Computed Tomography

Computed tomography (CT) is a fast and accurate imaging modality often used in emergency settings and trauma imaging. CT scans, with or without (or both) iodinated contrast are frequently used to image the brain, chest, abdomen and pelvis, but also have post-imaging reconstructive capabilities for detailed orthopedic imaging. It is now a standard imaging modality in emergency rooms to quickly assess patients. CT uses a series of X-ray images shot as the gantry rotates around the patient. Computer technology assembles these into into a dataset volume than can be slices on any access, or advanced visualization software can extract specific parts of the anatomy for study. Find more content specific to cardiac CT.

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Radiologists utilize novel CAD-RADS in 95% of coronary CTA reports

Massachusetts General Hospital doctors analyzed Coronary Artery Disease Reporting and Data System usage in their high-volume cardiac CT services center for the study.

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Hybrid imaging detects results missed by CT in patients with deadly pancreatic cancer

German researchers used 68Ga-FAPI PET/CT imaging to analyze 19 patients with pancreatic ductal adenocarcinomas.

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Why radiologists must carefully evaluate patient heart rates prior to coronary CTA exams

The number of CCTA exams is set to grow alongside an aging population and providers are key to ensuring these tests are high-quality.

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AI powers dual CT screening for lung cancer and cardiovascular disease

Rensselaer Polytechnic Institute teamed up with clinicians at Massachusetts General Hospital to develop and test the deep learning tool.

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CT data shows high rates of emphysema among marijuana users

Radiologists should take note of these findings as the drug's popularity and legalization continue to climb.

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Mobile stroke units improve patient outcomes, reduce risk of disability

Researchers tracked data from more than 1,000 patients who received care from 2014 to 2020. 

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New pulmonary embolism approach could substantially reduce imaging overuse

The pretest probability score produced false-negative rates below 1% and dropped imaging use by about 20%, according to a new JAMA Cardiology study. 

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AI spots dozens of missed incidental pulmonary embolism diagnoses at one hospital

The investigation was retrospective, but Duke scientists believe their algorithm could potentially aid radiologists in spotting near-misses in their work.