CT

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

Catch up on the top AI-related news and research in radiology over the past month.

Facilitating expedited assessment of pulmonary embolism severity, the emerging artificial intelligence (AI) tool Rapid RV/LV reportedly calculates the right ventricle/left ventricle (RV/LV) ratio within minutes of a computed tomography pulmonary angiogram (CTPA).

Noting that only 25 percent of incidental emboli are identified in reporting of initial computed tomography (CT) exams, Avicenna.AI said the artificial intelligence (AI)-enabled CINA-iPE is geared toward detecting incidental pulmonary embolism (PE) on chest CT scans.

Noting that pelvic coverage can increase radiation dosing for liver computed tomography (CT) by 29 to 39 percent, researchers found low three-year cumulative rates of incidental pelvic tumors and isolated pelvic metastasis in follow-up liver CT imaging of over 1,100 people treated for hepatocellular carcinoma.

Review the case study and test your knowledge to make the correct diagnosis.

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

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.

Review the case study and test your knowledge to make the correct diagnosis.

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.

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

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.

Review the case study and test your knowledge to make the correct diagnosis.

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

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?

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

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.