Search Results (4)

Introduction. Spinal cord ischemia (SCI) accounts for less than 1% of all strokes, and mostly affects the anterior cord. The ascending aorta (AA) is the rarest site of localization for aortic thrombi (5%). We report a singular case of posterior SCI due to a floating thrombus in the AA. Case presentation. A 75-year-old male with acute left hemiparesis and left tactile and proprioceptive sensory loss below the C5 dermatome (NIHSS 3) is presented. Spinal cord MRI showed a C4–C6 ischemic lesion, involving the left lateral posterior hemi-cord. CT angiography showed a 6 mm floating thrombus in the AA. According to cardiovascular surgeons, dual antiplatelet therapy and high-dose statin were started. After seven days, the patient was discharged with mild left distal hemiparesis and an unchanged sensory deficit. Conclusions. Posterior SCI is rarer than anterior ischemia and potentially unilateral. Its clinical presentation is mainly sensory with possible, but not systematic, weakness of the homolateral limbs. SCI is often caused by aortic pathologies in the elderly, but the incidence rate of non-aneurysmal aortic mural thrombus is about 0.45% and the AA represents a very rare location. In similar cases, conservative medical treatment is preferred despite the high-risk rates of embolic recurrences. Full article

This systematic review and meta-analysis of global peer-reviewed neuroimaging findings preliminarily assessed the magnitude of effect sizes (ES) of the influences of family poverty/low socioeconomic status (SES) on children’s neurocognition and whether these were consistently detrimental. The literature search (Web of Science; PUBMED; MEDLINE: PSYCNET; GOOGLE SCHOLAR; SCIENCEDIRECT) included 66 studies from 1988 to 2022; 85% of the studies included were conducted in Western, high-income nations. Bayesian models, corrected by study sizes and variances, revealed ESs were heterogeneous across countries and measurements. Bayesian and standard hypothesis testing indicated high and low SES groups showed similar behavioral performances in neuroimaging-concurrent tasks. Except for Magnetic Resonance Imaging studies, ESs were small-to-intermediate with modest reliability. The strongest ESs were found for attention, mathematical performance, language, and cortical volume, followed by intermediate ESs for reading and socioemotional processes. Differentials in resting activity and connectivity, working memory, and executive functions yielded small effects. A bibliometric analysis showed a significant proportion of the literature attributed neurocognitive deficits to low SES, despite overlooking the under-representativity of non-Western and low-income countries, potential influences of racial/ethnic differences, and measurement sensitivity/specificity discrepancies. To reach United Nations Sustainable Development Goals, policies and interventions should consider regional, structural, or environmental ecologies beyond the individual, critically probing implicit deficit attributions. Full article

There is much controversy about the link between motor symptom progression and the plethora of reported brain atrophy patterns in idiopathic Parkinson’s disease (PD). The main goal of this study is to provide empirical evidence for unique and common contributions of clinical phenotype characteristics on the dynamic changes of brain structure over time. We analyzed the behavioral and magnetic resonance imaging (MRI) data of PD patients (n = 22) and healthy individuals (n = 21) acquired two years apart through the computational anatomy framework of longitudinal voxel-based morphometry (VBM). This analysis revealed a symmetrical bi-hemispheric pattern of accelerated grey matter decrease in PD extending through the insula, parahippocampal gyrus, medial temporal lobes and the precuneus. We observed a hemisphere-specific correlation between the established scores for motor symptoms severity and the rate of atrophy within motor regions, which was further differentiated by the clinical phenotype characteristics of PD patients. Baseline cerebellum anatomy differences between the tremor-dominant and akineto-rigid PD remained stable over time and can be regarded as trait rather than state-associated features. We interpret the observed pattern of progressive brain anatomy changes as mainly linked to insular areas that determine together with basal ganglia the motor and non-motor phenotype in PD. Our findings provide empirical evidence for the sensitivity of computational anatomy to dynamic changes in PD, offering additional opportunities to establish reliable models of disease progression. Full article

(1) Background: To test the accuracy of a fully automated stroke tissue estimation algorithm (FASTER) to predict final lesion volumes in an independent dataset in patients with acute stroke; (2) Methods: Tissue-at-risk prediction was performed in 31 stroke patients presenting with a proximal middle cerebral artery occlusion. FDA-cleared perfusion software using the AHA recommendation for the Tmax threshold delay was tested against a prediction algorithm trained on an independent perfusion software using artificial intelligence (FASTER). Following our endovascular strategy to consequently achieve TICI 3 outcome, we compared patients with complete reperfusion (TICI 3) vs. no reperfusion (TICI 0) after mechanical thrombectomy. Final infarct volume was determined on a routine follow-up MRI or CT at 90 days after the stroke; (3) Results: Compared to the reference standard (infarct volume after 90 days), the decision forest algorithm overestimated the final infarct volume in patients without reperfusion. Underestimation was observed if patients were completely reperfused. In cases where the FDA-cleared segmentation was not interpretable due to improper definitions of the arterial input function, the decision forest provided reliable results; (4) Conclusions: The prediction accuracy of automated tissue estimation depends on (i) success of reperfusion, (ii) infarct size, and (iii) software-related factors introduced by the training sample. A principal advantage of machine learning algorithms is their improved robustness to artifacts in comparison to solely threshold-based model-dependent software. Validation on independent datasets remains a crucial condition for clinical implementations of decision support systems in stroke imaging. Full article