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BackgroundThe lives of half a million children in the United States are severely affected due to the alterations in their functional and mental abilities which epilepsy causes. This study aims to introduce a novel decision support system for the diagnosis of pediatric epilepsy based on scalp EEG data in a clinical environment.MethodsA new time varying approach for constructing functional connectivity networks (FCNs) of 18 subjects (7 subjects from pediatric control (PC) group and 11 subjects from pediatric epilepsy (PE) group) is implemented by moving a window with overlap to split the EEG signals into a total of 445 multi-channel EEG segments (91 for PC and 354 for PE) and finding the hypothetical functional connectivity strengths among EEG channels. FCNs are then mapped into the form of undirected graphs and subjected to extraction of graph theory based features. An unsupervised labeling technique based on Gaussian mixtures model (GMM) is then used to delineate the pediatric epilepsy group from the control group.ResultsThe study results show the existence of a statistically significant difference (p < 0.0001) between the mean FCNs of PC and PE groups. The system was able to diagnose pediatric epilepsy subjects with the accuracy of 88.8% with 81.8% sensitivity and 100% specificity purely based on exploration of associations among brain cortical regions and without a priori knowledge of diagnosis.ConclusionsThe current study created the potential of diagnosing epilepsy without need for long EEG recording session and time-consuming visual inspection as conventionally employed.

Intracranial volume (ICV) is a standard measure often used in morphometric analyses to correct for head size in brain studies. Inaccurate ICV estimation could introduce bias in the outcome. The current study provides a decision aid in defining protocols for ICV estimation across different subject groups in terms of sampling frequencies that can be optimally used on the volumetric MRI data, and type of software most suitable for use in estimating the ICV measure. Four groups of 53 subjects are considered, including adult controls (AC, adults with Alzheimer's disease (AD), pediatric controls (PC) and group of pediatric epilepsy subjects (PE). Reference measurements were calculated for each subject by manually tracing intracranial cavity without sub-sampling. The reliability of reference measurements were assured through intra- and inter- variation analyses. Three publicly well-known software packages (FreeSurfer Ver. 5.3.0, FSL Ver. 5.0, SPM8 and SPM12) were examined in their ability to automatically estimate ICV across the groups. Results on sub-sampling studies with a 95 % confidence showed that in order to keep the accuracy of the inter-leaved slice sampling protocol above 99 %, sampling period cannot exceed 20 mm for AC, 25 mm for PC, 15 mm for AD and 17 mm for the PE groups. The study assumes a priori knowledge about the population under study into the automated ICV estimation. Tuning of the parameters in FSL and the use of proper atlas in SPM showed significant reduction in the systematic bias and the error in ICV estimation via these automated tools. SPM12 with the use of pediatric template is found to be a more suitable candidate for PE group. SPM12 and FSL subjected to tuning are the more appropriate tools for the PC group. The random error is minimized for FS in AD group and SPM8 showed less systematic bias. Across the AC group, both SPM12 and FS performed well but SPM12 reported lesser amount of systematic bias.

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Several standard protocols based on repetitive transcranial magnetic stimulation (rTMS) have been employed for treatment of a variety of neurological disorders. Despite their advantages in patients that are retractable to medication, there is a lack of knowledge about the effects of rTMS on the autonomic nervous system that controls the cardiovascular system. Current understanding suggests that the shape of the so-called QRS complex together with the size of the different segments and intervals between the PQRST deflections of the heart could predict the nature of the different arrhythmias and ailments affecting the heart. This preliminary study involving 10 normal subjects from 20 to 30 years of age demonstrated that rTMS can induce changes in the heart rhythm. The autonomic activity that controls the cardiac rhythm was indeed altered by an rTMS session targeting the motor cortex using intensity below the subject's motor threshold and lasting no more than 5 minutes. The rTMS activation resulted in a reduction of the RR intervals (cardioacceleration) in most cases. Most of these cases also showed significant changes in the Poincare plot descriptor SD2 (long-term variability), the area under the low frequency (LF) power spectrum density curve, and the low frequency to high frequency (LF/HF) ratio. The RR intervals changed significantly in specific instants of time during rTMS activation showing either heart rate acceleration or heart rate deceleration.

Cutaneomeningospinal angiomatosis, or Cobb syndrome, is a rare metameric developmental disorder presenting as an extradural-intradural vascular malformation that involves bone, muscle, skin, spinal cord, and nerve roots. A 14-year-old girl with a red nevus involving the T6–9 dermatomes on the left side of her back presented with a 5-year history of bowel and bladder incontinence, paraplegia, and lower-extremity sensory loss. Magnetic resonance imaging demonstrated a hemangioma in the T-8 and T-9 vertebral bodies and a spinal cord AVM nidus extending from T-6 to T-9. The AVM was successfully embolized and the patient regained lower-extremity strength, ambulation, and normal sphincter functions after 5 years of having been wheelchair bound. The authors report the restoration of ambulation after endovascular embolization of a large spinal AVM in a patient with long-standing paraplegia due to Cobb syndrome.

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Stereotactic radiosurgery of the brain may be accomplished with a linear accelerator by performing several noncoplanar arcs of a highly collimated beam focused at a point. The shape of the radiation distribution produced by this technique is affected by the beam energy, field size, and the number and size of the arcs. The influence of these parameters on the resulting radiation distributions was analyzed by computing dose volume histograms for a typical brain. Dose volume functions were computed for: (a) the energy range of 4-24 MV x rays; (b) target sizes of 1-4 cm; and (c) 1-11 arcs and dynamic rotation. The dose volume histograms were found to be dependent on the number of arcs for target sizes of 1-4 cm. However, these differences were minimal for techniques with 4 arcs or more. The influence of beam energy on the dose volume histogram was also found to be minimal.