Here's what to expect this week on Diagnostic Imaging.
In this week’s preview, here are some highlights of what you can expect to see coming soon:
Imaging plays a key role in oncology care, but, to date, it has been relegated to diagnosis and detection. However, providers are actively investigating how artificial intelligence can augment the impact imaging can have. Recent work is looking not only at screening and detection, but also diagnosis and risk stratification, tumor segmentation, precision oncology, and prognosis prediction and treatment assessment. Look for an article this week based on findings published in Clinical Radiology.
For more coverage of oncology imaging, click here.
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Peer review has been widely used as a tactic for identifying diagnostic errors and opportunities for improvement. However, it has fallen short of its goal of helping radiologists learn from mistakes. Consequently, the specialty is shifting toward peer learning – a strategy that allows for anonymous critique of diagnostic oversights and gives providers guidance to avoid future errors. This week, look for an interview with Regan City, director of National Sub-speciality Divisions and Patient Safety Organization with RadPartners, about how facilities and institutions can implement their own peer learning models.
For additional articles on RadPartners, click here.
Molecular imaging is becoming more important in differentiating between active joint inflammation and chronic joint damage seen in patients with rheumatic disorders. These advancements can, potentially, impact how providers evaluate treatment responses. Keep an eye open for an article later this week based on findings from the European Journal of Radiology on what’s coming with CT and MRI in musculoskeletal imaging.
For other articles on musculoskeletal imaging, click here.
The Reading Room Podcast: Emerging Trends in the Radiology Workforce
February 11th 2022Richard Duszak, MD, and Mina Makary, MD, discuss a number of issues, ranging from demographic trends and NPRPs to physician burnout and medical student recruitment, that figure to impact the radiology workforce now and in the near future.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.
Study Shows Merits of CTA-Derived Quantitative Flow Ratio in Predicting MACE
December 11th 2024For patients with suspected or known coronary artery disease (CAD) without percutaneous coronary intervention (PCI), researchers found that those with a normal CTA-derived quantitative flow ratio (CT-QFR) had a 22 percent higher MACE-free survival rate.