Differentiating oral lesions in different carcinogenesis stages with optical coherence tomography

J Biomed Opt. 2009 Jul-Aug;14(4):044028. doi: 10.1117/1.3200936.

Abstract

A swept-source optical coherence tomography (SS-OCT) system is used to clinically scan oral lesions in different oral carcinogenesis stages, including normal oral mucosa control, mild dysplasia (MiD), moderate dysplasia (MoD), early-stage squamous cell carcinoma (ES-SCC), and well-developed SCC (WD-SCC), for diagnosis purpose. On the basis of the analyses of the SS-OCT images, the stages of dysplasia (MiD and MoD), and SCC (ES-SCC and WD-SCC) can be differentiated from normal control by evaluating the depth-dependent standard deviation (SD) values of lateral variations. In the dysplasia stage, the boundary between the epithelium (EP) and lamina propria (LP) layers can still be identified and the EP layer becomes significantly thicker than that of normal control. Also, in a certain range of the EP layer above the EP/LP boundary, the SD value becomes larger than a certain percentage of the maximum level, which is observed around the EP/LP boundary. On the other hand, in the ES-SCC and WD-SCC stages, the EP/LP boundary disappears. Because of the higher density of connective tissue papillae in the ES-SCC stage, the SD values of the slowly varying lateral scan profiles in the ES-SCC samples are significantly larger than those in the WD-SCC sample. Also, ES-SCC can be differentiated from WD-SCC by comparing the exponential decay constants of averaged A-mode scan profiles. Because of the higher tissue absorption in the WD-SCC lesion, the decay constants in the WD-SCC samples are significantly higher than those in the ES-SCC samples.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Artificial Intelligence*
  • Carcinoma, Squamous Cell / pathology*
  • Diagnosis, Differential
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Mouth Neoplasms / pathology*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Tomography, Optical Coherence / methods*