Montreal Cognitive Assessment score correlates with regional cerebral blood flow in post-stroke patients

Endothelial dysfunction in neurodegenerative disease: Is endothelial inflammation an overlooked druggable target?

Neurological diseases with a neurodegenerative component have been associated with alterations in the cerebrovasculature. At the anatomical level, these are centred around changes in cerebral blood flow and vessel organisation. At the molecular level, there is extensive expression of cellular adhesion molecules and increased release of pro-inflammatory mediators. Together, these has been found to negatively impact blood-brain barrier integrity. Systemic inflammation has been found to accelerate and exacerbate endothelial dysfunction, neuroinflammation and degeneration. Here, we review the role of cerebrovasculature dysfunction in neurodegenerative disease and discuss the potential contribution of intermittent pro-inflammatory systemic disease in causing endothelial pathology, highlighting a possible mechanism that may allow broad-spectrum therapeutic targeting in the future.

Computer-aided cognitive training combined with tDCS can improve post-stroke cognitive impairment and cerebral vasomotor function: a randomized controlled trial

BACKGROUND

Post-stroke cognitive impairment (PSCI) is the focus and difficulty of poststroke rehabilitation intervention with an incidence of up to 61%, which may be related to the deterioration of cerebrovascular function. Computer-aided cognitive training (CACT) can improve cognitive function through scientific training targeting activated brain regions, becoming a popular training method in recent years. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, can regulate the cerebral vascular nerve function, and has an effect on the rehabilitation of cognitive dysfunction after stroke. This study examined the effectiveness of both CACT and tDCS on cognitive and cerebrovascular function after stroke, and explored whether CACT combined with tDCS was more effective.

METHODS

A total of 72 patients with PSCI were randomly divided into the conventional cognitive training (CCT) group (n = 18), tDCS group (n = 18), CACT group (n = 18), and CACT combined with tDCS group (n = 18). Patients in each group received corresponding 20-minute treatment 15 times a week for 3 consecutive weeks. Montreal Cognitive Assessment (MoCA) and the Instrumental Activities of Daily Living Scale (IADL) were used to assess patients' cognitive function and the activities of daily living ability. Transcranial Doppler ultrasound (TCD) was used to assess cerebrovascular function, including cerebral blood flow velocity (CBFV), pulse index (PI), and breath holding index (BHI). These outcome measures were measured before and after treatment.

RESULTS

Compared with those at baseline, both the MoCA and IADL scores significantly increased after treatment (P < 0.01) in each group. There was no significantly difference in efficacy among CCT, CACT and tDCS groups. The CACT combined with tDCS group showed greater improvement in MoCA scores compared with the other three groups (P < 0.05), especially in the terms of visuospatial and executive. BHI significantly improved only in CACT combined with tDCS group after treatment (p ≤ 0.05) but not in the other groups. Besides, no significant difference in CBFV or PI was found before and after the treatments in all groups.

CONCLUSION

Both CACT and tDCS could be used as an alternative to CCT therapy to improve cognitive function and activities of daily living ability after stroke. CACT combined with tDCS may be more effective improving cognitive function and activities of daily living ability in PSCI patients, especially visuospatial and executive abilities, which may be related to improved cerebral vasomotor function reflected by the BHI.

TRIAL REGISTRATION NUMBER

The study was registered in the Chinese Registry of Clinical Trials (ChiCTR2100054063). Registration date: 12/08/2021.

Structural disconnectome mapping of cognitive function in poststroke patients

BACKGROUND AND PURPOSE

Sequalae following stroke represents a significant challenge in current rehabilitation. The location and size of focal lesions are only moderately predictive of the diverse cognitive outcome after stroke. One explanation building on recent work on brain networks proposes that the cognitive consequences of focal lesions are caused by damages to anatomically distributed brain networks supporting cognition rather than specific lesion locations.

METHODS

To investigate the association between poststroke structural disconnectivity and cognitive performance, we estimated individual level whole-brain disconnectivity probability maps based on lesion maps from 102 stroke patients using normative data from healthy controls. Cognitive performance was assessed in the whole sample using Montreal Cognitive Assessment, and a more comprehensive computerized test protocol was performed on a subset (n = 82).

