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  • 1
    Online Resource
    Online Resource
    Elsevier BV ; 2021
    In:  Parkinsonism & Related Disorders Vol. 85 ( 2021-04), p. 95-101
    In: Parkinsonism & Related Disorders, Elsevier BV, Vol. 85 ( 2021-04), p. 95-101
    Type of Medium: Online Resource
    ISSN: 1353-8020
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 2027635-7
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  • 2
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2022
    In:  Scientific Data Vol. 9, No. 1 ( 2022-05-27)
    In: Scientific Data, Springer Science and Business Media LLC, Vol. 9, No. 1 ( 2022-05-27)
    Abstract: Magnetic resonance image (MRI) processing pipelines use average templates to enable standardization of individual MRIs in a common space. MNI-ICBM152 is currently used as the standard template by most MRI processing tools. However, MNI-ICBM152 represents an average of 152 healthy young adult brains and is vastly different from brains of patients with neurodegenerative diseases. In those populations, extensive atrophy might cause inevitable registration errors when using an average template of young healthy individuals for standardization. Disease-specific templates that represent the anatomical characteristics of the populations can reduce such errors and improve downstream driven estimates. We present multi-sequence average templates for Alzheimer’s Dementia (AD), Fronto-temporal Dementia (FTD), Lewy Body Dementia (LBD), Mild Cognitive Impairment (MCI), cognitively intact and impaired Parkinson’s Disease patients (PD-CIE and PD-CI, respectively), individuals with Subjective Cognitive Impairment (SCI), AD with vascular contribution (V-AD), Vascular Mild Cognitive Impairment (V-MCI), Cognitively Intact Elderly (CIE) individuals, and a human phantom. We also provide separate templates for males and females to allow better representation of the diseases in each sex group.
    Type of Medium: Online Resource
    ISSN: 2052-4463
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2775191-0
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  • 3
    In: NeuroImage: Clinical, Elsevier BV, Vol. 36 ( 2022), p. 103204-
    Type of Medium: Online Resource
    ISSN: 2213-1582
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 2701571-3
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  • 4
    In: Alzheimer's & Dementia, Wiley, Vol. 16, No. S5 ( 2020-12)
    Abstract: Previous studies have found associations between atrophy in Substantia Nigra (SN) and White Matter Hyperintensities (WMH) of vascular origin and motor deficits in Parkinson’s disease (PD) patients (Zeighami et al. 2015, Pozorski et al. 2019). Here we assess the relationship between WMHs and SN atrophy and motor symptoms in PD. Method Data included 50 PD patients and 45 age‐matched controls with T1‐weighted and FLAIR scans at baseline, month18, and month36. WMHs were segmented using T1‐weighted and FLAIR images and a random forests classifier (Dadar et al. 2017, Figure 1.a). Deformation‐based morphometry was used to measure atrophy in Substantia Nigra (SN) (Figure 1.b, Ashburner et al 1998). The relationship between MRI features and clinical scores was assessed using mixed‐effects models: where Cohort denotes a categorical variable contrasting PD versus controls, and ID denotes the categorical random effects. The variables of interest were MRI‐Feature (implying an overall association between the MRI feature and clinical score of interest) and the interaction term Cohort:MRI‐Score (implying an additional PD‐specific impact of the MRI‐Feature on the Clinical‐Score). Log‐transformed WMH volumes and mean DBM score in left and right SN were used as MRI features. The motor subscore of Unified Parkinson's Disease Rating Scale (UPDRSIII) was used as the dependent variable of interest, reflecting motor deficits. Result WMH load significantly increased with age in both groups (t=9.95, p 〈 0.0001). We did not find a significant group difference in WMH volumes. However, WMH load was significantly associated with UPDRSIII in PDs (t=2.63, p=0.008), but not in controls (t=0.02, p=0.86), with a marginal interaction (t=1.67, p=0.05, Figure 2). DBM in both left and right SN significantly decreased with age (t LeftSN =‐5.79, t RightSN =‐6.33, p 〈 0.0001), and were significantly different between the cohorts (Figure 3, t LeftSN =‐4.19, t RightSN =‐3.95, p 〈 0.00001). UPDRSIII significantly increased with age (t=4.75, p 〈 0.00001) and decrease in SN DBM (t LeftSN =‐2.02, t RightSN =‐1.88, p 〈 0.05), with a significantly greater impact in PDs (Figure 4, t LeftSN =‐2.10, t RightSN =‐1.73, p 〈 0.04). Conclusion In our sample, both SN atrophy and WMH burden were significantly associated with additional motor deficits in PD, implying an additive contribution of both gray and white matter damage to the motor deficits in PD.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2201940-6
