Literature DB >> 32213295

Automated voxel- and region-based analysis of gray matter and cerebrospinal fluid space in primary dementia disorders.

Karl Egger1, Alexander Rau2, Shan Yang2, Stefan Klöppel3, Ahmed Abdulkadir3, Elias Kellner4, Lars Frings5, Sabine Hellwig6, Horst Urbach2.   

Abstract

PURPOSE: Previous studies showed voxel-based volumetry as a helpful tool in detecting pathologic brain atrophy. Aim of this study was to investigate whether the inclusion of CSF volume improves the imaging based diagnostic accuracy using combined automated voxel- and region-based volumetry.
METHODS: In total, 120 individuals (30 healthy elderly, 30 frontotemporal dementia (FTD), 30 Alzheimer's dementia (AD) and 30 Lewy body dementia (LBD) patients) were analyzed with voxel-based morphometry and compared to a reference group of 360 healthy elderly controls. Abnormal GM and CSF volumes were visualized via z-scores. Volumetric results were finally evaluated by ROC analyses.
RESULTS: Based on the volume of abnormal GM and CSF voxels high accuracy was shown in separating dementia from normal ageing (AUC 0.93 and 0.91, respectively) within 5 different brain regions per hemisphere (frontal, medial temporal, temporal, parietal, occipital). Accuracy for separating FTD and AD was higher based on CSF volume (FTD: AUC 0.80 vs. 0.75 in frontal regions; AD: AUC 0.78 vs. 0.68 in parietal regions based on CSF and GM respectively).
CONCLUSIONS: Differentiation of dementia patients from normal ageing persons shows high accuracy when based on automatic volumetry alone. Evaluating volumes of abnormal CSF performed better than volumes of abnormal GM, especially in AD and FTD patients.
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Alzheimer’s disease; Dementia; Frontotemporal dementia; Lewy body dementia; Machine learning; Volumetry

Year:  2020        PMID: 32213295     DOI: 10.1016/j.brainres.2020.146800

Source DB:  PubMed          Journal:  Brain Res        ISSN: 0006-8993            Impact factor:   3.252


  2 in total

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Authors:  Alexander Rau; Horst Urbach
Journal:  Eur Radiol       Date:  2021-10-02       Impact factor: 5.315

2.  White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation.

Authors:  Mary Clare McKenna; Marlene Tahedl; Aizuri Murad; Jasmin Lope; Orla Hardiman; Siobhan Hutchinson; Peter Bede
Journal:  Brain Behav       Date:  2022-01-24       Impact factor: 2.708

  2 in total

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