This Project Grant award of $580,331 from the National Eye Institute (CFDA 93.867 - Vision Research) aims to develop a deep learning-based diagnostic tool for retinopathy of prematurity (ROP), a leading cause of childhood blindness. The key products and services to be delivered under this award include: Optimizing and testing an animal-to-human (A2H) model to augment the training dataset for the deep learning-based ROP diagnostic model, using existing and newly acquired longitudinal animal ROP...
This Project Grant awarded by the National Eye Institute (NEI) under the Vision Research program (CFDA 93.867) funds the development and evaluation of novel surrogate augmented deep predictive learning algorithms to predict referral-warranted retinopathy of prematurity (RW-ROP). The primary goals are to: Develop algorithms that leverage early retinal images and demographic factors to accurately predict RW-ROP, enabling earlier identification of high-risk infants for close monitoring and...
This federal Project Grant award from the National Eye Institute (NEI) under the Vision Research program (CFDA 93.867) provides $881,796 to Siloam Vision, Inc. to develop two advanced, laser-based, AI-enabled retinal imaging systems. The key innovations are: A wider field-of-view camera design that can be paired with either a scanning laser ophthalmoscope (SLO) or optical coherence tomography (OCT) system, offering 2D or 3D imaging, respectively. This aims to address an unmet need in retinopathy...
This Project Grant award from the National Eye Institute (NEI), under the Vision Research federal grant program (CFDA 93.867), is providing $306,462 to Ifocus Imaging LLC to develop a software platform called OCT-ART-DR. The platform will automate the diagnosis and staging of diabetic retinopathy using optical coherence tomography angiography (OCTA) imaging and artificial intelligence. The key products to be delivered under this award include: 1) Improved AI-based segmentation of OCTA image...
The National Eye Institute (NEI), under the Department of Health and Human Services, awarded a $745,607 Project Grant through the Vision Research program (CFDA 93.867) to Retivue LLC, a for-profit limited liability company located in Charlottesville, Virginia. The grant supports the development of the Retivue Entire Eye, a handheld, high-resolution, non-contact, widefield retinal screening camera for premature and healthy newborn babies. The goal is to provide a simplified, single-image...
This Project Grant award from the National Eye Institute (NEI), under the federal Vision Research grant program (CFDA 93.867), supports research aimed at addressing key manufacturing hurdles for producing autologous cell therapies to treat inherited retinal degenerative blindness. The $618,600 award to the University of Iowa, with a performance period from March 1, 2025 to February 28, 2030, has two specific aims: Developing an AI algorithm to select patient-derived induced pluripotent stem cell...
This Project Grant award from the National Eye Institute (NEI) under the Vision Research federal grant program (CFDA 93.867) will fund the development of a new wide-field visible-light optical coherence tomography (WF-VIS-OCT) device to evaluate the oxygen-induced retinopathy (OIR) model in rats. The $623,090 award, effective September 1, 2024, will support the Oregon Health & Science University in three main efforts: 1) developing the WF-VIS-OCT system with 5-mm transverse resolution over a...
The National Eye Institute (NEI), under the federal Vision Research program (CFDA 93.867), awarded a $770,000 Project Grant to the Augusta University Research Institute, Inc. (doing business as Georgia Health Sciences) to support research aimed at identifying novel mechanisms and developing a new therapy for Retinopathy of Prematurity (ROP), the leading cause of preventable blindness in children. The research project, which runs from September 2024 to September 2025, will investigate the...
This Project Grant award from the National Eye Institute (NEI), under the Vision Research (CFDA 93.867) program, provides $2,636,322 to the University of Wisconsin-Madison to investigate an AI-based system to improve eye screening and follow-up care rates for patients with diabetes, particularly in socioeconomically disadvantaged communities. The study aims to determine if the "AI-Bridge" intervention can improve screening and follow-up rates across races/ethnicities and reduce...
This federal Project Grant award from the National Eye Institute (CFDA 93.867 - Vision Research) provides $628,531 to the University of Miami to validate and implement an artificial intelligence machine-to-machine (M2M) model for equitable glaucoma screening in underserved populations. The key objectives are to: 1) Refine the M2M model using large clinic and population-based datasets to improve accuracy and robustness for glaucoma screening, 2) Implement the M2M model for opportunistic...
