In March, the Malone Center for Engineering in Healthcare (MCEH) and the Johns Hopkins Wilmer Eye Institute announced a joint seed grant initiative to fund research that applies engineering solutions to ophthalmology-related problems. These grants – up to $50,000 each – promote new collaborative research between Wilmer and Malone faculty.

Proposals were reviewed and evaluated by an internal faculty committee. Ultimately, two projects were awarded funding to advance research related to detecting and treating ocular diseases.

The projects receiving grants are:

Automated Detection of Proliferative Sickle Cell Retinopathy
Research Team: Adrienne Scott (Wilmer Eye Institute); Mathias Unberath and Craig Jones (MCEH/Computer Science)

Proliferative sickle cell retinopathy (PSR) is a vision-threatening complication of sickle cell disease, the most common inherited blood disorder in the United States. The hallmark feature of PSR visible on a retinal exam is known as sea fan neovascularization. In a previous collaboration, the team found that a deep learning system can detect sea fan neovascularization characteristic of PSR from ultra-widefield fundus photographs with high sensitivity and specificity. The system was trained from 1,131 de-identified ultra-widefield color fundus photographs, retrospectively collected from 181 Wilmer patients with sickle cell disease but never previously treated for PSR.

Based on these encouraging results, ophthalmologist Adrienne Scott and computer scientists Mathias Unberath and Craig Jones aim to build prospective and additional retrospective databases of fundus photographs to validate and refine their existing algorithm. Automated screening technology can offer a rapid, reproducible, and relatively cost-effective approach to screening patients with sickle cell disease for early signs of PRS. Ultimately, the teams hopes to deploy this technology in places where patients may not have access to high-quality healthcare, and to identify those who most need referral to a retina specialist for preventative treatment.

Comparison of 2D and 3D Neural Networks for Establishing Structure-Function Correlations in Age-Related Macular Degeneration using Optical Coherence Tomography Images
Research Team: T.Y. Alvin Liu, Peter Campochiaro, Anam Akhlaq (Wilmer Eye Institute); Craig Jones (MCEH/CS)

Neovascular age-related macular degeneration (NVAMD) is the leading cause of central vision loss in US adults over 50 years of age. Although optical coherence tomography (OCT) has revolutionized the diagnosis and management of this disease, OCT analysis still has limitations; commonly-used OCT metrics, including central subfield thickness (CST), are not good predictors of functional outcomes like visual acuity, or the clarity and sharpness of one’s vision.

A promising strategy to create a clinical tool that can predict function based on OCT images is to harness the power of deep learning. Led by ophthalmologist T.Y. Alvin Liu and computer scientist Craig Jones, the research team plans to develop an alternative OCT metric by training a deep learning algorithm that more closely correlates structure (OCT image) with visual acuity. Such a meaningful metric will provide a useful secondary endpoint in clinical trials for new NVAMD therapies, and provide clinicians a new tool for tracking progression/improvement in NVAMD patients.

• The Malone Center Seed Grant Program aims to assist faculty and research staff with development of innovative, collaborative proposals that will advance the Malone Center mission. New partnerships and research directions are often achieved, opening up opportunities that may otherwise not come to fruition. The center has awarded ten Seed Grants since the program’s inception in 2018.

The next deadline for Malone Seed Grants is November 1, 2020. Interested in applying for a Malone Seed Grant? How to apply  >>