Use of simulated data to explore the application of optical coherence tomography for classifying middle-ear pathologies.

Abstract

Optical coherence tomography (OCT) vibrometry is a non-invasive tool for functional imaging of the middle ear. It provides spatially resolved vibrational responses and also anatomical images of the same ear. Our objective here was to explore the potential of OCT vibration measurements at the incus, as well as at the umbo, to distinguish among middle-ear disorders. Our approach was to build finite-element models of normal and pathological ears, generate large amounts of synthetic data, and then classify the simulated data into normal and pathological groups using a decision tree based on features extracted from simulated vibration magnitudes. We could distinguish between normal ears and ears with incudomallear joint (IMJ) disarticulation or stapes fixation, with the sensitivity and specificity both being 1.0; distinguish between stapes fixation and IMJ disarticulation with a sensitivity of 0.900 and a specificity of 0.889; and distinguish ears with ISJ disarticulation from normal ears with a sensitivity of 0.784 and a specificity of 0.872. Less extreme pathologies were also simulated. The results suggest that the vibration measurements within the middle ear that can be provided by OCT (e.g., at the incus) may be very valuable for diagnosis.