Study Reveals Benefits of Photon-Counting CT for Assessing Acute Pulmonary Embolism
In comparison to energy-integrating detector CT for the workup of suspected acute pulmonary embolism, the use of photon-counting detector CT reduced radiation dosing by 48 percent, according to newly published research.
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.