Improvement of the clinical utility of optical coherence tomography (OCT) retinal nerve fiber layer (RNFL) measurement by establishing data comparability across the OCT technology generations and models

Glaucoma is the second leading cause of blindness worldwide, which induces irreversible structural damage (retinal ganglion cell loss and retinal nerve fiber layer (RNFL) thinning) on the retina. Optical coherence tomography (OCT) provides RNFL thickness measurements, which have become an essential clinical measure for objective glaucoma assessment. RNFL thickness is measured on a cross-sectional retinal image sampled along a 3.4mm circle centered around the optic nerve head (ONH). With the conventional time-domain OCT (TD-OCT), its operator dependent scan registration is responsible for the majority of measurement variability. Recently, spectral domain OCT (SD-OCT) technology has been introduced. SD-OCT provides faster scanning (up to 100x) and finer axial resolution (up to 2x) compared to TD-OCT, allowing three-dimensional (3D) volume sampling. 3D SD-OCT data can be visualized as an en face image of the retina. This allows us to create a virtual OCT image along any sampling line (curved or straight), which permits virtually perfect scan registration. The objective of this study is to improve the clinical utility of OCT RNFL measurement by establishing data comparability across the multiple OCT generations and models. First, we developed an algorithm to match the TD-OCT scan location within the corresponding 3D SD-OCT volume. Scan location matching (SLM) enables computation of the calibration equation between TD-OCT and SD-OCT for direct comparison of measurements, bridging the old technology with new ones. Second, the performance of the SLM method was measured using various SD-OCT devices with different spatial sampling methods. By making TD-OCT measurements at one time point comparable to the most recent SD-OCT measurement using SLM, glaucoma progression can be assessed on one to one basis. However, due to the variable TD-OCT scan registration over multiple visits, one can still not analyze the trend of glaucoma progression because RNFL thickness measured at different locations is not directly comparable even after calibration. Therefore, we developed a mathematical model of the retinal nerve fiber bundle distribution pattern to normalize the off-centered TD-OCT RNFL thickness to a virtually centered one. The outcome of this study would facilitate more accurate and reliable glaucoma disease/progression detection in cross-sectional as well as longitudinal clinical settings

Deep learning-based improvement for the outcomes of glaucoma clinical trials

Glaucoma is the leading cause of irreversible blindness worldwide. It is a progressive optic neuropathy in which retinal ganglion cell (RGC) axon loss, probably as a consequence of damage at the optic disc, causes a loss of vision, predominantly affecting the mid-peripheral visual field (VF). Glaucoma results in a decrease in vision-related quality of life and, therefore, early detection and evaluation of disease progression rates is crucial in order to assess the risk of functional impairment and to establish sound treatment strategies. The aim of my research is to improve glaucoma diagnosis by enhancing state of the art analyses of glaucoma clinical trial outcomes using advanced analytical methods. This knowledge would also help better design and analyse clinical trials, providing evidence for re-evaluating existing medications, facilitating diagnosis and suggesting novel disease management. To facilitate my objective methodology, this thesis provides the following contributions: (i) I developed deep learning-based super-resolution (SR) techniques for optical coherence tomography (OCT) image enhancement and demonstrated that using super-resolved images improves the statistical power of clinical trials, (ii) I developed a deep learning algorithm for segmentation of retinal OCT images, showing that the methodology consistently produces more accurate segmentations than state-of-the-art networks, (iii) I developed a deep learning framework for refining the relationship between structural and functional measurements and demonstrated that the mapping is significantly improved over previous techniques, iv) I developed a probabilistic method and demonstrated that glaucomatous disc haemorrhages are influenced by a possible systemic factor that makes both eyes bleed simultaneously. v) I recalculated VF slopes, using the retinal never fiber layer thickness (RNFLT) from the super-resolved OCT as a Bayesian prior and demonstrated that use of VF rates with the Bayesian prior as the outcome measure leads to a reduction in the sample size required to distinguish treatment arms in a clinical trial

To Investigate the Foveal Avascular Zone in a Young Healthy Population Using Optical Coherence Tomography Angiography

