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Beheshti I, Perron J, Ko JH. Neuroanatomical Signature of the Transition from Normal Cognition to MCI in Parkinson's Disease. Aging Dis 2024:AD.2024.0323. [PMID: 38913040 DOI: 10.14336/ad.2024.0323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/23/2024] [Indexed: 06/25/2024] Open
Abstract
The progression of Parkinson's disease (PD) is often accompanied by cognitive decline. We had previously developed a brain age estimation program utilizing structural MRI data of 949 healthy individuals from publicly available sources. Structural MRI data of 244 PD patients who were cognitively normal at baseline was acquired from the Parkinson Progression Markers Initiative (PPMI). 192 of these showed stable normal cognitive function from baseline out to 5 years (PD-SNC), and the remaining 52 had unstable normal cognition and developed mild cognitive impairment within 5 years (PD-UNC). 105 healthy controls were also included in the analysis as a reference. First, we examined if there were any baseline differences in regional brain structure between PD-UNC and PD-SNC cohorts utilizing the three most widely used atrophy estimation pipelines, i.e., voxel-based morphometry (VBM), deformation-based morphometry and cortical thickness analyses. We then investigated if accelerated brain age estimation with our multivariate regressive machine learning algorithm was different across these groups (HC, PD-SNC, and PD-UNC). As per the VBM analysis, PD-UNC patients demonstrated a noticeable increase in GM volume in the posterior and anterior lobes of the cerebellum, sub-lobar, extra-nuclear, thalamus, and pulvinar regions when compared to PD-SNC at baseline. PD-UNC patients were observed to have significantly older brain age compared to both PD-SNC patients (p=0.009) and healthy controls (p<0.009). The increase in GM volume in the PD-UNC group could potentially indicate an inflammatory or neuronal hypertrophy response, which could serve as a biomarker for future cognitive decline among this population.
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Affiliation(s)
- Iman Beheshti
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- PrairieNeuro Research Centre, Kleysen Institute for Advanced Medicine, Health Science Centre, Winnipeg, MB, Canada
| | - Jarrad Perron
- PrairieNeuro Research Centre, Kleysen Institute for Advanced Medicine, Health Science Centre, Winnipeg, MB, Canada
- Graduate Program in Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Ji Hyun Ko
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- PrairieNeuro Research Centre, Kleysen Institute for Advanced Medicine, Health Science Centre, Winnipeg, MB, Canada
- Graduate Program in Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
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Castelli MB, Alonso-Recio L, Carvajal F, Serrano JM. Does the Montreal Cognitive Assessment (MoCA) identify cognitive impairment profiles in Parkinson's disease? An exploratory study. APPLIED NEUROPSYCHOLOGY. ADULT 2024; 31:238-247. [PMID: 34894908 DOI: 10.1080/23279095.2021.2011727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
An important proportion of patients with Parkinson's Disease (PD) present signs of cognitive impairment, although this is heterogeneous. In an attempt to classify this, the dual syndrome hypothesis distinguishes between two profiles: one defined by attentional and executive problems with damage in anterior cerebral regions, and another with mnesic and visuospatial alterations, with damage in posterior cerebral regions. The Montreal Cognitive Assessment (MoCA) is one of the recommended screening tools, and one of the most used, to assess cognitive impairment in PD. However, its ability to specifically identify these two profiles of cognitive impairment has not been studied. The aim of this study was, therefore, to analyze the capacity of the MoCA to detect cognitive impairment, and also to identify anterior and posterior profiles defined by the dual syndrome hypothesis. For this purpose, 59 patients with idiopathic PD were studied with the MoCA and a neuropsychological battery of tests covering all cognitive domains. Results of logistic regression analysis with ROC (Receiver Operating Characteristic) curves showed that MoCA detected cognitive impairment and identified patients with a profile of anterior/attentional and executive deficit, with acceptable sensibility and specificity. However, it did not identify patients with a posterior/mnesic-visuospatial impairment. We discuss the reasons for the lack of sensitivity of MoCA in this profile, and other possible implications of these results with regards the usefulness of this tool to assess cognitive impairment in PD.
