Advancing Parkinson’s Disease Diagnosis Through Digital Biomarkers

Wednesday, July 03, 2024

BrainTale, a medtech company that originated from the Paris Region Greater Hospitals, showcased its innovative approach at the European Academy of Neurology (EAN) congress in Helsinki, Finland, held from June 29 to July 02, 2024.

During their presentation, co-founder and scientific director, and data scientist, presented data demonstrating their ability to differentiate Parkinson's disease (PD) from closely related conditions such as Multisystem Atrophy (MSA) and Progressive Supranuclear Palsy (PSP).

This distinction is critical due to the overlapping clinical symptoms among these neurodegenerative disorders, which collectively affect around 5 million people worldwide.

In their oral communication titled "Differential diagnosis model in parkinsonian syndromes derived from calibrated diffusion tensor imaging," BrainTale reported on a study involving 189 subjects from three prospective trials.

These trials included 92 PD patients, 45 MSA patients, and 42 PSP patients. BrainTale utilized diffusion tensor imaging (DTI) to automatically process data and derive specific white matter markers.

Their supervised learning classification model, evaluated through receiver operating function (ROC) analysis, achieved significant results: a mean area under the ROC curve of 0.87 ± 0.05, mean specificity of 0.74 ± 0.10, and mean sensitivity of 0.90 ± 0.07.

These findings underscore the potential of BrainTale's technology to improve the accuracy of differential diagnoses in parkinsonian syndromes, particularly in distinguishing PD from MSA and PSP.

Neuroradiologist at Paris Region Greater Hospitals and Director at the Brain Institute, highlighted the platform's accessibility and clinical relevance.

He noted that BrainTale's approach not only aids in improving patient care through non-invasive diagnostics but also advances the understanding of disease pathophysiology, potentially accelerating treatment development.


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