Catch up on the latest MRI studies, AI innovations, and expert insights on abbreviated breast MRI with our Weekly Scan.
We scan the top radiology sources so you don’t have to.
From AI breakthroughs to imaging trends, we serve up real-time radiology insights.
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Photon-Counting CT Study Examines Impact of Scan Mode on Radiation Dosing for CCTA in Patients with Non-Acute Chest Pain
The dose length product (DLP) for the flash mode on a dual-source photon-counting CT system was less than a third of that for the spiral mode, according to a study of CTA findings for 1,000 patients presented at the Society of Cardiovascular Computed Tomography (SCCT) conference.
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The Reading Room Podcast: Current and Emerging Insights on Abbreviated Breast MRI, Part 1
In the first of a multi-part podcast episode, Stamatia Destounis, MD, Emily Conant, MD and Habib Rahbar, MD, share their insights on the role of abbreviated breast MRI in breast screening.
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Adjunctive AI Bolsters Lesion-Level PPVs for csPCa in International bpMRI Study
The use of adjunctive bpMRI-based AI led to 10 percent and greater increases in lesion-level PPV for csPCa and PCa with a threshold of PI-RADS > 3.
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Emerging Concepts in CT-Guided Treatment of Coronary Artery Disease
In a recent interview, Amir Ahmadi, M.D., discussed limitations of conventional diagnostic assessments for people with suspected coronary artery disease, and the emergence of AI-enabled plaque quantification to facilitate more timely detection and intervention.
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FDA Clears Point-Of-Care Ultrasound Platform and AI Software for Neuraxial Procedures
The dual FDA clearances for the Accuro 3S point-of-care ultrasound device and the SpineNav-AI machine learning-based software may enhance precision and safety with ultrasound-guided neuraxial procedures.
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Stroke MRI Study Assesses Impact of Motion Artifacts Upon AI and Radiologist Lesion Detection
Noting a 7.4 percent incidence of motion artifacts on brain MRI scans for suspected stroke patients, the authors of a new study found that motion artifacts can reduce radiologist and AI accuracy for detecting hemorrhagic lesions.
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Meta-Analysis Examines MRI-Based AI for Predicting Microvascular Invasion in Hepatocellular Carcinoma
In external validation findings from a 29-study meta-analysis, MRI-based AI had a pooled AUC of 85 percent for preoperative prediction for microvascular invasion in patients with hepatocellular carcinoma.
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Explainable AI Model for Breast MRI Shows Effectiveness in High and Low Prevalence Breast Cancer Datasets
A fully convolutional data description (FCDD) model for identifying anomalies on breast MRI demonstrated an 84 percent AUC for detection tasks in a balanced cohort with a 20 percent malignancy prevalence and a 72 percent AUC for detection tasks in an imbalanced group with a 1.85 percent cancer prevalence.
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Radiology Partners Launches Enterprise Imaging Platform MosiacOS
A cloud-based and AI-native radiology operating system, MosiacOS reportedly enables the combination of diagnostic AI tools and workflow enhancements into one scalable platform.