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Affiliation(s)
- María Belén Castelli
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Laura Alonso-Recio
- Departamento de Psicología y Salud, Facultad de Ciencias de la Salud y la Educación, Universidad a Distancia de Madrid, Madrid, Spain
| | - Fernando Carvajal
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
| | - Juan Manuel Serrano
- Departamento de Psicología Biológica y de la Salud, Facultad de Psicología, Universidad Autónoma de Madrid, Madrid, Spain
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Beheshti I, Ko JH. Predicting the occurrence of mild cognitive impairment in Parkinson's disease using structural MRI data. Front Neurosci 2024; 18:1375395. [PMID: 38699676 PMCID: PMC11063344 DOI: 10.3389/fnins.2024.1375395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 03/29/2024] [Indexed: 05/05/2024] Open
Abstract
Introduction Mild cognitive impairment (MCI) is a common symptom observed in individuals with Parkinson's disease (PD) and a main risk factor for progressing to dementia. Our objective was to identify early anatomical brain changes that precede the transition from healthy cognition to MCI in PD. Methods Structural T1-weighted magnetic resonance imaging data of PD patients with healthy cognition at baseline were downloaded from the Parkinson's Progression Markers Initiative database. Patients were divided into two groups based on the annual cognitive assessments over a 5-year time span: (i) PD patients with unstable healthy cognition who developed MCI over a 5-year follow-up (PD-UHC, n = 52), and (ii) PD patients who maintained stable healthy cognitive function over the same period (PD-SHC, n = 52). These 52 PD-SHC were selected among 192 PD-SHC patients using propensity score matching method to have similar demographic and clinical characteristics with PD-UHC at baseline. Seventy-five percent of these were used to train a support vector machine (SVM) algorithm to distinguish between the PD-UHC and PD-SHC groups, and tested on the remaining 25% of individuals. Shapley Additive Explanations (SHAP) feature analysis was utilized to identify the most informative brain regions in SVM classifier. Results The average accuracy of classifying PD-UHC vs. PD-SHC was 80.76%, with 82.05% sensitivity and 79.48% specificity using 10-fold cross-validation. The performance was similar in the hold-out test sets with all accuracy, sensitivity, and specificity at 76.92%. SHAP analysis showed that the most influential brain regions in the prediction model were located in the frontal, occipital, and cerebellar regions as well as midbrain. Discussion Our machine learning-based analysis yielded promising results in identifying PD individuals who are at risk of cognitive decline from the earliest disease stage and revealed the brain regions which may be linked to the prospective cognitive decline in PD before clinical symptoms emerge.
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Affiliation(s)
- Iman Beheshti
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- PrairieNeuro Research Centre, Kleysen Institute for Advanced Medicine, Health Science Centre, Winnipeg, MB, Canada
| | - Ji Hyun Ko
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- PrairieNeuro Research Centre, Kleysen Institute for Advanced Medicine, Health Science Centre, Winnipeg, MB, Canada
- Graduate Program in Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
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Doskas T, Vadikolias K, Ntoskas K, Vavougios GD, Tsiptsios D, Stamati P, Liampas I, Siokas V, Messinis L, Nasios G, Dardiotis E. Neurocognitive Impairment and Social Cognition in Parkinson's Disease Patients. Neurol Int 2024; 16:432-449. [PMID: 38668129 PMCID: PMC11054167 DOI: 10.3390/neurolint16020032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 04/06/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.
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Affiliation(s)
- Triantafyllos Doskas
- Department of Neurology, Athens Naval Hospital, 11521 Athens, Greece;
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | - Konstantinos Vadikolias
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | | | - George D. Vavougios
- Department of Neurology, Athens Naval Hospital, 11521 Athens, Greece;
- Department of Neurology, Faculty of Medicine, University of Cyprus, 1678 Lefkosia, Cyprus
- Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41500 Larissa, Greece
| | - Dimitrios Tsiptsios
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | - Polyxeni Stamati
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Ioannis Liampas
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Vasileios Siokas
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Lambros Messinis
- School of Psychology, Laboratory of Neuropsychology and Behavioural Neuroscience, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Grigorios Nasios
- Department of Speech and Language Therapy, School of Health Sciences, University of Ioannina, 45500 Ioannina, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
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Summers D, Spencer K, Okasaki C, Huber JE. An Examination of Cognitive Heterogeneity in Parkinson Disease: The Dual-Syndrome Hypothesis. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2024; 67:1127-1135. [PMID: 38446552 DOI: 10.1044/2024_jslhr-23-00621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
PURPOSE Cognitive impairment is one of the most debilitating nonmotor symptoms in Parkinson disease (PD), and its presentation is heterogeneous. One proposed model to explain cognitive variability in PD is the dual-syndrome hypothesis. This hypothesis delineates two cognitive profiles, a "fronto-striatal" profile and a "posterior cortical" profile according to symptom presentation, associated motor phenotype, and risk for dementia. The current study examined the dual-syndrome hypothesis in individuals with idiopathic PD to evaluate the existence of these profiles, determine the association with the motor phenotype (tremor dominant vs. postural instability/gait disorder), and assess the relative risk for dementia. METHOD A retrospective examination was conducted using data from the Parkinson's Progression Markers Initiative database at baseline (within 2 years of diagnosis) and 5 years after baseline. Descriptive categorizations, cluster analyses, generalized linear mixed models, and logistic regressions were used to address the research questions. RESULTS There was emerging evidence of cognitive profiles; however, these were not fully supported by cluster analyses. Baseline cognitive profile was associated with later motor phenotype, and as predicted, dementia risk was greatest in persons with baseline posterior cortical impairments. CONCLUSION The current results provide mixed support for the dual-syndrome hypothesis, with some evidence that the posterior cortical cognitive profile is associated with postural instability and gait disorder as well as greater dementia risk.
