Publications by authors named "Hugo J Kuijf"

69 Publications

An anomaly detection approach to identify chronic brain infarcts on MRI.

Sci Rep 2021 Apr 8;11(1):7714. Epub 2021 Apr 8.

Image Sciences Institute, UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.

The performance of current machine learning methods to detect heterogeneous pathology is limited by the quantity and quality of pathology in medical images. A possible solution is anomaly detection; an approach that can detect all abnormalities by learning how 'normal' tissue looks like. In this work, we propose an anomaly detection method using a neural network architecture for the detection of chronic brain infarcts on brain MR images. The neural network was trained to learn the visual appearance of normal appearing brains of 697 patients. We evaluated its performance on the detection of chronic brain infarcts in 225 patients, which were previously labeled. Our proposed method detected 374 chronic brain infarcts (68% of the total amount of brain infarcts) which represented 97.5% of the total infarct volume. Additionally, 26 new brain infarcts were identified that were originally missed by the radiologist during radiological reading. Our proposed method also detected white matter hyperintensities, anomalous calcifications, and imaging artefacts. This work shows that anomaly detection is a powerful approach for the detection of multiple brain abnormalities, and can potentially be used to improve the radiological workflow efficiency by guiding radiologists to brain anomalies which otherwise remain unnoticed.
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http://dx.doi.org/10.1038/s41598-021-87013-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032662PMC
April 2021

Detection of Cerebral Microbleeds With Venous Connection at 7 Tesla MRI.

Neurology 2021 Mar 2. Epub 2021 Mar 2.

Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany.

Objective: Cerebral microbleeds (MBs) are a common finding in cerebral small vessel disease (CSVD) and Alzheimer's disease patients as well as in healthy elderly people, but their pathophysiology remains unclear. To investigate a possible role of veins in the development of MBs, we performed an exploratory study, assessing in vivo presence of MBs with a direct connection to a vein.

Methods: 7 Tesla (7 T) MRI was conducted and MBs were counted on Quantitative Susceptibility Mapping (QSM). A submillimeter resolution QSM-based venogram allowed identification of MBs with a direct spatial connection to a vein.

Results: 51 subjects (mean age [SD] 70.5[8.6] years, 37% females) participated in the study: 20 were patients with CSVD (cerebral amyloid angiopathy (CAA) with strictly lobar MBs (n=8), hypertensive arteriopathy (HA) with strictly deep MBs (n=5), and mixed lobar and deep MBs (n=7), 72.4 [6.1] years, 30% females) and 31 were healthy controls (69.4 [9.9] years, 42% females). In our cohort, we counted a total of 96 MBs with a venous connection, representing 14% of all detected MBs on 7T QSM. Most venous MBs (86%, n = 83) were observed in lobar locations and all of these were cortical. CAA subjects showed the highest ratio of venous to total MBs (19%) (HA=9%, mixed=18%, controls=5%) CONCLUSIONS: Our findings establish a link between cerebral MBs and the venous vasculature, pointing towards a possible contribution of veins to CSVD in general and to CAA in particular. Pathological studies are needed to confirm our observations.
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http://dx.doi.org/10.1212/WNL.0000000000011790DOI Listing
March 2021

Bringing AI to the clinic: blueprint for a vendor-neutral AI deployment infrastructure.

Insights Imaging 2021 Feb 2;12(1):11. Epub 2021 Feb 2.

Department of Radiology | E.01.132, Utrecht University Medical Center, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.

AI provides tremendous opportunities for improving patient care, but at present there is little evidence of real-world uptake. An important barrier is the lack of well-designed, vendor-neutral and future-proof infrastructures for deployment. Because current AI algorithms are very narrow in scope, it is expected that a typical hospital will deploy many algorithms concurrently. Managing stand-alone point solutions for all of these algorithms will be unmanageable. A solution to this problem is a dedicated platform for deployment of AI. Here we describe a blueprint for such a platform and the high-level design and implementation considerations of such a system that can be used clinically as well as for research and development. Close collaboration between radiologists, data scientists, software developers and experts in hospital IT as well as involvement of patients is crucial in order to successfully bring AI to the clinic.
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http://dx.doi.org/10.1186/s13244-020-00931-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855120PMC
February 2021

Post-stroke cognitive impairment on the Mini-Mental State Examination primarily relates to left middle cerebral artery infarcts.

Int J Stroke 2021 Jan 20:1747493020984552. Epub 2021 Jan 20.

Department of Neurology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Republic of Korea.

Background: Post-stroke cognitive impairment can occur after damage to various brain regions, and cognitive deficits depend on infarct location. The Mini-Mental State Examination (MMSE) is still widely used to assess post-stroke cognition, but it has been criticized for capturing only certain cognitive deficits. Along these lines, it might be hypothesized that cognitive deficits as measured with the MMSE primarily involve certain infarct locations.

Aims: This comprehensive lesion-symptom mapping study aimed to determine which acute infarct locations are associated with post-stroke cognitive impairment on the MMSE.

Methods: We examined associations between impairment on the MMSE (<5th percentile; normative data) and infarct location in 1198 patients (age 67 ± 12 years, 43% female) with acute ischemic stroke using voxel-based lesion-symptom mapping. As a frame of reference, infarct patterns associated with impairments in individual cognitive domains were determined, based on a more detailed neuropsychological assessment.

Results: Impairment on the MMSE was present in 420 patients (35%). Large voxel clusters in the left middle cerebral artery territory and thalamus were significantly (p < 0.01) associated with cognitive impairment on the MMSE, with highest odds ratios (>15) in the thalamus and superior temporal gyrus. In comparison, domain-specific impairments were related to various infarct patterns across both hemispheres including the left medial temporal lobe (verbal memory) and right parietal lobe (visuospatial functioning).

Conclusions: Our findings indicate that post-stroke cognitive impairment on the MMSE primarily relates to infarct locations in the left middle cerebral artery territory. The MMSE is apparently less sensitive to cognitive deficits that specifically relate to other locations.
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http://dx.doi.org/10.1177/1747493020984552DOI Listing
January 2021

The Effects of Intracranial Stenosis on Cerebral Perfusion and Cognitive Performance.

J Alzheimers Dis 2021 ;79(3):1369-1380

Department of Pharmacology, National University of Singapore, Singapore.

