The Effect of Training Sample Size on the Prediction of White Matter Hyperintensity Volume in a Healthy Population Using BIANCA

White matter injury, plasma Alzheimer's disease, and neurodegenerative biomarkers on cognitive decline in community-dwelling older adults: A 10-year longitudinal study

INTRODUCTION

This study aimed to investigate the synergistic impact of white matter injury, Alzheimer's disease, and neurodegenerative pathology on long-term cognitive decline and dementia risk in older adults.

METHODS

We included 262 dementia-free participants with baseline and follow-up interviews (2010-2021). At baseline, peak width of skeletonized mean diffusivity (PSMD) was assessed from diffusion tensor imaging. Plasma phosphorylated tau 217 (p-tau217) and neurofilament light chain (NfL) were measured using a single-molecule immune-array assay. Cognitive function was evaluated using Mini-Mental State Examination (MMSE) and domain-specific cognitive tests.

RESULTS

Participants with high-level PSMD, p-tau217, and NfL showed the fastest decline of MMSE (β = -0.30) and the highest dementia incidence of 3.54/100 person-years. A combination model with three markers demonstrated a good predictive value for dementia, incorporating age, sex, education, and apolipoprotein E (area under the curve = 0.93, 95% confidence interval = 0.86, 0.99).

DISCUSSION

Combining co-pathology markers may identify individuals with a high risk of cognitive decline.

HIGHLIGHTS

Peak width of skeletonized mean diffusivity (PSMD) was correlated with long-term cognitive decline, and this correlation was modified by plasma phosphorylated tau (p-tau)217 and neurofilament light chain (NfL). Participants with high levels of PSMD, p-tau217, and NfL showed the fastest cognitive decline and the highest risk of dementia. A combination of the three markers exhibited a good predictive value of incident dementia over a 10-year follow-up period.

Optimizing automated white matter hyperintensity segmentation in individuals with stroke

White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.

Periodic limb movements in sleep are linked to decreased hippocampus and amygdala volumes in the population-based BiDirect Study

STUDY OBJECTIVES

Even though numerous studies indicate that sleep disorders are associated with altered brain morphology, MRI studies focusing on periodic limb movements in sleep (PLMS) are scarce. Our aim was to investigate the association of PLMS with global and regional gray matter volumes as well as white matter hyperintensity (WMH) volume.

METHODS

One hundred and eighty-nine subjects (57.0 ± 7.8 years, women: 50.5%) of the population-based BiDirect Study underwent a single-night polysomnography (PSG). Standard criteria of the American Academy of Sleep Medicine were applied to evaluate sleep characteristics and calculate the PLMS index (PLMSI). T1w and FLAIR images were acquired with cerebral MRI at 3 Tesla. Voxel-based morphometry was performed to determine the total gray matter volume as well as the volume of cortical segments and subcortical gray matter areas using SPM12 and CAT12. The WMH volume was quantified with the Brain Intensity AbNormality Classification Algorithm. The independent relationship between MRI markers and PLMSI was analyzed using multivariable linear regression with adjustment for age, sex, body mass index, intracranial volume, PSG scorer, PSG device, sleep apnea, and the use of antidepressants.

RESULTS

PLMSI was not significantly related to global gray matter volume and WMH volume. However, significant inverse associations of the PLMSI with the volume of the hippocampus (left and right hemisphere) and left amygdala were observed.

CONCLUSIONS

A significant relationship between a higher PLMSI and lower volumes of the hippocampus and amygdala was found among the participants of the BiDirect Study. Since these associations are based on exploratory analyses, further replications are required before drawing firm conclusions.

Sex-Specific Causes and Consequences of White Matter Damage in a Middle-Aged Cohort

Objective

To evaluate potential sex-specific effects of multiple cardiovascular risk factors on white matter pathology in normal aging men and women, as well as potential sex-differences in the association of white matter pathology and cognitive functions.

Methods

We analyzed cross-sectional data of 581 participants (median age: 53 years, 54% women) of the population-based cohort of the BiDirect Study who completed clinical examinations, five neuropsychological tests, and an 3T MRI examination. White matter pathology was determined by the extent of white matter hyperintensities (WMH) on FLAIR images as well as the magnitude of global fractional anisotropy (FA) based on diffusion tensor imaging. Main effects, interaction as well as sex-stratified generalized linear regression models were used to evaluate the moderating effect of sex on the association of hypertension, diabetes mellitus, smoking, and obesity with WMH and FA, respectively. Associations of imaging markers with cognitive test results were determined with linear regression models.

Results

Hypertension showed stronger associations with more extensive WMH and less FA in women compared to men. Current smoking was associated with more severe WMH in women only. Adjusted for age and education, WMH were not significantly associated with cognitive tests, but higher FA was associated with better performance in motor function in both sexes and with executive functions in men, even after adjustment for cardiovascular risk factors.

Conclusion

We observed a stronger association of hypertension and smoking with white matter damage in women, suggesting a higher susceptibility for vascular pathology in women. However, there was no association of WMH with cognition, and FA was associated with executive function tests only in men, suggesting a higher cognitive reserve in women.