White matter hyperintensities and quality of life in acute lacunar stroke

2012 ◽  
Vol 34 (8) ◽  
pp. 1347-1353 ◽  
Author(s):  
W. K. Tang ◽  
H. J. Liang ◽  
Y. K. Chen ◽  
A. T. Ahuja ◽  
Winnie C. W. Chu ◽  
...  
Keyword(s):  
Quality Of Life ◽  
White Matter ◽  
White Matter Hyperintensities ◽  
Lacunar Stroke

Associations of MRI white matter hyperintensities with cognitive functions, depression and quality of life

2013 ◽  
Vol 333 ◽  
pp. e347-e348
Author(s):  
A. Amintaeva ◽  
M. Kravchenko ◽  
O. Andreeva ◽  
Y. Varakin ◽  
E. Gnedovskaya ◽  
...  
Keyword(s):  
Quality Of Life ◽  
White Matter ◽  
Cognitive Functions ◽  
White Matter Hyperintensities

scholarly journals Association between Perivascular Spaces and Progression of White Matter Hyperintensities in Lacunar Stroke Patients

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137323 ◽  
Author(s):  
Caroline M. J. Loos ◽  
Pim Klarenbeek ◽  
Robert J. van Oostenbrugge ◽  
Julie Staals
Keyword(s):  
White Matter ◽  
White Matter Hyperintensities ◽  
Perivascular Spaces ◽  
Lacunar Stroke ◽  
Stroke Patients

scholarly journals Plasma tPA-Activity and Progression of Cerebral White Matter Hyperintensities in Lacunar Stroke Patients

PLoS ONE ◽  
2016 ◽  
Vol 11 (3) ◽  
pp. e0150740 ◽  
Author(s):  
Ellen C. van Overbeek ◽  
Julie Staals ◽  
Iris L. H. Knottnerus ◽  
Hugo ten Cate ◽  
Robert J. van Oostenbrugge
Keyword(s):  
White Matter ◽  
White Matter Hyperintensities ◽  
Cerebral White Matter ◽  
Lacunar Stroke ◽  
Stroke Patients

scholarly journals Small cerebellar cortex volume in patients with active Cushing's syndrome

2014 ◽  
Vol 171 (4) ◽  
pp. 461-469 ◽  
Author(s):  
Alicia Santos ◽  
Eugenia Resmini ◽  
Iris Crespo ◽  
Patricia Pires ◽  
Yolanda Vives-Gilabert ◽  
...  
Keyword(s):  
Quality Of Life ◽  
White Matter ◽  
Cerebellar Cortex ◽  
Cushing’S Syndrome ◽  
Visual Memory ◽  
Cushing's Syndrome ◽  
Life Assessment ◽  
Age At Diagnosis ◽  
Cerebellar Volume

ObjectiveCushing's syndrome (CS) is associated with neuropsychological deficits. As the cerebellum plays a key role in neuropsychological functions it may be affected in CS. The aim of this study was to investigate whether patients with CS have a smaller cerebellar volume than healthy controls, and to analyse whether cerebellar volume is associated with neuropsychological performance and clinical parameters.DesignA cross-sectional study was performed.MethodsThirty-six CS patients (15 with active CS and 21 with CS in remission) and 36 controls matched for age, sex, and education underwent neuropsychological testing, quality of life assessment, clinical evaluation, and magnetic resonance imaging brain scan. Cerebellar volumes (white matter and cortex, bilateral) were calculated using FreeSurfer Software.ResultsPatients with active CS showed smaller bilateral cerebellar cortex volumes than controls (left,P=0.035 and right,P=0.034), as well as a trend toward smaller right cerebellar cortex volumes than patients in remission CS (P=0.051). No differences were observed in the volume of cerebellar white matter between the three groups. Both right and left cerebellar cortex volumes correlated negatively with triglyceride levels (right:r=−0.358,P=0.002 and left:r=−0.317,P=0.005) and age at diagnosis (right:r=−0.433,P=0.008 and left:r=−0.457,P=0.005). Left cerebellar cortex volume also correlated positively with visual memory performance (r=0.245,P=0.038). Right cerebellar cortex volume positively correlated with quality-of-life scores (r=0.468,P=0.004).ConclusionsThe cerebellar cortex volume is smaller in active CS patients than in controls. This finding is associated with poor visual memory and quality of life and is mostly pronounced in patients with higher triglyceride levels and older age at diagnosis.

scholarly journals Functional and structural biomarkers of cognitive outcomes after brain tumor resection

2020 ◽  
Author(s):  
Meritxell Garcia ◽  
Jose Aguasvivas ◽  
Santiago Gil-Robles ◽  
Iñigo Pomposo ◽  
Lucia Amorouso ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Working Memory ◽  
Brain Tumor ◽  
White Matter ◽  
Decision Tree ◽  
Executive Control ◽  
Outcome Prediction ◽  
Naive Bayes ◽  
Tumor Resection