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  • 5
    In: Frontiers in Aging Neuroscience, Frontiers Media SA, Vol. 15 ( 2023-4-5)
    Abstract: Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) are part of a spectrum of Lewy body disorders, who exhibit a range of cognitive and gait impairments. Cognitive-motor interactions can be examined by performing a cognitive task while walking and quantified by a dual task cost (DTC). White matter hyperintensities (WMH) on magnetic resonance imaging have also been associated with both gait and cognition. Our goal was to examine the relationship between DTC and WMH in the Lewy body spectrum, hypothesizing DTC would be associated with increased WMH volume. Methods Seventy-eight participants with PD, PD with mild cognitive impairment (PD-MCI), PD with dementia or DLB (PDD/DLB), and 20 cognitively unimpaired participants were examined in a multi-site study. Gait was measured on an electronic walkway during usual gait, counting backward, animal fluency, and subtracting sevens. WMH were quantified from magnetic resonance imaging using an automated pipeline and visual rating. A median split based on DTC was performed. Models included age as well as measures of global cognition and cardiovascular risk. Results Compared to cognitively unimpaired participants, usual gait speed was lower and DTC was higher in PD-MCI and PDD/DLB. Low DTC participants had higher usual gait speed. WMH burden was greater in high counting DTC participants. Frontal WMH burden remained significant after adjusting for age, cardiovascular risk and global cognition. Conclusion Increased DTC was associated with higher frontal WMH burden in Lewy body disorders after adjusting for age, cardiovascular risk, and global cognition. Higher DTC was associated with age.
    Type of Medium: Online Resource
    ISSN: 1663-4365
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2558898-9
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  • 6
    In: Human Brain Mapping, Wiley, Vol. 42, No. 9 ( 2021-06-15), p. 2734-2745
    Abstract: Volumetric estimates of subcortical and cortical structures, extracted from T1‐weighted MRIs, are widely used in many clinical and research applications. Here, we investigate the impact of the presence of white matter hyperintensities (WMHs) on FreeSurfer gray matter (GM) structure volumes and its possible bias on functional relationships. T1‐weighted images from 1,077 participants (4,321 timepoints) from the Alzheimer's Disease Neuroimaging Initiative were processed with FreeSurfer version 6.0.0. WMHs were segmented using a previously validated algorithm on either T2‐weighted or Fluid‐attenuated inversion recovery images. Mixed‐effects models were used to assess the relationships between overlapping WMHs and GM structure volumes and overall WMH burden, as well as to investigate whether such overlaps impact associations with age, diagnosis, and cognitive performance. Participants with higher WMH volumes had higher overlaps with GM volumes of bilateral caudate, cerebral cortex, putamen, thalamus, pallidum, and accumbens areas ( p   〈  .0001). When not corrected for WMHs, caudate volumes increased with age ( p   〈  .0001) and were not different between cognitively healthy individuals and age‐matched probable Alzheimer's disease patients. After correcting for WMHs, caudate volumes decreased with age ( p   〈  .0001), and Alzheimer's disease patients had lower caudate volumes than cognitively healthy individuals ( p   〈  .01). Uncorrected caudate volume was not associated with ADAS13 scores, whereas corrected lower caudate volumes were significantly associated with poorer cognitive performance ( p   〈  .0001). Presence of WMHs leads to systematic inaccuracies in GM segmentations, particularly for the caudate, which can also change clinical associations. While specifically measured for the Freesurfer toolkit, this problem likely affects other algorithms.
