Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.

BACKGROUND: MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods. OBJECTIVE: To compare FTD with Alzheimer's Disease (AD) and Mild Cognitive Impairment...

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Main Authors: Miguel Ángel Muñoz-Ruiz, Päivi Hartikainen, Juha Koikkalainen, Robin Wolz, Valtteri Julkunen, Eini Niskanen, Sanna-Kaisa Herukka, Miia Kivipelto, Ritva Vanninen, Daniel Rueckert, Yawu Liu, Jyrki Lötjönen, Hilkka Soininen
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3527560?pdf=render
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spelling doaj-b4dc6c26c0fb47b1989dcbeb961398b12020-11-25T02:36:26ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-01712e5253110.1371/journal.pone.0052531Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.Miguel Ángel Muñoz-RuizPäivi HartikainenJuha KoikkalainenRobin WolzValtteri JulkunenEini NiskanenSanna-Kaisa HerukkaMiia KivipeltoRitva VanninenDaniel RueckertYawu LiuJyrki LötjönenHilkka SoininenBACKGROUND: MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods. OBJECTIVE: To compare FTD with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal Volumetry (HV), Tensor-based Morphometry (TBM) and Voxel-based Morphometry (VBM), in specific regions of interest in order to determine the highest classification accuracy. METHODS: Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI) and 48 patients with stable MCI (SMCI) were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR), sensitivity (SS) and specificity (SP) between the study groups. RESULTS: We found unequivocal results differentiating controls from FTD with HV (hippocampus left side) (CCR = 0.83; SS = 0.84; SP = 0.80), with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94), and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn) (CCR = 0.87/SS = 0.81/SP = 0.96). VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76), particularly in lateral ventricle (frontal horn, central part and occipital horn) (CCR = 0.73), whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73). TBM resulted in low accuracy (CCR = 0.62) in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55). CONCLUSION: Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD.http://europepmc.org/articles/PMC3527560?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Miguel Ángel Muñoz-Ruiz
Päivi Hartikainen
Juha Koikkalainen
Robin Wolz
Valtteri Julkunen
Eini Niskanen
Sanna-Kaisa Herukka
Miia Kivipelto
Ritva Vanninen
Daniel Rueckert
Yawu Liu
Jyrki Lötjönen
Hilkka Soininen
spellingShingle Miguel Ángel Muñoz-Ruiz
Päivi Hartikainen
Juha Koikkalainen
Robin Wolz
Valtteri Julkunen
Eini Niskanen
Sanna-Kaisa Herukka
Miia Kivipelto
Ritva Vanninen
Daniel Rueckert
Yawu Liu
Jyrki Lötjönen
Hilkka Soininen
Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
PLoS ONE
author_facet Miguel Ángel Muñoz-Ruiz
Päivi Hartikainen
Juha Koikkalainen
Robin Wolz
Valtteri Julkunen
Eini Niskanen
Sanna-Kaisa Herukka
Miia Kivipelto
Ritva Vanninen
Daniel Rueckert
Yawu Liu
Jyrki Lötjönen
Hilkka Soininen
author_sort Miguel Ángel Muñoz-Ruiz
title Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
title_short Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
title_full Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
title_fullStr Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
title_full_unstemmed Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
title_sort structural mri in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2012-01-01
description BACKGROUND: MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods. OBJECTIVE: To compare FTD with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal Volumetry (HV), Tensor-based Morphometry (TBM) and Voxel-based Morphometry (VBM), in specific regions of interest in order to determine the highest classification accuracy. METHODS: Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI) and 48 patients with stable MCI (SMCI) were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR), sensitivity (SS) and specificity (SP) between the study groups. RESULTS: We found unequivocal results differentiating controls from FTD with HV (hippocampus left side) (CCR = 0.83; SS = 0.84; SP = 0.80), with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94), and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn) (CCR = 0.87/SS = 0.81/SP = 0.96). VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76), particularly in lateral ventricle (frontal horn, central part and occipital horn) (CCR = 0.73), whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73). TBM resulted in low accuracy (CCR = 0.62) in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55). CONCLUSION: Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD.
url http://europepmc.org/articles/PMC3527560?pdf=render
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