May 3rd 2024
A computed tomography (CT)-based radiomics model that includes 28 radiomic features showed significantly higher accuracy, sensitivity, and specificity than conventional CT in differentiating benign and malignant thyroid nodules, according to newly published research.
How Accurate is the CT Severity Score for Predicting COVID-19 Severity?
February 17th 2023The computed tomography severity score (CTSS) has sensitivity rates of 85 percent for predicting the severity of COVID-19 and 77 percent for predicting COVID-19 related mortality, according to a newly published meta-analysis.
Could Photon Counting CT Supplant MRI for Imaging Assessment of Hepatic Steatosis?
February 16th 2023Preliminary research suggests no significant differences between photon-counting computed tomography (CT) and magnetic resonance imaging (MRI) in the quantification of liver fat fraction in obese patients.
CT Study Reveals Persistent Lung Abnormalities Two Years After COVID-19
February 15th 2023In their review of follow-up chest computed tomography (CT) scans, researchers from Wuhan, China found that nearly 40 percent of patients had interstitial lung abnormalities two years after having COVID-19.
Can an Emerging Radiomics Model Improve CT Angiography Assessment of Heart Attack Risk?
February 14th 2023Derived from coronary computed tomography angiography (CCTA) images, a radiomics model demonstrated a 75 percent or greater area under the curve (AUC) in multiple test sets for identifying vulnerable plaque.
Study: AI More Than Doubles the Sensitivity Rate for Lung-RADS Category 4 Nodules on Chest X-Rays
February 7th 2023In newly published research, researchers found that an artificial intelligence (AI) computer-aided detection (CAD) system was more than twice as likely as non-AI assessment to diagnose actionable lung nodules on chest X-rays.
Could Photon Counting Reduce Iodinated Contrast Media for CT Angiography?
January 27th 2023Preliminary research suggests the use of photon-counting detector computed tomography (CT) may facilitate a 25 percent reduction of iodinated contrast media (ICM) in comparison to energy-integrating detector CT for angiographic imaging of the thoracoabdominal aorta.
Could an Emerging Deep Learning Modality Enhance CCTA Assessment of Coronary Artery Disease?
January 26th 2023Employing deep learning capabilities, the DeepVessel FFR reportedly provides enhanced non-invasive evaluation of coronary arteries through semi-automated analysis of coronary computed tomography angiography (CCTA) imaging.
Deep Learning Model May Predict Lung Cancer Risk from a Single CT Scan
January 23rd 2023Trained and developed on over 35,000 low-dose computed tomography (LDCT) scans and validated in three independent data sets, a deep learning algorithm demonstrated an average area under the curve (AUC) of 90.6 percent for predicting lung cancer within one year.
Nine Takeaways from New Article Examining Health Equity in the Radiology Field
January 17th 2023In a provocative new article, radiology researchers discuss the impact of social determinants of health (SDoH) upon access to care and patient outcomes, and present strategies within the realms of radiology education, research, clinical care, and innovation that may help mitigate health-care disparities.
Viz.ai Launches AI-Powered Vascular Imaging Software
January 16th 2023The artificial intelligence (AI)-enabled Viz™ Vascular Suite reportedly allows automated detection of vascular conditions, shown on computed tomography (CT) and other imaging modalities, and facilitates timely triage among interdisciplinary teams.
Can Dual-Energy CT Have an Impact in Differentiating Primary Lung Cancer and Pulmonary Metastases?
January 12th 2023In comparison to primary lung cancer, pulmonary metastases had a 33 percent higher frequency of ring-like peripheral high iodine concentration on dual-energy computed tomography (DECT), according to a new retrospective study.
Nine Takeaways from Recent Meta-Analysis on Lung Cancer Screening with Low-Dose CT
January 9th 2023From incidental findings and screening for chronic obstructive pulmonary disease (COPD) to surveillance imaging protocols and the advent of artificial intelligence (AI), the authors of a new meta-analysis examine insights and emerging trends from the last two decades of research on the use of low-dose computed tomography (CT) in lung cancer screening.
Study Shows Merits of Photon-Counting CT in Detecting Subtle Post-COVID Lung Abnormalities
December 22nd 2022In a recently published prospective study comparing photon-counting detector computed tomography (PCD CT) versus energy-integrating detector CT (EID CT) in patients with persistent symptoms after COVID-19 infection, researchers found that PCD CT discovered additional lung abnormalities in half of the study participants.