Introduction/Aims Inflammatory diseases such as diabetes, glaucoma and age-related macular degeneration (AMD) can alter the size and shape of the foveal avascular zone (FAZ). Macular pigment (MP), a powerful antioxidant, located at the macula can protect the eye from oxidative stress damage. This study aims to investigate possible factors affecting the FAZ, such as vessel perfusion and overweight/obesity, in association with MP status in a young, healthy population. Normative values for FAZ size/shape and vascularity will also be proposed. Methods One hundred and fifty-four subjects aged 18-35 years old were recruited. Superficial FAZ area, diameter, ganglion cell layer, central macular thickness (CMT), vascular perfusion and density were measured by Optical Coherence Tomography Angiography (OCTA). FAZ area/vascularity were assessed in relation to body mass index (BMI), trunk fat % and macular pigment optical density (MPOD). Results Mean FAZ area was 0.22±0.07millimetres squared (mm2). Reduced vessel perfusion central (≤ 24%), low MPOD (≤ 0.4optical density units (OD)) and high BMI (\u3e 25kilograms (kg)/metre (m2)) were associated with a larger FAZ area on multivariate analysis. Age, vessel perfusion and CMT were all negative predictors of FAZ area. Trunk fat % was a positive predictor of FAZ area (p = 0.03) while BMI was positively correlated with FAZ area, (Pearson’s r = 0.18, p = 0.03). Conclusions Optical Coherence Tomography Angiography has potential as a screening tool aiding in the earlier detection and monitoring of eye diseases associated with oxidative stress i.e., hypertensive and diabetic retinopathy (DR), glaucoma and AMD. FAZ size in association with MPOD assessment, may be useful in detecting and advising patients at risk of retinal oxidative stress damage

Multimodal imaging in hereditary retinal diseases

Introduction. In this retrospective study we evaluated the multimodal visualization of retinal genetic diseases to better understand their natural course. Material and Methods. We reviewed the charts of 70 consecutive patients with different genetic retinal pathologies who had previously undergone multimodal imaging analyses. Genomic DNA was extracted from peripheral blood and genotyped at the known locus for the different diseases. Results. The medical records of 3 families of a 4-generation pedigree affected by North Carolina macular dystrophy were reviewed. A total of 8 patients with Stargardt disease were evaluated for their two main defining clinical characteristics, yellow subretinal flecks and central atrophy. Nine male patients with a previous diagnosis of choroideremia and eleven female carriers were evaluated. Fourteen patients with Best vitelliform macular dystrophy and 6 family members with autosomal recessive bestrophinopathy were included. Seven patients with enhanced s-cone syndrome were ascertained. Lastly, we included 3 unrelated patients with fundus albipunctatus. Conclusions. In hereditary retinal diseases, clinical examination is often not sufficient for evaluating the patient's condition. Retinal imaging then becomes important in making the diagnosis, in monitoring the progression of disease, and as a surrogate outcome measure of the efficacy of an intervention

CRB1-associated Retinal Dystrophies: Genetics, Clinical Characteristics and Natural History

PURPOSE: To analyse the clinical characteristics, natural history, and genetics of CRB1-associated retinal dystrophies. DESIGN: Multicenter international retrospective cohort study. METHODS: Review of clinical notes, ophthalmic images, and genetic testing results of 104 patients (91 probands) with disease-causing CRB1 variants. Macular optical coherence tomography (OCT) parameters, visual function, fundus characteristics, and associations between variables were our main outcome measures. RESULTS: The mean age of the cohort at the first visit was 19.8 ± 16.1 (median 15) years of age, with a mean follow-up of 9.6 ± 10 years. Based on history, imaging, and clinical examination, 26 individuals were diagnosed with retinitis pigmentosa (RP, 26%), 54 with early-onset severe retinal dystrophy/Leber Congenital Amaurosis (EOSRD/LCA, 51%), and 24 with macular dystrophy (MD, 23%). Severe visual impairment was most frequent after 40 years of age for patients with RP and after 20 years of age for EOSRD/LCA. Longitudinal analysis revealed a significant difference between baseline and follow up best corrected visual acuity in the three sub-cohorts. Macular thickness decreased in most patients with EOSRD/LCA and MD, whereas the majority of patients with RP had increased perifoveal thickness. CONCLUSIONS: A subset of individuals with CRB1 variants present with mild, adult-onset RP. EOSRD/LCA phenotype was significantly associated with null variants, and 167_169 deletion was exclusively present in the MD cohort. The poor OCT lamination may have a degenerative component, as well as being congenital. Disease symmetry and reasonable window for intervention highlight CRB1 retinal dystrophies as a promising target for trials of novel therapeutics