Multi-Dimensional Diffusion Tensor Imaging Biomarkers for Cognitive Decline From the Preclinical Stage: A Study of Post-stroke Small Vessel Disease

White matter integrity and functional connectivity of the default mode network in acute stroke are associated with cognitive outcome three months post-stroke

BACKGROUND

Knowledge about factors that are associated with post-stroke cognitive outcome is important to identify patients with high risk for impairment. We therefore investigated the associations of white matter integrity and functional connectivity (FC) within the brain's default-mode network (DMN) in acute stroke patients with cognitive outcome three months post-stroke.

METHODS

Patients aged between 18 and 85 years with an acute symptomatic MRI-proven unilateral ischemic middle cerebral artery infarction, who had received reperfusion therapy, were invited to participate in this longitudinal study. All patients underwent brain MRI within 24-72 h after symptom onset, and participated in a neuropsychological assessment three months post-stroke. We performed hierarchical regression analyses to explore the incremental value of baseline white matter integrity and FC beyond demographic, clinical, and macrostructural information for cognitive outcome.

RESULTS

The study cohort comprised 34 patients (mean age: 64 ± 12 years, 35% female). The initial median National Institutes of Health Stroke Scale (NIHSS) score was 10, and significantly improved three months post-stroke to a median NIHSS = 1 (p < .001). Nonetheless, 50% of patients showed cognitive impairment three months post-stroke. FC of the non-lesioned anterior cingulate cortex of the affected hemisphere explained 15% of incremental variance for processing speed (p = .007), and fractional anisotropy of the non-lesioned cingulum of the affected hemisphere explained 13% of incremental variance for cognitive flexibility (p = .033).

CONCLUSIONS

White matter integrity and functional MRI markers of the DMN in acute stroke explain incremental variance for post-stroke cognitive outcome beyond demographic, clinical, and macrostructural information.

Exploring research hotspots and emerging trends in neuroimaging of vascular cognitive impairment: a bibliometric and visualized analysis

Background

Vascular cognitive impairment (VCI) manifests in memory impairment, mental slowness, executive dysfunction, behavioral changes, and visuospatial abnormalities, significantly compromising the quality of daily life for patients and causing inconvenience to caregivers. Neuroimaging serves as a crucial approach to evaluating the extent, location, and type of vascular lesions in patients suspected of VCI. Nevertheless, there is still a lack of comprehensive bibliometric analysis to discern the research status and emerging trends concerning VCI neuroimaging.

Objective

This study endeavors to explore the collaboration relationships of authors, countries, and institutions, as well as the research hotspots and frontiers of VCI neuroimaging by conducting a bibliometric analysis.

Methods

We performed a comprehensive retrieval within the Core Collection of Web of Science, spanning from 2000 to 2023. After screening the included literature, CiteSpace and VOSviewer were utilized for a visualized analysis aimed at identifying the most prolific author, institution, and journal, as well as extracting valuable information from the analysis of references.

Results

A total of 1,024 publications were included in this study, comprising 919 articles and 105 reviews. Through the analysis of keywords and references, the research hotspots involve the relationship between neuroimaging of cerebral small vessel disease (CSVD) and VCI, the diagnosis of VCI, and neuroimaging methods pertinent to VCI. Moreover, potential future research directions encompass CSVD, functional and structural connectivity, neuroimaging biomarkers, and lacunar stroke.

Conclusion

The research in VCI neuroimaging is constantly developing, and we hope to provide insights and references for future studies by delving into the research hotspots and frontiers within this field.

Alterations in structural integrity of superior longitudinal fasciculus III associated with cognitive performance in cerebral small vessel disease

BACKGROUND

This study aimed to investigate the alterations in structural integrity of superior longitudinal fasciculus subcomponents with increasing white matter hyperintensity severity as well as the relationship to cognitive performance in cerebral small vessel disease.

METHODS

110 cerebral small vessel disease study participants with white matter hyperintensities were recruited. According to Fazekas grade scale, white matter hyperintensities of each subject were graded. All subjects were divided into two groups. The probabilistic fiber tracking method was used for analyzing microstructure characteristics of superior longitudinal fasciculus subcomponents.

RESULTS

Probabilistic fiber tracking results showed that mean diffusion, radial diffusion, and axial diffusion values of the left arcuate fasciculus as well as the mean diffusion value of the right arcuate fasciculus and left superior longitudinal fasciculus III in high white matter hyperintensities rating group were significantly higher than those in low white matter hyperintensities rating group (p < 0.05). The mean diffusion value of the left superior longitudinal fasciculus III was negatively related to the Montreal Cognitive Assessment score of study participants (p < 0.05).

