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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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Diagnostic Imaging's Weekly Scan: April 13 — April 19
Catch up on the top radiology content of the past week.
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Nine Takeaways from New Research on CT Scans and Radiation-Induced Cancers
Recently published research projected that 103,000 future cases of radiation-induced cancer would result from 93 million computed tomography (CT) exams performed in the United States in 2023.
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What is the Best Use of AI in CT Lung Cancer Screening?
In comparison to radiologist assessment, the use of AI to pre-screen patients with low-dose CT lung cancer screening provided a 12 percent reduction in mean interpretation time with a slight increase in specificity and a slight decrease in the recall rate, according to new research.
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FDA Clears Emerging Digital Tomosynthesis System
The Nanox.ARC X system reportedly provides enhanced 3D imaging for a variety of indications, ranging from pulmonary imaging and intra-abdominal views to musculoskeletal assessment.
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Recent Mammography Screening in Seniors Associated with 54 Percent Lower Risk of Later-Stage Diagnosis
Seniors who had at least one prior screening mammography exam in the five years prior to breast cancer diagnosis were over a third less likely to die from breast cancer, according to new research.
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Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque
Artificial intelligence demonstrated higher AUC, sensitivity, and specificity than radiologists for detecting coronary artery stenosis > 50 percent on computed tomography angiography (CTA), according to a new 17-study meta-analysis.
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FDA Expands Clearance for AI Mammography Software for Breast Arterial Calcification Detection
The additional FDA 510(k) clearance for the AI-powered cmAngio platform covers use of the software for GE HealthCare mammography systems.
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Breast MRI Quantification of Intra-Tumoral Heterogeneity May Help Predict Response to Neoadjuvant Chemotherapy
An emerging nomogram model for intra-tumoral heterogeneity quantification with breast MRI demonstrated an average 85 percent sensitivity in external validation testing for predicting pathologic complete response to neoadjuvant chemotherapy for breast cancer.
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New bpMRI Study Suggests AI Offers Comparable Results to Radiologists for PCa Detection
Demonstrating no significant difference with radiologist detection of clinically significant prostate cancer (csPCa), a biparametric MRI-based AI model provided an 88.4 percent sensitivity rate in a recent study.