Abraham Kim[email protected]CTQuality improvement effort slashes CT radiation doseA simple and cost-effective intervention led to reductions in CT radiation dose as high as 58% -- without a notable drop in image quality -- for a cohort of nearly 1 million individuals from 100 facilities across the globe in a new study. The findings were published online March 30 in JAMA Internal Medicine.March 29, 2020Advanced VisualizationAR, 3D printing set to improve cranial surgery outcomesResearchers from Brazil have developed a way to visualize and interact with patient-specific anatomy using augmented reality (AR) and 3D printing. They describe how the technique could improve preoperative planning for cranial surgery and patient outcomes in an article in the March issue of Neurosurgical Focus.March 26, 2020CTRSNA proposes standardized CT reporting for COVID-19CT is currently not recommended as a first-line diagnostic or screening tool for COVID-19, but its use to understand and manage the disease continues to grow. In response, the RSNA proposed standardized CT reporting language for COVID-19 in a special report posted on March 25 in Radiology: Cardiothoracic Imaging.March 26, 2020CTImaging confirms coronavirus transmits from mother to fetusThe combination of CT, x-ray, and DNA testing confirmed that the novel coronavirus was transmitted from pregnant women to nearly 10% of newborns in a new study, published online March 26 in JAMA Pediatrics. The findings underscore the need for strict infection control measures for this vulnerable population.March 25, 2020CTCT shows parallels between vaping lung injury, COVID-19COVID-19 and vaping-related lung injury share many features on CT, but the imaging modality's role in diagnosing the diseases has taken diverging paths, according to a March webinar hosted by the American Roentgen Ray Society.March 25, 2020CTCT depicts how COVID-19 abnormalities change over timeCT scans revealed rapid progression of abnormalities in COVID-19 patients, typically peaking on the 10th day from symptom onset, in a new study published March 19 in Radiology. The persistence of CT abnormalities through the final stages of disease underscores the need to monitor patients well after discharge.March 19, 2020CTCT details effect of COVID-19 on pregnant womenDoes COVID-19 have a more devastating effect on pregnant women? Is the disease passed down to newborns after birth? What's the best management strategy for this vulnerable population? Researchers from China addressed these and similar questions in a March 18 study published in the American Journal of Roentgenology.March 19, 2020CTWomen have more chest pain despite less stenosis on CCTAWomen with coronary artery disease are much more likely to have frequent chest pain than men, despite having less extensive disease on coronary CT angiography (CCTA) and less severe ischemia on stress imaging, according to a study.March 18, 2020CTReport: Medical radiation dose plummets 20%Radiation dose from medical imaging has fallen 20% over the past decade, according to a report from the U.S. National Council on Radiation Protection and Measurements (NCRP) that was published March 17 in Radiology.March 17, 2020CTACR recommends sparing use of CT for COVID-19CT should not be used as a first-line diagnostic or screening tool for the novel coronavirus disease (COVID-19), according to a March 11 statement by the American College of Radiology (ACR). The statement covers the appropriate use of chest x-ray and CT for the screening, diagnosis, and management of COVID-19.March 10, 2020Page 1 of 63Next PageTop StoriesWomens ImagingWomen's Imaging MinnieCast, Episode 8: New NCCN guidance on AI and breast cancer riskBethany Niell, MD, PhD, talks new guidance on breast cancer screening by the NCCN, which includes image-based AI risk assessment.Digital X-RayLLMs excel at scoliosis detection on spine x-raysHomeExpanding opportunities for interventional radiology practiceCTWelding fumes linked to distinct lung CT changes, functionSponsor ContentTurning Innovation into Everyday Efficiency
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)