VALIDATION OF ARTIFICIAL INTELLIGENCE (AI) BASED SOFTWARE AS MEDICAL DEVICE (SAMD) FOR RETINOPATHY OF PREMATURITY (ROP) - THE PURPOSE OF THIS APPLICATION IS TO PERFORM THE NECESSARY CLINICAL STUDIES TO SEEK REGULATORY APPROVAL FOR AN ARTIFICIAL INTELLIGENCE (AI) SOFTWARE AS MEDICAL DEVICE (SAMD) FOR RETINOPATHY OF PREMATURITY (ROP) DIAGNOSIS. ROP IS A LEADING CAUSE OF CHILDHOOD BLINDNESS WORLDWIDE, WITH APPROXIMATELY 50,000 BABIES GOING BLIND ANNUALLY, MOST OF WHICH IS PREVENTABLE WITH ACCURATE AND TIMELY DIAGNOSIS. THE I-ROP DL ALGORITHM WAS DEVELOPED BY THE I-ROP RESEARCH CONSORTIUM AND HAS BEEN SHOWN TO PROVIDE EXPERT-LEVEL DIAGNOSIS OF PLUS DISEASE, A COMPONENT OF SEVERE ROP, BASED ON IMAGES FROM THE RETCAM (NATUS, MIDDLETON, WI) DIGITAL FUNDUS CAMERA. THE OUTPUT IS A VASCULAR SEVERITY SCORE (VSS) THAT CORRESPONDS TO SPECTRUM OF PLUS DISEASE, AS DEFINED BY THE INTERNATIONAL CLASSIFICATION OF ROP, AND HAS BEEN ENDORSED BY THE FOOD & DRUG ADMINISTRATION (FDA) AS AN APPROPRIATE OUTPUT FOR AN ROP SAMD. IF INCORPORATED INTO A CLINICAL WORKFLOW, THIS TECHNOLOGY COULD PROVIDE AUTOMATED, IMMEDIATE, EXPERT-LEVEL DIAGNOSIS OF ROP TO THE BEDSIDE, SOLVING ONE OF THE KEY GAPS IN CARE THAT RESULTS IN PREVENTABLE BLINDNESS WORLDWIDE. THE FIRST AIM OF THIS PROJECT IS TO UPDATE AND RETRAIN THE I-ROP DL ALGORITHM TO IMPROVE SPEED AND REPEATABILITY FOR CLINICAL USE, FINALIZE THE IMAGE QUALITY AND PRE-PROCESSING PIPELINE, AND INTEGRATE IT INTO THE ITELEGEN DATA MANAGEMENT SYSTEM, AN ROP TELEMEDICINE SOFTWARE PLATFORM. THE SECOND AIM IS TO PERFORM THE NECESSARY CLINICAL STUDIES FOR THE TWO PROPOSED INDICATIONS FOR USE (IFU): THE FIRST IFU WILL BE AS AN ASSISTIVE DIAGNOSTIC STUDY TO IMPROVE THE CLINICAL DIAGNOSIS OF PLUS DISEASE WITH REGULATORY APPROVAL BASED ON A MULTI-READER MULTI-CASE STUDY WITH A PRIMARY OUTCOME OF IMPROVED DIAGNOSIS OF PLUS DISEASE, BASED ON A FIVE EXPERT REFERENCE STANDARD DIAGNOSIS, WITH THE USE OF THE VSS. THE SECOND IFU WILL BE FOR AUTONOMOUS ROP SCREENING FOR MORE THAN MILD ROP (MTMROP, DEFINED AS TYPE 2 OR WORSE ACCORDING TO THE EARLY TREATMENT FOR ROP STUDY DEFINITION). THE PIVOTAL STUDY WILL HAVE A PRIMARY OUTCOME OF 85% SENSITIVITY AND 85% SPECIFICITY FOR THE DIAGNOSIS OF MTMROP, WITH A SECONDARY OUTCOME OF GREATER THAN 95% SENSITIVITY FOR DETECTION OF TREATMENT-REQUIRING ROP. THE THIRD AIM OF THE PROPOSAL IS TO VALIDATE THE I-ROP DL ALGORITHM ON A DIGITAL FUNDUS CAMERA MADE BY FORUS HEALTH (BENGALURU, INDIA), A DIGITAL EYE CARE COMPANY, WITH ROP CAMERA DISTRIBUTION IN MORE THAN 20 COUNTRIES. IF SUCCESSFUL, THEN ONCE FDA APPROVAL IS OBTAINED ON THE RETCAM IT MAY BE EXTENDED THROUGH A 510K PROCESS TO A CAMERA THAT IS MORE AFFORDABLE THAN THE RETCAM AND WIDELY AVAILABLE IN LOW- AND MIDDLE-INCOME COUNTRIES. THIS WORK WILL BE DONE BY SILOAM VISION, A COMPANY STARTED BY TWO OF THE INVENTORS OF THE I-ROP DL ALGORITHM, IN CONJUNCTION WITH OREGON HEALTH & SCIENCE UNIVERSITY. AT THE END OF THE STUDY PERIOD, THE GOAL WILL BE TO HAVE THE NECESSARY DATA TO SUPPORT FDA APPROVAL OF THE I-ROP DL ALGORITHM FOR TWO IFUS ON TWO DIGITAL FUNDUS CAMERAS AND BEING ONE STEP CLOSER TO BRINGING THIS TECHNOLOGY TO THE BEDSIDE TO REDUCE THE NUMBER OF BABIES GOING BLIND FROM ROP WORLDWIDE.