Could a Newly FDA-Cleared C-Arm Device Bolster Efficiency for Interventional Radiologists?
In addition to advanced imaging quality and dose efficiency, the Philips Zenition 30 mobile C-arm device emphasizes personalized user profiles and automated customization to help reduce procedure time.
New AI-Powered Ultrasound Devices May Enhance Efficiency in Women's Imaging
One of the features on the new Voluson Signature 20 and 18 ultrasound devices reportedly uses automated AI tools to facilitate a 40 percent reduction in the time it takes to perform second trimester exams.
New Literature Review Assesses Merits of Cardiac MRI After Survival of Sudden Cardiac Arrest
While noting inconsistencies with the diagnostic yield of cardiac MRI in patients who survived sudden cardiac arrest, researchers cited unique advantages in characterizing ischemic cardiomyopathy (ICM) and facilitating alternate diagnoses.
FDA Approves Fluorescence Imaging System for Detecting Residual Breast Cancer
The combination of the optical imaging agent Lumisight and the fluorescence imaging device Lumicell Direct Visualization System, collectively known as LumiSystem, reportedly offers 84 percent accuracy with real-time detection of residual breast cancer after lumpectomy procedures.
Study of Ofatumumab for Multiple Sclerosis Shows 'Profoundly Suppressed MRI Lesion Activity'
The use of continuous ofatumumab in patients within three years of a relapsing multiple sclerosis diagnosis led to substantial reductions in associated lesions on brain MRI scans, according to research recently presented at the American Academy of Neurology (AAN) conference.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
MRI-Based AI Model Shows Promise in Predicting Lymph Node Metastasis with Breast Cancer
For the prediction of axillary lymph node metastasis in patients with breast cancer, an MRI-based, 4D convolutional neural network model demonstrated an AUC of 87 percent and sensitivity of 89 percent, according to new research.
Improving the Quality of Breast MRI Acquisition and Processing
Discussing findings from a new study presented at the Society for Breast Imaging (SBI) conference, Shahrzad Tavana, M.D., detailed the significant impact of training sessions for MRI technologists in improving breast positioning, optimal field of view and accuracy of sequence submissions to PACS for breast MRI exams.
AI Adjudication Bolsters Chest CT Assessment of Lung Adenocarcinoma
The inclusion of simulated adjudication for resolving discordant nodule classifications in a deep learning model for assessing lung adenocarcinoma on chest CT resulted in a 12 percent increase in sensitivity rate.
New Research Examines Socioeconomic Factors with Mammography No-Shows
Patients with Medicaid or means-tested insurance were over 27 percent more likely to miss mammography appointments, and only 65 percent of women with three of more adverse social determinants of health had a mammography exam in a two-year period covering 2020 and 2021, according to new research and a report from the CDC.