Use of CT/CT angiography, often more readily available than MRI, after a transient ischemic attack or minor stroke predicts risk of recurrent stroke and clinical outcome.
Use of CT/CT angiography (CTA) as soon as possible in patients presenting with transient ischemic attacks (TIA) or minor stroke predicts risk of recurrent stroke and clinical outcome, according to a study published online in Stroke: Journal of the American Heart Association.
Although MRIs are frequently used for early assessment, CT scanners are usually more readily available to the emergency department, said the study authors. The median waiting time for diffusion-weighted MRI was 17.5 hours, but for CTA imaging, the wait was only 5.5 hours. In addition, CTA does not take much time, adding only five minutes to the standard CT brain scan.
It is estimated that there is a 10 percent risk of recurrent stroke within 90 days of a patient experiencing a TIA or minor stroke, with the majority recurrent strokes occurring within 48 hours of TIA or mild stroke onset. CTA, which uses contrast media to image the vasculature, can identify large artery disease, allowing physicians to determine risk. “A symptomatic intracranial or extracranial severe arterial stenosis or occlusion was predictive of recurrent stroke,” wrote the authors.
In the study, 491 patients with either TIA or minor stroke underwent CT/CTA within 24 hours of onset and most had subsequent MRI. Results showed there were 36 recurrent strokes, with a median time to the event of one day, and a positive CT/CTA scan was a predictor of recurrent stroke.
The authors concluded, “Adoption of CT/CTA into clinical practice for the assessment of patients with TIA and minor stroke identifies a high risk group suitable for aggressive acute stroke prevention treatment.”
Can Radiomics Enhance Differentiation of Intracranial Aneurysms on Computed Tomography Angiography?
September 17th 2024Radiomics models offered a pooled AUC of 86 percent for differentiating between ruptured and unruptured intracranial aneurysms, according to a recently published meta-analysis.
The Reading Room: Racial and Ethnic Minorities, Cancer Screenings, and COVID-19
November 3rd 2020In this podcast episode, Dr. Shalom Kalnicki, from Montefiore and Albert Einstein College of Medicine, discusses the disparities minority patients face with cancer screenings and what can be done to increase access during the pandemic.
Study Assesses Lung CT-Based AI Models for Predicting Interstitial Lung Abnormality
September 6th 2024A machine-learning-based model demonstrated an 87 percent area under the curve and a 90 percent specificity rate for predicting interstitial lung abnormality on CT scans, according to new research.