Brain Morphological Alterations Are Detected in Early-Stage Parkinson's Disease with MRI Morphometry.
CAT12
MRI morphometry
Parkinson's disease
early diagnosis
Journal
Journal of neuroimaging : official journal of the American Society of Neuroimaging
ISSN: 1552-6569
Titre abrégé: J Neuroimaging
Pays: United States
ID NLM: 9102705
Informations de publication
Date de publication:
11 2020
11 2020
Historique:
received:
07
06
2020
accepted:
27
07
2020
entrez:
6
1
2021
pubmed:
7
1
2021
medline:
16
6
2021
Statut:
ppublish
Résumé
To detect brain morphological alterations in patients with early Parkinson's disease (PD) by using magnetic resonance imaging (MRI) morphometry under radiological diagnostic conditions. T1-weighted brain images of 18 early PD patients and 18 age-sex-matched healthy controls (HCs) were analyzed with free software Computational Anatomy Toolbox (CAT12). Regional cortical thickness (rCTh) in 68 atlas-defined regions-of-interest (ROIs) and subcortical gray matter volume (SGMV) in 14 atlas-defined ROIs were determined and compared between patients and HCs by paired comparison using both ROI-wise and voxel-wise analyses. False-discovery rate (FDR) was used multiple comparison correction. Possible correlations between brain morphological changes in patients and clinical observations were also analyzed. Comparing to the HCs, the ROI-wise analysis revealed rCTh thinning significantly in left medial orbitofrontal (P = .001), by trend (P < .05 but not significant after FDR correction) in four other ROIs located in frontal and temporal lobes, and a volume decreasing trend in left pallidum of the PD patients, while the voxel-wise analysis revealed one cluster with rCTh thinning trend located between left insula and superior temporal region of the patients. In addition, the patients showed more distinct rCTh thinning in ipsilateral hemisphere and SGMV deceasing trends in contralateral hemisphere in respect of the symptom-onset body side. Brain morphological alterations in early PD patients are evident despite of their inconspicuous findings in standard MRI. Quantitative morphological measurements with CAT12 may be an applicable add-on tool for clinical diagnosis of early PD. These results have to be verified in future studies with larger patient samples.
Sections du résumé
BACKGROUND AND PURPOSE
To detect brain morphological alterations in patients with early Parkinson's disease (PD) by using magnetic resonance imaging (MRI) morphometry under radiological diagnostic conditions.
METHODS
T1-weighted brain images of 18 early PD patients and 18 age-sex-matched healthy controls (HCs) were analyzed with free software Computational Anatomy Toolbox (CAT12). Regional cortical thickness (rCTh) in 68 atlas-defined regions-of-interest (ROIs) and subcortical gray matter volume (SGMV) in 14 atlas-defined ROIs were determined and compared between patients and HCs by paired comparison using both ROI-wise and voxel-wise analyses. False-discovery rate (FDR) was used multiple comparison correction. Possible correlations between brain morphological changes in patients and clinical observations were also analyzed.
RESULTS
Comparing to the HCs, the ROI-wise analysis revealed rCTh thinning significantly in left medial orbitofrontal (P = .001), by trend (P < .05 but not significant after FDR correction) in four other ROIs located in frontal and temporal lobes, and a volume decreasing trend in left pallidum of the PD patients, while the voxel-wise analysis revealed one cluster with rCTh thinning trend located between left insula and superior temporal region of the patients. In addition, the patients showed more distinct rCTh thinning in ipsilateral hemisphere and SGMV deceasing trends in contralateral hemisphere in respect of the symptom-onset body side.
CONCLUSION
Brain morphological alterations in early PD patients are evident despite of their inconspicuous findings in standard MRI. Quantitative morphological measurements with CAT12 may be an applicable add-on tool for clinical diagnosis of early PD. These results have to be verified in future studies with larger patient samples.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
786-792Informations de copyright
© 2020 The Authors. Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.
Références
Postuma RB, Berg D, Stern M, et al. MDS clinical diagnostic criteria for Parkinson's disease. Mov Disord 2015;30:1591‐601.
Adler CH, Beach TG, Hentz JG, et al. Low clinical diagnostic accuracy of early vs advanced Parkinson disease: clinicopathologic study. Neurology 2014;83:406‐12.
Danti S, Toschi N, Diciotti S, et al. Cortical thickness in de novo patients with Parkinson disease and mild cognitive impairment with consideration of clinical phenotype and motor laterality. Eur J Neurol 2015;22:1564‐72.
Tinaz S, Courtney MG, Stern CE. Focal cortical and subcortical atrophy in early Parkinson's disease. Mov Disord 2011;26:436‐41.
Jubault T, Gagnon J‐F, Karama S, et al. Patterns of cortical thickness and surface area in early Parkinson's disease. Neuroimage 2011;55:462‐7.
Claassen DO, McDonell KE, Donahue M, et al. Cortical asymmetry in Parkinson's disease: early susceptibility of the left hemisphere. Brain Behav 2016;6:e00573.
Pereira JB, Ibarretxe‐Bilbao N, Marti M‐J, et al. Assessment of cortical degeneration in patients with Parkinson's disease by voxel‐based morphometry, cortical folding, and cortical thickness. Hum Brain Mapp 2012;33:2521‐34.
Huppertz HJ, Möller L, Südmeyer M, et al. Differentiation of neurodegenerative Parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification. Mov Disord 2016;31:1506‐17.
Zarei M, Ibarretxe‐Bilbao N, Compta Y, et al. Cortical thinning is associated with disease stages and dementia in Parkinson's disease. J Neurol Neurosurg Psychiatry 2013;84:875‐81.
