57 research outputs found

    Bayesian segmentation of brainstem structures in MRI

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    VK: Lampinen, J.In this paper we present a method to segment four brainstem structures (midbrain, pons, medulla oblongata and superior cerebellar peduncle) from 3D brain MRI scans. The segmentation method relies on a probabilistic atlas of the brainstem and its neighboring brain structures. To build the atlas, we combined a dataset of 39 scans with already existing manual delineations of the whole brainstem and a dataset of 10 scans in which the brainstem structures were manually labeled with a protocol that was specifically designed for this study. The resulting atlas can be used in a Bayesian framework to segment the brainstem structures in novel scans. Thanks to the generative nature of the scheme, the segmentation method is robust to changes in MRI contrast or acquisition hardware. Using cross validation, we show that the algorithm can segment the structures in previously unseen T1 and FLAIR scans with great accuracy (mean error under 1 mm) and robustness (no failures in 383 scans including 168 AD cases). We also indirectly evaluate the algorithm with a experiment in which we study the atrophy of the brainstem in aging. The results show that, when used simultaneously, the volumes of the midbrain, pons and medulla are significantly more predictive of age than the volume of the entire brainstem, estimated as their sum. The results also demonstrate that the method can detect atrophy patterns in the brainstem structures that have been previously described in the literature. Finally, we demonstrate that the proposed algorithm is able to detect differential effects of AD on the brainstem structures. The method will be implemented as part of the popular neuroimaging package FreeSurfer.Peer reviewe

    Genetic and behavioral determinants of hippocampal volume recovery during abstinence from alcohol

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    Alcohol-dependent individuals (ALC) have smaller hippocampi and poorer neurocognition than healthy controls. Results from studies on the association between alcohol consumption and hippocampal volume have been mixed, suggesting that comorbid or premorbid factors (i.e., those present prior to the initiation of alcohol dependence) determine hippocampal volume in ALC. We aimed to characterize the effects of select comorbid (i.e., cigarette smoking) and premorbid factors (brain-derived neurotrophic factor [BDNF] genotype [Val66Met rs6265]) on hippocampal volume in an ALC cohort followed longitudinally into extended abstinence. One hundred twenty-one adult ALC in treatment (76 smokers, 45 non-smokers) and 35 non-smoking light-drinking controls underwent quantitative magnetic resonance imaging, BDNF genotyping, and neurocognitive assessments. Representative subgroups were studied at 1 week, 1 month, and at an average of 7 months of abstinence. ALC had smaller hippocampi than healthy controls at all time points. Hippocampal volume at 1 month of abstinence correlated with lower visuospatial function. Smoking status did not influence hippocampal volume or hippocampal volume recovery during abstinence. However, only BDNF Val homozygotes tended to have hippocampal volume increases over 7 months of abstinence, and Val homozygotes had significantly larger hippocampi than Met carriers at 7 months of abstinence. These findings suggest that BDNF genotype, but not smoking status or measures of drinking severity, regulate functionally relevant hippocampal volume recovery in abstinent ALC. Future studies aimed at exploring genetic determinants of brain morphometry in ALC may need to evaluate individuals during extended abstinence after the acute environmental effects of chronic alcohol consumption have waned

    Genetic and behavioral determinants of hippocampal volume recovery during abstinence from alcohol.

