Can Deep Learning Assessment of X-Rays Improve Triage of Patients with Acute Chest Pain?
In a study involving patients who presented to emergency departments with acute chest pain, a deep learning model demonstrated significantly improved prediction of aortic dissection and all-cause mortality and indicated that additional pulmonary and cardiovascular testing could be deferred in seven times as many patients as suggested by conventional risk factors and testing measures.
Nine Takeaways from New Article Examining Health Equity in the Radiology Field
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.
Viz.ai Launches AI-Powered Vascular Imaging Software
The artificial intelligence (AI)-enabled Viz™ Vascular Suite reportedly allows automated detection of vascular conditions, shown on computed tomography (CT) and other imaging modalities, and facilitates timely triage among interdisciplinary teams.
Enjoying Quiet Moments Amid the Boilerplate Blather in Radiology Reporting
January 16th 2023Acknowledging the repetitive reality that accompanies productivity incentives and seemingly extraneous verbiage to satisfy certain insurance requirements in radiology, this author has developed an appreciation for filler-free brevity and quiet.
Pie Medical Imaging Launches AI-Powered Echocardiography Platform
CAAS Qardia 2.0, an updated version of the CAAS Qardia echocardiography software platform, reportedly incorporates artificial intelligence (AI)-enabled workflows, and provides enhanced imaging and analysis of key cardiac measures.
Assessing the Value Proposition of AI in Radiology
In the second part of a recent interview, Nina Kottler, M.D., M.S., discussed keys to evaluating the potential value of artificial intelligence (AI) systems and emerging developments with AI that were discussed at the recent Radiological Society of North America (RSNA) conference.
Can Dual-Energy CT Have an Impact in Differentiating Primary Lung Cancer and Pulmonary Metastases?
In comparison to primary lung cancer, pulmonary metastases had a 33 percent higher frequency of ring-like peripheral high iodine concentration on dual-energy computed tomography (DECT), according to a new retrospective study.
While breast cancer imaging guidelines recommend annual screening for five years after treatment for ductal carcinoma in situ (DCIS), a new study of over 12,000 women found that only 52 percent had consistent surveillance screening with researchers noting disproportionately lower follow-up imaging rates for Black and Hispanic women.
Should Vertebral Fracture Assessment be Standard Prior to ADT Treatment for Prostate Cancer?
A new study found that approximately one-third of men with prostate cancer were diagnosed with at least one vertebral fracture prior to the initiation of androgen deprivation therapy (ADT).
Nine Takeaways from Recent Meta-Analysis on Lung Cancer Screening with Low-Dose CT
From incidental findings and screening for chronic obstructive pulmonary disease (COPD) to surveillance imaging protocols and the advent of artificial intelligence (AI), the authors of a new meta-analysis examine insights and emerging trends from the last two decades of research on the use of low-dose computed tomography (CT) in lung cancer screening.
What a New Study Reveals About Breast Density Awareness
January 6th 2023In a recent interview from the Radiological Society of North America (RSNA) conference, Mary Yamashita, M.D. discussed a variety of findings from a survey of over 8,000 women about breast density awareness, challenges with current breast density notification after mammography exams, and the ongoing need to educate patients as well as referring providers on breast density awareness.
Can Deep Learning Enhance Ultrasound Assessment of Hepatic Steatosis in Patients with NAFLD?
In a new prospective study, an emerging deep learning model, which incorporates parametric mapping with quantitative ultrasound to estimate liver fat fraction, demonstrated a 90 percent sensitivity rate and a 91 percent specificity rate for diagnosing hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD).
What a New Study Reveals About MRI and Predicting Muscle Injury Recurrence in Pro Athletes
In a study looking at acute muscle injuries in professional athletes, the use of magnetic resonance imaging (MRI) within a week prior to their return to play demonstrated significant re-injury risk with intermuscular edema, callus gap and transversal and/or mixed connective tissue gap.