Vascular changes caused by deep brain stimulation using double-dose gadolinium-enhanced brain MRI

We retrospectively analyzed the clinical data of 32 patients with medically intractable idiopathic Parkinson＇s disease who had undergone staged bilateral deep brain stimulation of the subtha-lamic nuclei from January 2007 to May 2011. The vascularture of the patients who received two deep brain stimulations was detected using double-dose gadolinium-enhanced brain MRI. The dimensions of straight sinus, superior sagittal sinus, ipsilateral internal cerebral vein in the tha- lamic branch and ipsilateral anterior caudate vein were reduced. These findings demonstrate that bilateral deep brain stimulation of the subthalamic nuclei affects cerebral venous blood flow.

A brief report on MRI investigation of experimental traumatic brain injury

Traumatic brain injury is a major cause of death and disability. This is a brief report based on a symposium presentation to the 2014 Chinese Neurotrauma Association Meeting in San Francisco, USA. It covers the work from our laboratory in applying multimodal MRI to study experimental traumatic brain injury in rats with comparisons made to behavioral tests and histology. MRI protocols include structural, perfusion, manganese-enhanced, diffusion-tensor MRI, and MRI of blood-brain barrier integrity and cerebrovascular reactivity.

Magnetic resonance imaging and cell-based neurorestorative therapy after brain injury

Restorative cell-based therapies for experimental brain injury, such as stroke and traumatic brain injury,substantially improve functional outcome. We discuss and review state of the art magnetic resonance imaging methodologies and their applications related to cell-based treatment after brain injury. We focus on the potential of magnetic resonance imaging technique and its associated challenges to obtain useful new information related to cell migration, distribution, and quantitation, as well as vascular and neuronal remodeling in response to cell-based therapy after brain injury. The noninvasive nature of imaging might more readily help with translation of cell-based therapy from the laboratory to the clinic.

Brainstem abscesses caused by Listeria monocytogenes:A case report

BACKGROUNDIntracranial Listeria infections are common in newborns and immunocompromisedindividuals, but brainstem abscesses are rare.CASE SUMMARYWe report a rare case of brainstem abscesses caused by Listeria monocytogenes in apreviously healthy adult patient. The patient’s magnetic resonance imagingexamination showed multiple brain abscesses, and his second cerebrospinal fluidculture test indicated the presence of Listeria monocytogenes. Despite earlyempirical therapy, the patient’s condition progressively deteriorated. Because thepatient's abscesses were located in the brainstem and multiple lobes, surgery wasnot possible. The patient died 40 d after admission.CONCLUSIONThis case highlights the importance of rational clinical use of drugs to avoidpotentially serious infectious complications.

Unusual Cystic and Papillary Appearance of Brain Metastasis from Papillary Lung Adenocarcinoma on MRI. Radiologic-Pathologic Correlations in Two Similar Cases

We report two cases of brain metastasis from a lung adenocarcinoma. Magnetic Resonance Imaging (MRI) appearance was closely correlated with the macroscopic and microscopic findings that showed multiples nodules of a well-differentiated papillary adenocarcinoma with secreting tubules, surrounded by mucoid fluid.

Modified Visual Geometric Group Architecture for MRI Brain Image Classification

The advancement of automated medical diagnosis in biomedical engineering has become an important area of research.Image classification is one of the diagnostic approaches that do not require segmentation which can draw quicker inferences.The proposed non-invasive diagnostic support system in this study is considered as an image classification system where the given brain image is classified as normal or abnormal.The ability of deep learning allows a single model for feature extraction as well as classification whereas the rational models require separate models.One of the best models for image localization and classification is the Visual Geometric Group(VGG)model.In this study,an efficient modified VGG architecture for brain image classification is developed using transfer learning.The pooling layer is modified to enhance the classification capability of VGG architecture.Results show that the modified VGG architecture outperforms the conventional VGG architecture with a 5%improvement in classification accuracy using 16 layers on MRI images of the REpository of Molecular BRAin Neoplasia DaTa(REMBRANDT)database.

SC-Net:A New U-Net Network for Hippocampus Segmentation

Neurological disorders like Alzheimer’s disease have a significant impact on the lives and health of the elderly as the aging population con-tinues to grow.Doctors can achieve effective prevention and treatment of Alzheimer’s disease according to the morphological volume of hippocam-pus.General segmentation techniques frequently fail to produce satisfactory results due to hippocampus’s small size,complex structure,and fuzzy edges.We develop a new SC-Net model using complete brain MRI images to achieve high-precision segmentation of hippocampal structures.The proposed network improves the accuracy of hippocampal structural segmentation by retaining the original location information of the hippocampus.Extensive experimental results demonstrate that the proposed SC-Net model is signif-icantly better than other models,and reaches a Dice similarity coefficient of 0.885 on Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset.