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Affiliation(s)
- Dale Summers
- Department of Speech and Hearing Sciences, University of Washington, Seattle
| | - Kristie Spencer
- Department of Speech and Hearing Sciences, University of Washington, Seattle
| | - Connie Okasaki
- Quantitative Ecology and Resource Management, University of Washington, Seattle
| | - Jessica E Huber
- Department of Communicative Disorders and Sciences, University at Buffalo, NY
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Maggi G, Giacobbe C, Vitale C, Amboni M, Obeso I, Santangelo G. Theory of mind in mild cognitive impairment and Parkinson's disease: The role of memory impairment. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024; 24:156-170. [PMID: 38049608 PMCID: PMC10827829 DOI: 10.3758/s13415-023-01142-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/14/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND Social cognition is impaired in Parkinson's disease (PD). Whether social cognitive impairment (iSC) is a by-product of the underlying cognitive deficits in PD or a process independent of cognitive status is unknown. To this end, the present study was designed to investigate the weight of specific cognitive deficits in social cognition, considering different mild cognitive impairment subtypes of PD (PD-MCI). METHODS Fifty-eight PD patients underwent a neuropsychological battery assessing executive functions, memory, language, and visuospatial domains, together with social cognitive tests focused on theory of mind (ToM). Patients were divided into subgroups according to their clinical cognitive status: amnestic PD-MCI (PD-aMCI, n = 18), non-amnestic PD-MCI (PD-naMCI, n = 16), and cognitively unimpaired (PD-CU, n = 24). Composite scores for cognitive and social domains were computed to perform mediation analyses. RESULTS Memory and language impairments mediated the effect of executive functioning in social cognitive deficits in PD patients. Dividing by MCI subgroups, iSC occurred more frequently in PD-aMCI (77.8%) than in PD-naMCI (18.8%) and PD-CU (8.3%). Moreover, PD-aMCI performed worse than PD-CU in all social cognitive measures, whereas PD-naMCI performed worse than PD-CU in only one subtype of the affective and cognitive ToM tests. CONCLUSIONS Our findings suggest that ToM impairment in PD can be explained by memory dysfunction that mediates executive control. ToM downsides in the amnesic forms of PD-MCI may suggest that subtle changes in social cognition could partly explain future transitions into dementia. Hence, the evaluation of social cognition in PD is critical to characterize a possible behavioral marker of cognitive decline.
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Affiliation(s)
- Gianpaolo Maggi
- Department of Psychology, University of Campania "Luigi Vanvitelli," Viale Ellittico, 31, 81100, Caserta, Italy.
| | - Chiara Giacobbe
- Department of Psychology, University of Campania "Luigi Vanvitelli," Viale Ellittico, 31, 81100, Caserta, Italy
| | - Carmine Vitale
- Institute of Diagnosis and Health, IDC-Hermitage Capodimonte, Naples, Italy
- Department of Motor Sciences and Wellness, University "Parthenope, Naples, Italy
| | - Marianna Amboni
- Institute of Diagnosis and Health, IDC-Hermitage Capodimonte, Naples, Italy
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Ignacio Obeso
- HM Hospitales - Centro Integral de Neurociencias AC HM CINAC, Hospital Universitario HM Puerta del Sur, HM Hospitales, Avda. Carlos V, 70. 28938, Móstoles, Madrid, Spain.
- Department of Psychobiology and Methods on Behavioural Sciences, Complutense University of Madrid, Madrid, Spain.
| | - Gabriella Santangelo
- Department of Psychology, University of Campania "Luigi Vanvitelli," Viale Ellittico, 31, 81100, Caserta, Italy.
