AI in eye scans helps improve diagnosis of inherited retinal disease
Inherited retinal diseases (IRDs), single-gene disorders affecting the retina, are very difficult to diagnose since they are uncommon and involve changes in one of many candidate genes. Outside specialist centres, there are few experts who have adequate knowledge of these diseases, and this makes it difficult for patients to access proper testing and diagnosis. But now, researchers from the UK and Germany have used artificial intelligence (AI) to develop a system that they believe will enable more widespread provision of testing, together with improved efficiency.
Eye2Gene, an AI system is capable of identifying the genetic cause of IRDs from retinal scans.
The researchers were able to utilise Moorfields Hospital’s vast database of information on IRDs, covering over 30 years of research.
Identification of the gene involved in a retinal disease is often guided by using the patient’s phenotype defined using the Human Phenotype Ontology (HPO). The HPO involves the use of standardised and structured descriptions of medical terms of a patient’s phenotype, which are observable characteristics of an individual resulting from the expression of genes, to allow scientists and doctors to communicate more effectively. “However, HPO terms are often imperfect descriptions of retinal imaging phenotypes, and the promise of Eye2Gene is that is can provide a much richer source of information than HPO terms alone by working directly from the retinal imaging,” says Dr Pontikos.
The team benchmarked Eye2Gene on 130 IRD cases with a known gene diagnosis for which whole exome/genome, retinal scans, and detailed HPO descriptions were available, and compared their HPO gene scores with the Eye2Gene gene scores. They found Eye2Gene provided a rank for the correct gene higher or equal to the HPO-only score in over 70% of cases.
Dr Nikolas Pontikos et al,EUROPEAN SOCIETY OF HUMAN GENETICS
B.Sc Life Sciences, M.Sc Biotechnology, B.Ed