A New Medical Image Enhancement Algorithm Based on Fractional Calculus

The enhancement of medical images is a challenging research task due to the unforeseeable variation in the quality of the captured images.The captured images may present with low contrast and low visibility,which might inuence the accuracy of the diagnosis process.To overcome this problem,this paper presents a new fractional integral entropy(FITE)that estimates the unforeseeable probabilities of image pixels,posing as the main contribution of the paper.The proposed model dynamically enhances the image based on the image contents.The main advantage of FITE lies in its capability to enhance the low contrast intensities through pixels’probability.Initially,the pixel probability of the fractional power is utilized to extract the illumination value from the pixels of the image.Next,the contrast of the image is then adjusted to enhance the regions with low visibility.Finally,the fractional integral entropy approach is implemented to enhance the low visibility contents from the input image.Tests were conducted on brain MRI,lungs CT,and kidney MRI scans datasets of different image qualities to show that the proposed model is robust and can withstand dramatic variations in quality.The obtained comparative results show that the proposed image enhancement model achieves the best BRISQUE and NIQE scores.Overall,this model improves the details of brain MRI,lungs CT,and kidney MRI scans,and could therefore potentially help the medical staff during the diagnosis process.

Prevalence of Cerebral Atherosclerosis among Patients with Metabolic Syndrome: A Case Control Study on Egyptian Subjects

Background: The metabolic syndrome (MetS) is a clustering of vascular risk factors that tend to increase the risk of occurrence of diabetes mellitus type 2 (DMT2), cardiovascular and cerebro-vascular ischemic events. The aim of the present study is to investigate the association of extra-cranial and intracranial arterial atherosclerosis as well as silent brain infarction (SBI) with MetS, thereby determining the potential cerebrovascular atherosclerotic risk of MetS in the Egyptian population. Methods: A case control study was conducted on 50 Egyptian subjects with MetS and 30 without with age range from 40 - 60 years old. All participants were free from cerebrovascular ischemic events [stroke or transient ischemic attack (TIA)]. All participants underwent complete neurological examination, assessment of the diagnostic criteria for MetS, carotid and transcranial duplex ultrasonography (U/S) and brain MRI. Results: Preclinical carotid atherosclerosis (athero-sclerotic plaques with <50% stenosis) was associated with MetS (P value = 0.02) that persisted after adjustment for age and other confounders. There was no significant association between increased intima media thickness (IMT) and MetS. There was non-significant association between MetS and intracranial atherosclerotic disease (ICAD) or the degree of intracranial stenosis (ICS). Conversely, there was a highly significant association between MetS and SBI even after adjustment for age and other confounders (P value = 0.001). Conclusion: Metabolic syndrome is an important factor associated with mild to moderate atherosclerosis (<50% stenosis) and silent brain infarcts among asymptomatic individuals. Interventions to reduce MetS are important for prevention of subclinical and clinical cerebral atherosclerotic disease.

Ischaemic Stroke Complicating Infective Endocarditis: Microbleeds Are the Diagnostic Clue

Introduction: Ischemic strokes represent a classic complication of infective endocarditis (IE) and are most often related to the fragmentation of valvular vegetation. In most cases, they occur in the Sylvian territory and are related to Staphylococcus aureus. MRI can demonstrate, in addition to the AVCI image, cerebral microbleeds (CMBs) that are very suggestive of the diagnosis. We present the case of a patient who presented an ischemic stroke occurring in the context of infective endocarditis. Observation: A 32-year-old woman with no previous medical history initially presented with acute febrile headache, two weeks later she developed right hemiplegia with aphasia in the context of fever. Her general examination revealed lesions on the soles of her feet, in the form of nodules, infected in places, suggestive of Janeway nodules (characteristic of IE). The brain MRI showed an ischemic stroke in the Sylvian territory, with the presence of multiple microbleeds on the magnetic susceptibility sequences. The biological examination showed a severe inflammatory syndrome;the transthoracic echocardiography (TTE) confirmed the presence of vegetation on the aortic valve;and the blood cultures showed a Staphylococcus aureus. Antibiotic therapy was started, and the patient was transferred to the cardiology department. Discussion: Our observation has a double interest. The first is clinical due to the presence of plantar nodules (Janeway’s nodules) that are characteristic of IE which should orientate the diagnosis before the installation of the stroke, and the second is radiological and linked to the discovery of microbleeds. Their presence is increasingly reported in the literature, but their pathophysiology is not yet very clear. Conclusion: Stroke is the most frequent extracardiac complication during IE. The presence of microbleeds contributes to early diagnosis, especially in asymptomatic forms.