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Dan XJ, Wang YW, Sun JY, Gao LL, Chen X, Yang XY, Xu EH, Ma JH, Yan CG, Wu T, Chan P. Reorganization of intrinsic functional connectivity in early-stage Parkinson's disease patients with probable REM sleep behavior disorder. NPJ Parkinsons Dis 2024; 10:5. [PMID: 38172178 PMCID: PMC10764752 DOI: 10.1038/s41531-023-00617-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 12/07/2023] [Indexed: 01/05/2024] Open
Abstract
REM sleep behavior disorder (RBD) symptoms in Parkinson's disease (PD) suggest both a clinically and pathologically malignant subtype. However, whether RBD symptoms are associated with alterations in the organization of whole-brain intrinsic functional networks in PD, especially at early disease stages, remains unclear. Here we use resting-state functional MRI, coupled with graph-theoretical approaches and network-based statistics analyses, and validated with large-scale network analyses, to characterize functional brain networks and their relationship with clinical measures in early PD patients with probable RBD (PD+pRBD), early PD patients without probable RBD (PD-pRBD) and healthy controls. Thirty-six PD+pRBD, 57 PD-pRBD and 71 healthy controls were included in the final analyses. The PD+pRBD group demonstrated decreased global efficiency (t = -2.036, P = 0.0432) compared to PD-pRBD, and decreased network efficiency, as well as comprehensively disrupted nodal efficiency and whole-brain networks (all eight networks, but especially in the sensorimotor, default mode and visual networks) compared to healthy controls. The PD-pRBD group showed decreased nodal degree in right ventral frontal cortex and more affected edges in the frontoparietal and ventral attention networks compared to healthy controls. Furthermore, the assortativity coefficient was negatively correlated with Montreal cognitive assessment scores in the PD+pRBD group (r = -0.365, P = 0.026, d = 0.154). The observation of altered whole-brain functional networks and its correlation with cognitive function in PD+pRBD suggest reorganization of the intrinsic functional connectivity to maintain the brain function in the early stage of the disease. Future longitudinal studies following these alterations along disease progression are warranted.
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Affiliation(s)
- Xiao-Juan Dan
- Department of Neurology, Xuanwu Hospital of Capital Medical University, 100053, Beijing, China
- Key Laboratory on Neurodegenerative Disorders of Ministry of Education, Key Laboratory on Parkinson's Disease of Beijing, 100053, Beijing, China
| | - Yu-Wei Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, 100101, Beijing, China
| | - Jun-Yan Sun
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China
| | - Lin-Lin Gao
- Department of Neurobiology, Xuanwu Hospital of Capital Medical University, 100053, Beijing, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, 100101, Beijing, China
| | - Xue-Ying Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, 100101, Beijing, China
| | - Er-He Xu
- Department of Neurology, Xuanwu Hospital of Capital Medical University, 100053, Beijing, China
| | - Jing-Hong Ma
- Department of Neurology, Xuanwu Hospital of Capital Medical University, 100053, Beijing, China
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, 100101, Beijing, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, 100070, Beijing, China.
| | - Piu Chan
- Department of Neurology, Xuanwu Hospital of Capital Medical University, 100053, Beijing, China.
- Key Laboratory on Neurodegenerative Disorders of Ministry of Education, Key Laboratory on Parkinson's Disease of Beijing, 100053, Beijing, China.
- National Clinical Research Center for Geriatric Disorders, 100053, Beijing, China.
- Beijing Institute for Brain Disorders Parkinson's Disease Center, Advanced Innovation Center for Human Brain Protection, Capital Medical University, 100069, Beijing, China.
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Tchetchenian A, Zhu Y, Zhang F, O'Donnell LJ, Song Y, Meijering E. A comparison of manual and automated neural architecture search for white matter tract segmentation. Sci Rep 2023; 13:1617. [PMID: 36709392 PMCID: PMC9884270 DOI: 10.1038/s41598-023-28210-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 01/16/2023] [Indexed: 01/30/2023] Open
Abstract
Segmentation of white matter tracts in diffusion magnetic resonance images is an important first step in many imaging studies of the brain in health and disease. Similar to medical image segmentation in general, a popular approach to white matter tract segmentation is to use U-Net based artificial neural network architectures. Despite many suggested improvements to the U-Net architecture in recent years, there is a lack of systematic comparison of architectural variants for white matter tract segmentation. In this paper, we evaluate multiple U-Net based architectures specifically for this purpose. We compare the results of these networks to those achieved by our own various architecture changes, as well as to new U-Net architectures designed automatically via neural architecture search (NAS). To the best of our knowledge, this is the first study to systematically compare multiple U-Net based architectures for white matter tract segmentation, and the first to use NAS. We find that the recently proposed medical imaging segmentation network UNet3+ slightly outperforms the current state of the art for white matter tract segmentation, and achieves a notably better mean Dice score for segmentation of the fornix (+ 0.01 and + 0.006 mean Dice increase for left and right fornix respectively), a tract that the current state of the art model struggles to segment. UNet3+ also outperforms the current state of the art when little training data is available. Additionally, manual architecture search found that a minor segmentation improvement is observed when an additional, deeper layer is added to the U-shape of UNet3+. However, all networks, including those designed via NAS, achieve similar results, suggesting that there may be benefit in exploring networks that deviate from the general U-Net paradigm.
