Dear AuntMinnie Member,
A key trend in medical imaging these days is using incidental CT data to diagnose and track disease. In this first 2025 edition of our CT Insider, we're covering a study that suggests that body composition information culled from routine CT imaging can help clinicians diagnose, develop treatment, and predict outcomes of metastatic non-small cell lung cancer. Click here for the full story.
Once you've read that article, navigate over to our CT content area for more reporting on the modality, including three articles that showcase the use of AI in CT imaging: one that explores the use of deep learning with CT to predict decompensation in patients with primary sclerosing cholangitis, another that describes how AI can improve the diagnosis of pulmonary embolism, and a third that outlines the use of AI with one-inhale CT for diagnosis of chronic obstructive pulmonary disease.
Don't miss our article on how measuring fatty tissue on chest CT can help predict esophageal cancer outcomes and our coverage of a study that suggests that clinical decision support can improve the diagnostic yield of pulmonary embolism on CT pulmonary angiogram exams.
You'll also want to read our coverage of the following studies:
- CT-defined coronary artery calcification scores help predict cardiovascular events in lung cancer patients.
- Head CT offers new insights into old strokes.
- Climate change seems to be boosting emergency department use of CT imaging.
It's our pleasure to provide AuntMinnie.com readers with up-to-date coverage of CT's many capabilities in our CT content area. If you have CT-related topics you'd like us to consider, please contact me.
Kate Madden Yee
Senior Editor
AuntMinnie.com