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    Alcohol-dependent individuals (ALC) have smaller hippocampi and poorer neurocognition than healthy controls. Results from studies on the association between alcohol consumption and hippocampal volume have been mixed, suggesting that comorbid or premorbid factors (i.e., those present prior to the initiation of alcohol dependence) determine hippocampal volume in ALC. We aimed to characterize the effects of select comorbid (i.e., cigarette smoking) and premorbid factors (brain-derived neurotrophic factor [BDNF] genotype [Val66Met rs6265]) on hippocampal volume in an ALC cohort followed longitudinally into extended abstinence. One hundred twenty-one adult ALC in treatment (76 smokers, 45 non-smokers) and 35 non-smoking light-drinking controls underwent quantitative magnetic resonance imaging, BDNF genotyping, and neurocognitive assessments. Representative subgroups were studied at 1 week, 1 month, and at an average of 7 months of abstinence. ALC had smaller hippocampi than healthy controls at all time points. Hippocampal volume at 1 month of abstinence correlated with lower visuospatial function. Smoking status did not influence hippocampal volume or hippocampal volume recovery during abstinence. However, only BDNF Val homozygotes tended to have hippocampal volume increases over 7 months of abstinence, and Val homozygotes had significantly larger hippocampi than Met carriers at 7 months of abstinence. These findings suggest that BDNF genotype, but not smoking status or measures of drinking severity, regulate functionally relevant hippocampal volume recovery in abstinent ALC. Future studies aimed at exploring genetic determinants of brain morphometry in ALC may need to evaluate individuals during extended abstinence after the acute environmental effects of chronic alcohol consumption have waned

    PEGylated-nanoliposomal clusterin for amyloidogenic light chain-induced endothelial dysfunction

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    Light chain (AL) amyloidosis is a disease associated with significant morbidity and mortality arising from multi-organ injury induced by amyloidogenic light chain proteins (LC). There is no available treatment to reverse the toxicity of LC. We previously showed that chaperone glycoprotein clusterin (CLU) and nanoliposomes (NL), separately, restore human microvascular endothelial function impaired by LC. In this work, we aim to prepare PEGylated-nanoliposomal clusterin (NL-CLU) formulations that could allow combined benefit against LC while potentially enabling efficient delivery to microvascular tissue, and test efficacy on human arteriole endothelial function. NL-CLU was prepared by a conjugation reaction between the carboxylated surface of NL and the primary amines of the CLU protein. NL were made of phosphatidylcholine (PC), cholesterol (Chol) and 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[carboxy(polyethylene glycol)-2000] (DSPE-PEG 2000 carboxylic acid) at 70:25:5mol%. The protective effect of NL-CLU was tested by measuring the dilation response to acetylcholine and papaverine in human adipose arterioles exposed to LC. LC treatment significantly reduced the dilation response to acetylcholine and papaverine; co-treatment of LC with PEGylated-nanoliposomal CLU or free CLU restored the dilator response. NL-CLU is a feasible and promising approach to reverse LC-induced endothelial damage.College of Pharmacy-Glendale, Midwestern UniversityOpen access article.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

    Identifying cognitively healthy elderly individuals with subsequent memory decline by using automated MR temporoparietal volumes.

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    PURPOSE: To determine whether automated temporoparietal brain volumes can be used to accurately predict future memory decline among a multicenter cohort of cognitively healthy elderly individuals. MATERIALS AND METHODS: The study was approved by the institutional review board at each site and was HIPAA compliant, with written consent obtained from all participants. One hundred forty-nine cognitively healthy study participants were recruited through the Alzheimer\u27s Disease Neuroimaging Initiative and underwent a standardized baseline 1.5-T magnetic resonance (MR) imaging examination, as well as neuropsychological assessment at baseline and after 2 years of follow-up. A composite memory score for the 2-year change in the results of two delayed-recall tests was calculated, and memory decline was defined as a composite score that was at least 1 standard deviation below the group mean score. The predictive accuracy of the brain volumes was estimated by using areas under receiver operating characteristic curves and was further assessed by using leave-one-out cross validation. RESULTS: Use of the most accurate region model, which included the hippocampus; parahippocampal gyrus; amygdala; superior, middle, and inferior temporal gyri; superior parietal lobe; and posterior cingulate gyrus, resulted in a fitted accuracy of 94% and a cross-validated accuracy of 81%. CONCLUSION: Study results indicate that automated temporal and parietal volumes can be used to identify with high accuracy cognitively healthy individuals who are at risk for future memory decline. Further validation of this predictive model in a new cohort is required
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