Document Detail


Cerebellar atrophy in essential tremor using an automated segmentation method.
MedLine Citation:
PMID:  19342539     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND AND PURPOSE: Essential tremor (ET) is a slowly progressive disorder characterized by postural and kinetic tremors most commonly affecting the forearms and hands. Several lines of evidence from physiologic and neuroimaging studies point toward a major role of the cerebellum in this disease. Recently, voxel-based morphometry (VBM) has been proposed to quantify cerebellar atrophy in ET. However, VBM was not originally designed to study subcortical structures, and the complicated anatomy of the cerebellum may hamper the automatic processing of VBM. The aim of this study was to determine the efficacy and utility of using automated subcortical segmentation to identify atrophy of the cerebellum and other subcortical structures in patients with ET. MATERIALS AND METHODS: We used a recently developed automated volumetric method (FreeSurfer) to quantify subcortical atrophy in ET by comparing results obtained with this method with those provided by previous evidence. The study included T1-weighted MR images of 46 patients with ET grouped into those having arm ET (n = 27, a-ET) or head ET (n = 19, h-ET) and 28 healthy controls. RESULTS: Results revealed the expected reduction of cerebellar volume in patients with h-ET with respect to healthy controls after controlling for intracranial volume. No significant difference was detected in any other subcortical area. CONCLUSIONS: Volumetric data obtained with automated segmentation of subcortical and cerebellar structures approximate data from a previous study based on VBM. The current findings extend the literature by providing initial validation for using fully automated segmentation to derive cerebellar volumetric information from patients with ET.
Authors:
A Cerasa; D Messina; G Nicoletti; F Novellino; P Lanza; F Condino; G Arabia; M Salsone; A Quattrone
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Publication Detail:
Type:  Journal Article     Date:  2009-04-02
Journal Detail:
Title:  AJNR. American journal of neuroradiology     Volume:  30     ISSN:  1936-959X     ISO Abbreviation:  AJNR Am J Neuroradiol     Publication Date:  2009 Jun 
Date Detail:
Created Date:  2009-06-12     Completed Date:  2009-08-26     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8003708     Medline TA:  AJNR Am J Neuroradiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1240-3     Citation Subset:  IM    
Affiliation:
Institute of Neurological Sciences, National Research Council, Piano Lago di Mangone, Cosenza, Italy.
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MeSH Terms
Descriptor/Qualifier:
Aged
Algorithms
Artificial Intelligence
Cerebellum / pathology*
Diffusion Magnetic Resonance Imaging / methods*
Essential Tremor / complications,  pathology*
Female
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Male
Myoclonic Cerebellar Dyssynergia / complications,  pathology*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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