RESULTS

Multivariate analysis using Partial Least Squares on the disconnectome maps revealed that higher disconnectivity in right insular and frontal operculum, superior temporal gyrus and putamen was associated with poorer MoCA performance, indicating that lesions in regions connected with these brain regions are more likely to cause cognitive impairment. Furthermore, our results indicated that disconnectivity within these clusters was associated with poorer performance across multiple cognitive domains.

CONCLUSIONS

These findings demonstrate that the extent and distribution of structural disconnectivity following stroke are sensitive to cognitive deficits and may provide important clinical information predicting poststroke cognitive sequalae.

A Nationwide Multi-Center Questionnaire Survey on the Real-World State and Clinical Management of Poststroke Dementia in Japan

Background:

Poststroke dementia (PSD) is a serious problem for stroke survivors. However, there is still limited data on the real-world state and clinical management of PSD worldwide, and several countries already have a super-aged society.

Objective:

We conducted a nationwide questionnaire survey to examine the real-world state and management of PSD in Japan.

Methods:

A survey was conducted in the top 500 Japanese hospitals regarding the number of stroke patients treated between July 2018 and August 2019. Thirteen questions regarding PSD were mailed to doctors responsible for stroke management.

Results:

Responses were obtained from 251 hospitals (50.2%). The chief doctors responsible for stroke management answered the questionnaires. The median numbers of patients admitted annually with stroke in the departments of neurology and neurosurgery in the hospitals were 281.0 (interquartile range [IQR], 231.8–385.3) and 253.5 (IQR, 210.0–335.3), respectively, and most hospitals were acute care hospitals. Executive dysfunction was the most common cognitive dysfunction (10.9%), followed by amnesia (9.5%) and apathy (4.1%). Surprisingly, many stroke survivors lived alone at home (23.7%). Montreal Cognitive Assessment was significantly uncommon compared to Mini-Mental State Examination (p < 0.01). Furthermore, objective evaluation tests for behavioral and psychological symptoms of dementia were not often performed. Cognitive rehabilitation treatments were performed more often and earlier than drug treatments. The first drug of choice for PSD was predominantly donepezil (79.1%), followed by galantamine (6.1%), cilostazol (4.9%), memantine (2.5%), and rivastigmine (1.8%).

Conclusion:

Our study provides real-world evidence for the state of clinical practice related to PSD in Japan.

Blood pressure variability is related to faster cognitive decline in ischemic stroke patients: PICASSO subanalysis

Blood pressure variability (BPV) is associated with higher cardiovascular morbidity risks; however, its association with cognitive decline remains unclear. We investigated whether higher BPV is associated with faster declines in cognitive function in ischemic stroke (IS) patients. Cognitive function was evaluated between April 2010 and August 2015 using the Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment in 1,240 Korean PICASSO participants. Patients for whom baseline and follow-up cognitive test results and at least five valid BP readings were available were included. A restricted maximum likelihood–based Mixed Model for Repeated Measures was used to compare changes in cognitive function over time. Among a total of 746 participants (64.6 ± 10.8 years; 35.9% female). Baseline mean-MMSE score was 24.9 ± 4.7. The median number of BP readings was 11. During a mean follow-up of 2.6 years, mean baseline and last follow-up MMSE scores were 25.4 ± 4.8 vs. 27.8 ± 4.4 (the lowest BPV group) and 23.9 ± 5.2 vs. 23.2 ± 5.9 (the highest BPV group). After adjusting for multiple variables, higher BPV was independently associated with faster cognitive decline over time. However, no significant intergroup difference in cognitive changes associated with mean systolic BP was observed. Further research is needed to elucidate how BPV might affect cognitive function.

Predicting the progression of Parkinson's disease using conventional MRI and machine learning: An application of radiomic biomarkers in whole-brain white matter

PURPOSE

This study aimed to develop and validate a radiomics model based on whole-brain white matter and clinical features to predict the progression of Parkinson disease (PD).

METHODS

PD patient data from the Parkinson's Progress Markers Initiative (PPMI) database was evaluated. Seventy-two PD patients with disease progression, as measured by the Hoehn-Yahr Scale (HYS) (stage 1-5), and 72 PD patients with stable PD were matched by sex, age, and category of HYS and included in the current study. Each individual's T₁ -weighted MRI scans at the baseline timepoint were segmented to isolate whole-brain white matter for radiomics feature extraction. The total dataset was divided into a training and test set according to subject serial number. The size of the training dataset was reduced using the maximum relevance minimum redundancy (mRMR) algorithm to construct a radiomics signature using machine learning. Finally, a joint model was constructed by incorporating the radiomics signature and clinical progression scores. The test data were then used to validate the prediction models, which were evaluated based on discrimination, calibration, and clinical utility.