CONCLUSIONS

The structural integrity injury of bilateral arcuate fasciculus and left superior longitudinal fasciculus III is more severe with the aggravation of white matter hyperintensities. The structural integrity injury of the left superior longitudinal fasciculus III correlates to cognitive impairment in cerebral small vessel disease.

Causal relationship between multiparameter brain MRI phenotypes and age: evidence from Mendelian randomization

To explore the causal relationship between age and brain health (cortical atrophy, white matter integrity, white matter hyperintensities and cerebral microbleeds in various brain regions) related multiparameter imaging features using two-sample Mendelian randomization. Age was determined as chronological age of the subject. Cortical volume, white matter micro-integrity, white matter hyperintensity volume and cerebral microbleeds of each brain region were included as phenotypes for brain health. Age and imaging of brain health related genetic data were analysed to determine the causal relationship using inverse-variance weighted model, validated by heterogeneity and horizontal pleiotropy variables. Age is causally related to increased volumes of white matter hyperintensities (β = 0.151). For white matter micro-integrity, fibres of the inferior cerebellar peduncle (axial diffusivity β = -0.128, orientation dispersion index β = 0.173), cerebral peduncle (axial diffusivity β = -0.136), superior fronto-occipital fasciculus (isotropic volume fraction β = 0.163) and fibres within the limbic system were causally deteriorated. We also detected decreased cortical thickness of multiple frontal and temporal regions (P < 0.05). Microbleeds were not related with aging (P > 0.05). Aging is a threat of brain health, leading to cortical atrophy mainly in the frontal lobes, as well as the white matter degeneration especially abnormal hyperintensity and deteriorated white matter integrity around the hippocampus.

Mendelian randomization analysis implicates bidirectional associations between brain imaging-derived phenotypes and ischemic stroke

Brian imaging-derived phenotypes (IDPs) have been suggested to be associated with ischemic stroke, but the causality between them remains unclear. In this bidirectional two-sample Mendelian randomization (MR) study, we explored the potential causal relationship between 461 imaging-derived phenotypes (n = 33,224, UK Biobank) and ischemic stroke (n = 34,217 cases/406,111 controls, Multiancestry Genome-Wide Association Study of Stroke). Forward MR analyses identified five IDPs associated with ischemic stroke, including mean diffusivity (MD) in the right superior fronto-occipital fasciculus (1.22 [95% CI, 1.11-1.34]), MD in the left superior fronto-occipital fasciculus (1.30 [1.17-1.44]), MD in the anterior limb of the right internal capsule (1.36 [1.22-1.51]), MD in the right anterior thalamic radiation (1.17 [1.09-1.26]), and MD in the right superior thalamic radiation (1.23 [1.11-1.35]). In the reverse MR analyses, ischemic stroke was identified to be associated with three IDPs, including high isotropic or free water volume fraction in the body of corpus callosum (beta, 0.189 [95% confidence interval, 0.107-0.271]), orientation dispersion index in the pontine crossing tract (0.175 [0.093-0.257]), and volume of the third ventricle (0.219 [0.138-0.301]). This bidirectional two-sample MR study suggested five predictors and three diagnostic markers for ischemic stroke at the brain-imaging level. Further studies are warranted to replicate our findings and clarify underlying mechanisms.

Characterization of white matter microstructural abnormalities associated with cognitive dysfunction in cerebral small vessel disease with cerebral microbleeds

BACKGROUND

Diffusion tensor imaging (DTI) is recommended as a sensitive method to explore white matter (WM) microstructural alterations. Cerebral small vessel disease (CSVD) may be accompanied by extensive WM microstructural deterioration, while cerebral microbleeds (CMBs) are an important factor affecting CSVD.

METHODS

Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) images from 49 CSVD patients with CMBs (CSVD-c), 114 CSVD patients without CMBs (CSVD-n), and 83 controls were analyzed using DTI-derived tract-based spatial statistics to detect WM diffusion changes among groups.

RESULTS

Compared with the CSVD-n and control groups, the CSVD-c group showed a significant FA decrease and AD, RD and MD increases mainly in the cognitive and sensorimotor-related WM tracts. There was no significant difference in any diffusion metric between the CSVD-n and control groups. Furthermore, the widespread regional diffusion alterations among groups were significantly correlated with cognitive parameters in both the CSVD-c and CSVD-n groups. Notably, we applied the multiple kernel learning technique in multivariate pattern analysis to combine multiregion and multiparameter diffusion features, yielding an average accuracy >77 % for three binary classifications, which showed a considerable improvement over the single modality approach.

LIMITATIONS

We only grouped the study according to the presence or absence of CMBs.

