Automated classification of optical coherence tomography images for the diagnosis of oral malignancy in the hamster cheek pouch

Abstract

Abstract. Most studies evaluating the potential of optical coherence tomography (OCT) for the diagnosis of oral cancer are based on visual assessment of OCT B-scans by trained experts. Human interpretation of the large pool of data acquired by modern high-speed OCT systems, however, can be cumbersome and extremely time consuming. Development of image analysis methods for automated and quantitative OCT image analysis could therefore facilitate the evaluation of such a large volume of data. We report automated algorithms for quantifying structural features that are associated with the malignant transformation of the oral epithelium based on image processing of OCT data. The features extracted from the OCT images were used to design a statistical classification model to perform the automated tissue diagnosis. The sensitivity and specificity of distinguishing malignant lesions from benign lesions were found to be 90.2% and 76.3%, respectively. The results of the study demonstrate the feasibility of using quantitative image analysis algorithms for extracting morphological features from OCT images to perform the automated diagnosis of oral malignancies in a hamster cheek pouch model.

Remodeling of the Epithelial–Connective Tissue Interface in Oral Epithelial Dysplasia as Visualized by Noninvasive 3D Imaging

“…This algorithm is adaptable to other image stacks with a hard interface, as seen in SHGM. More advanced edge detection algorithms could be developed in future when detection of subtle changes in fluorescence intensities is necessary as has been done for OCT or CRM (25, 43). Given that depth of imaging encompasses the epithelium and LP, the algorithm could be readily applied in similar mucosal structures and in those in which rete-like ridges extend in depth.…”

“…OED was induced by topical treatment of 0.5% 9,10-dimethyl-1,2-benzanthracene (DMBA) in mineral oil on the left cheek pouch of four-week old male Golden Syrian Hamsters (Harlan Laboratories) three times a week for 8–12 weeks (25, 30). Controls were treated with mineral oil following the same procedure.…”

“…Automated approaches have been applied to optical coherence tomography (OCT) 2D (x–z) B-scan images to separate epithelium from LP in studies by Lee et al in human patients and by Pande et al in a hamster model of neoplasia (25, 26). ECTI shape parameters were not evaluated, and though feasible, the 3D ECTI structure was not delineated.…”

Quantitative characterization of mechanically indented in vivo human skin in adults and infants using optical coherence tomography

“…[26][27][28] Commonly performed on OCT images, texture analysis often takes advantage of other statistical features that are both intensity sensitive and directionally sensitive, such as the co-occurrence matrices 29 and the gray-scale run-length matrices. 30 In this paper, fractal analysis was utilized to characterize the intensity distribution within the tissue. The central concept of fractal analysis is to reveal the statistical self-similarity and geometrical complexity of an object based on the box-counting dimension.…”

In vivo wide-field reflectance/fluorescence imaging and polarization-sensitive optical coherence tomography of human oral cavity with a forward-viewing probe

“…Feasibility of OCT as a diagnostic tool has been demonstrated in various pre-clinical animal [24,25] and human [14,[26][27][28][29][30] oral cavity studies. Computational methods for automated OCT image analysis and classification [31], quantitative assessment [28,32] have been developed to aid diagnosis of oral cavity lesions. Polarization-sensitive OCT (PS-OCT) is an augmented OCT providing information of both structure and birefringence [33,34].…”