Contribution of diffusion, perfusion and functional MRI to the disconnection hypothesis in subcortical vascular cognitive impairment

Abstract

Vascular cognitive impairment (VCI) describes all forms of cognitive impairment caused by any type of cerebrovascular disease. Early identification of VCI is quite difficult due to the lack of both sensitive and specific biomarkers. Extensive damage to the white matter tracts, which connect the cortical and subcortical regions, has been shown in subcortical VCI (SVCI), the most common subtype of VCI that is caused by small vessel disease. Two specific MRI sequences, including diffusion tensor imaging (DTI) and functional MRI (fMRI), have emerged as useful tools for identifying subtle white matter changes and the intrinsic connectivity between distinct cortical regions. This review describes the advantages of these two modalities in SVCI research and the current DTI and fMRI findings on SVCI. Using DTI technique, a variety of studies found that white matter microstructural damages in the anterior and superior areas are more specific to SVCI. Similarly, functional brain abnormalities detected by fMRI have also been mainly shown in anterior brain areas in SVCI. The characteristic distribution of brain abnormalities in SVCI interrupts the prefrontal-subcortical loop that results in cognitive impairments in particular domains, which further confirms the ‘disconnection syndrome’ hypothesis. In addition, another MRI technique, arterial spin labelling (ASL), has been used to describe the disconnection patterns in a variety of conditions by measuring cerebral blood flow. The role of the ASL technique in SVCI research is also assessed. Finally, the review proposes the application of multimodality fusion in the investigation of SVCI pathogenesis.

Early Segmental White Matter Fascicle Microstructural Damage Predicts the Corresponding Cognitive Domain Impairment in Cerebral Small Vessel Disease Patients by Automated Fiber Quantification

“…Microstructural damage detected by DTI precedes the development of WMH on T2-W FLAIR MRI. DTI parameters are more sensitive and serve as early markers of microstructural neurodegenerative changes in CSVD patients (Ye and Bai, 2018 ). It should also be noted that we included the spectrum of CSVD patients, rather than limiting the study to patients with specific diagnoses such as vascular cognitive dysfunction, with the purpose of generalizing the results to all patients with at least minimal CSVD load, regardless of the final diagnosis.…”

Magnetic Resonance Image Feature Analysis under Deep Learning in Diagnosis of Neurological Rehabilitation in Patients with Cerebrovascular Diseases

“…The results of the study on the FA and MD values of fibers related to the recovery of nerve function showed that the FA values of patients in the VCI group were considerably reduced ( P < 0.05), and the MD values related to each nerve fiber were considerably increased ( P < 0.05). The research results of scholars such as Ye and Bai [ 18 ] also found that multimodal CNN can detect part of the brain nerve damage in a timely and efficient manner in VCI patients. In addition, it can be correlated with the degree of neurological damage in critically ill patients.…”

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“…MCI patients have hypoperfusion in bilateral parietal lobes [76], posterior cingulate cortex (PCC) [77] and precuneus [78], left (L) occipital lobe, and bilateral frontal and temporal lobes [79], compared to healthy controls (HC). A study also showed an increase in perfusion in the L hippocampus, [80] right (R) amygdala and basal ganglia [including a rostral head of the R caudate nucleus, ventral putamen, and globus pallidus] [81].…”