    Type of Medium: Online Resource
    ISSN: 1065-9471 , 1097-0193
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 1492703-2
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  • 7
    Online Resource
    Online Resource
    Elsevier BV ; 2020
    In:  NeuroImage: Clinical Vol. 27 ( 2020), p. 102353-
    In: NeuroImage: Clinical, Elsevier BV, Vol. 27 ( 2020), p. 102353-
    Type of Medium: Online Resource
    ISSN: 2213-1582
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2020
    detail.hit.zdb_id: 2701571-3
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  • 8
    Online Resource
    Online Resource
    Frontiers Media SA ; 2022
    In:  Frontiers in Neuroimaging Vol. 1 ( 2022-8-26)
    In: Frontiers in Neuroimaging, Frontiers Media SA, Vol. 1 ( 2022-8-26)
    Abstract: Cerebral microbleeds are small perivascular hemorrhages that can occur in both gray and white matter brain regions. Microbleeds are a marker of cerebrovascular pathology and are associated with an increased risk of cognitive decline and dementia. Microbleeds can be identified and manually segmented by expert radiologists and neurologists, usually from susceptibility-contrast MRI. The latter is hard to harmonize across scanners, while manual segmentation is laborious, time-consuming, and subject to interrater and intrarater variability. Automated techniques so far have shown high accuracy at a neighborhood (“patch”) level at the expense of a high number of false positive voxel-wise lesions. We aimed to develop an automated, more precise microbleed segmentation tool that can use standardizable MRI contrasts. Methods We first trained a ResNet50 network on another MRI segmentation task (cerebrospinal fluid vs. background segmentation) using T1-weighted, T2-weighted, and T2 * MRIs. We then used transfer learning to train the network for the detection of microbleeds with the same contrasts. As a final step, we employed a combination of morphological operators and rules at the local lesion level to remove false positives. Manual segmentation of microbleeds from 78 participants was used to train and validate the system. We assessed the impact of patch size, freezing weights of the initial layers, mini-batch size, learning rate, and data augmentation on the performance of the Microbleed ResNet50 network. Results The proposed method achieved high performance, with a patch-level sensitivity, specificity, and accuracy of 99.57, 99.16, and 99.93%, respectively. At a per lesion level, sensitivity, precision, and Dice similarity index values were 89.1, 20.1, and 0.28% for cortical GM; 100, 100, and 1.0% for deep GM; and 91.1, 44.3, and 0.58% for WM, respectively. Discussion The proposed microbleed segmentation method is more suitable for the automated detection of microbleeds with high sensitivity.
    Type of Medium: Online Resource
    ISSN: 2813-1193
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 3123824-5
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  • 9
    Online Resource
    Online Resource
    Wiley ; 2021
    In:  Alzheimer's & Dementia Vol. 17, No. S4 ( 2021-12)
    In: Alzheimer's & Dementia, Wiley, Vol. 17, No. S4 ( 2021-12)
    Abstract: Individuals with mild cognitive impairment (MCI) have variable clinical outcomes, with a proportion converting to dementia in a short follow‐up period. Subtyping MCI subjects based on biomarker levels can provide additional insights on why some individuals progress faster, aiding clinical treatment strategy and facilitating cohort enrichment for clinical trials. Method Data included 562 individuals with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) project with baseline MRI, CSF amyloid beta (Aβ), t‐tau, and p‐tau data and a minimum of one‐year follow‐up information on clinical diagnosis. White matter hyperintensities (WMHs) were segmented using a previously validated random forests classifier (Dadar et al. 2017). SNIPE (Scoring by Nonlocal Image Patch Estimator) was used to measure Alzheimer’s‐disease‐like atrophy patterns in the hippocampi (HC) and entorhinal cortex (EC) (Coupé et al. 2019). CSF Aβ, p‐tau and t‐tau levels