RESULTS

Based on the overall data, the areas under curve (AUCs) of the joint model, signature and Unified Parkinson Disease Rating Scale III PD rating score were 0.836, 0.795, and 0.550, respectively. Furthermore, the sensitivities were 0.805, 0.875, and 0.292, respectively, and the specificities were 0.722, 0.697, and 0.861, respectively. In addition, the predictive accuracy of the model was 0.827, the sensitivity was 0.829 and the specificity was 0.702 for stage-1 PD. For stage-2 PD, the predictive accuracy of the model was 0.854, the sensitivity was 0.960, and the specificity was 0.600.

CONCLUSION

Our results provide evidence that conventional structural MRI can predict the progression of PD. This work also supports the use of a simple radiomics signature built from whole-brain white matter features as a useful tool for the assessment and monitoring of PD progression.

Relationship Between the Japanese Version of the Montreal Cognitive Assessment and PET Imaging in Subjects with Mild Cognitive Impairment

BACKGROUND

The Montreal Cognitive Assessment (MoCA) test has high sensitivity and specificity for detecting mild cognitive impairment or early dementia. How the MoCA score relates to findings of positron emission tomography imaging, however, remains unclear.

OBJECTIVE

This prospective study examined the relationship between the Japanese version of the MoCA (MoCA-J) test and brain amyloid deposition or cerebral glucose metabolism among subjects with mild cognitive impairment.

METHODS

A total of 125 subjects with mild cognitive impairment underwent the MoCA-J test, and amyloid- and 18F-fluorodeoxyglucose- positron emission tomography. Linear correlation analysis and multiple linear regression analysis were conducted to investigate the relationship between the MoCA-J score and demographic characteristics, amyloid deposition, and cerebral glucose metabolism. Moreover, Statistical Parametric Mapping 8 was used for a voxel-wise regression analysis of the MoCA-J score and cerebral glucose metabolism.

RESULTS

The MoCA-J score significantly correlated with age, years of education, and the Mini-Mental State Examination score. After adjusting for age, sex, and education, the MoCA-J score significantly correlated negatively with amyloid retention (β= -0.174, p= 0.031) and positively with cerebral glucose metabolism (β= 0.183, p= 0.044). Statistical Parametric Mapping showed that Japanese version of MoCA score correlated with glucose metabolism in the bilateral frontal and parietal lobes, and the left precuneus.

CONCLUSION

The total MoCA-J score correlated with amyloid deposition and frontal and parietal glucose metabolism in subjects with mild cognitive impairment. Our findings support the usefulness of the MoCA-J test for screening subjects at high risk for Alzheimer's disease.

Microstructural damage of normal-appearing white matter in subcortical ischemic vascular dementia is associated with Montreal Cognitive Assessment scores

Objectives

This study was performed to determine whether multimodal biomarkers are more strongly associated with the Montreal Cognitive Assessment (MoCA) scores compared with the Mini-Mental State Examination (MMSE) scores, and whether they are correlated with the Clinical Dementia Rating (CDR) in patients with subcortical ischemic vascular dementia (SIVD).

Methods

Patients diagnosed with SIVD were enrolled. Peripheral blood hypersensitive C-reactive protein, white matter lesion volume (WMLV), fractional anisotropy (FA)/mean diffusivity (MD) of whole brain white matter (WBWM), and normal-appearing white matter (NAWM) were measured and correlated with MMSE, MoCA, and CDR scores.

Results

Bivariate analyses of data from 48 included patients revealed that both MoCA and MMSE were significantly associated with age, education, and FA of NAWM. Only MD of NAWM was correlated with MoCA scores. In partial correlation analysis adjusted for demographic and neuroimaging variables, MD/FA of NAWM and the MoCA scores were significantly correlated. FA/MD of NAWM had a modest trend toward a correlation with the CDR, but it was not significant.

Conclusions

In the patients with SIVD, FA/MD of NAWM were more strongly related to MoCA scores compared with MMSE scores.