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Affiliation(s)
- Ari Tchetchenian
- Biomedical Image Computing Group, School of Computer Science and Engineering, University of New South Wales (UNSW), Sydney, NSW, Australia.
| | - Yanming Zhu
- Biomedical Image Computing Group, School of Computer Science and Engineering, University of New South Wales (UNSW), Sydney, NSW, Australia
| | - Fan Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | | | - Yang Song
- Biomedical Image Computing Group, School of Computer Science and Engineering, University of New South Wales (UNSW), Sydney, NSW, Australia
| | - Erik Meijering
- Biomedical Image Computing Group, School of Computer Science and Engineering, University of New South Wales (UNSW), Sydney, NSW, Australia
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Deng JH, Zhang HW, Liu XL, Deng HZ, Lin F. Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis. World J Psychiatry 2022; 12:1356-1366. [PMID: 36579355 PMCID: PMC9791612 DOI: 10.5498/wjp.v12.i12.1356] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 11/02/2022] [Accepted: 11/22/2022] [Indexed: 12/16/2022] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra, resulting in clinical symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. The pathophysiological changes in PD are inextricably linked to the subcortical structures. Shape analysis is a method for quantifying the volume or surface morphology of structures using magnetic resonance imaging. In this review, we discuss the recent advances in morphological analysis techniques for studying the subcortical structures in PD in vivo. This approach includes available pipelines for volume and shape analysis, focusing on the morphological features of volume and surface area.
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Affiliation(s)
- Jin-Huan Deng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Han-Wen Zhang
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Xiao-Lei Liu
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Hua-Zhen Deng
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
| | - Fan Lin
- Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People’s Hospital, Shenzhen 518035, Guangdong Province, China
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10
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Specific pattern of linguistic impairment in Parkinson's disease patients with subjective cognitive decline and mild cognitive impairment predicts dementia. J Int Neuropsychol Soc 2022:1-9. [PMID: 36226685 DOI: 10.1017/s1355617722000571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVE Parkinson's disease patients with subjective cognitive decline (PD-SCD) and mild cognitive impairment (PD-MCI) have an increased risk of dementia (PDD). Thus, the identification of early cognitive changes that can be useful predictors of PDD is a highly relevant challenge. Posterior cortically based functions, including linguistic processes, have been associated with PDD. However, investigations that have focused on linguistic functions in PD-MCI are scarce and none of them include PD-SCD patients. Our aim was to study language performance in PD-SCD and PD-MCI. Moreover, language subcomponents were considered as predictors of PDD. METHOD Forty-six PD patients and twenty controls were evaluated with a neuropsychological protocol. Patients were classified as PD-SCD and PD-MCI. Language production and comprehension was assessed. Follow-up assessment was conducted to a mean of 7.5 years after the baseline. RESULTS PD-MCI patients showed a poor performance in naming (actions and nouns), action generation, anaphora resolution and sentence comprehension (with and without center-embedded relative clause). PD-SCD showed a poor performance in action naming and action generation. Deficit in action naming was an independent risk factor for PDD during the follow-up. Moreover, the combination of deficit in action words and sentence comprehension without a center-embedded relative clause was associated with a greater risk. CONCLUSIONS The results are of relevance because they suggest that a specific pattern of linguistic dysfunctions, that can be present even in the early stages of the disease, can predict future dementia, reinforcing the importance of advancing in the knowledge of linguistic dysfunctions in predementia stages of PD.
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11
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The structural changes of gray matter in Parkinson disease patients with mild cognitive impairments. PLoS One 2022; 17:e0269787. [PMID: 35857782 PMCID: PMC9299333 DOI: 10.1371/journal.pone.0269787] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 05/30/2022] [Indexed: 11/19/2022] Open
Abstract
Objectives
Parkinson disease (PD) is associated with cognitive impairments. However, the underlying neural mechanism of cognitive impairments in PD is still not clear. This study aimed to investigate the anatomic alternations of gray matter in PD patients with mild cognitive impairment (MCI) and their associations with neurocognitive measurements.
Methods
T1-weighted magnetic resonance imaging (MRI) data were acquired from 23 PD patients with MCI, 23 PD patients without MCI, and 23 matched healthy controls. The MRI data were analyzed using voxel-based morphometry (VBM) and surfaced-based morphometry (SBM) methods to assess the structural changes in gray matter volume and cortical thickness respectively. Receiver operating characteristic (ROC) analysis was used to examine the diagnostic accuracies of the indexes of interest. The correlations between the structural metrics and neurocognitive assessments (e.g., Montreal cognitive assessment, MOCA; Mini-mental state examination, MMSE) were further examined.
Results
PD patients with MCI showed reduced gray matter volume (GMV) in the frontal cortex (e.g., right inferior frontal gyrus and middle frontal gyrus) and extended to insula as well as cerebellum compared with the healthy controls and PD patients without MIC. Thinner of cortical thickens in the temporal lobe (e.g., left middle temporal gyrus and right superior temporal gyrus) extending to parietal cortex (e.g., precuneus) were found in the PD patients with MCI relative to the healthy controls and PD patients without MCI.ROC analysis indicated that the area under the ROC curve (AUC) values in the frontal, temporal, and subcortical structures (e.g., insula and cerebellum) could differentiate the PD patients with MCI and without MCI and healthy controls. Furthermore, GMV of the right middle frontal gyrus and cortical thickness of the right superior temporal gyrus were correlated with neurocognitive dysfunctions (e.g., MOCA and MMSE) in PD patients with MCI.