Background: Intracranial stenosis (ICS) may contribute to cognitive dysfunction by decreased cerebral blood flow (CBF) which can be measured quantitatively by arterial spin labelling (ASL). Interpretation of CBF measurements with ASL, however, becomes difficult in patients with vascular disease due to prolonged arterial transit time (ATT). Recently, spatial coefficient of variation (sCoV) of ASL signal has been proposed that approximates ATT and utilized as a proxy marker for assessment of hemodynamic status of cerebral circulation.

Objective: We investigate the association of ICS with CBF and sCoV parameters and its eventual effects on cognition in a memory clinic population.

Methods: We included 381 patients (mean age = 72.3±7.9 years, women = 53.7%) who underwent 3T MRI and detailed neuropsychological assessment. ICS was defined as≥50% stenosis in any intracranial vessel on 3D Time-of-Flight MR Angiography. Gray matter sCoV and CBF were obtained from 2D EPI pseudo-continuous ASL images.

Results: ICS was present in 58 (15.2%) patients. Patients with ICS had higher gray matter sCoV and lower CBF. The association with sCoV remained statistically significant after correction for cardiovascular risk factors. Moreover, ICS was associated with worse performance on visuoconstruction, which attenuated with higher sCoV. Mediation analysis showed that there was an indirect effect of ICS on visuoconstruction via sCoV.

Conclusion: These findings suggest that compromised CBF as detected by higher sCoV is related to cognitive impairment among individuals diagnosed with ICS. We also showed that sCoV partially mediates the link between ICS and cognition. Therefore, sCoV may provide valuable hemodynamic information in patients with vascular disease.
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http://dx.doi.org/10.3233/JAD-201131DOI Listing
January 2021

Patient-specific fine-tuning of convolutional neural networks for follow-up lesion quantification.

J Med Imaging (Bellingham) 2020 Nov 17;7(6):064003. Epub 2020 Dec 17.

University Medical Center Utrecht and Utrecht University, Image Sciences Institute, Utrecht, The Netherlands.

Convolutional neural network (CNN) methods have been proposed to quantify lesions in medical imaging. Commonly, more than one imaging examination is available for a patient, but the serial information in these images often remains unused. CNN-based methods have the potential to extract valuable information from previously acquired imaging to better quantify lesions on current imaging of the same patient. A pretrained CNN can be updated with a patient's previously acquired imaging: patient-specific fine-tuning (FT). In this work, we studied the improvement in performance of lesion quantification methods on magnetic resonance images after FT compared to a pretrained base CNN. We applied the method to two different approaches: the detection of liver metastases and the segmentation of brain white matter hyperintensities (WMH). The patient-specific fine-tuned CNN has a better performance than the base CNN. For the liver metastases, the median true positive rate increases from 0.67 to 0.85. For the WMH segmentation, the mean Dice similarity coefficient increases from 0.82 to 0.87. We showed that patient-specific FT has the potential to improve the lesion quantification performance of general CNNs by exploiting a patient's previously acquired imaging.
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http://dx.doi.org/10.1117/1.JMI.7.6.064003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744252PMC
November 2020

Arterial Remodeling of the Intracranial Arteries in Patients With Hypertension and Controls: A Postmortem Study.

Hypertension 2021 Jan 23;77(1):135-146. Epub 2020 Nov 23.

Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, the Netherlands (C.M., I.S.E.W., M.P.D.B., M.J.A.P.D., D.M.A.H.).

The intracranial arteries play a major role in cerebrovascular disease, but arterial remodeling due to hypertension has not been well described in humans. We aimed to quantify this remodeling for: the basilar artery, the vertebral, internal carotid, middle/anterior (inferior)/posterior cerebral, posterior communicating, and superior cerebellar arteries of the circle of Willis. Ex vivo circle of Willis specimens, selected from individuals with (n=24) and without (n=25) a history of hypertension, were imaged at 7T magnetic resonance imaging using a 3-dimensional gradient-echo sequence. Subsequently, histological analysis was performed. We validated the vessel wall thickness and area measurements from magnetic resonance imaging against histology. Next, we investigated potential differences in vessel wall thickness and area between both groups using both techniques. Finally, using histological analysis, we investigated potential differences in arterial wall stiffness and atherosclerotic plaque severity and load. All analyses were unadjusted. Magnetic resonance imaging and histology showed comparable vessel wall thickness (mean difference: 0.04 mm (limits of agreement:-0.12 to 0.19 mm) and area (0.43 mm [-0.97 to 1.8 mm]) measurements. We observed no statistically significant differences in vessel wall thickness and area between both groups using either technique. Histological analysis showed early and advanced atherosclerotic plaques in almost all arteries for both groups. The arterial wall stiffness was significantly higher for the internal carotid artery in the hypertensive group. Concluding, we did not observe vessel wall thickening in the circle of Willis arteries in individuals with a history of hypertension using either technique. Using histological analysis, we observed a difference in vessel wall composition for the internal carotid artery.
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http://dx.doi.org/10.1161/HYPERTENSIONAHA.120.16029DOI Listing
January 2021

Subvoxel vessel wall thickness measurements of the intracranial arteries using a convolutional neural network.

Med Image Anal 2021 01 30;67:101818. Epub 2020 Sep 30.

Image Sciences Institute, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3584CX, the Netherlands.

Vessel wall thickening of the intracranial arteries has been associated with cerebrovascular disease and atherosclerotic plaque development. Visualization of the vessel wall has been enabled by recent advancements in vessel wall MRI. However, quantifying early wall thickening from these MR images is difficult and prone to severe overestimation, because the voxel size of clinically used acquisitions exceeds the wall thickness of the intracranial arteries. In this study, we aimed for accurate and precise subvoxel vessel wall thickness measurements. A convolutional neural network was trained on MR images of 34 ex vivo circle of Willis specimens, acquired with a clinically used protocol (isotropic acquired voxel size: 0.8 mm). Ground truth measurements were performed on images acquired with an ultra-high-resolution protocol (isotropic acquired voxel size: 0.11 mm) and were used for evaluation. Additionally, we determined the robustness of our method by applying Monte Carlo dropout and test time augmentation. Lastly, we applied our method on in vivo images of three intracranial aneurysms to measure their wall thickness. Our method shows resolvability of different vessel wall thicknesses, well below the acquired voxel size. The method described may facilitate quantitative measurements on MRI data for a wider range of clinical applications.
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http://dx.doi.org/10.1016/j.media.2020.101818DOI Listing
January 2021

Intracranial vessel wall lesions on 7T MRI and MRI features of cerebral small vessel disease-The SMART-MR study.

