Abstract
Hypertension (HT) is the leading risk factor for cerebral small vessel disease (CSVD). White matter lesions (WML) linked to CSVD are visible on conventional neuroimaging, likely reflecting late irreversible stages of the CSVD pathological cascade. Despite the prevalence of this disease, the mechanistic link between CSVD, hypertension and WML remains poorly understood. In this prospective, cross-sectional study, 44 hypertensive patients asymptomatic of CSVD underwent diffusion-weighted magnetic resonance imaging (dMRI) and transcranial Doppler (TCD) monitoring of the right middle and left posterior cerebral arteries (MCA and PCA, respectively) to assess dynamic cerebral autoregulation (dCA) and vasomotor reactivity to CO2 (VRCO2). Diffusion measures from two dMRI models quantified the WM structural integrity: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity from diffusion tensor imaging (DTI), and quantitative anisotropy (QA) and isotropy from q-space diffeomorphic reconstruction (QSDR). We examined the association of dMRI measures with dCA and VRCO2 through correlational tractography. We observed that impaired VRCO2 was associated with decreased WM structural integrity, indicated by the associations of reduced QA and increased MD and RD with lower VRCO2. Regarding dCA, we found a negative association between QA and the phase parameter, indicating an increased dCA in association with reduced WM structural integrity. Our results suggest that HT-induced remodeling of the cerebrovasculature, with enhanced dCA and impaired VRCO2, may contribute to impaired brain function and lead to CSVD, and highlight the potential of integrating TCD studies and dMRI, including QSDR-derived metrics, to investigate the natural progression of CSVD from its early, asymptomatic stages.

Abstract
Purpose: Our aim was to test the capability of the NeuroKinect 3D-method, as a movement visualization technique and quantitative analysis to differentiate ictal movements such as hyperkinetic and focal seizures with manual automatisms. The dataset is extracted from the NeuroKinect dataset, which is a RGB-D-IR dataset of epileptic seizures. The dataset is recorded with Kinect v2 and consists of RGB, Infrared (IR) and depth streams. Quantitative 3D-movement analysis of 20 motor seizures was performed. Velocity, acceleration, jerk, covered distance, displacement and movement extent of Regions of Interests (= ROI: head, right hand, left hand and trunk) were captured. Results: Among the analyzed seizures were 10 hyperkinetic (n = 7: 4 male, 3 female; mean age 39.6 years (SD f 9.7)) and 10 focal seizures with manual automatisms (n = 10: 2 male, 8 female; mean age 39.2 years (SD f 17.6)). Hyperkinetic seizures exhibited higher mean velocity in all ROIs (e.g. head = 0.62 f 0.28 (m/s) vs. 0.12 f 0.07 (m/s)) as well as higher mean acceleration and mean jerk in most ROIs; these differences were statistically significant. Mean movement extent, covered distance, and displacement for all ROIs were larger for hyperkinetic seizures, however not significantly. The duration of ictal movements (80 s f 38 s versus 26 s f 14 s; p = 0.001) was significantly longer in focal seizures with manual automatisms. Conclusions: This new visualization technique allows to reconstruct tracked movement via 3D viewer and supports a 3D movement quantification which is capable to differentiate seizures characterized by movements, which may help to localize the epileptogenic zone.

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Abstract