images were graded as unable to interpret (2 squamous cell carcinoma, 1 lichen planus). On white light images the observers graded the lesions correctly in 67% and 68% of the cases. In 6% resp 20% of the cases OCT was considered relevant in the diagnosis of which 50% resp 39% was diagnosed incorrectly. The number of biopsies correctly omitted was 1.5% resp 3%. Interobserver agreement ranged from 41-80% on items of the grading list. Conclusion: In newly diagnosed lesions the value of OCT seems limited. Images are difficult to interpret and the OCT diagnosis is often wrong. In selected cases OCT may have an added value in long term follow up of lesions.

Cite

CITATION STYLE

APA

Witjes, M., Renting, M., Roodenburg, J., & Schepman, K. P. (2011). Optical coherence tomography for classification of oral mucosal lesions. Photodiagnosis and Photodynamic Therapy, 8(2), 228. https://doi.org/10.1016/j.pdpdt.2011.03.008

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free