Unmet Need
According to the NIH, approximately 14,000 – 16,000 of prematurely born infants within the United States are affected by a form of retinopathy of prematurity (see NIH). Retinopathy of prematurity (ROP), is due to incomplete retinal vascularization that has the potential to lead to visual impairment as the infant grows. Currently, there are five stages that guide a physician’s assessment in terms of ROP severity, however, some cases of ROP can progress rapidly. A diagnostic platform that is able to further assist physician assessment and provide predictive potential for the subset of infants with rapidly progressing ROP onsets may evade future states of visual impairment and improve care. Therefore, there is a strong need for a diagnostic platform that may identify infants born with ROP that are at high-risk for developing severe visual impairment.
Technology Overview
Researchers at Johns Hopkins have developed a novel computational diagnostic platform capable of predicting onset of retinopathy of prematurity. This invention is capable of stratifying infants at risk for ROP with 85% accuracy and the potential to assist in diagnostic settings to improve the care of infants that may possess forms of rapid progression.
Stage of Development
Diagnostic algorithm is complete with further large-scale validation pending.
Publication
N/A
