Mnemonic function in small vessel disease and associations with white matter tract microstructure

The microstructural abnormalities of cingulum was related to patients with mild cognitive impairment: a diffusion kurtosis imaging study

OBJECTIVE

Our study aimed to investigate the correlations between microstructural changes of cingulum and patients with mild cognitive impairment (MCI) by diffusion kurtosis imaging (DKI) technique.

METHOD

A total of 104 patients with cerebral small vessel diseases (cSVD) were retrospectively enrolled in this study. According to Montreal Cognitive Assessment Scale (MoCA) scores, these patients were divided into MCI group (n = 59) and non-MCI group (n = 45). The general clinical data was collected and analyzed. The regions of interests (ROIs) were selected for investigation in cingulum. The values of DKI parameters were measured in each ROI and compared between the two groups, the correlations between DKI parameters and MoCA scores were examined.

RESULTS

Compared to non-MCI group, MCI patients had more severe white matter hyperintensities (WMHs) (P = 0.038) and lower MoCA scores (P < 0.01). MCI patients showed significantly decreased fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK), radial kurtosis (RK), and kurtosis fractional anisotropy (KFA) in the left cingulum in the cingulated cortex (CgC) region (all P < 0.0125). In the left CgC region, FA, AK, MK, RK, and KFA were positively correlated with MoCA scores (r = 0.348, 0.409, 0.310, 0.441, 0.422, all P < 0.001). Meanwhile, FA, AK, MK, RK, and KFA were also positively correlated with MoCA scores (r = 0.338, 0.352, 0.289, 0.380, 0.370, all P < 0.001) in the right CgC region.

CONCLUSION

DKI technique could be used to explore the microstructural changes of cingulum in MCI patients and DKI-derived parameters might be feasible to evaluate MCI patients.

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.

Discriminating VCID subgroups: A diffusion MRI multi-model fusion approach

BACKGROUND

Vascular cognitive impairment and dementia (VCID) and Alzheimer's disease are predominant diseases among the aging population resulting in decline of various cognitive domains. Diffusion weighted MRI (DW-MRI) has been shown to be a promising aid in the diagnosis of such diseases. However, there are various models of DW-MRI and the interpretation of diffusion metrics depends on the model used in fitting data. Most previous studies are entirely based on parameters calculated from a single diffusion model.

NEW METHOD

We employ a data fusion framework wherein diffusion metrics from different models such as diffusion tensor imaging, diffusion kurtosis imaging and constrained spherical deconvolution model are fused using well known blind source separation approach to investigate white matter microstructural changes in population comprising of controls and VCID subgroups. Multiple comparisons between subject groups and prediction analysis using features from individual models and proposed fusion model are carried out to evaluate performance of proposed method.

RESULTS

Diffusion features from individual models successfully distinguished between controls and disease groups, but failed to differentiate between disease groups, whereas fusion approach showed group differences between disease groups too. WM tracts showing significant differences are superior longitudinal fasciculus, anterior thalamic radiation, arcuate fasciculus, optic radiation and corticospinal tract.

COMPARISON WITH EXISTING METHOD

ROC analysis showed increased AUC for fusion (AUC = 0.913, averaged across groups and tracts) compared to that of uni-model features (AUC = 0.77) demonstrating increased sensitivity of proposed method.

CONCLUSION

Overall our results highlight the benefits of multi-model fusion approach, providing improved sensitivity in discriminating VCID subgroups.

Predictive role of subcomponents of the left arcuate fasciculus in prognosis of aphasia after stroke: A retrospective observational study

The relationship between the left arcuate fasciculus (AF) and stroke-related aphasia is unclear. In this retrospective study, we aimed to investigate the role of subcomponents of the left AF in predicting prognosis of aphasia after stroke. Twenty stroke patients with aphasia were recruited and received language assessment as well as diffusion tensor tractography scanning at admission. According to injury of the left AF, the participants were classified into four groups: group A (4 cases), the AF preserved intactly; group B (6 cases), the anterior segment injured; group C (4 cases), the posterior segment injured; and group D (6 cases), completely injured. After a consecutive speech therapy, language assessment was performed again. Changes of language functions among the groups were compared and the relation between these changes with segments injury of the AF was analyzed. After therapy, relatively high increase score percentage changes in terms of all the subcategories of language assessment were observed both in group A and C; by contrast, only naming in group B, and spontaneous speech in group D. Although no statistical difference was demonstrated among the four groups. In addition, there was no significant correlation between improvement of language function with segments injury of the AF. The predictive role of subcomponents of the left AF in prognosis of aphasia is obscure in our study. Nevertheless, it indicates the importance of integrity of the left AF for recovery of aphasia, namely that preservation of the left AF on diffusion tensor tractography could mean recovery potential of aphasia after stroke.

Review of diffusion MRI studies in chronic white matter diseases

Diffusion MRI studies characterizing the changes in white matter (WM) due to vascular cognitive impairment, which includes all forms of small vessel disease are reviewed. We reviewed the usefulness of diffusion methods in discriminating the affected WM regions and its relation to cognitive impairment. These studies were categorized based on the diffusion MRI techniques used. The most common method was the diffusion tensor imaging, whereas other methods included diffusion weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and studies based on diffusion tractography. The diffusion measures showed correlation with cognitive scores and disease progression, with mean diffusivity being the most robust parameter. Future studies should focus on incorporating multi-compartment and higher order diffusion models, which can handle the presence of multiple and crossing fibers inside a voxel.

Memory decline in elderly with cerebral small vessel disease explained by temporal interactions between white matter hyperintensities and hippocampal atrophy

White matter hyperintensities (WMH) constitute the visible spectrum of cerebral small vessel disease (SVD) markers and are associated with cognitive decline, although they do not fully account for memory decline observed in individuals with SVD. We hypothesize that WMH might exert their effect on memory decline indirectly by affecting remote brain structures such as the hippocampus. We investigated the temporal interactions between WMH, hippocampal atrophy and memory decline in older adults with SVD. Five hundred and three participants of the RUNDMC study underwent neuroimaging and cognitive assessments up to 3 times over 8.7 years. We assessed WMH volumes semi-automatically and calculated hippocampal volumes (HV) using FreeSurfer. We used linear mixed effects models and causal mediation analyses to assess both interaction and mediation effects of hippocampal atrophy in the associations between WMH and memory decline, separately for working memory (WM) and episodic memory (EM). Linear mixed effect models revealed that the interaction between WMH and hippocampal volumes explained memory decline (WM: β = .067; 95%CI[.024-0.111]; p < .01; EM: β = .061; 95%CI[.025-.098]; p < .01), with better model fit when the WMH*HV interaction term was added to the model, for both WM (likelihood ratio test, χ² [1] = 9.3, p < .01) and for EM (likelihood ratio test, χ² [1] = 10.7, p < .01). Mediation models showed that both baseline WMH volume (β = -.170; p = .001) and hippocampal atrophy (β = 0.126; p = .009) were independently related to EM decline, but the effect of baseline WMH on EM decline was not mediated by hippocampal atrophy (p value indirect effect: 0.572). Memory decline in elderly with SVD was best explained by the interaction of WMH and hippocampal volumes. The relationship between WMH and memory was not causally mediated by hippocampal atrophy, suggesting that memory decline during aging is a heterogeneous condition in which different pathologies contribute to the memory decline observed in elderly with SVD.