CT

The 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.

Preliminary 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.

In 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.

Derived 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.

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When you are asked about your occupation, how do you respond?

In a recent video interview, Sonia Gupta, MD discussed a number of ongoing developments with artificial intelligence (AI) in radiology, ranging from market consolidation of AI vendors to maximizing automation and efficiency with patient triage, reporting and follow-up of incidental findings.

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Approximately 43 percent of patients with COVID-19 and preexisting cancer presented with atypical or indeterminate findings on chest computed tomography (CT) scans.

In 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.

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Researchers showed that adjunctive use of a deep learning algorithm resulted in an eight percent increase in sensitivity and a nearly 10 percent increase in specificity for differentiating between colon carcinoma and acute diverticulitis on computed tomography (CT) scans.

When you’re asked to review an X-ray for a patient who already had follow-up imaging, do you consider the results of follow-up imaging or evaluate the X-ray with fresh eyes?

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Preliminary 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.

Employing 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.

Catch up on the top AI-related news and research of the past month.

Trained 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.

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Noting the significant administrative fees for the Independent Dispute Resolution (IDR) process of the No Surprises Act and onerous restrictions that have led to a nearly “non-existent” use of batching of disputed claims in radiology, the American College of Radiology (ACR) has sent formal recommendations to the United States Departments of Health and Human Services, Labor, and Treasury for addressing these issues.

In 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.

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The 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.

Catch up on the top radiology content of the past week.