Conclusion
This study provided further evidence that PD with MCI was associated with structural alternations of brain. Morphometric analysis focusing on the cortical and subcortical regions could be biomarkers of cognitive impairments in PD patients.
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12
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The frontostriatal subtype of mild cognitive impairment in Parkinson’s disease, but not the posterior cortical one, is associated with specific EEG alterations. Cortex 2022; 153:166-177. [DOI: 10.1016/j.cortex.2022.04.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/27/2022] [Accepted: 04/07/2022] [Indexed: 11/22/2022]
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13
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Calderón-Garcidueñas L, Hernández-Luna J, Mukherjee PS, Styner M, Chávez-Franco DA, Luévano-Castro SC, Crespo-Cortés CN, Stommel EW, Torres-Jardón R. Hemispheric Cortical, Cerebellar and Caudate Atrophy Associated to Cognitive Impairment in Metropolitan Mexico City Young Adults Exposed to Fine Particulate Matter Air Pollution. TOXICS 2022; 10:toxics10040156. [PMID: 35448417 PMCID: PMC9028857 DOI: 10.3390/toxics10040156] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/14/2022] [Accepted: 03/22/2022] [Indexed: 12/16/2022]
Abstract
Exposures to fine particulate matter PM2.5 are associated with Alzheimer's, Parkinson's (AD, PD) and TDP-43 pathology in young Metropolitan Mexico City (MMC) residents. High-resolution structural T1-weighted brain MRI and/or Montreal Cognitive Assessment (MoCA) data were examined in 302 volunteers age 32.7 ± 6.0 years old. We used multivariate linear regressions to examine cortical surface area and thickness, subcortical and cerebellar volumes and MoCA in ≤30 vs. ≥31 years old. MMC residents were exposed to PM2.5 ~ 30.9 µg/m3. Robust hemispheric differences in frontal and temporal lobes, caudate and cerebellar gray and white matter and strong associations between MoCA total and index scores and caudate bilateral volumes, frontotemporal and cerebellar volumetric changes were documented. MoCA LIS scores are affected early and low pollution controls ≥ 31 years old have higher MoCA vs. MMC counterparts (p ≤ 0.0001). Residency in MMC is associated with cognitive impairment and overlapping targeted patterns of brain atrophy described for AD, PD and Fronto-Temporal Dementia (FTD). MMC children and young adult longitudinal studies are urgently needed to define brain development impact, cognitive impairment and brain atrophy related to air pollution. Identification of early AD, PD and FTD biomarkers and reductions on PM2.5 emissions, including poorly regulated heavy-duty diesel vehicles, should be prioritized to protect 21.8 million highly exposed MMC urbanites.
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Affiliation(s)
- Lilian Calderón-Garcidueñas
- College of Health, The University of Montana, Missoula, MT 59812, USA
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
- Correspondence: ; Tel.: +1-406-243-4785
| | | | - Partha S. Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata 700108, India;
| | - Martin Styner
- Neuro Image Research and Analysis Lab, University of North Carolina, Chapel Hill, NC 27599, USA;
| | - Diana A. Chávez-Franco
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Samuel C. Luévano-Castro
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Celia Nohemí Crespo-Cortés
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Elijah W. Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA;
| | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico;
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Devignes Q, Lopes R, Dujardin K. Neuroimaging outcomes associated with mild cognitive impairment subtypes in Parkinson's disease: A systematic review. Parkinsonism Relat Disord 2022; 95:122-137. [DOI: 10.1016/j.parkreldis.2022.02.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 01/26/2022] [Accepted: 02/11/2022] [Indexed: 02/07/2023]
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15
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Devignes Q, Daoudi S, Viard R, Lopes R, Betrouni N, Kuchcinski G, Rolland AS, Moreau C, Defebvre L, Bardinet E, Bonnet M, Brefel-Courbon C, Delmaire C, El Mountassir F, Fluchère F, Fradet A, Giordana C, Hainque E, Houvenaghel JF, Jarraya B, Klinger H, Maltête D, Marques A, Meyer M, Rascol O, Rouaud T, Tir M, Wirth T, Corvol JC, Devos D, Dujardin K. Heterogeneity of PD-MCI in Candidates to Subthalamic Deep Brain Stimulation: Associated Cortical and Subcortical Modifications. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1507-1526. [PMID: 35599498 DOI: 10.3233/jpd-223232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
BACKGROUND Parkinson's disease mild cognitive impairment (PD-MCI) is frequent and heterogenous. There is no consensus about its influence on subthalamic deep brain stimulation (STN-DBS) outcomes. OBJECTIVE To determine the prevalence of PD-MCI and its subtypes in candidates to STN-DBS. Secondarily, we sought to identify MRI structural markers associated with cognitive impairment in these subgroups. METHODS Baseline data from the French multicentric PREDISTIM cohort were used. Candidates to STN-DBS were classified according to their cognitive performance in normal cognition (PD-NC) or PD-MCI. The latter included frontostriatal (PD-FS) and posterior cortical (PD-PC) subtypes. Between-group comparisons were performed on demographical and clinical variables as well as on T1-weighted MRI sequences at the cortical and subcortical levels. RESULTS 320 patients were included: 167 (52%) PD-NC and 153 (48%) PD-MCI patients. The latter group included 123 (80%) PD-FS and 30 (20%) PD-PC patients. There was no between-group difference regarding demographic and clinical variables. PD-PC patients had significantly lower global efficiency than PD-FS patients and significantly worse performance on visuospatial functions, episodic memory, and language. Compared to PD-NC, PD-MCI patients had cortical thinning and radiomic-based changes in the left caudate nucleus and hippocampus. There were no significant differences between the PD-MCI subtypes. CONCLUSION Among the candidates to STN-DBS, a significant proportion has PD-MCI which is associated with cortical and subcortical alterations. Some PD-MCI patients have posterior cortical deficits, a subtype known to be at higher risk of dementia.