J Cereb Blood Flow Metab 2020 Oct 6:271678X20958517. Epub 2020 Oct 6.

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.

The etiology of cerebral small vessel disease (CSVD) is the subject of ongoing research. Although intracranial atherosclerosis (ICAS) has been proposed as a possible cause, studies on their relationship remain sparse. We used 7 T vessel wall magnetic resonance imaging (MRI) to study the association between intracranial vessel wall lesions-a neuroimaging marker of ICAS-and MRI features of CSVD. Within the SMART-MR study, cross-sectional analyses were performed in 130 patients (68 ± 9 years; 88% male). ICAS burden-defined as the number of vessel wall lesions-was determined on 7 T vessel wall MRI. CSVD features were determined on 1.5 T and 7 T MRI. Associations between ICAS burden and CSVD features were estimated with linear or modified Poisson regression, adjusted for age, sex, vascular risk factors, and medication use. In 125 patients, ≥1 vessel wall lesions were found (mean 8.5 ± 5.7 lesions). ICAS burden (per + 1 SD) was associated with presence of large subcortical and/or cortical infarcts (RR = 1.65; 95%CI: 1.12-2.43), lacunes (RR = 1.45; 95% CI: 1.14-1.86), cortical microinfarcts (RR = 1.48; 95%CI: 1.13-1.94), and total white matter hyperintensity volume ( = 0.24; 95%CI: 0.02-0.46). Concluding, patients with a higher ICAS burden had more CSVD features, although no evidence of co-location was observed. Further longitudinal studies are required to determine if ICAS precedes development of CSVD.
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http://dx.doi.org/10.1177/0271678X20958517DOI Listing
October 2020

Vascular Risk Factors of Hippocampal Subfield Volumes in Persons without Dementia: The Medea 7T Study.

J Alzheimers Dis 2020 ;77(3):1223-1239

Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.

Background: Vascular risk factors have been associated with risk of Alzheimer's disease (AD) and volume loss of the hippocampus, but the associations with subfields of the hippocampus are understudied. Knowing if vascular risk factors contribute to hippocampal subfield atrophy may improve our understanding of vascular contributions to neurodegenerative diseases.

Objective: To investigate the associations between age, sex, and vascular risk factors with hippocampal subfields volumes on 7T MRI in older persons without dementia.

Methods: From the Medea 7T study, 283 participants (67±9 years, 68% men) without dementia had 7T brain MRI and hippocampal subfield segmentation. Subfields were automatically segmented on the 3D T2-weighted 7T images with ASHS software. Using linear mixed models, we estimated adjusted associations of age, sex, and vascular risk factors with z-scores of volumes of the entorhinal cortex (ERC), subiculum (SUB), Cornu Ammonis (CA)1, CA2, CA3, CA4, and dentate gyrus (DG), and tail as multivariate correlated outcomes.

Results: Increasing age was associated with smaller volumes in all subfields, except CA4/DG. Current smoking was associated with smaller ERC and SUB volumes; moderate alcohol use with smaller CA1 and CA4/DG, obesity with smaller volumes of ERC, SUB, CA2, CA3, and tail; and diabetes mellitus with smaller SUB volume. Sex, former smoking, and hypertension were not associated with subfield volumes. When formally tested, no risk factor affected the subfield volumes differentially.

Conclusion: Several vascular risk factors were associated with smaller volumes of specific hippocampal subfields. However, no statistical evidence was found that subfields were differentially affected by these risk factors.
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http://dx.doi.org/10.3233/JAD-200159DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683058PMC
January 2020

Sex differences in memory clinic patients with possible vascular cognitive impairment.

Alzheimers Dement (Amst) 2020 25;12(1):e12090. Epub 2020 Aug 25.

Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam the Netherlands.

Introduction: We aimed to establish sex differences in vascular brain damage of memory clinic patients with possible vascular cognitive impairment (VCI).

Methods: A total of 860 memory clinic patients (aged 67.7 ± 8.5; 46% female) with cognitive complaints and vascular brain damage (ie, possible VCI) from the prospective TRACE-VCI (Utrecht-Amsterdam Clinical Features and Prognosis in Vascular Cognitive Impairment) cohort study with 2-year follow-up were included. Age-adjusted female-to-male differences were calculated with general linear models, for demographic variables, vascular risk factors, clinical diagnosis, cognitive performance, and brain magnetic resonance imaging markers.

Results: We found no difference in age nor distribution of clinical diagnoses between females and males. Females performed worse on the MMSE (Mini-Mental State Examination) and CAMCOG (Cognitive and Self-Contained Part of the Cambridge Examination for Mental Disorders of the Elderly). Females had a larger white matter hyperintensity volume, while males more often showed (lacunar) infarcts. There was no difference in microbleed prevalence. Males had smaller normalized total brain and gray matter volumes. During follow-up, occurrence of cognitive decline and institutionalization was comparable, but mortality was higher in males.

Discussion: Our results suggest that susceptibility and underlying etiology of VCI might differ by sex. Males seem to have more large vessel brain damage compared to females that have more small vessel brain damage.
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http://dx.doi.org/10.1002/dad2.12090DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7447910PMC
August 2020

Small vessel disease lesion type and brain atrophy: The role of co-occurring amyloid.

Alzheimers Dement (Amst) 2020 13;12(1):e12060. Epub 2020 Jul 13.

Department of Neurology and Neurosurgery UMC Utrecht Brain Center Utrecht University Utrecht the Netherlands.

Introduction: It is unknown whether different types of small vessel disease (SVD), differentially relate to brain atrophy and if co-occurring Alzheimer's disease pathology affects this relation.

