Oncology CT

A retrospective review of insurance claim data from over one million people eligible for lung cancer screening with low-dose computed tomography (LDCT) found that less than five percent were screened.

In a study of over 1,000 patients who had surgery for invasive lung adenocarcinoma, researchers found that solid adenocarcinoma on pre-op CT imaging was associated with more than double the risks of recurrence and brain metastasis in patients with clinical stage I disease in comparison to ground-glass opacity (GGO) adenocarcinoma.

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Noting that computed tomography (CT) scans are obtained for more than 30 million emergency department (ED) patients annually and that 31.3 percent of ED CT scans reveal incidental findings, representatives from the American College of Radiology (ACR) and the American College of Emergency Physicians (ACEP) recently collaborated on best practice recommendations for addressing incidental imaging findings in EDs.

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The new launches include the 80/160-slice computed tomography (CT) scanner Aquilion Serve, which allows simultaneous previews of axial, lateral and AP views, and Celex, a multipurpose X-ray system that offers automated and customizable features to help maximize workflow efficiencies.

New research from the American Cancer Society comparing pre-pandemic cancer screening prevalence to the second year of the COVID-19 pandemic in the United States showed a 1.1 million decrease in breast cancer screenings, a 4.4 million decrease in cervical cancer screening and a 600,000 decrease in prostate cancer screenings.

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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.

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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.

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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.

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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In 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.

From 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.

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