were obtained from project files. Agglomerative hierarchical clustering as used to cluster the data based on baseline age, education, APOE4 status, CSF Aβ, p‐tau and t‐tau levels, WMH load, and HC and EC grading scores. We then investigated differences in baseline ADAS13 cognitive scores as well as rate of conversion to dementia between different subtypes. Result Figure 1 shows the clustering dendrogram, splitting the data into three subtypes of 152, 200, and 210 participants, respectively. Figure 2 compares biomarker values across subtypes. Baseline ADAS13 scores and conversion rates were significantly different across all subtypes (p 〈 0.0001). Subtype 1 had the oldest subjects with largest WMH loads (p 〈 0.0001), with a conversion rate of 30.2%. Subtype 2 had the highest conversion rate (70.0%), with significantly lower CSF Aβ and EC grading scores, and higher CSF p‐tau and t‐tau values (p 〈 0.0001). Subtype 3 had the lowest conversion rate (15.2%), with significantly higher HC and EC grading scores and lower age and WMH loads than the other two subtypes (p 〈 0.0001). Conclusion Biomarker‐based subtyping of MCI subjects led to three distinct groups with significantly different clinical outcomes: 1) older individuals with cerebrovascular pathology and moderate conversion rates, 2) individuals with abnormal CSF biomarker levels, hippocampal and entorhinal atrophy, and high conversion rates, and 3) younger individuals without abnormal biomarker levels and low conversion rates.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2021
    detail.hit.zdb_id: 2201940-6
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  • 10
    In: Alzheimer's & Dementia, Wiley, Vol. 16, No. S5 ( 2020-12)
    Abstract: MRI features of grey matter atrophy and White Matter Hyperintensities (WMHs) of cerebrovascular origin have been linked to cognitive symptoms in Parkinson’s disease (PD) (Yau 2018, Dadar 2018). Here we assess the relationship between WMH burden, gray matter atrophy in the Hippocampi and cognitive symptoms in PD. Method Data included 50 PD patients and 45 age‐matched controls with T1‐weighted and FLAIR scans at baseline, month18, and month36. WMHs were segmented using T1‐weighted and FLAIR images and a random forests classifier (Dadar et al. 2017, Figure 1.a). SNIPE (Scoring by Nonlocal Image Patch Estimator) was used to measure Alzheimer’s‐disease‐like atrophy patterns in the left and right hippocampi (Figure 1.b, Coupé et al. 2019). The relationship between MRI features and clinical scores was assessed using mixed‐effects models: where Cohort denotes a categorical variable contrasting PD versus controls, and ID denotes the categorical random effects. The variables of interest were MRI‐Feature (implying an overall association between the MRI feature and clinical score of interest) and the interaction term Cohort:MRI‐Score (implying an additional PD‐specific impact of the MRI‐Feature on the Clinical‐Score). Log‐transformed WMH volumes and SNIPE grading in the left and right Hippocampi were used as MRI features. Total Dementia Rating Scale (DRS) was the dependent variable of interest reflecting cognitive performance. Result WMH load significantly increased with age in both groups (t=9.95, p 〈 0.0001). We did not find a significant group difference in WMH volumes. We did not find a significant association between WMH load and Total DRS score in either group. Total DRS significantly decreased with age (t=‐2.23, p 〈 0.04) and decrease in Hippocampal grading (t LeftHC =2.83, p RighHC =0.005, t LeftHC =2.55, p RighHC =0.01), with a marginally greater impact in PDs (Figure 2, t LeftHC =1.80, p RighHC =0.07, t LeftHC =1.58, p RighHC =0.10). Conclusion In our cohort, hippocampal atrophy was significantly associated with cognitive deficits in both controls and PD patients, with a slightly greater impact in the PD group. We did not observe an impact of vascular disease burden on cognitive performance.
    Type of Medium: Online Resource
    ISSN: 1552-5260 , 1552-5279
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2201940-6
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