Oncology CT

A hybrid computed tomography radiomics model demonstrated up to an 86 percent area under the curve in predicting microvascular invasion in patients with hepatocellular carcinoma in a recently published study.

While one computed tomography (CT) scan appears to have no elevated cancer risk in pediatric patients, four or more pediatric exposures to CT scans are associated with increased risks for intracranial tumor, leukemia, and non-Hodgkin lymphoma, according to newly published research out of Taiwan.

Lamenting a lack of control over imaging requests from referring clinicians, this author suggests that a more collaborative approach between referrers and radiologists may facilitate more efficient use of imaging.

An emerging artificial intelligence (AI) software reportedly detected liver metastases in 53.7 percent of cases involving missed findings by radiologists.

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New prospective research demonstrated that the combination of ultra-low-dose (ULD) computed tomography (CT) and an artificial intelligence (AI)-based denoising method offered a greater than 95 percent sensitivity rate for differentiating negative and actionable Lung-RADS category findings with significantly reduced radiation dosing.

A recent prospective study found that progression-free survival (PFS) and disease-specific survival (DSS) were significantly associated with breast cancer tumor treatment response on 2-(18F)FDG-PET/CT imaging in comparison to contrast-enhanced computed tomography (CT), which showed no evidence of a significant association with tumor response.

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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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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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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.

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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