Methods: In 725 memory clinic patients with SVD (mean age 67 ± 8 years, 48% female) we compared brain volumes of those with moderate/severe white matter hyperintensities (WMHs; n = 326), lacunes (n = 132) and cerebral microbleeds (n = 321) to a reference group with mild WMHs (n = 197), also considering cerebrospinal fluid (CSF) amyloid status in a subset of patients (n = 488).

Results: WMHs and lacunes, but not cerebral microbleeds, were associated with smaller gray matter (GM) volumes. In analyses stratified by CSF amyloid status, WMHs and lacunes were associated with smaller total brain and GM volumes only in amyloid-negative patients. SVD-related atrophy was most evident in frontal (cortical) GM, again predominantly in amyloid-negative patients.

Discussion: Amyloid status modifies the differential relation between SVD lesion type and brain atrophy in memory clinic patients.
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http://dx.doi.org/10.1002/dad2.12060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7364862PMC
July 2020

The Impact of Strategic White Matter Hyperintensity Lesion Location on Language.

Am J Geriatr Psychiatry 2021 02 17;29(2):156-165. Epub 2020 Jun 17.

Memory Aging and Cognition Center, National University Health System (SH, EC, CC), Singapore; Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore (SH, CC), Singapore.

Objective: The impact of white matter hyperintensities (WMH) on language possibly depends on lesion location through disturbance of strategic white matter tracts. We examined the impact of WMH location on language in elderly Asians.

Design: Cross-sectional.

Setting: Population-based.

Participants: Eight-hundred nineteen residents of Singapore, ages (≥65 years).

Measurements: Clinical, cognitive and 3T magnetic resonance imaging assessments were performed on all participants. Language was assessed using the Modified Boston Naming Test (MBNT) and Verbal Fluency (VF). Hypothesis-free region-of-interest-based (ROI) analyses based on major white matter tracts were used to determine the association between WMH location and language. Conditional dependencies between the regional WMH volumes and language were examined using Bayesian-network analysis.

Results: ROI-based analyses showed that WMH located within the anterior thalamic radiation (mean difference: -0.12, 95% confidence interval [CI]: -0.22; -0.02, p = 0.019) and uncinate fasciculus (mean difference: -0.09, 95% CI: -0.18; -0.01, p = 0.022) in the left hemisphere were significantly associated with worse VF but did not survive multiple testing. Conversely, WMH volume in the left cingulum of cingulate gyrus was significantly associated with MBNT performance (mean difference: -0.09, 95% CI: -0.17; -0.02, p = 0.016). Bayesian-network analyses confirmed the left cingulum of cingulate gyrus as a direct determinant of MBNT performance.

Conclusion: Our findings identify the left cingulum of cingulate gyrus as a strategic white matter tract for MBNT, suggesting that language - is sensitive to subcortical ischemic damage. Future studies on the role of sporadic ischemic lesions and vascular cognitive impairment should not only focus on total WMH volume but should also take WMH lesion location into account when addressing language.
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http://dx.doi.org/10.1016/j.jagp.2020.06.009DOI Listing
February 2021

High white matter hyperintensity burden in strategic white matter tracts relates to worse global cognitive performance in community-dwelling individuals.

J Neurol Sci 2020 Jul 13;414:116835. Epub 2020 Apr 13.

Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, SAR, China; Therese Pei Fong Chow Research Centre for Prevention of Dementia, Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, The Chinese University of Hong Kong, Hong Kong, SAR, China; BrainNow Research Institute, Shenzhen, Guangdong Province, China. Electronic address:

Background: White matter hyperintensities (WMH) are associated with cognitive impairment. The impact of WMH on cognitive domains (e.g. processing speed, executive functioning) depends on location. We determined whether the relevance of WMH location also applies to global cognitive functioning by testing if WMH in strategic white matter tracts are associated with global cognitive functioning independent of total WMH burden.

Methods: We included 830 community-dwelling individuals. WMH volume within two a priori specified strategic white matter tracts (forceps minor and anterior thalamic radiation) were entered in a linear regression model with the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) as outcome variables and corrected for total WMH volume and other MRI markers for vascular injury and neurodegenerations (i.e. brain parenchymal fraction, and the presence of lacunes and microbleeds).

Results: WMH in the forceps minor and left anterior thalamic radiation inversely correlated with MoCA, and WMH in the forceps minor inversely correlated with MMSE, independent of total WMH volume and other MRI markers.

Conclusion: The impact of WMH on global cognitive functioning depends on location. Whether this reflects accumulated impairment in isolated cognitive domains or disruption of a network that is crucially involved in global cognitive performance remains to be determined.
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http://dx.doi.org/10.1016/j.jns.2020.116835DOI Listing
July 2020

Perinatal thalamic injury: MRI predictors of electrical status epilepticus in sleep and long-term neurodevelopment.

Neuroimage Clin 2020 25;26:102227. Epub 2020 Feb 25.

Department of Pediatric Neurology, Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.

Objective: Perinatal thalamic injury is associated with epilepsy with electrical status epilepticus in sleep (ESES). The aim of this study was to prospectively quantify the risk of ESES and to assess neuroimaging predictors of neurodevelopment.

Methods: We included patients with perinatal thalamic injury. MRI scans were obtained in the neonatal period, around three months of age and during childhood. Thalamic and total brain volumes were obtained from the three months MRI. Diffusion characteristics were assessed. Sleep EEGs distinguished patients into ESES (spike-wave index (SWI) >85%), ESES-spectrum (SWI 50-85%) or no ESES (SWI < 50%). Serial Intelligence Quotient (IQ)/Developmental Quotient (DQ) scores were obtained during follow-up. Imaging and EEG findings were correlated to neurodevelopmental outcome.

Results: Thirty patients were included. Mean thalamic volume at three months was 8.11 (±1.67) ml and mean total brain volume 526.45 (±88.99) ml. In the prospective cohort (n = 23) 19 patients (83%) developed ESES (-spectrum) abnormalities after a mean follow-up of 96 months. In the univariate analysis, larger thalamic volume, larger total brain volume and lower SWI correlated with higher mean IQ/DQ after 2 years (Pearson's r = 0.74, p = 0.001; Pearson's r = 0.64, p = 0.005; and Spearman's rho -0.44, p = 0.03). In a multivariable mixed model analysis, thalamic volume was a significant predictor of IQ/DQ (coefficient 9.60 [p < 0.001], i.e., corrected for total brain volume and SWI and accounting for repeated measures within patients, a 1 ml higher thalamic volume was associated with a 9.6 points higher IQ). Diffusion characteristics during childhood correlated with IQ/DQ after 2 years.

