Spontaneous spinal subarachnoid haemorrhage: a rare complication of dengue fever / Nur Hidayati Mohd Sharif … [et al.]

A 37-year-old woman presented with a short history of fever and bilateral lower limb weakness. She also had impaired sensory function up to T4 spine level and lax anal tone. Laboratory investigations confirmed dengue infection with mild thrombocytopenia. MRI of the spine showed a spinal subarachnoid haemorrhage from the level of T4 till T9. Despite medical and surgical interventions, her lower limb weakness persists. A high index of suspicion is needed to recognise dengue-related neurological complications. This diagnosis should be considered in any patients from dengue endemic areas presenting with acute febrile illness with atypical neurological manifestations

Uterine Arteriovenous Malformation

Uterine arteriovenous malformation (AVM) is a rare condition, with fewer than 100 cases reported in the literature. Despite it being rare, it is a potentially life-threatening condition. This case report describes a 33-year-old woman who presented with secondary post-partum hemorrhage. Transabdominal ultrasound (US) of the pelvis showed increased vascularity with multidirectional flow of the uterus and a prominent vessel, located on the left lateral wall. She also had retained product of conception, which complicated the diagnosis. A uterine artery angiogram confirmed an AVM in the fundal region with an early draining vein. Embolisation of the AVM was performed successfully

Evaluation of time-dependent pathways in an acute ischemic stroke protocol that incorporates CT perfusion: A tertiary referral center experience

Background and Objective: Intravenous thrombolysis service for stroke was introduced at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) in 2009, based on the recommendations of a multidisciplinary team of clinicians. We report the experience at our center in establishing a stroke protocol incorporating computed tomography perfusion (CTP) of the brain, to assess the feasibility of incorporating CTP in the stroke protocol. Methods: A retrospective review of all patients who had a CTP between January 2010 and December 2011 was performed. Results: Of 272 patients who were admitted with acute ischemic stroke, 44 (16.2%) arrived within 4.5 hours from symptom onset and had a CTP performed with the intention to treat. The median time for symptom-to-door, symptom-to-scan and door-to-scan was 90.0 minutes (62.5 – 146.3), 211.0 minutes (165.5 – 273.5) and 85.0 minutes (48.0 – 144.8) respectively. Eight patients (2.9%) were thrombolysed of whom five received IV thrombolysis and three underwent mechanical thrombolysis. The median symptom-to-needle and door-to-needle times were 290.5 minutes (261.3 – 405.0) and 225.0 minutes (172.5 – 316.8) respectively. Four patients were thrombolysed despite being outside the window of treatment based on the CTP findings. Six of the thrombolysed patients had a Modified Rankin Score (MRS) of 1-2 at 5 months post procedure. Conclusions: CTP provides a benefit to management decisions and subsequent patient outcome. It is feasible to incorporate CTP as a standard imaging modality in a stroke protocol. The delays in the time-dependent pathways are due to our work flow and organisational process rather than performing the CTP per se

Wavelet-Based Fractal Analysis of rs-fMRI for Classification of Alzheimer’s Disease

The resting-state functional magnetic resonance imaging (rs-fMRI) modality has gained widespread acceptance as a promising method for analyzing a variety of neurological and psychiatric diseases. It is established that resting-state neuroimaging data exhibit fractal behavior, manifested in the form of slow-decaying auto-correlation and power-law scaling of the power spectrum across low-frequency components. With this property, the rs-fMRI signal can be broken down into fractal and nonfractal components. The fractal nature originates from several sources, such as cardiac fluctuations, respiration and system noise, and carries no information on the brain’s neuronal activities. As a result, the conventional correlation of rs-fMRI signals may not accurately reflect the functional dynamic of spontaneous neuronal activities. This problem can be solved by using a better representation of neuronal activities provided by the connectivity of nonfractal components. In this work, the nonfractal connectivity of rs-fMRI is used to distinguish Alzheimer’s patients from healthy controls. The automated anatomical labeling (AAL) atlas is used to extract the blood-oxygenation-level-dependent time series signals from 116 brain regions, yielding a 116 × 116 nonfractal connectivity matrix. From this matrix, significant connections evaluated using the p-value are selected as an input to a classifier for the classification of Alzheimer’s vs. normal controls. The nonfractal-based approach provides a good representation of the brain’s neuronal activity. It outperformed the fractal and Pearson-based connectivity approaches by 16.4% and 17.2%, respectively. The classification algorithm developed based on the nonfractal connectivity feature and support vector machine classifier has shown an excellent performance, with an accuracy of 90.3% and 83.3% for the XHSLF dataset and ADNI dataset, respectively. For further validation of our proposed work, we combined the two datasets (XHSLF+ADNI) and still received an accuracy of 90.2%. The proposed work outperformed the recently published work by a margin of 8.18% and 11.2%, respectively