Lee HM, Kwon KY, Kim MJ, et al. Subcortical grey matter changes in untreated, early stage Parkinson's disease without dementia. Parkinsonism Relat Disord 2014;20:622‐6.
Lewis MM, Du G, Lee EY, et al. The pattern of gray matter atrophy in Parkinson's disease differs in cortical and subcortical regions. J Neurol 2016;263:68‐75.
Hoehn MM, Yahr MD. Parkinsonism: onset, progression, and mortality. Neurology 1967;17:427‐42.
Kalbe E, Kessler J, Calabrese P, et al. DemTect: a new, sensitive cognitive screening test to support the diagnosis of mild cognitive impairment and early dementia. Int J Geriatr Psychiatry 2004;19:136‐43.
Goetz CG, Fahn S, Martinez‐Martin P, et al. Movement disorder society‐sponsored revision of the unified Parkinson's disease rating scale (MDS‐UPDRS): process, format, and clinimetric testing plan. Mov Disord 2007;22:41‐7.
Tomlinson CL, Stowe R, Patel S, et al. Systematic review of levodopa dose equivalency reporting in Parkinson's disease. Mov Disord 2010;25:2649‐53.
Steer RA, Clark DA, Beck AT, et al. Common and specific dimensions of self‐reported anxiety and depression: the BDI‐II versus the BDI‐IA. Behav Res Ther 1999;37:183‐90.
Farokhian F, Beheshti I, Sone D, et al. Comparing CAT12 and VBM8 for detecting brain morphological abnormalities in temporal lobe epilepsy. Front Neurol 2017;8:428.
Tavares V, Prata D, Ferreira HA. Comparing SPM12 and CAT12 segmentation pipelines: a brain tissue volume‐based age and Alzheimer's disease study. J Neurosci Methods 2020;334:108565.
Fellhauer I, Zöllner FG, Schröder J, et al. Comparison of automated brain segmentation using a brain phantom and patients with early Alzheimer's dementia or mild cognitive impairment. Psychiatry Res 2015;233:299‐305.
Seiger R, Ganger S, Kranz GS, et al. Cortical Thickness estimations of FreeSurfer and the CAT12 Toolbox in patients with Alzheimer's disease and healthy controls. J Neuroimaging 2018;28:515‐23.
Dahnke R, Yotter RA, Gaser C. Cortical thickness and central surface estimation. Neuroimage 2013;65:336‐48.
Desikan RS, Ségonne F, Fischl B, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968‐80.
Caviness Jr VS, Lange NT, Makris N, et al. MRI‐based brain volumetrics: emergence of a developmental brain science. Brain Dev 1999;21:289‐95.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Statist Soc B 1995;57:289‐300.
Ferguson CJ. An effect size primer: a guide for clinicians and researchers. Prof Psychol Res Pract 2009;40:532‐8.
Cohen S. Psychosocial models of the role of social support in the etiology of physical disease. Health Psychol 1988;7:269‐97.
Rosenthal R. Parametric measures of effect size. In: Cooper H, Hedges LV, eds. The Handbook of Research Synthesis. New York: Russell Sage Foundation; 1994:231‐44.
Smith SM, Nichols TE. Threshold‐free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference. Neuroimage 2009;44:83‐98.
Goetz CG, Tilley BC, Shaftman SR, et al. Movement disorder society‐sponsored revision of the unified Parkinson's Disease Rating Scale (MDS‐UPDRS): scale presentation and clinimetric testing results. Mov Disord 2008;23:2129‐70.
Sakuma K, Nakashima K, Takahashi K. Olfactory evoked potentials in Parkinson's disease, Alzheimer's disease and anosmic patients. Psychiatry Clin Neurosci 1996;50:35‐40.
Braak H, Del Tredici K, Rüb U, et al. Staging of brain pathology related to sporadic Parkinson's disease. Neurobiol Aging 2003;24:197‐211.
Christopher L, Marras C, Duff‐Canning S, et al. Combined insular and striatal dopamine dysfunction are associated with executive deficits in Parkinson's disease with mild cognitive impairment. Brain 2014;137:565‐75.
Klietz M, Schnur T, Drexel S, et al. Association of motor and cognitive symptoms with health‐related quality of life and caregiver burden in a German cohort of advanced Parkinson's disease patients. Parkinsons Dis 2020;2020:5184084.
Huang YZ, Rothwell JC, Lu CS, et al. Abnormal bidirectional plasticity‐like effects in Parkinson's disease. Brain 2011;134:2312‐20.
Jia X, Liang P, Li Y, et al. Longitudinal study of gray matter changes in Parkinson disease. Am J Neuroradiol 2015;36:2219‐26.
Jellinger KA. Pathology of Parkinson's disease. Mol Chem Neuropathol 1991;14:153‐97.
Focke NK, Helms G, Scheewe S, et al. Individual voxel‐based subtype prediction can differentiate progressive supranuclear palsy from idiopathic Parkinson syndrome and healthy controls. Hum Brain Mapp 2011;32:1905‐15.
Menke RAL, Szewczyk‐Krolikowski K, Jbabdi S, et al. Comprehensive morphometry of subcortical grey matter structures in early‐stage Parkinson's disease. Hum Brain Mapp 2013;35:1681‐90.
Gerrits NJHM, van der Werf YD, Hofman M, et al. Gray matter differences contribute to variation in cognitive performance in Parkinson's disease. Eur J Neurol 2014;21:245‐52.
Riederer P, Sian‐Hülsmann J. The significance of neuronal lateralisation in Parkinson's disease. J Neural Transm(Vienna) 2012;119:953‐62.
Ashburner J, Friston KJ. Voxel‐based morphometry—the methods. Neuroimage 2000;11:805‐21.