Literature DB >> 26852326

Pathophysiology of the behavioral variant of frontotemporal lobar degeneration: A study combining MRI and FDG-PET.

M-S Buhour1,2,3,4, F Doidy1,2,3,4, M Laisney1,2,3,4, A L Pitel1,2,3,4, V de La Sayette1,2,3,5, F Viader1,2,3,5, F Eustache1,2,3,4, B Desgranges6,7,8,9.   

Abstract

Gray matter (GM) lobar atrophy and glucose hypometabolism are well-described hallmarks of frontotemporal lobar degeneration (FTLD), but the relationships between them are still poorly understood. In this study, we aimed to show the patterns of GM atrophy and hypometabolism in a sample of 15 patients with the behavioral variant of FTLD (bv-FTD), compared to 15 healthy controls, then to provide a direct comparison between GM atrophy and hypometabolism, using a voxel-based method specially designed to statistically compare the two imaging modalities. The participants underwent structural magnetic resonance imaging and 18F-fluorodeoxyglucose (FDG) positron emission tomography examinations. First, between-group comparisons of GM volume and metabolism were performed. Then, in the patient group, correlations between regional alterations and direct between-modality voxelwise comparison were performed. Finally, we examined individual patterns of brain abnormalities for each imaging modality and each patient. The observed patterns of GM atrophy and hypometabolism were consistent with previous studies. We found significant voxelwise correlations between changes in GM and FDG uptake, mainly in the frontal cortex, corresponding to the typical profile of alterations in bv-FTD. The direct comparison revealed regional variability in the relationship between hypometabolism and atrophy. This analysis revealed greater atrophy than hypometabolism in the right putamen and amygdala, and left insula and superior temporal gyrus, whereas hypometabolism was more severe than GM atrophy in the left caudate nucleus and anterior cingulate cortex. Finally, GM atrophy affected the right amygdala/hippocampus and left insula in 95 % of the patients. These findings provide evidence for regional variations in the hierarchy of hypometabolism and GM atrophy and the relationships between them, and enhance our understanding of the pathophysiology of bv-FTD.

Entities:  

Keywords:  Individual analysis; Structural MRI, FDG-PET; Voxel-based morphometry; bv-FTD

Mesh:

Substances:

Year:  2017        PMID: 26852326     DOI: 10.1007/s11682-016-9521-x

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  81 in total

1.  Patterns of brain atrophy in frontotemporal dementia and semantic dementia.

Authors:  H J Rosen; M L Gorno-Tempini; W P Goldman; R J Perry; N Schuff; M Weiner; R Feiwell; J H Kramer; B L Miller
Journal:  Neurology       Date:  2002-01-22       Impact factor: 9.910

Review 2.  Neuroimaging in frontotemporal lobar degeneration--predicting molecular pathology.

Authors:  Jennifer L Whitwell; Keith A Josephs
Journal:  Nat Rev Neurol       Date:  2012-01-31       Impact factor: 42.937

3.  Distinct behavioural profiles in frontotemporal dementia and semantic dementia.

Authors:  J S Snowden; D Bathgate; A Varma; A Blackshaw; Z C Gibbons; D Neary
Journal:  J Neurol Neurosurg Psychiatry       Date:  2001-03       Impact factor: 10.154

4.  Pathologically proven frontotemporal dementia presenting with severe amnesia.

Authors:  Andrew Graham; Rhys Davies; John Xuereb; Glenda Halliday; Jillian Kril; Helen Creasey; Kim Graham; John Hodges
Journal:  Brain       Date:  2005-01-05       Impact factor: 13.501

5.  Comparison of grey matter and metabolic reductions in frontotemporal dementia using FDG-PET and voxel-based morphometric MR studies.

Authors:  Tomonori Kanda; Kazunari Ishii; Takafumi Uemura; Naokazu Miyamoto; Toshiki Yoshikawa; Atsushi K Kono; Etsuro Mori
Journal:  Eur J Nucl Med Mol Imaging       Date:  2008-07-26       Impact factor: 9.236

6.  Concordance and discordance between brain perfusion and atrophy in frontotemporal dementia.

Authors:  Soichiro Shimizu; Yu Zhang; Joel Laxamana; Bruce L Miller; Joel H Kramer; Michael W Weiner; Norbert Schuff
Journal:  Brain Imaging Behav       Date:  2010-03       Impact factor: 3.978

