Researchers have developed an innovative approach to diagnosing multiple sclerosis (MS) using advanced eye imaging techniques.
It integrated two types of eye scans: optical coherence tomography (OCT) and infrared scanning laser ophthalmoscopy (IR-SLO).
By training computer models with large numbers of these eye scans, the researchers have created a diagnostic tool that they say can identify MS with “remarkable accuracy.
What sets this approach apart is its ability to detect subtle changes in the eye that are often indicative of MS. The eye, being directly connected to the brain, can reveal early signs of neurological damage that might otherwise go unnoticed.
By training computers to recognise hidden patterns and abnormalities in eye images, this method offers the potential for earlier diagnosis and better management of Multiple Sclerosis symptoms.
The results of the study are impressive, with the computer model correctly identifying MS in 92 per cent of cases during initial tests.
The system maintained a strong 85 per cent accuracy when tested on a different set of data from other hospitals and populations, demonstrating its reliability and potential for widespread use.
Dr Kafieh of Durham University’s engineering department emphasised the significance of these findings and said: “Incorporating all available medical imaging, including those with subtle changes that are difficult to discern through non-computerised diagnosis, is crucial for achieving more reliable diagnoses and improving patient outcomes.”
This approach could have far-reaching implications for patients and healthcare providers alike, the researchers say. Early and accurate diagnosis of MS can dramatically impact the quality of life for those affected, potentially slowing the progression of the disease and improving overall outcomes.
The non-invasive nature of eye scans makes this method more comfortable for patients and easier to implement in various healthcare settings, including high street opticians.
The eye imaging technique also opens doors for similar applications in other neurological conditions such as Alzheimer’s and Parkinson’s disease, according to the study authors.
