Emergent neuroimaging of intracranial infection/inflammation

Labeling Noncontrast Head CT Reports for Common Findings Using Natural Language Processing

BACKGROUND AND PURPOSE

Prioritizing reading of noncontrast head CT examinations through an automated triage system may improve time to care for patients with acute neuroradiologic findings. We present a natural language-processing approach for labeling findings in noncontrast head CT reports, which permits creation of a large, labeled dataset of head CT images for development of emergent-finding detection and reading-prioritization algorithms.

MATERIALS AND METHODS

In this retrospective study, 1002 clinical radiology reports from noncontrast head CTs collected between 2008 and 2013 were manually labeled across 12 common neuroradiologic finding categories. Each report was then encoded using an n-gram model of unigrams, bigrams, and trigrams. A logistic regression model was then trained to label each report for every common finding. Models were trained and assessed using a combination of L2 regularization and 5-fold cross-validation.

RESULTS

Model performance was strongest for the fracture, hemorrhage, herniation, mass effect, pneumocephalus, postoperative status, and volume loss models in which the area under the receiver operating characteristic curve exceeded 0.95. Performance was relatively weaker for the edema, hydrocephalus, infarct, tumor, and white-matter disease models (area under the receiver operating characteristic curve > 0.85). Analysis of coefficients revealed finding-specific words among the top coefficients in each model. Class output probabilities were found to be a useful indicator of predictive error on individual report examples in higher-performing models.

CONCLUSIONS

Combining logistic regression with n-gram encoding is a robust approach to labeling common findings in noncontrast head CT reports.

Neuroimaging in Central Nervous System Infections

Radiologic imaging is often employed to supplement clinical evaluation in cases of suspected central nervous system (CNS) infection. While computed tomography (CT) is superior for evaluating osseous integrity, demineralization, and erosive changes and may be more readily available at many institutions, magnetic resonance imaging (MRI) has significantly greater sensitivity for evaluating the cerebral parenchyma, cord, and marrow for early changes that have not yet reached the threshold for CT detection. For these reasons, MRI is generally superior to CT for characterizing bacterial, viral, fungal, and parasitic infections of the CNS. The typical imaging features of common and uncommon CNS infectious processes are reviewed.

Knockdown of miR-155 protects microglia against LPS-induced inflammatory injury via targeting RACK1: a novel research for intracranial infection

Background

Intracranial infection, one of the complications of traumatic brain injury, is usually associated with inflammation. Several microRNAs (miRNAs), including miR-155, have been reported to be critical modulators in peripheral and central nervous system inflammation. In this study, we investigated the role of miR-155 in lipopolysaccharide (LPS)-induced inflammatory injury in mouse microglia BV2 cells.

Results

The expression level of miR-155 was significantly up-regulated after LPS stimulation in BV2 cells. LPS administration decreased BV2 cell viability, promoted apoptosis and increased the release of pro-inflammatory cytokines; while miR-155 knockdown rescued BV2 cell from LPS-induced injury. RACK1 was a directly target of miR-155. Interestingly, miR-155 knockdown did not attenuate LPS-induced inflammatory injury when RACK1 was knocked down. The mechanistic study indicated that miR-155 knockdown deactivated MAPK/NF-κB and mTOR signaling pathways under LPS-treated conditions.

Conclusions

Knockdown of miR-155 protected mouse microglia BV2 cells from LPS-induced inflammatory injury via targeting RACK1 and deactivating MAPK/NF-κB and mTOR signaling pathways.

Parasitic diseases of the central nervous system: lessons for clinicians and policy makers

Parasitic diseases of the central nervous system are associated with high mortality and morbidity, especially in resource-limited settings. The burden of these diseases is amplified as survivors are often left with neurologic sequelae affecting mobility, sensory organs, and cognitive functions, as well as seizures/epilepsy. These diseases inflict suffering by causing lifelong disabilities, reducing economic productivity, and causing social stigma. The complexity of parasitic life cycles and geographic specificities, as well as overlapping clinical manifestations in the host reflecting the diverse pathogenesis of parasites, can present diagnostic challenges. We herein provide an overview of these parasitic diseases and summarize clinical aspects, diagnosis, therapeutic strategies and recent milestones, and aspects related to prevention and control.

Select topics in neurocritical care

Neurocritical care aims to improve outcomes in patients with life-threatening neurologic illness. The scope of neurocritical care extends beyond the more commonly encountered and important field of cerebrovascular disease, as described previously. This article focuses on neuromuscular, neuroinfectious, and neuroimmunologic conditions that are significant causes of morbidity and mortality in the acutely neurologically ill patient. As understanding continues to increase regarding the physiology of these conditions and the best treatment, rapid identification, triage, and treatment of these patients in the emergency department is paramount.

Neuroimaging of infectious disease

This article provides an imaging overview of several of the common central nervous system (CNS) infections. Neurologic clinicians who provide acute care for patients should be familiar with the range of imaging findings for patients with acute neurologic infections, including knowledge of the appropriate study and the best protocol and views to show the disorder, and the ability to properly interpret them. This requirement applies particularly for CNS infections, as in stroke, in which a rapid appreciation of the exact cause of a patient's infection may play a major role in reducing mortality and morbidity.