Improving Blood Pressure Control Using Digital Communication Methods in Serbia.

Background: The purpose of this study was to compare home and office BP in the adjustment of antihypertensive treatment. Methods: This study was an open, prospective, noninterventional, multicenter clinical trial that occurred between July 2019 and February 2020, in 34 cities in the territory of the Republic of Serbia, which monitored 1581 participants for 6 months. Depending on the used blood pressure monitoring method used, all patients were divided into control (office BP monitoring) and experimental (home BP telemonitoring) groups. We collected anamnestic data and data about systolic blood pressure (SP), in mmHg, diastolic blood pressure (DP), in mmHg, and heart rate (HR), in beats/minute, from all patients. Results: SP values were significantly different at baseline, and at the second, third, and fourth visits between the two tested groups. Home and office BP decreased significantly (p < 0.000) during the 6-month follow-up. We observed a statistically significant influence of the presence of diabetes mellitus and dyslipidemia on the dynamics of differences between SP monitoring values. Conclusions: Our study suggests that novel technologies in BP monitoring can be excellent alternatives for BP assessment in hypertensive patients with other cardiovascular risk factors such as diabetes and dyslipidemia.

Brain size and white matter content of cerebrospinal tracts determine the upper cervical cord area: evidence from structural brain MRI.

INTRODUCTION: Measurement of the upper cervical cord area (UCCA) from brain MRI may be an effective way to quantify spinal cord involvement in neurological disorders such as multiple sclerosis. However, knowledge on the determinants of UCCA in healthy controls (HCs) is limited. METHODS: In two cohorts of 133 and 285 HCs, we studied the influence of different demographic, body-related, and brain-related parameters on UCCA by simple and partial correlation analyses as well as by voxel-based morphometry (VBM) across both cerebral gray matter (GM) and white matter (WM). RESULTS: First, we confirmed the known but moderate effect of age on UCCA in the older cohort. Second, we studied the correlation of UCCA with sex, body height, and total intracranial volume (TIV). TIV was the only variable that correlated significantly with UCCA after correction for the other variables. Third, we studied the correlation of UCCA with brain-related parameters. Brain volume correlated stronger with UCCA than TIV. Both volumes of the brain tissue compartments GM and WM correlated with UCCA significantly. WM volume explained variance of UCCA after correction for GM volume, whilst the opposite was not observed. Correspondingly, VBM did not yield any brain region, whose GM content correlated significantly with UCCA, whilst cerebral WM content of cerebrospinal tracts strongly correlated with UCCA. This latter effect increased along a craniocaudal gradient. CONCLUSION: UCCA is mainly determined by brain volume as well as by WM content of cerebrospinal tracts.

White-matter lesions drive deep gray-matter atrophy in early multiple sclerosis: support from structural MRI.

BACKGROUND: In MS, the relationship between lesions within cerebral white matter (WM) and atrophy within deep gray matter (GM) is unclear. OBJECTIVE: To investigate the spatial relationship between WM lesions and deep GM atrophy. METHODS: We performed a cross-sectional structural magnetic resonance imaging (MRI) study (3 Tesla) in 249 patients with clinically-isolated syndrome or relapsing-remitting MS (Expanded Disability Status Scale score: median, 1.0; range, 0-4) and in 49 healthy controls. Preprocessing of T1-weighted and fluid-attenuated T2-weighted images resulted in normalized GM images and WM lesion probability maps. We performed two voxel-wise analyses: 1. We localized GM atrophy and confirmed that it is most pronounced within deep GM; 2. We searched for a spatial relationship between WM lesions and deep GM atrophy; to this end we analyzed WM lesion probability maps by voxel-wise multiple regression, including four variables derived from maxima of regional deep GM atrophy (caudate and pulvinar, each left and right). RESULTS: Atrophy of each deep GM region was explained by ipsilateral WM lesion probability, in the area most densely connected to the respective deep GM region. CONCLUSION: We demonstrated that WM lesions and deep GM atrophy are spatially related. Our results are best compatible with the hypothesis that WM lesions contribute to deep GM atrophy through axonal pathology.