7.  Distinct MRI atrophy patterns in autopsy-proven Alzheimer's disease and frontotemporal lobar degeneration.

Authors:  G D Rabinovici; W W Seeley; E J Kim; M L Gorno-Tempini; K Rascovsky; T A Pagliaro; S C Allison; C Halabi; J H Kramer; J K Johnson; M W Weiner; M S Forman; J Q Trojanowski; S J Dearmond; B L Miller; H J Rosen
Journal:  Am J Alzheimers Dis Other Demen       Date:  2007 Dec-2008 Jan       Impact factor: 2.035

8.  Cerebral metabolic patterns at early stages of frontotemporal dementia and semantic dementia. A PET study.

Authors:  J Diehl; T Grimmer; A Drzezga; M Riemenschneider; H Förstl; A Kurz
Journal:  Neurobiol Aging       Date:  2004-09       Impact factor: 4.673

9.  Behavioural variant frontotemporal dementia: not all it seems?

Authors:  C M Kipps; P J Nestor; T D Fryer; J R Hodges
Journal:  Neurocase       Date:  2007-08       Impact factor: 0.881

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

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Journal:  PLoS One       Date:  2012-12-20       Impact factor: 3.240

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  14 in total

Review 1.  Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias.

Authors:  A Del Sole; S Malaspina; Alberto Magenta Biasina
Journal:  Funct Neurol       Date:  2016 Oct/Dec

Review 2.  Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis.

Authors:  Suvi Häkkinen; Stephanie A Chu; Suzee E Lee
Journal:  Neurobiol Dis       Date:  2020-09-02       Impact factor: 5.996

Review 3.  Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus.

Authors:  Kazunari Ishii
Journal:  Jpn J Radiol       Date:  2019-09-23       Impact factor: 2.374

4.  Enhancing theory of mind in behavioural variant frontotemporal dementia with transcranial direct current stimulation.

Authors:  Maria Cotelli; Mauro Adenzato; Valentina Cantoni; Rosa Manenti; Antonella Alberici; Ivan Enrici; Alberto Benussi; Valentina Dell'Era; Elisa Bonetta; Alessandro Padovani; Barbara Borroni
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Review 5.  Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility.

Authors:  Sheena I Dev; Bradford C Dickerson; Alexandra Touroutoglou
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

6.  Voxel-based mapping of grey matter volume and glucose metabolism profiles in amyotrophic lateral sclerosis.

Authors:  M-S Buhour; F Doidy; A Mondou; A Pélerin; L Carluer; F Eustache; F Viader; B Desgranges
Journal:  EJNMMI Res       Date:  2017-03-06       Impact factor: 3.138

7.  Brain Structural and Perfusion Signature of Amyotrophic Lateral Sclerosis With Varying Levels of Cognitive Deficit.

Authors:  Dongchao Shen; Bo Hou; Yinyan Xu; Bo Cui; Pan Peng; Xiaolu Li; Hongfei Tai; Kang Zhang; Shuangwu Liu; Hanhui Fu; Jing Gao; Mingsheng Liu; Feng Feng; Liying Cui
Journal:  Front Neurol       Date:  2018-05-24       Impact factor: 4.003

8.  Investigating Neuroimaging Correlates of Early Frailty in Patients With Behavioral Variant Frontotemporal Dementia: A MRI and FDG-PET Study.

Authors:  Martina Amanzio; Sara Palermo; Mario Stanziano; Federico D'Agata; Antonello Galati; Salvatore Gentile; Giancarlo Castellano; Massimo Bartoli; Giuseppina Elena Cipriani; Elisa Rubino; Paolo Fonio; Innocenzo Rainero
Journal:  Front Aging Neurosci       Date:  2021-04-14       Impact factor: 5.750

Review 9.  Imaging and fluid biomarkers in frontotemporal dementia.

Authors:  Lieke H Meeter; Laura Donker Kaat; Jonathan D Rohrer; John C van Swieten
Journal:  Nat Rev Neurol       Date:  2017-06-16       Impact factor: 42.937

10.  Static and dynamic alterations in the amplitude of low-frequency fluctuation in patients with amyotrophic lateral sclerosis.

Authors:  Xujing Ma; Fengmei Lu; Heng Chen; Caihong Hu; Jiao Wang; Sheng Zhang; Shuqin Zhang; Guiran Yang; Jiuquan Zhang
Journal:  PeerJ       Date:  2020-11-02       Impact factor: 2.984

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