The proposed study will utilize in vivo, ultra-high resolution, adaptive optics scanning laser ophthalmoscopy (AOSLO) in combination with spectral domain optical coherence tomography (SDOCT) to identify combined characteristics of vascular and neural retina in the human diabetic eye that predict future vision loss and response to anti-vascular endothelial growth factor (antiVEGF) agents. Despite advances in treatment for diabetic eye complications, including laser photocoagulation and the recent use of intravitreal steroids and antiVEGF agents, diabetes continues to be the leading cause of preventable blindness in working age adults. Given the rapidly increasing global epidemic of diabetes and its associated complications of diabetic macular edema (DME) and proliferative diabetic retinopathy (DR) as well as our current inability to reliably predict future visual outcomes, these efforts address a critical need. The ability to accurately predict long term visual potential after treatment for DME could dramatically improve care for patients, reveal underlying mechanisms of vision loss, and speed efficacy evaluation of novel therapies. The studies proposed here utilize the innovative technology of AOSLO to correct over 90% of the optical aberrations in an individual eye resulting in retinal image resolution of 2 ?m. Using AOSLO, our group has visualized and demonstrated perfusion of characteristic DR lesions such as microaneurysms and retinal neovascularization even when they are not identifiable or visibly perfused on standard fundus photographs. Our preliminary data demonstrate that wall hyperreflectivity of microaneurysms on AOSLO and retinal inner layer disorganization on SDOCT images are both associated with worse visual acuity in eyes of patients with DME. Furthermore, we have shown that retinal inner layer disorganization is predictive of future VA even once DME has resolved. We now propose long term, prospective studies that will build upon these early findings to develop multivariable models predictive of future vision and treatment response to antiVEGF in eyes with DME and proliferative DR. The simultaneous evaluation of retinal vascular and neural components in vivo at high resolution in the human eye will allow comprehensive evaluation of diabetic retinal pathology, and increase chances for identification of anatomic factors predictive of visual outcome and response to antiVEGF therapy. This proposal leverages the technological advances represented by deformable mirror technology incorporated into the AOSLO along with the study team's extensive experience in the design and implementation of clinical trials for diabetic retinopathy and its access to the unique Joslin Diabetes Center patient population. The high rates of diabetic ocular pathology in this cohort will make the proposed studies readily achievable within the overall 5 year time frame. Given that these results may help predict vision outcomes and response to antiVEGF treatment in the diabetic eye, this work could have a major impact on future strategies for patient care and research for novel therapeutics in DR and DME.

Public Health Relevance

Diabetic retinopathy and diabetic macular edema continue to be the leading causes of visual loss in the working age population of the United States and other developed countries. An important unmet need exists for predictors of visual and anatomic outcomes in these conditions in both treated and untreated eyes in order to improve patient care, reveal response mechanisms, and speed evaluation of new therapies. This study could substantiate the novel use of adaptive optics retinal imaging for prediction of visual outcomes and anti- vascular endothelial growth factor treatment response in eyes with vascular and neural pathology from diabetes.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
Project #
Application #
Study Section
Program Officer
Shen, Grace L
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Joslin Diabetes Center
United States
Zip Code
Bernabeu, Miguel O; Lu, Yang; Abu-Qamar, Omar et al. (2018) Estimation of Diabetic Retinal Microaneurysm Perfusion Parameters Based on Computational Fluid Dynamics Modeling of Adaptive Optics Scanning Laser Ophthalmoscopy. Front Physiol 9:989
Lammer, Jan; Karst, Sonja G; Lin, Michael M et al. (2018) Association of Microaneurysms on Adaptive Optics Scanning Laser Ophthalmoscopy With Surrounding Neuroretinal Pathology and Visual Function in Diabetes. Invest Ophthalmol Vis Sci 59:5633-5640
Karst, Sonja G; Lammer, Jan; Radwan, Salma H et al. (2018) Characterization of In Vivo Retinal Lesions of Diabetic Retinopathy Using Adaptive Optics Scanning Laser Ophthalmoscopy. Int J Endocrinol 2018:7492946
Duh, Elia J; Sun, Jennifer K; Stitt, Alan W (2017) Diabetic retinopathy: current understanding, mechanisms, and treatment strategies. JCI Insight 2:
Lu, Yang; Bernabeu, Miguel O; Lammer, Jan et al. (2016) Computational fluid dynamics assisted characterization of parafoveal hemodynamics in normal and diabetic eyes using adaptive optics scanning laser ophthalmoscopy. Biomed Opt Express 7:4958-4973
Lammer, Jan; Prager, Sonja G; Cheney, Michael C et al. (2016) Cone Photoreceptor Irregularity on Adaptive Optics Scanning Laser Ophthalmoscopy Correlates With Severity of Diabetic Retinopathy and Macular Edema. Invest Ophthalmol Vis Sci 57:6624-6632
Bernabeu, Miguel O; Yang Lu; Lammer, Jan et al. (2015) Characterization of parafoveal hemodynamics associated with diabetic retinopathy with adaptive optics scanning laser ophthalmoscopy and computational fluid dynamics. Conf Proc IEEE Eng Med Biol Soc 2015:8070-3
Sun, Jennifer K; Radwan, Salma H; Soliman, Ahmed Z et al. (2015) Neural Retinal Disorganization as a Robust Marker of Visual Acuity in Current and Resolved Diabetic Macular Edema. Diabetes 64:2560-70