Variation within the Huntington's disease gene influences normal brain structure.

Genetics of the variability of normal and diseased brain structure largely remains to be elucidated. Expansions of certain trinucleotide repeats cause neurodegenerative disorders of which Huntington's disease constitutes the most common example. Here, we test the hypothesis that variation within the IT15 gene on chromosome 4, whose expansion causes Huntington's disease, influences normal human brain structure. In 278 normal subjects, we determined CAG repeat length within the IT15 gene on chromosome 4 and analyzed high-resolution T1-weighted magnetic resonance images by the use of voxel-based morphometry. We found an increase of GM with increasing long CAG repeat and its interaction with age within the pallidum, which is involved in Huntington's disease. Our study demonstrates that a certain trinucleotide repeat influences normal brain structure in humans. This result may have important implications for the understanding of both the healthy and diseased brain.

An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis.

In Multiple Sclerosis (MS), detection of T2-hyperintense white matter (WM) lesions on magnetic resonance imaging (MRI) has become a crucial criterion for diagnosis and predicting prognosis in early disease. Automated lesion detection is not only desirable with regard to time and cost effectiveness but also constitutes a prerequisite to minimize user bias. Here, we developed and evaluated an algorithm for automated lesion detection requiring a three-dimensional (3D) gradient echo (GRE) T1-weighted and a FLAIR image at 3 Tesla (T). Our tool determines the three tissue classes of gray matter (GM) and WM as well as cerebrospinal fluid (CSF) from the T1-weighted image, and, then, the FLAIR intensity distribution of each tissue class in order to detect outliers, which are interpreted as lesion beliefs. Next, a conservative lesion belief is expanded toward a liberal lesion belief. To this end, neighboring voxels are analyzed and assigned to lesions under certain conditions. This is done iteratively until no further voxels are assigned to lesions. Herein, the likelihood of belonging to WM or GM is weighed against the likelihood of belonging to lesions. We evaluated our algorithm in 53 MS patients with different lesion volumes, in 10 patients with posterior fossa lesions, and 18 control subjects that were all scanned at the same 3T scanner (Achieva, Philips, Netherlands). We found good agreement with lesions determined by manual tracing (R2 values of over 0.93 independent of FLAIR slice thickness up to 6mm). These results require validation with data from other protocols based on a conventional FLAIR sequence and a 3D GRE T1-weighted sequence. Yet, we believe that our tool allows fast and reliable segmentation of FLAIR-hyperintense lesions, which might simplify the quantification of lesions in basic research and even clinical trials.

Grey-matter atrophy in Alzheimer's disease is asymmetric but not lateralized.

In Alzheimer's disease (AD), brain atrophy has been proposed to be left lateralized. Here, we reinvestigated the asymmetry and lateralization (i.e., asymmetry directed toward one hemisphere) of grey-matter (GM) distribution in 35 patients with AD, 24 patients with amnestic mild cognitive impairment (aMCI, a state of increased risk for AD), and 30 age-matched healthy controls (HC). We analyzed GM distribution by applying voxel-based morphometry (VBM) including analyses for asymmetry and lateralization. When comparing MCI with AD patients, VBM revealed GM loss in the entorhinal, temporoparietal, dorsofrontal, and occipital cortices as well as in the precuneus; when comparing HCs with MCI patients, we found similar differences, which were less pronounced especially within the temporoparietal cortex and precuneus. Analyses of regional asymmetry and regional lateralization as well as global lateralization did not yield significant results. However, lobar asymmetry of the temporal, parietal, and occipital lobes increased from HC to AD. Moreover, in aMCI and AD patients, performance of language-based neuropsychological tests correlated with lateralization of GM loss to the left hemisphere. We conclude that, in principle, brain atrophy in AD is asymmetric rather than lateralized. At the individual level however, asymmetry contributes to cognitive deficits.