Limbic Encephalitis as the First Manifestation of Neurosyphilis: A Diagnostic Challenge

Limbic encephalitis (LE) is a clinical entity related to a mesial temporal lesion resulting in a combination of anterograde memory dysfunction, behavioral changes, and seizures. The most common causes of limbic encephalitis are Herpes Simplex Virus (HSV) encephalitis, autoimmune encephalitis. Neurosyphilis is an exceptional aetiology. The early diagnosis and management of the disease determine the prognosis. This clinical course highlights the diagnostic challenge limbic encephalitis can cause and the importance of considering neurosyphilis in patients with specific or unspecific neurological symptoms. We report a case of a mesiotemporal form of neurosyphilis revealed by a LE.

Age-related connectivity differences between attention deficit and hyperactivity disorder patients and typically developing subjects：a resting-state functional MRI study

Attention deficit and hyperactivity disorder（ADHD） is a disorder characterized by behavioral symptoms including hyperactivity/impulsivity among children,adolescents,and adults.These ADHD related symptoms are influenced by the complex interaction of brain networks which were under explored.We explored age-related brain network differences between ADHD patients and typically developing（TD） subjects using resting state f MRI（rs-f MRI） for three age groups of children,adolescents,and adults.We collected rs-f MRI data from 184 individuals（27 ADHD children and 31 TD children;32 ADHD adolescents and 32 TD adolescents;and 31 ADHD adults and 31 TD adults）.The Brainnetome Atlas was used to define nodes in the network analysis.We compared three age groups of ADHD and TD subjects to identify the distinct regions that could explain age-related brain network differences based on degree centrality,a well-known measure of nodal centrality.The left middle temporal gyrus showed significant interaction effects between disease status（i.e.,ADHD or TD） and age（i.e.,child,adolescent,or adult）（P 0.001）.Additional regions were identified at a relaxed threshold（P 0.05）.Many of the identified regions（the left inferior frontal gyrus,the left middle temporal gyrus,and the left insular gyrus） were related to cognitive function.The results of our study suggest that aberrant development in cognitive brain regions might be associated with age-related brain network changes in ADHD patients.These findings contribute to better understand how brain function influences the symptoms of ADHD.

An improved brain MR image binarization method as a preprocessing for abnormality detection and features extraction

This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.

A Survey of MRI-Based Brain Tumor Segmentation Methods

Brain tumor segmentation aims to separate the different tumor tissues such as active cells, necrotic core,and edema from normal brain tissues of White Matter（WM）, Gray Matter（GM）, and Cerebrospinal Fluid（CSF）. MRIbased brain tumor segmentation studies are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast of Magnetic Resonance Imaging（MRI） images. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting brain tumor are becoming more and more mature and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for MRI-based brain tumor segmentation methods. Firstly, a brief introduction to brain tumors and imaging modalities of brain tumors is given. Then, the preprocessing operations and the state of the art methods of MRI-based brain tumor segmentation are introduced. Moreover, the evaluation and validation of the results of MRI-based brain tumor segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for MRI-based brain tumor segmentation methods.

Cerebral amyloid angiopathy-related inflammation: current status and future implications

Cerebral amyloid angiopathy-related inflammation (CAA-RI) is a rare but increasingly recognized subtype of CAA. CAA-RI consists of two subtypes: inflammatory cerebral amyloid angiopathy and amyloid β (Aβ)-related angiitis. Acute or subacute onset of cognitive decline or behavioral changes is the most common symptom of CAA-RI. Rapid progressive dementia, headache, seizures, or focal neurological deficits, with patchy or confluent hyperintensity on T2 or fluid-attenuated inversion recovery sequences and evidence of strictly lobar microbleeds or cortical superficial siderosis on susceptibility-weighted imaging imply CAA-RI. The gold standard for diagnosis is autopsy or brain biopsy. However, biopsy is invasive;consequently, most clinically diagnosed cases have been based on clinical and radiological data. Other diagnostic indexes include the apolipoprotein E ε4 allele, Aβ and anti-Aβ antibodies in cerebral spinal fluid and amyloid positron emission tomography. Many diseases with similar clinical manifestations should be carefully ruled out. Immunosuppressive therapy is effective both during initial presentation and in relapses. The use of glucocorticoids and immunosuppressants improves prognosis. This article reviews the pathology and pathogenesis, clinical and imaging manifestations, diagnostic criteria, treatment, and prognosis of CAA-RI, and highlights unsolved problems in the existing research.