Transcranial Doppler (TCD) is a noninvasive ultrasound (US) study used to measure cerebral blood flow velocity (CBF-V) in the major intracranial arteries. It involves use of low-frequency (≤2 MHz) US waves to insonate the basal cerebral arteries through relatively thin bone windows. TCD allows dynamic monitoring of CBF-V and vessel pulsatility, with a high temporal resolution. It is relatively inexpensive, repeatable, and portable. However, the performance of TCD is highly operator dependent and can be difficult, with approximately 10–20% of patients having inadequate transtemporal acoustic windows. Current applications of TCD include vasospasm in sickle cell disease, subarachnoid haemorrhage (SAH), and intra- and extracranial arterial stenosis and occlusion. TCD is also used in brain stem death, head injury, raised intracranial pressure (ICP), intraoperative monitoring, cerebral microembolism, and autoregulatory testing.

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A 72-year-old male presented with progressive right axial proptosis and red eye. Catheter angiography demonstrated an intraorbital arteriovenous fistula (IAVF) distal to the central retinal artery (CRA). Transvenous embolisation following direct surgical exposure of the superior ophthalmic vein (SOV) resulted in rapid resolution of his symptoms and signs. Transvenous embolisation via the SOV is a safe, effective alternative to transarterial embolisation for treating spontaneous IAVF where transarterial embolisation poses a risk of CRA occlusion.

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Abstract. We describe a fully-automated system for analysing X-rays of the wrist to identify possible fractures. Fractures of the distal radius in the wrist are estimated to be about 18% of the fractures seen in adults and 25% of those seen in children. Unfortunately such fractures are amongst the most frequently missed by doctors in Emergency Departments (EDs). A system which can identify suspicious areas could reduce the number of misdiagnoses. We automatically locate the outline of the radius in both posteroanterior (PA) and lateral (LAT) radiographs, then use shape and texture features to classify abnormalities. We show for the first time that fractures can be better identified in the lateral view, and that combining information from both views leads to an overall improvement in performance.