Non-invasive CT angiography effectively detects cerebral aneurysms and should be considered for first-line imaging.
CT angiography should be the first-line imaging technique for the noninvasive evaluation of aneurysms, according to a study published in the journal Radiology.
Researchers from China undertook a study to assess the accuracy of 320-detector row CT angiography for detection of cerebral aneurysms compared with 3D digital subtraction angiography (DSA). A total of 282 patients (138 men, 144 women) were assessed.
Mean age was 58 years. The patients underwent CT angiography with 320-detector row volumetric CT scanner and 3D rotational DSA. The researchers evaluated sensitivity, specificity, and accuracy of nonsubtracted and subtracted volumetric CT angiography for depiction of aneurysms.
Results showed that 3D DAS detected 239 cerebral aneurysms among 198 patients. The CT angiography showed 231 of the aneurysms (96.7 percent). The researchers noted that aneurysms that were missed were generally proximal to bone tissue. Sensitivity, specificity, and accuracy of subtracted volumetric CT angiography for depicting aneurysms were 99.2 percent, 100 percent, and 99.4 percent, respectively, on a per-aneurysm basis.
“Subtracted 320–detector row volumetric CT angiography provides excellent sensitivity for detection of cerebral aneurysms and should be the first-line imaging technique for the noninvasive evaluation of aneurysms,” the authors wrote.
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.