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- Coenen, Mirthe, et al.
(författare)
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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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Ingår i: NeuroImage. Clinical. - 2213-1582. ; 40
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Exalto, Lieza G, et al.
(författare)
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Midlife risk score for the prediction of dementia four decades later
- 2013
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Ingår i: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 10:5, s. 562-570
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Tidskriftsartikel (refereegranskat)abstract
- ObjectiveThe objective of this study was to obtain external validation of the only available midlife dementia risk score cardiovascular risk factors , aging and dementia study (CAIDE) constituting age, education, hypertension, obesity, and hyperlipidemia in a larger, more diverse population. Our second aim was to improve the CAIDE risk score by additional midlife risk factors.MethodsThis retrospective cohort study was conducted in an integrated health care delivery system. A total of 9480 Kaiser Permanente members who participated in a health survey study (age range, 40–55 years) from 1964 to 1973 were included in this study. Dementia diagnoses from primary care and medical specialist visits were collected from January 1, 1994 to January 16, 2006, using International Classification of Diseases 9 codes 290.0, 290.1 for “possible dementia,” and 331.0 and 290.4 for “specialist confirmed dementia.” Risk model prediction and validation were examined with the C statistic, net reclassification improvement, and integrated discrimination improvement. Dementia risk per sum score was calculated with Kaplan-Meier estimates.ResultsA total of 2767 participants (25%) were diagnosed with any type of dementia, of which 1011 diagnoses (10.7%) were specialist-confirmed diagnoses. Average time between midlife examination and end of follow-up was 36.1 years. The CAIDE risk score replicated well with a C statistic of 0.75, quite similar to the original CAIDE C statistic of 0.78. The CAIDE score also predicted well within different race strata. Other midlife risk factors (central obesity, depressed mood, diabetes mellitus, head trauma, lung function, and smoking) did not improve predictability. The risk score allowed stratification of participants into those with 40-year low (9%) and high (29%) dementia risk.ConclusionsA combination of modifiable vascular risk factors in midlife is highly predictive of the likelihood of dementia decades later. Possible dementia prevention strategies should point to a life course perspective on maintaining vascular health.
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