Significance: Perinatal thalamic injury is followed by electrical status epilepticus in sleep in the majority of patients. Thalamic volume and diffusion characteristics correlate to neurodevelopmental outcome.
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http://dx.doi.org/10.1016/j.nicl.2020.102227DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7076143PMC
February 2021

Temporal Dynamics of Cortical Microinfarcts in Cerebral Small Vessel Disease.

JAMA Neurol 2020 05;77(5):643-647

Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Radboud University Medical Center, Nijmegen, the Netherlands.

Importance: Neuropathology studies show a high prevalence of cortical microinfarcts (CMIs) in aging individuals, especially in patients with cerebrovascular disease and dementia. However, most, are invisible on T1- and T2-weighted magnetic resonance imaging (MRI), raising the question of how to explain this mismatch. Studies on small acute infarcts, detected on diffusion-weighted imaging (DWI), suggest that infarcts are largest in their acute phase and reduce in size thereafter. Therefore, we hypothesized that a subset of the CMI that are invisible on MRI can be detected on MRI in their acute phase. However, to our knowledge, a serial imaging study investigating the temporal dynamics of acute CMI (A-CMI) is lacking.

Objective: To determine the prevalence of chronic CMI (C-CMI) and the cumulative incidence and temporal dynamics of A-CMI in individuals with cerebral small vessel disease (SVD).

Design, Setting, Participants And Exposures: The RUN DMC-Intense study is a single-center hospital-based prospective cohort study on SVD performed between March 2016 and November 2017 and comprising 10 monthly 3-T MRI scans, including high-resolution DWI, 3-dimensional T1, 3-dimensional fluid-attenuated inversion recovery, and T2. One hundred six individuals from the previous longitudinal RUN DMC study were recruited based on the presence of progression of white matter hyperintensities on MRI between 2006 and 2015 and exclusion of causes of cerebral ischemia other than SVD. Fifty-four individuals (50.9%) participated. The median total follow-up duration was 39.5 weeks (interquartile range, 37.8-40.3). Statistical data analysis was performed between May and October 2019.

Main Outcomes And Measures: We determined the prevalence of C-CMI using the baseline T1, fluid-attenuated inversion recovery, and T2 scans. Monthly high-resolution DWI scans (n = 472) were screened to determine the cumulative incidence of A-CMI. The temporal dynamics of A-CMI were determined based on the MRI scans collected during the first follow-up visit after A-CMI onset and the last available follow-up visit.

Results: The median age of the cohort at baseline MRI was 69 years (interquartile range, 66-74 years) and 34 participants (63%) were men. The prevalence of C-CMI was 35% (95% CI, 0.24-0.49). Monthly DWI detected 21 A-CMI in 7 of 54 participants, resulting in a cumulative incidence of 13% (95% CI, 0.06-0.24). All A-CMI disappeared on follow-up MRI.

Conclusions And Relevance: Acute CMI never evolved into chronically MRI-detectable lesions. We suggest that these A-CMI underlie part of the submillimeter C-CMI encountered on neuropathological examination and thereby provide a source for the high CMI burden on neuropathology.
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http://dx.doi.org/10.1001/jamaneurol.2019.5106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042834PMC
May 2020

Performance of five automated white matter hyperintensity segmentation methods in a multicenter dataset.

Sci Rep 2019 11 14;9(1):16742. Epub 2019 Nov 14.

Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease, that is increasingly studied with large, pooled multicenter datasets. This data pooling increases statistical power, but poses challenges for automated WMH segmentation. Although there is extensive literature on the evaluation of automated WMH segmentation methods, such evaluations in a multicenter setting are lacking. We performed WMH segmentations in sixty patients scanned on six different magnetic resonance imaging (MRI) scanners (10 patients per scanner) using five freely available and fully-automated WMH segmentation methods (Cascade, kNN-TTP, Lesion-TOADS, LST-LGA and LST-LPA). Different MRI scanner vendors and field strengths were included. We compared these automated WMH segmentations with manual WMH segmentations as a reference. Performance of each method both within and across scanners was assessed using spatial and volumetric correspondence with the reference segmentations by Dice's similarity coefficient (DSC) and intra-class correlation coefficient (ICC) respectively. We found the best performance, both within and across scanners, for kNN-TTP, followed by LST-LPA and LST-LGA, with worse performance for Lesion-TOADS and Cascade. Our findings can serve as a guide for choosing a method and also highlight the importance to further improve and evaluate consistency of methods in a multicenter setting.
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http://dx.doi.org/10.1038/s41598-019-52966-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6856351PMC
November 2019

Liver segmentation and metastases detection in MR images using convolutional neural networks.

J Med Imaging (Bellingham) 2019 Oct 15;6(4):044003. Epub 2019 Oct 15.

UMC Utrecht and Utrecht University, Image Sciences Institute Utrecht, The Netherlands.

Primary tumors have a high likelihood of developing metastases in the liver, and early detection of these metastases is crucial for patient outcome. We propose a method based on convolutional neural networks to detect liver metastases. First, the liver is automatically segmented using the six phases of abdominal dynamic contrast-enhanced (DCE) MR images. Next, DCE-MR and diffusion weighted MR images are used for metastases detection within the liver mask. The liver segmentations have a median Dice similarity coefficient of 0.95 compared with manual annotations. The metastases detection method has a sensitivity of 99.8% with a median of two false positives per image. The combination of the two MR sequences in a dual pathway network is proven valuable for the detection of liver metastases. In conclusion, a high quality liver segmentation can be obtained in which we can successfully detect liver metastases.
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http://dx.doi.org/10.1117/1.JMI.6.4.044003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6792006PMC
October 2019

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping.

J Vis Exp 2019 09 25(151). Epub 2019 Sep 25.

Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University.

