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Edward Rams
Edward Rams

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Abnormalities in cognitive function and brain structure have been reported in acutely ill adolescents with anorexia nervosa, but whether these abnormalities persist or are reversible in the context of weight restoration remains unclear. Brain structure and cognitive function in female subjects with adolescent-onset anorexia nervosa assessed at long-term follow-up were studied in comparison with healthy female subjects, and associations with clinical outcome were investigated. Sixty-six female subjects (aged 21.3 +/- 2.3 years) who had a diagnosis of adolescent-onset anorexia nervosa and treated 6.5 +/- 1.7 years earlier in a tertiary care hospital and 42 healthy female control subjects (aged 20.7 +/- 2.5 years) were assessed. All participants underwent a clinical examination, magnetic resonance brain scan, and cognitive evaluation. Clinical data were analyzed first as a function of weight recovery (n = 14, or=85% ideal body weight) and as a function of menstrual status (n = 18, absent/irregular menses; n = 29, oral contraceptive pill; n = 19, regular menses). Group comparisons were made across structural brain volumes and cognitive scores. Compared with control subjects, participants with anorexia nervosa who remained at low weight had larger lateral ventricles. Twenty-four-hour urinary free-cortisol levels were positively correlated with volumes of the temporal horns of the lateral ventricles and negatively correlated with volumes of the hippocampi in clinical participants. Participants who were amenorrheic or had irregular menses showed significant cognitive deficits across a broad range of many domains. Female subjects with adolescent-onset anorexia nervosa showed abnormal cognitive function and brain structure compared with healthy individuals despite an extended period since diagnosis. To our knowledge, this is the first study to report a specific relationship between menstrual function and cognitive function in this patient


Brain tumour segmentation in medical images is a very challenging task due to the large variety in tumour shape, position, appearance, scanning modalities and scanning parameters. Most existing segmentation algorithms use information from four different MRI-sequences, but since this is often not available, there is need for a method able to delineate the different tumour tissues based on a minimal amount of data. We present a novel approach using a Random Forests model combining voxelwise texture and abnormality features on a contrast-enhanced T1 and FLAIR MRI. We transform the two scans into 275 feature maps. A random forest model next calculates the probability to belong to 4 tumour classes or 5 normal classes. Afterwards, a dedicated voxel clustering algorithm provides the final tumour segmentation. We trained our method on the BraTS 2013 database and validated it on the larger BraTS 2017 dataset. We achieve median Dice scores of 40.9% (low-grade glioma) and 75.0% (high-grade glioma) to delineate the active tumour, and 68.4%/80.1% for the total abnormal region including edema. Our fully automated brain tumour segmentation algorithm is able to delineate contrast enhancing tissue and oedema with high accuracy based only on post-contrast T1-weighted and FLAIR MRI, whereas for non-enhancing tumour tissue and necrosis only moderate results are obtained. This makes the method especially suitable for high-grade glioma. Copyright 2018 Elsevier Ltd. All rights reserved.


Contemporary neuroimaging methods disclosed structural and functional cerebral abnormalities in idiopathic generalized epilepsies (IGEs). However, individual electrical (EEG) abnormalities have not been evaluated yet in IGE patients. IGE patients were investigated in the drug-free condition and after 3-6 month of antiepileptic treatment. To estimate the reproducibility of qEEG variables a retrospective recruited cohort of IGE patients was investigated. 19-channel resting state EEG activity was recorded. For each patient a total of 2 minutes EEG activity was analyzed by LORETA (Low Resolution Electromagnetic Tomography). Raw LORETA values were Z-transformed and projected to a MRI template. Z-values outside within the [+3Z] to [-3Z] range were labelled as statistically abnormal. 1. In drug-free condition, 41-50% of IGE patients showed abnormal LORETA values. 2. Abnormal LORETA findings showed great inter-individual variability. 3. Most abnormal LORETA-findings were symmetrical. 4. Most maximum Z-values were localized to frontal or temporal cortex. 5. Succesfull treatment was mostly coupled with disappearence of LORETA-abnormality, persistent seizures were accompanied by persistent LORETA abnormality. 1. LORETA abnormalities detected in the untreated condition reflect seizure-generating property of the cortex in IGE patients. 2. Maximum LORETA-Z abnormalities were topographically congruent with structural abnormalities reported by other research groups. 3. LORETA might help to investigate drug effects at the whole-brain level.


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