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- Coenen, Mirthe, et al.
(author)
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Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts
- 2023
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In: NeuroImage. Clinical. - 2213-1582. ; 40
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Journal article (peer-reviewed)abstract
- INTRODUCTION: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS: Individual participant data (N = 3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.
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- DeCarli, Charles, et al.
(author)
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Measures of brain morphology and infarction in the framingham heart study: establishing what is normal.
- 2005
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In: Neurobiology of aging. - : Elsevier BV. - 0197-4580. ; 26:4, s. 491-510
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Journal article (peer-reviewed)abstract
- Numerous anatomical and brain imaging studies find substantial differences in brain structure between men and women across the span of human aging. The ability to extend the results of many of these studies to the general population is limited, however, due to the generally small sample size and restrictive health criteria of these studies. Moreover, little attention has been paid to the possible impact of brain infarction on age-related differences in regional brain volumes. Given the current lack of normative data on gender and aging related differences in regional brain morphology, particularly with regard to the impact of brain infarctions, we chose to quantify brain MRIs from more than 2200 male and female participants of the Framingham Heart Study who ranged in age from 34 to 97 years. We believe that MRI analysis of the Framingham Heart Study more closely represents the general population enabling more accurate estimates of regional brain changes that occur as the consequence of normal aging. As predicted, men had significantly larger brain volumes than women, but these differences were generally not significant after correcting for gender related differences in head size. Age explained approximately 50% of total cerebral brain volume differences, but age-related differences were generally small prior to age 50, declining substantially thereafter. Frontal lobe volumes showed the greatest decline with age (approximately 12%), whereas smaller differences were found for the temporal lobes (approximately 9%). Age-related differences in occipital and parietal lobe were modest. Age-related gender differences were generally small, except for the frontal lobe where men had significantly smaller lobar brain volumes throughout the age range studied. The prevalence of MRI infarction was common after age 50, increased linearly with age and was associated with significantly larger white matter hyperintensity (WMH) volumes beyond that associated with age-related differences in these measures. Amongst men, the presence of MRI infarction was associated with significant age-related reductions in total brain volume. Finally, statistically significant associations were found between the volume of MRI infarcts in cubic centimeters and all brain measures with the exception of parietal lobe volume for individuals where the volume of MRI infarctions was measured. These data serve to define age and gender differences in brain morphology for the Framingham Heart Study. To the degree participants of the Framingham Heart Study are representative the general population, these data can serve as norms for comparison with morphological brain changes associated with aging and disease. In this regard, these cross-sectional quantitative estimates suggest that age-related tissue loss differs quantitatively and qualitatively across brain regions with only minor differences between men and women. In addition, MRI evidence of cerebrovascular disease is common to the aging process and associated with smaller regional brain volumes for a given age, particularly for men. We believe quantitative MRI studies of the Framingham community enables exploration of numerous issues ranging from understanding normal neurobiology of brain aging to assessing the impact of various health factors, particularly those related to cerebrovascular disease, that appear important to maintaining brain health for the general population.
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- Wang, Li-San, et al.
(author)
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Rarity of the Alzheimer Disease-Protective APP A673T Variant in the United States.
- 2015
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In: JAMA neurology. - : American Medical Association (AMA). - 2168-6157 .- 2168-6149. ; 72:2
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Journal article (peer-reviewed)abstract
- Recently, a rare variant in the amyloid precursor protein gene (APP) was described in a population from Iceland. This variant, in which alanine is replaced by threonine at position 673 (A673T), appears to protect against late-onset Alzheimer disease (AD). We evaluated the frequency of this variant in AD cases and cognitively normal controls to determine whether this variant will significantly contribute to risk assessment in individuals in the United States.
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