White matter hyperintensities mediate the association between frailty and cognitive impairment in moyamoya disease

OBJECTIVES

The relationship between cognitive function and frailty in moyamoya disease (MMD) remains unclear, and the underlying mechanism is poorly understood. This study aims to investigate whether white matter hyperintensities (WMHs) mediate the association between frailty and cognitive impairment in MMD.

METHODS

Patients with MMD were consecutively enrolled in our study from January 2021 to May 2023. Pre-admission frailty and cognition were assessed using the Clinical Frailty Scale (CFS) and cognitive tests, respectively. Regional deep WMH (DWMH) and periventricular WMH (PWMH) volumes were calculated using the Brain Anatomical Analysis using Diffeomorphic deformation toolbox based on SPM 12 software. Multivariate logistic regression analysis was conducted to evaluate the association between frailty and cognitive function in MMD. Mediation analysis was performed to assess whether WMHs explained the association between frailty and cognition.

RESULTS

A total of 85 patients with MMD were enrolled in this study. On the basis of the CFS scores, 24 patients were classified as frail, 38 as pre-frail, and 23 as robust. Significant differences were observed in learning, memory, processing speed, executive functions, and semantic memory among the three groups (p < 0.001). Frailty was independently associated with memory and executive functions (p < 0.05); even after controlling for WMH. Mediation analysis indicated that the associations of frailty with memory and executive functions were partially mediated by WMH, DWMH, and PWMH (p < 0.05).

CONCLUSION

Frailty is significantly correlated with a higher risk of cognitive impairment in MMD, even after adjusting for other covariates. WMHs partially mediate the association between frailty and cognitive impairment.

Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data

BACKGROUND

White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain.

METHODS

We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis.

RESULTS

The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score.

CONCLUSION

Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.

Association of white matter hyperintensities with migraine phenotypes and response to treatment

INTRODUCTION

White matter hyperintensities (WMHs) are frequently found in migraineurs. However, their clinical significance and correlation to different migraine phenotypes and treatment responses are not well defined. The study aimed to examine the association of WMHs with migraine clinical patterns and treatment response.

AIM OF WORK

We aimed to evaluate the association between WMHs and migraine phenotypes and explore the relationship of WMHs to treatment response.

METHODS

Our cross-sectional study formed of 500 migraineurs who sought treatment in Kafr el-sheik university hospital and underwent (3 T) MRI to evaluate WMHs. Different migraine phenotypes were compared between patients with and without WMHs. According to reduced headache pain intensity and frequency, these patients were divided into treatment responder and non-responder groups.

RESULTS

A total of 145 patients (29%) had WMHs. Patients with WMHs were significantly older, had a longer disease duration, and higher attack frequency. Patients who did not respond to acute and maintenance medications had a higher frequency of WMHs and high WMHs Scheltens score. Migraine with Aura and the presence of vomiting and dizziness were predictors for the development of WMHs.

CONCLUSION

WMHs are more common in migraine with aura. It is more frequent in migraine associated with vomiting and dizziness. WMHs increased with advancing age and more severe disease burden. Poorer response to acute and prophylactic medications was found in patients with WMHs.

Cerebrovascular pathology in Alzheimer's disease: Hopes and gaps

Alzheimer's disease (AD) is recognized as multifactorial and heterogeneous disease with multiple contributors to its pathophysiology, including vascular dysfunction. Given that a revision of the AT(N) classification is expected in the near future, the present work supports the importance to add an additional vascular (V) category to the framework. In particular, we attempt to shed light on the vascular markers and risk factors that are currently ready-to-be-added to the framework: i) lacunes, ii) white matter hyperintensities and iii) microbleeds seen in Flair, T2* weighted imaging and susceptibility images (SWI). Next, we discuss the added value of other types of imaging, such as diffusion-based metrics and advanced perfusion sequences to encompass more subtle vascular dysfunction. Finally, we highlight the importance to add information about the following cardiovascular risk factors to the framework: history of hypertension, obesity, and diabetes. We believe that adding a V category to the AT(N) framework will improve AD classification and foster efforts to apply the right drug(s) at the right time in the right AD subgroups. Brief communication The present work supports the importance to add an additional vascular (V) category to the AT(N) framework and shed light on the vascular MRI markers and risk factors that are currently ready-to-be-added to the framework.

White matter hyperintensities in young individuals with bipolar disorder or at high genetic risk

BACKGROUND

Increased white matter hyperintensities (WMHs) is one of the most consistent imaging findings amongst participants with bipolar disorder (BD). This study investigated WMHs in a young population at high genetic risk for bipolar disorder (HR).

METHODS

MRI scans were conducted at baseline in HR individuals (n = 131), patients with BD (n = 47) and controls (CON) (n = 108). Most of the HR (n = 77) and CON (n = 74) group completed scans after two years. Scans were examined for the presence of WMHs.

RESULTS

There were significantly more periventricular WMHs in the BD compared to the CON group at baseline (p = .04). Although the prevalence of periventricular WMHs was intermediate in the HR group, there were no significant differences between the HR and CON or BD participants. Deep WMHs did not differ significantly between the groups. Over time, there was a significant increase in the prevalence of periventricular WMHs in both the HR and CON groups (p = .02).

LIMITATIONS

The use of a visual rating scale to examine WMHs is subjective. As the gradings were collapsed into 'present' or 'absent', we could not ascertain whether the severity of hyperintensities worsened over time.

CONCLUSIONS

Periventricular WMHs are more prevalent in young individuals with BD than controls. As these are not more prevalent in HR individuals, it is possible that these are either secondary to the development of bipolar disorder, its treatment, or resulting changes in lifestyle. In a novel finding, there were similar increases in the prevalence of WMHs in controls and HR youth over the 2-year period.

Interaction of white matter hyperintensities (WMHs) and apolipoprotein E (APOE) genotypes on cognition in patients with amnestic mild cognitive impairment (aMCI)

The clinical implications of WMHs in aMCI are inconclusive. Moreover, clinical interactions between APOE genotypes and WMHs remain unclear. This study was conducted to investigate the relationship between WMHs and cognitive functions and how this relationship interacted with APOE genotype in people with aMCI. This study included a total of 1472 patients with aMCI from the Clinical Research Center for Dementia of South Korea (CREDOS) and divided them into 3 groups according to the severity of WMHs as assessed by visual ratings of brain magnetic resonance images. The associations of WMHs with the various cognitive domains and with APOE epsilon 4 (ɛ4) status were evaluated. After multivariable adjustments, the severity of WMHs was independently associated with semantic/phonemic verbal fluency and Stroop test-color reading, while APOE ɛ4 status was associated with verbal and visual memory-immediate, delayed recall, and recognition. Moreover, there were interaction between WMHs and APOE ɛ4 status in semantic verbal fluency (animal, P=0.033; supermarket, P=0.047)/Stroop test-color reading (P=0.024). WMHs independently deleteriously affected frontal executive functions in aMCI patients, regardless of APOE ɛ4 presence. Furthermore, APOE ɛ4 possession caused a rapid decline in frontal executive functions with the increase in the WMHs severity (vs. absence), suggesting that WMHs and APOE ɛ4 genotypes synergistically contribute to frontal executive dysfunctions in aMCI.