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Affiliation(s)
- Quentin Devignes
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
| | - Sami Daoudi
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
| | - Romain Viard
- Univ. Lille, CNRS, Inserm, US 41 - UMS 2014 - PLBS, CHU Lille, Lille Pasteur Institute, Lille, France
| | - Renaud Lopes
- Univ. Lille, CNRS, Inserm, US 41 - UMS 2014 - PLBS, CHU Lille, Lille Pasteur Institute, Lille, France
| | - Nacim Betrouni
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
| | - Gregory Kuchcinski
- Univ. Lille, CNRS, Inserm, US 41 - UMS 2014 - PLBS, CHU Lille, Lille Pasteur Institute, Lille, France
| | - Anne-Sophie Rolland
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Department of Medical Pharmacology, NS-Park/F-CRIN, Lille, France
| | - Caroline Moreau
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
| | - Luc Defebvre
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
| | - Eric Bardinet
- Institut du Cerveau (ICM), Centre de Neuro-Imagerie de Recherche (CENIR), UMR S 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Marie Bonnet
- Centre Expert Parkinson, NS-Park/F-CRIN, Centre Mémoire de Ressources et de Recherche, IMNc, Hôpital Pellegrin, CHU de Bordeaux, France
| | - Christine Brefel-Courbon
- Service de Neurologie B8, Centre Expert Parkinson, NS-Park/F-CRIN, Hôpital Pierre Paul Riquet, CHU Purpan, Toulouse, France
| | - Christine Delmaire
- Department of Radiology, NS-Park/F-CRIN, Hôpital Fondation A de Rothschild, Paris, France
| | - Fouzia El Mountassir
- Université Paris-Saclay, CEA, CNRS, Baobab, Neurospin, Gif-sur-Yvette, France and Institut du Cerveau (ICM), UMR S 1127, CNRS UMR 7225, Sorbonne Université, Paris, France
| | - Frédérique Fluchère
- Department of Neurology, NS-Park/F-CRIN, Assistance Publique - Hôpitaux de Marseille (APHM), Timone University Hospital and Institut de Neurosciences de la Timone, Marseille, France
| | - Anne Fradet
- Neurology Department, NS-Park/F-CRIN, University Hospital of Poitiers and INSERM, University of Poitiers, Centre d'Investigation Clinique CIC 1402, Poitiers, France
| | - Caroline Giordana
- Department of Neurology, NS-Park/F-CRIN, Centre Hospitalier Universitaire de Nice, Nice, France
| | - Elodie Hainque
- Sorbonne Université, Paris Brain Institute - ICM, NS-Park/F-CRIN, Assistance publique Hôpitaux de Paris, Inserm, CRNS, Hôpital Pitié-Salpêtrière, Department of Neurology, Paris, France
| | | | - Béchir Jarraya
- Neuroscience Pole, NS-Park/F-CRIN, Hôpital Foch, Suresnes, University of Versailles Paris-Saclay, INSERM-CEA NeuroSpin, Saclay, France
| | - Hélène Klinger
- Hospices Civils de Lyon, Hôpital Neurologique Pierre Wertheimer, Service de Neurologie C, NS-Park/F-CRIN, Lyon, France
| | - David Maltête
- Department of Neurology, NS-Park/F-CRIN, Rouen University Hospital and University of Rouen, France; INSERM U1239, Laboratory of Neuronal and Neuroendocrine Differentiation and Communication, Mont-Saint-Aignan, France
| | - Ana Marques
- Université Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand University Hospital, Neurology department, NS-Park/F-CRIN, Clermont-Ferrand, France
| | - Mylène Meyer
- Neurology department, NS-Park/F-CRIN, Central Hospital, CHRU-Nancy, Nancy, France
| | - Olivier Rascol
- Department of Clinical Pharmacology and Neuroscience, NS-Park/F-CRIN, Toulouse University Hospital, Toulouse, France
| | - Tiphaine Rouaud
- Department of Neurology, Centre Expert Parkinson, NS-Park/F-CRIN, CHU Nantes, Nantes, France
| | - Melissa Tir
- Department of Neurology, NS-PARK/FCRIN, Amiens University Hospital, Amiens, France
| | - Thomas Wirth
- Service de Neurologie, NS-Park/F-CRIN, Hôpitaux Universitaires de Strasbourg et Fédération de Médecine Translationnelle de Médecine de Strasbourg, Strasbourg, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, INSERM-U964/CNRS-UMR7104/Université de Strasbourg, Illkirch, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Paris Brain Institute - ICM, NS-Park/F-CRIN, Assistance publique Hôpitaux de Paris, Inserm, CRNS, Hôpital Pitié-Salpêtrière, Department of Neurology, Paris, France
| | - David Devos
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Department of Medical Pharmacology, NS-Park/F-CRIN, Lille, France