Sellar and parasellar lesions: a pictorial illustration

Learning Objective: To present imaging characteristics of various common and uncommon Sellar and Parasellar lesions. Brief Content: The Sella Turcica and adjacent area is a small but complex part of the central nervous system. It contains many structures that can give rise to myriad of pathological lesion. This pictorial exhibit will review common and some uncommon types of pathological processes that occur in this region. Some of the lesions that will be displayed will include: Pituitary Microadenoma, Macroadenoma, Pituitary Apoplexy, Rathke cleft cyst, empty Sella, Aneurysms, Epidermoid/Dermoid, Metastases, Craniopharyngioma, Germinoma, Arachnoid Cyst, Tuber Cinerium Hamartoma, Chiasmatic Glioma, , Lymphocytic Hypophysitis, and Infundibular Histiocytosi

A severe anti-NMDA-receptor encephalitis case with extensive cortical and white matter changes, cerebral atrophy and communicating hydrocephalus

A 21-year-old woman presented with a viral prodrome, abnormal behaviours, confusion and short-term memory loss, followed by status epilepticus that later evolved to orofacial dyskinesias, autonomic dysfunctions and hypoventilation requiring prolonged ventilator support and ICU admission. Cerebrospinal fluid (CSF) and serum analysis confirmed the presence of anti-NMDAR autoantibodies. A left salpingoopherectomy was performed on day 35 of admission revealing an immature ovarian teratoma. Following surgical and two courses of intravenous immunoglobulin therapy, her response remained poor. Initial brain magnetic resonance imaging (MRI) during the acute stage showed enlarged left hippocampus. Further MRI follow-up 13 weeks after admission showed unusual findings of extensive cortical and white matter changes, generalised cerebral atrophy, dilated ventricles and possible transependymal CSF seepage of communicating hydrocephalus. A ventriculo-peritoneal shunt was performed subsequently and she was discharged 6 months after admission without significant change in her clinical status. Follow-up 4 months later showed some improvement but patient remained severely disabled

Non-contrast computed tomography in acute ischaemic stroke: a pictorial review

Non-contrast computed tomography (NCCT) remains a widely used imaging technique and plays an important role in the evaluation of patients with acute ischaemic stroke. However,the task ofidentifying the signs of acute ischaemia and quantifying areas of brain involvement on NCCT scan is not easy due to its subtle findings. The reliability of arly ischemic sign detection can be improved with experience, clinical history and the use of stroke window width and level on viewing the images. The Alberta Stroke Program Early CT Score (ASPECTS) was developed to overcome the difficulty of volume estimation in patients eligible for thrombolysis. It is a systematic, robust and practical method that can standardized the detection and reporting of the extent of acute ischaemic stroke. This article serves as an educational material that illustrates those findings which are important for all clinicians involved in acute stroke car

Pictorial essay: Neuroimaging of stroke

Evaluation of early stroke is one of the most common radiological procedures requested. This pictorial essay illustrates on the basic neuroimaging findings of ischemic stroke. The early signs of ischemia including loss of the insular ribbon sign, hyperdense middle cerebral artery and focal loss of grey white matter differentiation on computed tomography (CT) and localization of stroke using diffusion- weighted MR sequences will be presented. It will expose the clinician through the spectrum of imaging findings of ischemic stroke. Integration of MRI, vascular and perfusion imaging is given in different clinical scenario

Detection of subtle white matter lesions in MRI through texture feature extraction and boundary delineation using an embedded clustering strategy.

White matter lesions (WML) underlie multiple brain disorders, and automatic WML segmentation is crucial to evaluate the natural disease course and effectiveness of clinical interventions, including drug discovery. Although recent research has achieved tremendous progress in WML segmentation, accurate detection of subtle WML present early in the disease course remains particularly challenging. Here we propose an approach to automatic WML segmentation of mild WML loads using an intensity standardisation technique, gray level co-occurrence matrix (GLCM) embedded clustering technique, and random forest (RF) classifier to extract texture features and identify morphology specific to true WML. We precisely define their boundaries through a local outlier factor (LOF) algorithm that identifies edge pixels by local density deviation relative to its neighbors. The automated approach was validated on 32 human subjects, demonstrating strong agreement and correlation (excluding one outlier) with manual delineation by a neuroradiologist through Intra-Class Correlation (ICC = 0.881, 95% CI 0.769, 0.941) and Pearson correlation (r = 0.895, p-value < 0.001), respectively, and outperforming three leading algorithms (Trimmed Mean Outlier Detection, Lesion Prediction Algorithm, and SALEM-LS) in five of the six established key metrics defined in the MICCAI Grand Challenge. By facilitating more accurate segmentation of subtle WML, this approach may enable earlier diagnosis and intervention