Current clinical assessments of Parkinson's disease rely largely on functional scales, which lack sensitivity to subtle muscle alterations.Therefore, developing objective and quantitative tools to support both diagnosis and disease monitoring is needed.Quantitative ultrasound radiofrequency imaging, particularly through Nakagami analysis, offers a non-invasive means of characterizing tissue scattering properties that may reflect Parkinson's disease -related effects.This study aimed to assess the feasibility of quantitative ultrasound radiofrequency imaging in identifying muscle alterations and disease severity in individuals with Parkinson's disease.Seventeen individuals with Parkinson's disease and 14 healthy controls participated in this study.Patients with Parkinson's disease were divided into early and late stages based on the Hoehn and Yahr scale.Quantitative ultrasound radiofrequency data were collected on each individual's gastrocnemius medialis, tibialis anterior, triceps brachii, and biceps brachii, and analyzed to estimate the Nakagami m parameter.The Nakagami m parameter was significantly higher in patients with Parkinson's disease compared to healthy controls across all muscles, with the largest differences in the gastrocnemius medialis.The Nakagami m parameter in this muscle was strongly associated with disease severity and showed excellent diagnostic performance.No significant asymmetry was observed between the most and least affected limb.These data indicate that quantitative ultrasound radiofrequency Nakagami imaging can detect muscle microstructural alterations associated with Parkinson's disease and is associated with disease severity.This approach shows strong potential as a rapid, low-cost, and quantitative biomarker for the diagnosis and longitudinal monitoring of Parkinson's disease.
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Baptiste Bizet
Michele Trinchi
Francesca Nardello
Neuroscience
University of Verona
University of Trento
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Bizet et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d894526c1944d70ce053f2 — DOI: https://doi.org/10.1016/j.neuroscience.2026.04.002