An Inherited Small Microdeletion at 15q13.3 in a Patient with Early- Onset Obsessive-Compulsive Disorder

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Intraoperative ultrasonography for presumed brain metastases: a case series study

Brain metastases (BM) are one of the most common intracranial tumors and surgical treatment can improve both the functional outcomes and patient survival, particularly when systemic disease is controlled. Image-guided BM resection using intraoperative exams, such as intraoperative ultrasound (IOUS), can lead to better surgical results. Methods: To evaluate the use of IOUS for BM resection, 20 consecutives patients were operated using IOUS to locate tumors, identify their anatomical relationships and surgical cavity after resection. Technical difficulties, complications, recurrence and survival rates were noted. Results: IOUS proved effective for locating, determining borders and defining the anatomical relationships of BM, as well as to identify incomplete tumor resection. No complications related to IOUS were seen. Conclusion: IOUS is a practical supporting method for the resection of BM, but further studies comparing this method with other intraoperative exams are needed to evaluate its actual contribution and reliability.

Late-onset social anxiety disorder following traumatic brain injury

Background: Neuropsychiatric sequelae are the predominant long-term disability after traumatic brain injury (TBI). This study reports a case of late-onset social anxiety disorder (SAD) following TBI. Case report: A patient that was spontaneous and extroverted up to 18-years-old started to exhibit significant social anxiety symptoms. These symptoms became progressively worse and he sought treatment at age 21. He had a previous history of traumatic brain injury (TBI) at age 17. Neuroimaging investigations (CT, SPECT and MRI) showed a bony protuberance on the left frontal bone, with mass effect on the left frontal lobe. He had no neurological signs or symptoms. The patient underwent neurosurgery with gross total resection of the lesion and the pathological examination was compatible with intradiploic haematoma. Conclusions: Psychiatric symptoms may be the only findings in the initial manifestation of slowly growing extra-axial space-occupying lesions that compress the frontal lobe from the outside. Focal neurological symptoms may occur only when the lesion becomes large. This case report underscores the need for careful exclusion of general medical conditions and TBI history in cases of late-onset SAD and may also contribute to the elucidation of the neurobiology of this disorder.

Altered Oxygen Metabolism Associated to Neurogenesis of Induced Pluripotent Stem Cells Derived From a Schizophrenic Patient

Schizophrenia has been defined as a neurodevelopmental disease that causes changes in the process of thoughts, perceptions. and emotions, usually leading to a mental deterioration and affective blunting. Studies have shown altered cell respiration and oxidative stress response in schizophrenia; however, most of the knowledge has been acquired from postmortem brain analyses or from nonneural cells. Here we describe that neural cells, derived from induced pluripotent stem cells generated from skin fibroblasts of a schizophrenic patient, presented a twofold increase in extramitochondrial oxygen consumption as well as elevated levels of reactive oxygen species (ROS), when compared to controls. This difference in ROS levels was reverted by the mood stabilizer valproic acid. Our model shows evidence that metabolic changes occurring during neurogenesis are associated with schizophrenia, contributing to a better understanding of the development of the disease and highlighting potential targets for treatment and drug screening.

BK virus associated meningoencephalitis in an AIDS patient treated with HAART

A severely immune-suppressed AIDS patient was suspected of suffering from BK virus (BKV) meningoencephalitis, after being studied for common causes of neurological complications of co-infectious origin. Polymerase chain reaction (PCR) and sequence analysis of cerebrospinal fluid and brain samples, confirmed the presence of BKV. His clinical condition improved along with the regression of brain lesions, after modifications on his antiretroviral regime. Five months after discharge, the patient was readmitted because of frequent headaches, and a marked inflammatory reaction was evidenced by a new magnetic resonance imaging (MRI). The symptoms paralleled a rising CD4+ lymphocyte count, and immune reconstitution syndrome was suspected. This is the first non-postmortem report of BKV meningoencephalitis in an AIDS patient, showing clinical and radiographic improvement solely under HAART.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

Ventricular enlargement due to acute hypernatremia in a patient with a ventriculoperitoneal shunt

Patients requiring CSF shunts frequently have comorbidities that can influence water and electrolyte balances. The authors report on a case involving a ventriculoperitoneal shunt in a patient who underwent intravenous hyperhydration and withdrawal of vasopressin substitution prior to scheduled high-dose chemotherapy regimen for a metastatic suprasellar germinoma. After acute neurological deterioration, the patient underwent CT scanning that demonstrated ventriculomegaly. A shunt tap revealed no flow and negative opening pressure. Due to suspicion of proximal shunt malfunction, the comatose patient underwent immediate surgical exploration of the ventricle catheter, which was found to be patent. However, acute severe hypernatremia was diagnosed during the procedure. After correction of the electrolyte disturbances, the patient regained consciousness and made a good recovery. Although rare, the effects of acute severe hypernatremia on brain volume and ventricular size should be considered in the differential diagnosis of ventriculoperitoneal shunt failure.

