A machine learning approach from diffusion tensor imaging (DTI) multi-spectral diffusion weighted imaging (DWI) showed prediction of gait dysfunction in PD according to a study released today at the International Congress of Parkinson’s Disease and Movement Disorders® in Copenhagen, Denmark.
COPENHAGEN, Denmark, Aug. 27, 2023 /PRNewswire-PRWeb/ — A machine learning approach from diffusion tensor imaging (DTI) multi-spectral diffusion weighted imaging (DWI) showed prediction of gait dysfunction in PD according to a study released today at the International Congress of Parkinson’s Disease and Movement Disorders® in Copenhagen, Denmark.
Several neuroimaging studies in Parkinson’s disease (PD) suggest an altered interplay between cortical and subcortical brain areas at a structural and functional level each that contributes to gait dysfunction in PD.
This study used 7 different quantitative DTI measures from 43 PD patients along with UPDRS III, to develop a prediction model for gait dysfunction using different machine learning approaches and 60 template regions of interest (ROIs). The analysis concluded that the multilayer perceptron (MLP) machine learning approach with 5 hidden layers and Rectified Linear Unit (ReLU) activation performed best to predict gait dysfunction in PD with an area under the curve (AUC) of 0.78.
Klaus Seppi, Director of the Department of Neurology at the Hospital Kufstein and Professor for Neurology with the focus on Movement Disorders of the Department of Neurology at the Medical University Innsbruck, responded to this study.
“Recent advances in MR methodology allowing quantitative evaluation of biochemical changes and macro- and microstructural alterations as well as analytic approaches including voxel-based analyses, machine-learning techniques and other post-processing algorithms have gained growing popularity in medical image analysis offering insights into the pathophysiology underlying key symptoms such as gait dysfunction in PD,” Seppi said. “This study suggests that a machine learning approach of DTI analysis may have potential in predicting gait dysfunction in PD patients if confirmed by larger confirmative studies. Moreover, future studies have to explore if this pattern changes with disease progression.”
View the full-text abstract:
http://www.mdsabstracts.org – Reference #: 297
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The MDS International Congress is the premiere annual event to advance the clinical and scientific discipline of Movement Disorders, including Parkinson’s disease. Convening thousands of leading clinicians, scientists and other health professionals from around the globe, the International Congress will introduce more than 1,800 scientific abstracts and provide a forum for education and collaboration on latest research findings and state-of-the-art treatment options.
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