Cognitive explorations have demonstrated the activation of plastic mechanisms in slow-growing brain lesions, generating structural and functional changes. Due to its incidence, it is essential to investigate the reorganization of functional areas in brain tumor patients as well as formulating new approaches for predicting patient quality of life after tumor resection. Following this perspective, we formulated an efficient methodology for postsurgical prognosis prediction, not only in terms of the structural damage but also to measure the neuroplastic changes associated with tumor appearence. Of note, most of previous studies employed a limited number of neuropsychological and clinical features for predicting patient prognosis. Our objective is to optimize the traditional model and to develop a method that can predict outcomes with high accuracy and identify the most significant features for cognitive impairment, working memory, executive control and language outcomes. Our approach is based on the inclusion of a large battery of neuropsychological tests as well as the introduction of grey and white matter morphological measures for model optimization. We employed Support Vector Machine (SVM), Decision Tree, and Naïve Bayes algorithms for testing the models and outcomes. Overall, SVM performance showed to be more accurate as compared to Decision Tree and Naïve Bayes. Specifically, we found that, by introducing connectivity variables (e.g., grey and white matter measures) Cognitive Status and Working Memory exhibited a predictive improvement. However, Language and Executive Control outcomes were not significantly predicted in none of the models. The importance of the present study resides in the employment of structural and functional variables for postsurgical outcome prediction. We found that connectivity variables are sensitive for predicting the postsurgical quality of life. Keywords: glioma, resection, postoperative outcome, prediction, neuropsychological test, mapping

scholarly journals Volume of White Matter Hyperintensities Predicts Neurocognitive Functioning in Children with Sickle Cell Disease

Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 2720-2720 ◽  
Author(s):  
Veronica Van Der Land ◽  
Channa T. Hijmans ◽  
Marieke A. de Ruiter ◽  
Henri J.M.M. Mutsaerts ◽  
Marjon H. Cnossen ◽  
...  
Keyword(s):  
White Matter ◽  
Processing Speed ◽  
White Matter Hyperintensities ◽  
Full Scale ◽  
Neurocognitive Functioning ◽  
Neurocognitive Outcome ◽  
Verbal Iq ◽  
Quality Of Life Inventory ◽  
Processing Speed Index

Abstract Introduction Approximately 40% of children with a severe form of sickle cell disease (SCD) will develop cerebral white matter hyperintensities (WMHs), visible on magnetic resonance imaging (MRI). This may be associated with impaired neurocognitive functioning. It is unknown whether the volume of these WHMs is associated with the degree of neurocognitive dysfunction. Our objective was to investigate the association between volume of WMHs and neurocognitive functioning. Methods We prospectively included children with HbSS or HbS-beta(0)thalassemia aged 8-16 years. Exclusion criteria were prior stroke and chronic blood transfusion therapy. Volume of WMHs was calculated on MRI and patients were ranked by size of WMHs. Neurocognitive function was evaluated by testing intelligence (IQ, intelligence quotient), memory, visuo-motor functioning and executive functioning. Fatigue was measured using a validated questionnaire (Pediatric Quality of Life Inventory Multidimensional Fatigue Scale, PedsQL Fatigue) in which lower scores indicate more symptoms of fatigue. For each neurocognitive outcome, univariate linear regression was used to identify which variables (age, sex and hemoglobin level) were confounders. The independent association of volume of WMHs on neurocognitive outcomes was analyzed by multivariate linear regression, adjusted for these confounders when appropriate. The explained variance (R2) refers to the independently explained variance of volume of WMHs on the neurocognitive outcome and the presented p-value corresponds to the unique contribution of volume of WMHs on the outcome, both adjusted for confounders when appropriate. Results We included 38 children; mean age was 12.5 ± 2.7 years, WMHs were present in 50%. Mean full-scale, verbal IQ, performal IQ and Processing Speed Index were all between 85 and 90; this is significantly lower compared to the mean norm scores of 100. Our patients had significantly more symptoms of fatigue compared to Dutch reference values. A higher volume of WMHs was significantly associated with lower scores on full-scale IQ, verbal IQ and Processing Speed Index (see table). In addition, higher volume of WMHs was associated with higher scores of total and cognitive fatigue. Standardized beta coefficients ranged from -0.350 to -0.461, indicating a substantial negative effect of an increasing volume of WMHs on neurocognitive outcome. The volume of WMHs could explain between 12.1% and 21.2% of the variance of these outcomes. Conclusion Our findings suggest that the volume of WMHs is an independent predictor of full-scale IQ, verbal IQ, Processing Speed Index and fatigue in children with SCD. As WMHs are mostly found in the frontal lobe, this could explain the association with processing speed, which is an executive function and thought to be located in the frontal lobe. The association between WMHs and measures of fatigue has not been investigated before. Our results suggest the PedsQL Fatigue could be a promising screening tool for larger studies as it is easy and quick to administer and has a high validity. We suggest that future studies should consider taking the total volume of WMHs into account as an independent predictor of neurocognitive outcome, instead of only the presence or absence of WMHs. Taking the volume of WMHs into account is an important approach for individualized diagnostic and treatment strategies that could be further explored in a clinical setting. Table Prediction model of neurocognitive outcome by volume of white matter hyperintensities ß R2 p Full-scale IQ -0.382 0.146 0.018 Verbal IQ -0.460 0.212 0.004 Performal IQ -0.170 0.029 0.314 Processing Speed Index -0.461 0.212 0.005 PedsQL Fatigue, Total Score -0.350 0.121 0.025 PedsQL Fatigue, General Fatigue -0.289 0.083 0.071 PedsQL Fatigue, Cognitive Fatigue -0.352 0.123 0.026 IQ, Intelligence Quotient; PedsQL Fatigue, Pediatric Quality of Life Inventory Multidimensional Fatigue Scale. Disclosures No relevant conflicts of interest to declare.

scholarly journals F3-05-04: WHITE MATTER HYPERINTENSITIES AND COGNITION: THE MODERATING ROLE OF QUALITY OF EDUCATION IN A MULTIRACIAL COMMUNITY SAMPLE

2019 ◽  
Vol 15 ◽  
pp. P871-P872
Author(s):  
Miguel Arce Renteria ◽  
Patrick J. Lao ◽  
Indira C. Turney ◽  
Jet Vonk ◽  
Kay C. Igwe ◽  
...  
Keyword(s):  
White Matter ◽  
White Matter Hyperintensities ◽  
Community Sample ◽  
Quality Of Education ◽  
Moderating Role
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