HealthDay News - Multidetector CT more accurate than single-detector CT in diagnosing small cerebral aneurysms
HealthDay News - Computed tomographic (CT) angiography, especially by modern multidetector CT, is a highly accurate tool for diagnosing cerebral aneurysms, according to a meta-analysis published online March 9 in the Annals of Neurology.
Jan Menke, MD, from the University Hospital in Goettingen, Germany, and colleagues examined data from 45 studies, including 3,643 patients with cerebral aneurysms, to evaluate noninvasive CT angiography in diagnosing intracranial aneurysms. The accuracy of CT angiography was compared with digital subtraction angiography and/or intraoperative findings in patients suspected of having cerebral aneurysms.
The investigators found that 77 percent of patients had cerebral aneurysms and 86 percent had nontraumatic subarachnoid hemorrhage. On a per-patient basis, the pooled sensitivity of CT angiography for detecting cerebral aneurysms was 97.2 percent, and specificity for ruling out cerebral aneurysms was 97.9 percent. On a per-aneurysm basis, the sensitivity and specificity were 95.0 and 96.2 percent, respectively. CT angiography with multidetector CT (16- or 64-row) had a significantly higher diagnostic accuracy than that of single-detector CT, especially in case of small aneurysms (diameter of 4 mm or less).
"CT angiography has a high accuracy in diagnosing cerebral aneurysms, specifically when using modern multidetector CT," the authors write.
AbstractFull Text (subscription or payment may be required)
Copyright © 2011 HealthDay. All rights reserved.
What is the Best Use of AI in CT Lung Cancer Screening?
April 18th 2025In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
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.
Can CT-Based AI Radiomics Enhance Prediction of Recurrence-Free Survival for Non-Metastatic ccRCC?
April 14th 2025In comparison to a model based on clinicopathological risk factors, a CT radiomics-based machine learning model offered greater than a 10 percent higher AUC for predicting five-year recurrence-free survival in patients with non-metastatic clear cell renal cell carcinoma (ccRCC).
Could Lymph Node Distribution Patterns on CT Improve Staging for Colon Cancer?
April 11th 2025For patients with microsatellite instability-high colon cancer, distribution-based clinical lymph node staging (dCN) with computed tomography (CT) offered nearly double the accuracy rate of clinical lymph node staging in a recent study.