| | - Kathy Dujardin
- Univ. Lille, Inserm, Lille Neurosciences and Cognition, CHU-Lille, Neurology and Movement Disorders department, NS-Park/F-CRIN, Lille, France
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16
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Devignes Q, Bordier C, Viard R, Defebvre L, Kuchcinski G, Leentjens AFG, Lopes R, Dujardin K. Resting-State Functional Connectivity in Frontostriatal and Posterior Cortical Subtypes in Parkinson's Disease-Mild Cognitive Impairment. Mov Disord 2021; 37:502-512. [PMID: 34918782 DOI: 10.1002/mds.28888] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/10/2021] [Accepted: 11/29/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND The "dual syndrome hypothesis" distinguished two subtypes in mild cognitive impairment (MCI) in Parkinson's disease: frontostriatal, characterized by attentional and executive deficits; and posterior cortical, characterized by visuospatial, memory, and language deficits. OBJECTIVE The aim was to identify resting-state functional modifications associated with these subtypes. METHODS Ninety-five nondemented patients categorized as having normal cognition (n = 31), frontostriatal (n = 14), posterior cortical (n = 20), or mixed (n = 30) cognitive subtype had a 3 T resting-state functional magnetic resonance imaging scan. Twenty-four age-matched healthy controls (HCs) were also included. A group-level independent component analysis was performed to identify resting-state networks, and the selected components were subdivided into 564 cortical regions in addition to 26 basal ganglia regions. Global intra- and inter-network connectivity along with global and local efficiencies was compared between groups. The network-based statistics approach was used to identify connections significantly different between groups. RESULTS Patients with posterior cortical deficits had increased intra-network functional connectivity (FC) within the basal ganglia network compared with patients with frontostriatal deficits. Patients with frontostriatal deficits had reduced inter-network FC between several networks, including the visual, default-mode, sensorimotor, salience, dorsal attentional, basal ganglia, and frontoparietal networks, compared with HCs, patients with normal cognition, and patients with a posterior cortical subtype. Similar results were also found between patients with a mixed subtype and HCs. CONCLUSION MCI subtypes are associated with specific changes in resting-state FC. Longitudinal studies are needed to determine the predictive potential of these markers regarding the risk of developing dementia. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Quentin Devignes
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France
| | - Cécile Bordier
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France.,Univ. Lille, CNRS, Inserm, US 41-UMS 2014-PLBS, CHU Lille, Lille Pasteur Institute, Lille, France.,Department of Neuroradiology, CHU Lille, Lille, France
| | - Romain Viard
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France.,Univ. Lille, CNRS, Inserm, US 41-UMS 2014-PLBS, CHU Lille, Lille Pasteur Institute, Lille, France.,Department of Neuroradiology, CHU Lille, Lille, France
| | - Luc Defebvre
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France.,Neurology and Movement Disorders Department, CHU Lille, Lille, France
| | - Grégory Kuchcinski
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France.,Univ. Lille, CNRS, Inserm, US 41-UMS 2014-PLBS, CHU Lille, Lille Pasteur Institute, Lille, France.,Department of Neuroradiology, CHU Lille, Lille, France
| | - Albert F G Leentjens
- Department of Psychiatry, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Renaud Lopes
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France.,Univ. Lille, CNRS, Inserm, US 41-UMS 2014-PLBS, CHU Lille, Lille Pasteur Institute, Lille, France.,Department of Neuroradiology, CHU Lille, Lille, France
| | - Kathy Dujardin
- Univ. Lille, Inserm 1172, Lille Neurosciences and Cognition, CHU Lille, Lille, France.,Neurology and Movement Disorders Department, CHU Lille, Lille, France
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