CONCLUSIONS

CSVD patients with CMBs have extensive WM microstructural deterioration. Combining DTI-derived diffusivity and anisotropy metrics can provide complementary information for assessing WM alterations associated with cognitive dysfunction and serve as a potential discriminative pattern to detect CSVD at the individual level.

Superficial white matter microstructure affects processing speed in cerebral small vessel disease

White matter hyperintensities (WMH) are a typical feature of cerebral small vessel disease (CSVD), which contributes to about 50% of dementias worldwide. Microstructural alterations in deep white matter (DWM) have been widely examined in CSVD. However, little is known about abnormalities in superficial white matter (SWM) and their relevance for processing speed, the main cognitive deficit in CSVD. In 141 CSVD patients, processing speed was assessed using Trail Making Test Part A. White matter abnormalities were assessed by WMH burden (volume on T2-FLAIR) and diffusion MRI measures. SWM imaging measures had a large contribution to processing speed, despite a relatively low SWM WMH burden. Across all imaging measures, SWM free water (FW) had the strongest association with processing speed, followed by SWM mean diffusivity (MD). SWM FW was the only marker to significantly increase between two subgroups with the lowest WMH burdens. When comparing two subgroups with the highest WMH burdens, the involvement of WMH in the SWM was accompanied by significant differences in processing speed and white matter microstructure. Mediation analysis revealed that SWM FW fully mediated the association between WMH volume and processing speed, while no mediation effect of MD or DWM FW was observed. Overall, results suggest that the SWM has an important contribution to processing speed, while SWM FW is a sensitive imaging marker associated with cognition in CSVD. This study extends the current understanding of CSVD-related dysfunction and suggests that the SWM, as an understudied region, can be a potential target for monitoring pathophysiological processes.

Associations of Peak-Width Skeletonized Mean Diffusivity and Post-Stroke Cognition

Post-stroke cognitive impairment is common and can have major impact on life after stroke. Peak-width of Skeletonized Mean Diffusivity (PSMD) is a diffusion imaging marker of white matter microstructure and is also associated with cognition. Here, we examined associations between PSMD and post-stroke global cognition in an ongoing study of mild ischemic stroke patients. We studied cross-sectional associations between PSMD and cognition at both 3-months (N = 229) and 1-year (N = 173) post-stroke, adjusted for premorbid IQ, sex, age, stroke severity and disability, as well as the association between baseline PSMD and 1-year cognition. At baseline, (mean age = 65.9 years (SD = 11.1); 34% female), lower Montreal Cognitive Assessment (MoCA) scores were associated with older age, lower premorbid IQ and higher stroke severity, but not with PSMD (βstandardized = −0.116, 95% CI −0.241, 0.009; p = 0.069). At 1-year, premorbid IQ, older age, higher stroke severity and higher PSMD (βstandardized = −0.301, 95% CI −0.434, −0.168; p < 0.001) were associated with lower MoCA. Higher baseline PSMD was associated with lower 1-year MoCA (βstandardized = −0.182, 95% CI −0.308, −0.056; p = 0.005). PSMD becomes more associated with global cognition at 1-year post-stroke, possibly once acute effects have settled. Additionally, PSMD in the subacute phase after a mild stroke could help predict long-term cognitive impairment.

Diffusion tensor imaging pipeline measures of cerebral white matter integrity: An overview of recent advances and prospects

Cerebral small vessel disease (CSVD) is a leading cause of age-related microvascular cognitive decline, resulting in significant morbidity and decreased quality of life. Despite a progress on its key pathophysiological bases and general acceptance of key terms from neuroimaging findings as observed on the magnetic resonance imaging (MRI), key questions on CSVD remain elusive. Enhanced relationships and reliable lesion studies, such as white matter tractography using diffusion-based MRI (dMRI) are necessary in order to improve the assessment of white matter architecture and connectivity in CSVD. Diffusion tensor imaging (DTI) and tractography is an application of dMRI that provides data that can be used to non-invasively appraise the brain white matter connections via fiber tracking and enable visualization of individual patient-specific white matter fiber tracts to reflect the extent of CSVD-associated white matter damage. However, due to a lack of standardization on various sets of software or image pipeline processing utilized in this technique that driven mostly from research setting, interpreting the findings remain contentious, especially to inform an improved diagnosis and/or prognosis of CSVD for routine clinical use. In this minireview, we highlight the advances in DTI pipeline processing and the prospect of this DTI metrics as potential imaging biomarker for CSVD, even for subclinical CSVD in at-risk individuals.

Contrast agent-free state-of-the-art magnetic resonance imaging on cerebral small vessel disease - Part 2: Diffusion tensor imaging and functional magnetic resonance imaging

Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast agent-free, state-of-the-art MRI techniques, particularly diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published from 2000 to 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast agent-free, state-of-the-art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.