Incomplete Subacute Transverse Myelitis Following Vaccination With Pfizer-BioNTech COVID-19 mRNA Vaccine: A Case Report.

In response to the coronavirus disease 2019 (COVID-19) pandemic, rapid development, clinical testing, and regulatory approval of vaccines occurred. The tozinameran COVID-19 vaccine is the first mRNA vaccine approved for use in humans. Transverse myelitis is a rare inflammatory disorder of the spinal cord that is associated with traditional vaccinations.

Hypoperfusion Intensity Ratio Correlates with CTA Collateral Status in Large-Vessel Occlusion Acute Ischemic Stroke.

Background And Purpose: Collateral blood supply is a key determinant of outcome in large-vessel occlusion acute ischemic stroke. Single- and multiphase CTA collateral scoring systems have been described but are subjective and require training. We aimed to test whether the CTP-derived hypoperfusion intensity ratio is associated with CTA collateral status and whether a threshold hypoperfusion intensity ratio exists that predicts poor CTA collaterals.

MRI-visible perivascular spaces as an imaging biomarker in Fabry disease.

Introduction: Fabry disease (FD) is an X-linked lysosomal storage disorder resulting in vascular glycosphingolipid accumulation and increased stroke risk. MRI findings associated with FD include white matter hyperintensities (WMH) and cerebral microbleeds (CMBs), suggesting the presence of cerebral small vessel disease. MRI-visible perivascular spaces (PVS) are another promising marker of small vessel disease associated with impaired interstitial fluid drainage.

Dural masses: meningiomas and their mimics.

Meningiomas are the most common dural tumour. They are regularly being seen as an incidental finding on brain imaging and treated conservatively. However, there are many other dural masses which mimic their appearances, including primary neoplastic processes, metastases, granulomatous diseases and infection.

An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification.

The availability of medical imaging data from clinical archives, research literature, and clinical manuals, coupled with recent advances in computer vision offer the opportunity for image-based diagnosis, teaching, and biomedical research. However, the content and semantics of an image can vary depending on its modality and as such the identification of image modality is an important preliminary step. The key challenge for automatically classifying the modality of a medical image is due to the visual characteristics of different modalities: some are visually distinct while others may have only subtle differences.