CT Scan Identifies Risk for COPD Exacerbation
CT imaging can identify pulmonary artery enlargement, which is associated with exacerbation of chronic obstructive pulmonary disease (COPD).
CT imaging can identify pulmonary artery enlargement, which is associated with exacerbation of chronic obstructive pulmonary disease (COPD), according to a study published in the most recent issue of New England Journal of Medicine.
Researchers assessed the use of CT imaging to determine the ratio of the diameter of the pulmonary artery to the diameter of the aorta, with the hypothesis that a PA:A ratio of more than 1 would be associated with severe COPD exacerbations.
The 3,464 participating patients were 45 to 80 years old and current or former smokers, with a history of 10 pack-years or more of cigarette smoking. Volumetric CT scans of the chest were obtained without contrast material.
Findings showed “a significant association between a PA:A ratio >1 and a history of severe COPD exacerbations at the time of enrollment in the trial,” wrote the authors. Fifty-three percent of patients with a PA:A ratio of more than 1 reported a severe COPD exacerbation in the year before enrollment into the study, compared with 13 percent with a PA:A ratio of 1 or less who experienced exacerbations. Many of the exacerbations required hospitalization.
This ratio was also independently associated with an increased risk of future severe exacerbations in both the trial cohort and the external validation cohort, the authors noted.
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.
