Literature DB >> 24729430

Magnetic resonance support vector machine discriminates essential tremor with rest tremor from tremor-dominant Parkinson disease.

Andrea Cherubini1, Rita Nisticó, Fabiana Novellino, Maria Salsone, Salvatore Nigro, Giulia Donzuso, Aldo Quattrone.   

Abstract

BACKGROUND: The aim of the current study was to distinguish patients who had tremor-dominant Parkinson's disease (tPD) from those who had essential tremor with rest tremor (rET).
METHODS: We combined voxel-based morphometry-derived gray matter and white matter volumes and diffusion tensor imaging-derived mean diffusivity and fractional anisotropy in a support vector machine (SVM) to evaluate 15 patients with rET and 15 patients with tPD. Dopamine transporter single-photon emission computed tomography imaging was used as ground truth.
RESULTS: SVM classification of individual patients showed that no single predictor was able to fully discriminate patients with tPD from those with rET. By contrast, when all predictors were combined in a multi-modal algorithm, SVM distinguished patients with rET from those with tPD with an accuracy of 100%.
CONCLUSIONS: SVM is an operator-independent and automatic technique that may help distinguish patients with tPD from those with rET at the individual level.
© 2014 International Parkinson and Movement Disorder Society.

Entities:  

Keywords:  computer-aided diagnosis; magnetic resonance imaging; resting tremor; support vector machine

Mesh:

Year:  2014        PMID: 24729430     DOI: 10.1002/mds.25869

Source DB:  PubMed          Journal:  Mov Disord        ISSN: 0885-3185            Impact factor:   10.338


  13 in total

1.  Structural connectivity differences in essential tremor with and without resting tremor.

Authors:  Maria Eugenia Caligiuri; Gennarina Arabia; Gaetano Barbagallo; Angela Lupo; Maurizio Morelli; Rita Nisticò; Fabiana Novellino; Andrea Quattrone; Maria Salsone; Basilio Vescio; Andrea Cherubini; Aldo Quattrone
Journal:  J Neurol       Date:  2017-07-20       Impact factor: 4.849

Review 2.  Linking Essential Tremor to the Cerebellum-Neuroimaging Evidence.

Authors:  Antonio Cerasa; Aldo Quattrone
Journal:  Cerebellum       Date:  2016-06       Impact factor: 3.847

Review 3.  Connectivity Changes in Parkinson's Disease.

Authors:  Antonio Cerasa; Fabiana Novellino; Aldo Quattrone
Journal:  Curr Neurol Neurosci Rep       Date:  2016-10       Impact factor: 5.081

4.  Differentiating Patients with Parkinson's Disease from Normal Controls Using Gray Matter in the Cerebellum.

Authors:  Ling-Li Zeng; Liang Xie; Hui Shen; Zhiguo Luo; Peng Fang; Yanan Hou; Beisha Tang; Tao Wu; Dewen Hu
Journal:  Cerebellum       Date:  2017-02       Impact factor: 3.847

5.  Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

Authors:  Mutlu Mete; Unal Sakoglu; Jeffrey S Spence; Michael D Devous; Thomas S Harris; Bryon Adinoff
Journal:  BMC Bioinformatics       Date:  2016-10-06       Impact factor: 3.169

6.  Discriminating cognitive status in Parkinson's disease through functional connectomics and machine learning.

Authors:  Alexandra Abós; Hugo C Baggio; Bàrbara Segura; Anna I García-Díaz; Yaroslau Compta; Maria José Martí; Francesc Valldeoriola; Carme Junqué
Journal:  Sci Rep       Date:  2017-03-28       Impact factor: 4.379

7.  Predictive markers for Parkinson's disease using deep neural nets on neuromelanin sensitive MRI.

Authors:  Sumeet Shinde; Shweta Prasad; Yash Saboo; Rishabh Kaushick; Jitender Saini; Pramod Kumar Pal; Madhura Ingalhalikar
Journal:  Neuroimage Clin       Date:  2019-03-06       Impact factor: 4.881

8.  A machine learning-based classification approach on Parkinson's disease diffusion tensor imaging datasets.

Authors:  Jannik Prasuhn; Marcus Heldmann; Thomas F Münte; Norbert Brüggemann
Journal:  Neurol Res Pract       Date:  2020-11-10

9.  Classification of symptom-side predominance in idiopathic Parkinson's disease.

Authors:  Delia-Lisa Feis; Esther A Pelzer; Lars Timmermann; Marc Tittgemeyer
Journal:  NPJ Parkinsons Dis       Date:  2015-10-29

10.  Clinical Characteristics and Electrophysiological Biomarkers of Parkinson's Disease Developed From Essential Tremor.

Authors:  Xuemei Wang; Zhentang Cao; Genliang Liu; Zhu Liu; Ying Jiang; Huizi Ma; Zhan Wang; Yaqin Yang; Huimin Chen; Tao Feng
Journal:  Front Neurol       Date:  2020-10-29       Impact factor: 4.003

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