Voxel based morphometry in optical coherence tomography: validation and core findings

Abstract

Optical coherence tomography (OCT) of the human retina is now becoming established as an important modality for the detection and tracking of various ocular diseases. Voxel based morphometry (VBM) is a long standing neuroimaging analysis technique that allows for the exploration of the regional differences in the brain. There has been limited work done in developing registration based methods for OCT, which has hampered the advancement of VBM analyses in OCT based population studies. Following on from our recent development of an OCT registration method, we explore the potential benefits of VBM analysis in cohorts of healthy controls (HCs) and multiple sclerosis (MS) patients. Specifically, we validate the stability of VBM analysis in two pools of HCs showing no significant difference between the two populations. Additionally, we also present a retrospective study of age and sex matched HCs and relapsing remitting MS patients, demonstrating results consistent with the reported literature while providing insight into the retinal changes associated with this MS subtype.

Automated Deformation-Based Analysis of 3D Optical Coherence Tomography in Diabetic Retinopathy

“…Previous reports of cross-subject OCT volume registration were based on 1D nonlinear registration and were not designed to align tilted volumes or those with edema [28], [48]. The current study is the first, to our knowledge, that present a technique for 3D OCT registration in presence of DR abnormalities.…”

“…OCT registration has been performed for studying retinal diseases [19]–[21], evaluating treatment efficiency [20], assisting with layer segmentation [22], [23], motion correction [24], noise compensation [25], and analysis of same subject longitudinal data [26]. To our knowledge, three methods have focused explicitly on cross-subject OCT registration.…”

Intensity inhomogeneity correction of SD-OCT data using macular flatspace

“…Such an analysis is sometimes called voxel based morphometry (VBM). Recently, Antony et al (2016a) used VBM to show localized statistically significant differences between populations of healthy controls and patients with multiple sclerosis. Considering its success and popularity in other imaging modalities like CT and MRI Isgum et al (2009); Cabezas et al (2011), registration will likely become a more common technique for analyzing retinal OCT data in the future.…”

“…In recent years, many automated methods have been developed for the segmentation of the retinal layers (Garvin et al, 2009; Chiu et al, 2010; Vermeer et al, 2011; Lang et al, 2013, 2015a, 2017) and fluid-filled regions (Wilkins et al, 2012; Chen et al, 2012; Swingle et al, 2014, 2015; Lang et al, 2015b; Antony et al, 2016b). Image registration, which has received much less attention, has been used to align scans from different subjects (Chen et al, 2014), for longitudinal intra-subject registration (Niemeijer et al, 2012; Wu et al, 2014), and in applications of registration including voxel based morphometry (Antony et al, 2016a).…”

Age and Glaucoma-Related Characteristics in Retinal Nerve Fiber Layer and Choroid: Localized Morphometrics and Visualization Using Functional Shapes Registration

“…Chen et al ( 2014 ) performed intensity-based non-rigid registration of macular OCT scans by a combination of rigid alignment of foveae, and A-scan-wise affine and non-rigid registration using radial basis functions for refined alignment of the retinal layers (Chen et al, 2014 ). A more recent work (Anthony et al, 2016 ) by the same group applies this registration technique to perform voxel based morphometry in macular OCT of healthy controls and multiple sclerosis patients. Our group's approach has focused on retinal surface-based registrations and atlas generation.…”