MDS Abstracts

Abstracts from the International Congress of Parkinson’s and Movement Disorders.

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Articles tagged "Magnetic resonance imaging(MRI)"

  • 2024 International Congress

    Prediction of The Monopolar Review in Deep Brain Stimulation for Parkinson’s Disease using Imaging

    V. Lavu, M. Godhala, T. Batchali, S. Aghili-Mehrizi, J. Wong (Gainesville, USA)

    Objective: To build an AI model that can predict the monopolar review in deep brain stimulation (DBS) for Parkinson’s disease (PD) based on imaging. Background:…
  • 2024 International Congress

    Accuracy of AI-driven automated diagnostic software analyzing Susceptibility Map-Weighted Imaging to Differentiate Neurodegenerative from Non-neurodegenerative Parkinsonism

    E. Wallert, E. V.D. Giessen, M. Beudel, T. van Mierlo, J. Blankevoort, DH. Shin, R. de Bie, J. Booij (Amsterdam, Netherlands)

    Objective: To determine the accuracy of AI-driven automated diagnostic software analyzing susceptibility map-weighted imaging (SMWI) to distinguish neurodegenerative from non-neurodegenerative parkinsonism in patients who had…
  • 2024 International Congress

    From Images to Insights: Subtyping Parkinson’s Disease Using Unsupervised Learning on MRI Data

    D. Teixeira-Dos-Santos, A. De-Oliveira-Franco, A. Bieger, C. Mattjie, F. Suzuki, G. Magalhães Pereira, J. Rossi Catao, L. Angi Souza, L. Silveira Kupssinskü, L. Vinícius Moura, MA. Machado Schlindwein, R. Ravazio, S. Duarte Pinto, T. Hugentobler Schlickmann, E. R. Zimmer, MA. de Bastiani, R. C. Barros, AF. Schumacher Schuh (Porto Alegre, Brazil)

    Objective: To explore the heterogeneity of Parkinson's disease (PD) using unsupervised clustering of neuroimaging data, aiming to identify distinct subtypes based on volumetric features. Background:…
  • 2024 International Congress

    Responsive morphometric fingerprints in deep brain stimulation for Parkinson’s disease

    Y. Lai, Y. Pan, N. He, P. Huang, F. Wang, C. Ying, M. Hnazaee, C. Cao, V. Voon, B. Sun, F. Yan, D. Li (Shanghai, China)

    Objective: In this study, we identified differential network characteristics based on graph theory of structural covariance network (SCN) between responders and non-responders of DBS. Background:…
  • 2024 International Congress

    Diffusion MRI and Machine Learning Distinguish Alzheimer’s Disease and Dementia with Lewy Bodies

    R. Chen, W. Wang, A. Barmpoutis, D. Vaillancourt (Gainesville, USA)

    Objective: This study reports recent updates in the development of a support vector machine learning model to discriminate between dementia variants (i.e., Alzheimer’s disease (AD)…
  • 2024 International Congress

    Increased Brain Free Water is Associated with Regional Gene Expression in Parkinson’s Disease

    D. Zhang, J. Yao, H. He, T. Wu (Beijing, China)

    Objective: In this study, we used brain free water scores and regional gene expression profiles from the Allen Human Brain Atlas transcriptomic data to investigate…
  • 2024 International Congress

    The 2-Minute Walking Test Predicts Aerobic Fitness, Motor Function, and Brain Health in Parkinson’s Disease

    E. Uc, V. Magnotta, E. Axelson, J. Dawson, M. Mani, A. Comellas, J. Kline, N. Narayanan, D. Mcgehee, S. Anderson, C. Weber, W. Darling (Iowa City, USA)

    Objective: To determine the association of performance on the 2-Minute Walking Test (2MWT) with aerobic fitness, motor and cognitive function, and brain health in mild…
  • 2024 International Congress

    White Matter Tractography in Spinocerebellar Ataxia type 1 and 2 in comparison with Healthy Controls

    P. Pankaj, A. Srivastava, M. Kumar, S. Kumaran, A. Garg, R. Agarwal, A. Nehra (New Delhi, India)

    Objective: To assess and quantify microstructural white matter atrophy in brain of spinocerebellar ataxia (SCA) types SCA1 and SCA2 patients in comparison with healthy subjects.…
  • 2024 International Congress

    A Phase 2 Study of ATH434 a Novel Inhibitor of α-Synuclein Aggregation for the Treatment of Multiple System Atrophy

    D. Stamler, C. Wong, P. Trujillo, M. Bradbury, C. Lucas, D. Claassen (Newark, USA)

    Objective: Describe baseline fluid and neuroimaging biomarker data of an early MSA study population Background: MSA is a rapidly progressive neurodegenerative disorder characterized by aggregated…
  • 2024 International Congress

    Developing a Supervised Machine Learning Model for Long-Term Cognitive Status Prediction in Parkinson Disease

    L. Saadatpour, A. Vijayakumari, D. Floden, H. Fernandez, B. Walter (Cleveland, USA)

    Objective: The study aims to develop a supervised machine learning (ML) model to predict long-term cognitive outcome in patients with Parkinson disease (PD). Background: Cognitive…
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