In lesion-symptom mapping (LSM), brain function is inferred by relating the location of acquired brain lesions to behavioral or cognitive symptoms in a group of patients. With recent advances in brain imaging and image processing, LSM has become a popular tool in cognitive neuroscience. LSM can provide fundamental insights into the functional architecture of the human brain for a variety of cognitive and non-cognitive functions. A crucial step in performing LSM studies is the segmentation of lesions on brains scans of a large group of patients and registration of each scan to a common stereotaxic space (also called standard space or a standardized brain template). Described here is an open-access, standardized method for infarct segmentation and registration for the purpose of LSM, as well as a detailed and hands-on walkthrough based on exemplary cases. A comprehensive tutorial for the manual segmentation of brain infarcts on CT scans and DWI or FLAIR MRI sequences is provided, including criteria for infarct identification and pitfalls for different scan types. The registration software provides multiple registration schemes that can be used for processing of CT and MRI data with heterogeneous acquisition parameters. A tutorial on using this registration software and performing visual quality checks and manual corrections (which are needed in some cases) is provided. This approach provides researchers with a framework for the entire process of brain image processing required to perform an LSM study, from gathering of the data to final quality checks of the results.
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http://dx.doi.org/10.3791/59653DOI Listing
September 2019

Cortical microinfarcts in memory clinic patients are associated with reduced cerebral perfusion.

J Cereb Blood Flow Metab 2020 09 26;40(9):1869-1878. Epub 2019 Sep 26.

Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore, Singapore.

Cerebral cortical microinfarcts (CMIs) are small ischemic lesions associated with cognitive impairment and dementia. CMIs are frequently observed in cortical watershed areas suggesting that hypoperfusion contributes to their development. We investigated if presence of CMIs was related to a decrease in cerebral perfusion, globally or specifically in cortex surrounding CMIs. In 181 memory clinic patients (mean age 72 ± 9 years, 51% male), CMI presence was rated on 3-T magnetic resonance imaging (MRI). Cerebral perfusion was assessed from cortical gray matter of the anterior circulation using pseudo-continuous arterial spin labeling parameters (CBF) (perfusion in mL blood/100 g tissue/min) and (CoV) (reflecting arterial transit time (ATT)). Patients with CMIs had a 12% lower CBF (beta = -.20) and 22% higher spatial CoV (beta = .20) (both  < .05) without a specific regional pattern on voxel-based CBF analysis. CBF in a 2 cm region-of-interest around the CMIs did not differ from CBF in a reference zone in the contralateral hemisphere. These findings show that CMIs in memory clinic patients are primarily related to global reductions in cerebral perfusion, thus shedding new light on the etiology of vascular brain injury in dementia.
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http://dx.doi.org/10.1177/0271678X19877403DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7430096PMC
September 2020

Cerebral amyloid burden is associated with white matter hyperintensity location in specific posterior white matter regions.

Neurobiol Aging 2019 12 9;84:225-234. Epub 2019 Aug 9.

Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.

White matter hyperintensities (WMHs) are a common manifestation of cerebral small vessel disease. WMHs are also frequently observed in patients with familial and sporadic Alzheimer's disease, often with a particular posterior predominance. Whether amyloid and tau pathologies are linked to WMH occurrence is still debated. We examined whether cerebral amyloid and tau burden, reflected in cerebrospinal fluid amyloid-beta 1-42 (Aβ-42) and phosphorylated tau (p-tau), are related to WMH location in a cohort of 517 memory clinic patients. Two lesion mapping techniques were performed: voxel-based analyses and region of interest-based linear regression. Voxelwise associations were found between lower Aβ-42 and parieto-occipital periventricular WMHs. Regression analyses demonstrated that lower Aβ-42 correlated with larger WMH volumes in the splenium of the corpus callosum and posterior thalamic radiation, also after controlling for markers of vascular disease. P-tau was not consistently related to WMH occurrence. Our findings indicate that cerebral amyloid burden is associated with WMHs located in specific posterior white matter regions, possibly reflecting region-specific effects of amyloid pathology on the white matter.
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http://dx.doi.org/10.1016/j.neurobiolaging.2019.08.001DOI Listing
December 2019

Intracranial Vessel Wall Magnetic Resonance Imaging Does Not Allow for Accurate and Precise Wall Thickness Measurements: An Ex Vivo Study.

Stroke 2019 10 26;50(10):e283-e284. Epub 2019 Aug 26.

Image Sciences Institute (H.J.K.), University Medical Center Utrecht, the Netherlands.

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http://dx.doi.org/10.1161/STROKEAHA.119.026497DOI Listing
October 2019

Contribution of acute infarcts to cerebral small vessel disease progression.

Ann Neurol 2019 10 12;86(4):582-592. Epub 2019 Aug 12.

Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.

Objective: To determine the contribution of acute infarcts, evidenced by diffusion-weighted imaging positive (DWI+) lesions, to progression of white matter hyperintensities (WMH) and other cerebral small vessel disease (SVD) markers.

Methods: We performed monthly 3T magnetic resonance imaging (MRI) for 10 consecutive months in 54 elderly individuals with SVD. MRI included high-resolution multishell DWI, and 3-dimensional fluid-attenuated inversion recovery, T1, and susceptibility-weighted imaging. We determined DWI+ lesion evolution, WMH progression rate (ml/mo), and number of incident lacunes and microbleeds, and calculated for each marker the proportion of progression explained by DWI+ lesions.

Results: We identified 39 DWI+ lesions on 21 of 472 DWI scans in 9 of 54 subjects. Of the 36 DWI+ lesions with follow-up MRI, 2 evolved into WMH, 4 evolved into a lacune (3 with cavity <3mm), 3 evolved into a microbleed, and 27 were not detectable on follow-up. WMH volume increased at a median rate of 0.027 ml/mo (interquartile range = 0.005-0.073), but was not significantly higher in subjects with DWI+ lesions compared to those without (p = 0.195). Of the 2 DWI+ lesions evolving into WMH on follow-up, one explained 23% of the total WMH volume increase in one subject, whereas the WMH regressed in the other subject. DWI+ lesions preceded 4 of 5 incident lacunes and 3 of 10 incident microbleeds.

Interpretation: DWI+ lesions explain only a small proportion of the total WMH progression. Hence, WMH progression seems to be mostly driven by factors other than acute infarcts. DWI+ lesions explain the majority of incident lacunes and small cavities, and almost one-third of incident microbleeds, confirming that WMH, lacunes, and microbleeds, although heterogeneous on MRI, can have a common initial appearance on MRI. ANN NEUROL 2019;86:582-592.
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http://dx.doi.org/10.1002/ana.25556DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6771732PMC
October 2019

Contrast leakage distant from the hematoma in patients with spontaneous ICH: A 7 T MRI study.

