Diabetic retinopathy (DR) remains the leading cause of blindness, affecting over 4 million Americans. The prediction of DR progression and treatment outcome holds the key in the care for DR and the prevention of vision-threating conditions. However, clinicians are now faced with the challenge of limited established predictors for the development of DR and treatment response. Our hypothesis is that capillary dysfunction, as the central crux of the DR pathology, is a sensitive predictor of DR progression and treatment outcome. In diabetic eyes, hyperglycemia leads to capillary dysfunction which leads to a breakdown of the blood retinal barrier (BRB) resulting in capillary leakage. This capillary dysfunction further leads to capillary loss and non- perfusion, which causes ischemic hypoxia. The combined effects of capillary leakage and hypoxia results in neovascularization and retinal hemorrhage, signifying the onset of proliferative DR. In this pathogenic process, capillary leakage, oxygenation, and capillary blood flow are three key aspects of capillary function, and therefore have become our targets of imaging and quantification. We have developed visible light optical coherence tomography (OCTA) to non-invasively quantify blood oxygenation at the capillary level. We have also shown that measuring the dynamics of near infrared OCTA allows quantification of the flow dynamics of capillary flow. The quantification of both oxygenation and flow dynamics provides measurement of capillary perfusions. In addition, we have developed a novel multimodal 3D imaging technique, oblique scanning laser ophthalmology (oSLO), which unprecedentedly enables wide-field 3D fluorescence imaging in the retina. Since the administration of fluorescein dye is a component of the standard of care and fluorescein angiography (FA) is the gold standard for diagnosing DR, the 3D imaging capability of oSLO can uniquely provide sensitive detection of dye leakage. Taken altogether, we will explore three specific aims. 1) To develop a multimodal oSLO/OCT system to quantify capillary blood oxygenation, flow dynamics, and leakage, with large field of view, high resolution and high speed. 2) To conduct a pilot clinical study to assess the correlation of DR severity to retinal capillary function in humans. 3) To explore the prognostic value of imaging markers for capillary functions that can predict anti-VEGF treatment response. IMPACT ON PUBLIC HEALTH: 1) The success of this project will lead to a groundbreaking new imaging device that is currently not available. 2) The validity of the imaging method could also lead to further clinical studies on predictive imaging markers on DR progression and treatment response. 3) The multiple measurements of capillary functions will provide further insight into the pathophysiology and new treatment strategies for this debilitating eye disease.

Public Health Relevance

Prediction of diabetic retinopathy (DR) progression and treatment response holds the key to prevent vision- threatening conditions. We hypothesize that capillary dysfunction is a valid predictor of DR since it is the central crux of the DR pathology. However, existing retinal imaging techniques are still inadequate to provide comprehensive quantification of retinal capillary functions. To address this void, we propose to develop a multimodal volumetric imaging technique to quantify capillary level oxygenation, capillary flow dynamics, and capillary leakage in the retina. We also propose to perform two clinical studies to examine predictive imaging markers. The successful implementation of the technique could lead to a significant clinical impact on preventing vision loss by being able to predict DR progression and treatment outcome.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS108464-02
Application #
9786826
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Bosetti, Francesca
Project Start
2018-09-30
Project End
2023-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Boston Medical Center
Department
Type
DUNS #
005492160
City
Boston
State
MA
Country
United States
Zip Code
02118