Exploring the implications of widespread decreases in dynamic blood flow to the retina and choroid in dry macular degeneration

Iowa City Va Medical Center, Iowa City IA

Investigators

Abstract

Applicant: Edward F, Linton, MD is a fellowship-trained Neuro-Ophthalmologist with a long-term goal of becoming an independently funded translational clinician scientist, advancing sight-saving research with expertise in multimodal imaging and functional assessment of the optic nerve and retina. An over-reaching goal is to restore function in patients with visual loss (rehabilitation) and to intervene in patients with progressive forms of vision loss (prevention). Introduction: Poor blood flow has been identified as a risk factor for blindness from age-related non-exudative macular degeneration (AMD). To save vision, research in choroidal perfusion and its normalization is needed in AMD patients. This will be accomplished using an imaging technique that measures the dynamics of ocular blood flow, laser speckle flowgraphy (LSFG), to complement imaging of vascular structure, using Optical Coherence Tomography Angiography (OCT-A). This will enable the identification and monitoring of patients at high risk of progression to advanced stages of AMD, who will be candidates for emerging interventions to increase blood flow. Precise understanding of blood flow in AMD patients is required to capitalize on these treatments to prevent vision loss and restore function in the millions of Americans at risk. Our preliminary data using LSFG in the choroid and retina in a retrospective case-control study showed that ocular blood flow is reduced in large areas even in early and intermediate AMD, which agrees with previous literature. Methods: This proposal centers on a cross-sectional study of patients with non-exudative age-related macular degeneration in the early, intermediate and advanced stages, as well as a cohort of control subjects stratified by age. Blood flow will be measured in across a wide area of retina, including the macula, with laser speckle flowgraphy, using standard techniques and a novel approach with a wide field montage image. Blood flow will be compared between controls and patients with AMD at each stage to test the hypothesis that blood flow is measurably reduced in all stages of dry AMD, after controlling for other risk factors. Repeat variability of blood flow measurements will be assessed in preparation for following patients longitudinally to assess risk of progression as a function of reduced blood flow. To test the hypothesis that blood flow reduction may precede structural changes in the retina, we will compare the areas of reduced flow to the corresponding locations of retina containing photoreceptors, retinal pigmented epithelium and underlying choroid. Once we have established baseline studies of the cohort of AMD patients and age-matched control subjects in the proposed 2-year CDA-1 study, we will plan to study these subjects longitudinally in a follow-on prospective cohort study, which the applicant will be well positioned to perform as part of a future career development proposal (CDA-2). Career Development: Formal training will consist of university coursework in biostatistics related to clinical research design, as well as internet-based coursework in Python programming for data science, image processing, and introductory deep learning. Weekly interactions with mentors will advance skills in the design, execution, and coordination of clinical research, techniques for image analysis of OCT, OCTA, and LSFG, and communication of results. Primary mentor is Randy Kardon, MD, PhD, a neuro-ophthalmologist and career VA clinician scientist with specific expertise in structural, functional, and blood flow assessments of the retina and optic nerve. Co-mentor Elliott Sohn, MD is a vitreoretinal surgeon-scientist with expertise in the role of the choroid in the development of age-related macular degeneration, from genetics and histology to imaging including sophisticated OCT analysis of the choroid. Co-mentor Jui-Kai Wang PhD is an engineer and research scientist with expertise in developing deep learning approaches to ophthalmic image analysis. The mentors and career development activities will ensure Dr. Linton’s success in carrying out the proposed study and in his future career as a VA translational scientist.