Risk factors contributing to symptomatic miniplate removal: a retrospective study of 153 bilateral sagittal split osteotomy patients

Removal of miniplates is a controversial topic in oral and maxillofacial surgery. Originally, miniplates were designed to be removed on completion of bone healing. The introduction of low profile titanium miniplates has led to the routine removal of miniplates becoming comparatively rare in many parts of the world. Few studies have investigated the reasons for non-routine removal of miniplates and the factors that affect osteosynthesis after osteotomy in large numbers of patients. The aim of the present study was to investigate complications related to osteosynthesis after bilateral sagittal split osteotomy (BSSO) in a large number (n=153) of patients. In addition to the rates of removal, emphasis was placed on investigating the reasons and risk factors associated with symptomatic miniplate removal. The rate of plate removal per patient was 18.6%, the corresponding rate per plate being 18.2%. Reasons for plate removal included plate-related complications in 16 patients and subjective discomfort in 13 patients. Half of the plates were removed during the first postoperative year. Smoking was the only significant predictor for plate removal. Patients undergoing orthognathic surgery should be screened with regard to smoking and encouraged and assisted to cease smoking, at least perioperatively.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Effectiveness of protective patient equipment for CT: an anthropomorphic phantom study

Protective patient equipment for CT examinations is not routinely provided. The aim of this study was to determine whether, and if so what, specific protective equipment is beneficial during CT scans. The absorbed organ doses and the effective doses for thorax, abdomen/pelvis and brain CT investigation with and without the use of protective patient equipment have been determined and compared. All measurements were carried out on modern multislice CT scanner using an anthropomorphic phantom and thermoluminescence dosemeters. The measurements show that protective equipment reduces the dose within the scattered beam area. The highest organ dose reduction was found in organs that protrude from the trunk like the testes or the female breasts that can largely be covered by the protective equipment. The most reduction of the effective dose was found in the male abdomen/pelvis examination (0.32 mSv), followed by the brain (0.11 mSv) and the thorax (0.06 mSv). It is concluded that the use of protective equipment can reduce the applied dose to the patient.

Brain metabolite composition in relation to cognitive function and dystrophin mutations in boys with Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a hereditary X-linked recessive disorder affecting the synthesis of dystrophin, a protein essential for structural stability in muscle. Dystrophin also occurs in the central nervous system, particularly in the neocortex, hippocampus and cerebellum. Quantitative metabolic analysis by localized (1) H MRS was performed in the cerebellum (12 patients and 15 controls) and a temporo-parietal location (eight patients and 15 controls) in patients with DMD and healthy controls to investigate possible metabolic differences. In addition, the site of individual mutations on the dystrophin gene was analyzed and neuropsychological cognitive functions were examined. Cognitive deficits in the patient group were found in line with earlier investigations, mainly concerning verbal short-term memory, visuo-spatial long-term memory and verbal fluency, but also the full-scale IQ. Causal mutations were identified in all patients with DMD. Quantitative MRS showed consistent choline deficits, in both cerebellar white matter and temporo-parietal cortex, as well as small, but significant, metabolic abnormalities for glutamate and total N-acetyl compounds in the temporo-parietal region. Compartment water analysis did not reveal any abnormalities. In healthy subjects, choline levels were age related in the cerebellum. The choline deficit contrasts with earlier findings in DMD, where a surplus of choline was postulated for the cerebellum. In patients, total N-acetyl compounds in the temporo-parietal region were related to verbal IQ and verbal short-term memory. However, choline, the putative main metabolic abnormality, was not found to be associated with cognitive deficits. Furthermore, in contrast with the cognitive performance, the metabolic brain composition did not depend significantly on whether or not gene mutations concerned the expression of the dystrophin isoform Dp140, leading to the conclusion that the effect of the missing Dp140 isoform on cognitive performance is not mediated through the observed metabolite composition, or is caused by local effects beyond the resolution accessible to MRS investigations.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Multi-Scale Modeling for Image Analysis of Brain Tumor Studies

Image-based modeling of tumor growth combines methods from cancer simulation and medical imaging. In this context, we present a novel approach to adapt a healthy brain atlas to MR images of tumor patients. In order to establish correspondence between a healthy atlas and a pathologic patient image, tumor growth modeling in combination with registration algorithms is employed. In a first step, the tumor is grown in the atlas based on a new multi-scale, multi-physics model including growth simulation from the cellular level up to the biomechanical level, accounting for cell proliferation and tissue deformations. Large-scale deformations are handled with an Eulerian approach for finite element computations, which can operate directly on the image voxel mesh. Subsequently, dense correspondence between the modified atlas and patient image is established using nonrigid registration. The method offers opportunities in atlasbased segmentation of tumor-bearing brain images as well as for improved patient-specific simulation and prognosis of tumor progression.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Patient acceptance of awake craniotomy

The aim of this study was to objectively assess the patients' acceptance for awake craniotomy in a group of neurosurgical patients, who underwent this procedure for removal of lesions in or close to eloquent brain areas.