J Cereb Blood Flow Metab 2020 05 29;40(5):1002-1011. Epub 2019 May 29.

Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.

Disruption of the blood-brain barrier (BBB) might play a role in the pathophysiology of cerebral small vessel disease-related ICH. The aim of this study was to assess presence and extent of contrast agent leakage distant from the hematoma as a marker of BBB disruption in patients with spontaneous ICH. We prospectively performed 7 tesla MRI in adult patients with spontaneous ICH and assessed contrast leakage distant from the hematoma on 3D FLAIR images. Thirty-one patients were included (mean age 60 years, 29% women). Median time between ICH and MRI was 20 days (IQR 9-67 days). Seventeen patients (54%; seven lobar, nine deep, one infratentorial ICH) had contrast leakage, located cortical in 16 and cortical and deep in one patient. Patients with contrast leakage more often had lobar cerebral microbleeds (CMBs; 77%) than those without (36%; RR 2.5, 95% CI 1.1-5.7) and a higher number of lobar CMBs (patients with contrast leakage: median 2, IQR 1-8 versus those without: median 0, IQR 0-2;  = 0.02). This study shows that contrast leakage distant from the hematoma is common in days to weeks after spontaneous ICH. It is located predominantly cortical and related to lobar CMBs and therefore possibly to cerebral amyloid angiopathy.
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http://dx.doi.org/10.1177/0271678X19852876DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7178151PMC
May 2020

Automatic classification of focal liver lesions based on MRI and risk factors.

PLoS One 2019 16;14(5):e0217053. Epub 2019 May 16.

Image Sciences Institute, University Medical Center Utrecht & Utrecht University, Utrecht, the Netherlands.

Objectives: Accurate classification of focal liver lesions is an important part of liver disease diagnostics. In clinical practice, the lesion type is often determined from the abdominal MR examination, which includes T2-weighted and dynamic contrast enhanced (DCE) MR images. To date, only T2-weighted images are exploited for automatic classification of focal liver lesions. In this study additional MR sequences and risk factors are used for automatic classification to improve the results and to make a step forward to a clinically useful aid for radiologists.

Materials And Methods: Clinical MRI data sets of 95 patients with in total 125 benign lesions (40 adenomas, 29 cysts and 56 hemangiomas) and 88 malignant lesions (30 hepatocellular carcinomas (HCC) and 58 metastases) were included in this study. Contrast curve, gray level histogram, and gray level co-occurrence matrix texture features were extracted from the DCE-MR and T2-weighted images. In addition, risk factors including the presence of steatosis, cirrhosis, and a known primary tumor were used as features. Fifty features with the highest ANOVA F-score were selected and fed to an extremely randomized trees classifier. The classifier evaluation was performed using the leave-one-out principle and receiver operating characteristic (ROC) curve analysis.

Results: The overall accuracy for the classification of the five major focal liver lesion types is 0.77. The sensitivity/specificity is 0.80/0.78, 0.93/0.93, 0.84/0.82, 0.73/0.56, and 0.62/0.77 for adenoma, cyst, hemangioma, HCC, and metastasis, respectively.

Conclusion: The proposed classification system using features derived from clinical DCE-MR and T2-weighted images, with additional risk factors is able to differentiate five common types of lesions and is a step forward to a clinically useful aid for focal liver lesion diagnosis.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217053PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6522218PMC
February 2020

Impact of white matter hyperintensity location on depressive symptoms in memory-clinic patients: a lesion–symptom mapping study

J Psychiatry Neurosci 2019 07;44(4):E1-E10

From the Alzheimer Centre Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands (Leeuwis, Hooghiemstra, Prins, Scheltens, van der Flier); the Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, the Netherlands (Weaver, Biesbroek, Exalto, Biessels); the Image Sciences Institute, University Medical Centre Utrecht, Utrecht, the Netherlands (Kuijf); the Department of Medical Humanities, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands (Hooghiemstra); the Institutes of Neurology and Healthcare Engineering, UCL, London, United Kingdom (Barkhof); the Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands (Barkhof); and the Department of Epidemiology & Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands (Flier).

Background: We investigated the association between white matter hyperintensity location and depressive symptoms in a memoryclinic population using lesion–symptom mapping.

Methods: We included 680 patients with vascular brain injury from the TRACE-VCI cohort (mean age ± standard deviation: 67 ± 8 years; 52% female): 168 patients with subjective cognitive decline, 164 with mild cognitive impairment and 348 with dementia. We assessed depressive symptoms using the Geriatric Depression Scale. We applied assumptionfree voxel-based lesion–symptom mapping, adjusted for age, sex, total white matter hyperintensity volume and multiple testing. Next, we applied exploratory region-of-interest linear regression analyses of major white matter tracts, with additional adjustment for diagnosis.

Results: Voxel-based lesion–symptom mapping identified voxel clusters related to the Geriatric Depression Scale in the left corticospinal tract. Region-of-interest analyses showed no relation between white matter hyperintensity volume and the Geriatric Depression Scale, but revealed an interaction with diagnosis in the forceps minor, where larger regional white matter hyperintensity volume was associated with more depressive symptoms in subjective cognitive decline (β = 0.26, p < 0.05), but not in mild cognitive impairment or dementia.

Limitations: We observed a lack of convergence of findings between voxel-based lesion–symptom mapping and region-of-interest analyses, which may have been due to small effect sizes and limited lesion coverage despite the large sample size. This warrants replication of our findings and further investigation in other cohorts.

Conclusion: This lesion–symptom mapping study in depressive symptoms indicates the corticospinal tract and forceps minor as strategic tracts in which white matter hyperintensity is associated with depressive symptoms in memory-clinic patients with vascular brain injury. The impact of white matter hyperintensity on depressive symptoms is modest, but it appears to depend on the location of white matter hyperintensity and disease severity.
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http://dx.doi.org/10.1503/jpn.180136DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6606429PMC
July 2019

The Meta VCI Map consortium for meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping: Design and multicenter pilot study.

