A prospective multicentre study published in JAMA Neurology has validated the high accuracy of neuropacs™ AI technology in diagnosing Parkinson’s disease (PD) and atypical parkinsonism, including multiple system atrophy parkinsonian variant (MSA-P) and progressive supranuclear palsy (PSP). Conducted across 21 movement disorder centres in the US and Canada, the study involved 249 patients who underwent diffusion MRI scans on Siemens, General Electric, and Philips 3T scanners. The neuropacs™ AI software analysed these scans and achieved 96% accuracy in differentiating PD from atypical parkinsonism and 98% accuracy in distinguishing between MSA-P and PSP. Its diagnoses were further confirmed in 93.9% of postmortem autopsies.
Accurate differentiation between PD, MSA-P, and PSP remains a significant clinical challenge, even for experienced specialists, with studies indicating that up to 45% of clinically diagnosed PD cases are later found to be a different form of parkinsonism. The findings of this study underscore the urgent need for reliable, AI-driven biomarkers to improve parkinson’s diagnosis and guide treatment decisions earlier in the disease process.
“This is an important milestone for the parkinsonism community, including clinical providers and, most importantly, patients,” said David Vaillancourt, Ph.D., a Professor and the Orchid Endowed Chair of the Department of Applied Physiology & Kinesiology at the University of Florida, neuropacs™ co-Founder & Chief Scientific Officer, and Principal Investigator of the study. “We anticipate that the neuropacs™ AI technology will revolutionise the current standard of care for parkinson’s diagnosis and will have far-reaching impacts on clinical care and clinical trial testing of new therapeutics.”
Kristophe Diaz PhD, Executive Director and Chief Science Officer of CurePSP, added that, “Proper diagnosis of PSP remains a critical need to decrease burden for people living with the disease and ensure they receive proper clinical care as soon as possible. The results of this study are exciting progress towards a non-invasive and clinically scalable solution to help improve diagnosis. We look forward to seeing how the findings of this study can further impact the PSP community and advance our shared goal of better outcomes for all.”
Read the full press release here.
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