Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts

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.

Strategic white matter hyperintensity locations for cognitive impairment: A multicenter lesion-symptom mapping study in 3525 memory clinic patients

INTRODUCTION

Impact of white matter hyperintensities (WMH) on cognition likely depends on lesion location, but a comprehensive map of strategic locations is lacking. We aimed to identify these locations in a large multicenter study.

METHODS

Individual patient data (n = 3525) from 11 memory clinic cohorts were harmonized. We determined the association of WMH location with attention and executive functioning, information processing speed, language, and verbal memory performance using voxel-based and region of interest tract-based analyses.

RESULTS

WMH in the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus were significantly related to domain-specific impairment, independent of total WMH volume and atrophy. A strategic WMH score based on these tracts inversely correlated with performance in all domains.

DISCUSSION

The data show that the impact of WMH on cognition is location-dependent, primarily involving four strategic white matter tracts. Evaluation of WMH location may support diagnosing vascular cognitive impairment.

HIGHLIGHTS

We analyzed white matter hyperintensities (WMH) in 3525 memory clinic patients from 11 cohorts The impact of WMH on cognition depends on location We identified four strategic white matter tracts A single strategic WMH score was derived from these four strategic tracts The strategic WMH score was an independent determinant of four cognitive domains.

Brain imaging correlates of mild cognitive impairment and early dementia in patients with type 2 diabetes mellitus

BACKGROUND AND AIMS

The risk of mild cognitive impairment and dementia is increased in type 2 diabetes mellitus (T2DM). We aimed to identify the neuroanatomical correlates of mild cognitive impairment (MCI) and early dementia in patients with T2DM, using advanced multimodal MRI.

METHODS AND RESULTS

Twenty-five patients (≥70 years) with T2DM and MCI (n = 22) or early dementia (n = 3) were included. The reference group consisted of 23 patients with T2DM with intact cognition. All patients underwent a 3 T MRI. Brain volumes and white matter hyperintensity volumes were obtained with automated segmentation methods. White matter connectivity was assessed with diffusion tensor imaging and fiber tractography. Infarcts and microbleeds were rated visually. Compared to patients without cognitive impairment, those with impairment had a lower grey matter volume (effect size: -0.58, p=0.042), especially in the right temporal lobe and subcortical brain regions (effect sizes: -0.45 to -0.91, false discovery rate corrected p < 0.05). White matter volume (effect size: -0.47, p = 0.11) and white matter connectivity (effect size: 0.55, p = 0.054) were also reduced in patients with versus without cognitive impairment, albeit not statistically significant. White matter hyperintensity volumes and occurrence of other vascular lesions did not differ between the two patient groups.

CONCLUSION

In patients with T2DM, grey matter atrophy rather than vascular brain injury appears to be the primary imaging correlate of MCI and early dementia.

Case-finding for cognitive impairment among people with Type 2 diabetes in primary care using the Test Your Memory and Self-Administered Gerocognitive Examination questionnaires: the Cog-ID study

AIM

To evaluate two cognitive tests for case-finding for cognitive impairment in older patients with Type 2 diabetes.

METHODS

Of 1243 invited patients with Type 2 diabetes, aged ≥70 years, 228 participated in a prospective cohort study. Exclusion criteria were: diagnosis of dementia; previous investigation at a memory clinic; and inability to write or read. Patients first filled out two self-administered cognitive tests (Test Your Memory and Self-Administered Gerocognitive Examination). Secondly, a general practitioner, blinded to Test Your Memory and Self-Administered Gerocognitive Examination scores, performed a structured evaluation using the Mini-Mental State Examination. Subsequently, patients suspected of cognitive impairment (on either the cognitive tests or general practitioner evaluation) and a random sample of 30% of patients not suspected of cognitive impairment were evaluated at a memory clinic. Diagnostic accuracy and area under the curve were determined for the Test Your Memory, Self-Administered Gerocognitive Examination and general practitioner evaluation compared with a memory clinic evaluation to detect cognitive impairment (mild cognitive impairment or dementia).

RESULTS

A total of 44 participants were diagnosed with cognitive impairment. The Test Your Memory and Self-Administered Gerocognitive Examination questionnaires had negative predictive values of 81 and 85%, respectively. Positive predictive values were 39 and 40%, respectively. The general practitioner evaluation had a negative predictive value of 83% and positive predictive value of 64%. The area under the curve was ~0.70 for all tests.

CONCLUSIONS

Both the tests evaluated in the present study can easily be used in case-finding strategies for cognitive impairment in patients with Type 2 diabetes in primary care. The Self-Administered Gerocognitive Examination had the best diagnostic accuracy and therefore we would have a slight preference for this test. Applying the Self-Administered Gerocognitive Examination would considerably reduce the number of patients in whom the general practitioner needs to evaluate cognitive functioning to tailor diabetes treatment.