Alzheimers Dement (Amst) 2019 Dec 12;11:310-326. Epub 2019 Apr 12.

Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands.

Introduction: The Meta VCI Map consortium performs meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping. Integration of data from different cohorts will increase sample sizes, to improve brain lesion coverage and support comprehensive lesion-symptom mapping studies.

Methods: Cohorts with available imaging on white matter hyperintensities or infarcts and cognitive testing were invited. We performed a pilot study to test the feasibility of multicenter data processing and analysis and determine the benefits to lesion coverage.

Results: Forty-seven groups have joined Meta VCI Map (stroke n = 7800 patients; memory clinic n = 4900; population-based n = 14,400). The pilot study (six ischemic stroke cohorts, n = 878) demonstrated feasibility of multicenter data integration (computed tomography/magnetic resonance imaging) and achieved marked improvement of lesion coverage.

Discussion: Meta VCI Map will provide new insights into the relevance of vascular lesion location for cognitive dysfunction. After the successful pilot study, further projects are being prepared. Other investigators are welcome to join.
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http://dx.doi.org/10.1016/j.dadm.2019.02.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465616PMC
December 2019

Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge.

IEEE Trans Med Imaging 2019 11 19;38(11):2556-2568. Epub 2019 Mar 19.

Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are often still obtained from manual segmentations on brain MR images, which is a laborious procedure. The automatic WMH segmentation methods exist, but a standardized comparison of the performance of such methods is lacking. We organized a scientific challenge, in which developers could evaluate their methods on a standardized multi-center/-scanner image dataset, giving an objective comparison: the WMH Segmentation Challenge. Sixty T1 + FLAIR images from three MR scanners were released with the manual WMH segmentations for training. A test set of 110 images from five MR scanners was used for evaluation. The segmentation methods had to be containerized and submitted to the challenge organizers. Five evaluation metrics were used to rank the methods: 1) Dice similarity coefficient; 2) modified Hausdorff distance (95th percentile); 3) absolute log-transformed volume difference; 4) sensitivity for detecting individual lesions; and 5) F1-score for individual lesions. In addition, the methods were ranked on their inter-scanner robustness; 20 participants submitted their methods for evaluation. This paper provides a detailed analysis of the results. In brief, there is a cluster of four methods that rank significantly better than the other methods, with one clear winner. The inter-scanner robustness ranking shows that not all the methods generalize to unseen scanners. The challenge remains open for future submissions and provides a public platform for method evaluation.
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http://dx.doi.org/10.1109/TMI.2019.2905770DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7590957PMC
November 2019

Microbleeds colocalize with enlarged juxtacortical perivascular spaces in amnestic mild cognitive impairment and early Alzheimer's disease: A 7 Tesla MRI study.

J Cereb Blood Flow Metab 2020 04 19;40(4):739-746. Epub 2019 Mar 19.

Brain Center Rudolf Magnus, Department of Neurology, University Medical Center Utrecht, the Netherlands.

MRI-visible perivascular spaces (PVS) in the semioval centre are associated with cerebral amyloid angiopathy (CAA), but it is unknown if PVS co-localize with MRI markers of CAA. To examine this, we assessed the topographical association between cortical cerebral microbleeds (CMBs) - as an indirect marker of CAA - and dilatation of juxtacortical perivascular spaces (jPVS) in 46 patients with amnestic mild cognitive impairment (aMCI) or early Alzheimer's disease (eAD). The degree of dilatation of jPVS <1 cm around each cortical CMBs was compared with a similar reference site (no CMB) in the contralateral hemisphere, using a 4-point scale. Also, jPVS dilatation was compared between patients with and without cortical CMBs. Eleven patients (24%) had cortical CMBs [total=35, median=1, range=1-14] of whom five had >1 cortical CMBs. The degree of jPVS dilatation was higher around CMBs than at the reference sites [Wilcoxon signed rank test, Z = 2.2,  = 0.03]. Patients with >1 cortical CMBs had a higher degree of jPVS dilation [median=2.2, IQR = 1.8-2.3] than patients without cortical CMBs [median=1.4, IQR = 1.0-1.8],  = 0.02. We found a topographical association between a high degree of jPVS dilatation and cortical CMBs, supporting a common underlying pathophysiology - most likely CAA.
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http://dx.doi.org/10.1177/0271678X19838087DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074594PMC
April 2020

The Clinical Phenotype of Vascular Cognitive Impairment in Patients with Type 2 Diabetes Mellitus.

J Alzheimers Dis 2019 ;68(1):311-322

Department of Neurology, Brain Center Rudolph Magnus, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Background: Type 2 diabetes mellitus (T2DM) increases the risk of vascular cognitive impairment (VCI). It is unknown which type of vascular lesions and co-morbid etiologies, in particular Alzheimer's disease pathology, are associated with T2DM in patients with VCI, and how this relates to cognition and prognosis.

Objective: To compare brain MRI and cerebrospinal fluid (CSF) markers, cognition, and prognosis in patients with possible VCI with and without T2DM.

Methods: We included 851 memory clinic patients with vascular brain injury on MRI (i.e., possible VCI) from a prospective cohort study (T2DM: n = 147, 68.4±7.9 years, 63% men; no T2DM: n = 704, 67.6±8.5 years, 52% men). At baseline, we assessed between-group differences in brain MRI abnormalities, CSF markers of Alzheimer's disease, and cognitive profile. After two years follow-up, we compared occurrence of cognitive decline, stroke, and death.

Results: The distribution of clinical diagnoses did not differ between patients with and without T2DM. T2DM patients had more pronounced brain atrophy (total and white matter volume), and more lacunar infarcts, whereas microbleeds were less common (all p < 0.05). CSF amyloid-β levels were similar between the groups. T2DM patients performed worse on working memory (effect size: - 0.17, p = 0.03) than those without, whereas performance on other domains was similar. During follow-up, risk of further cognitive decline was not increased in T2DM.∥Conclusion: In patients with possible VCI, presence of T2DM is related to more pronounced brain atrophy and a higher burden of lacunar infarcts, but T2DM does not have a major impact on cognitive profile or prognosis.∥.
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http://dx.doi.org/10.3233/JAD-180914DOI Listing
June 2020