Powered by deep learning technology, Sonic DL reportedly facilitates the acquisition of cardiac magnetic resonance imaging (MRI) scans at 12 times the speed of conventional MRI systems.
The Food and Drug Administration (FDA) has granted 510(k) clearance to Sonic DL (GE HealthCare), a deep learning software that may reinvent scan time expectations and possibly expand the eligibility of patients for cardiac magnetic resonance imaging (MRI).
GE HealthCare said Sonic DL can improve radiology workflow efficiency and alleviate backlogs with its ability to slash scan times for cardiac MRI by up to 83 percent. Emphasizing the capability of Sonic DL to facilitate real-time functional imaging “as fast as a single heartbeat,” the company noted the artificial intelligence (AI) technology was designed to allow the acquisition of MRI scans at 12 times the rate of conventional MRI.
The accelerated scanning may also allow broader patient access to cardiac MRI, according to Gianluca Pontone, M.D., Ph.D., F.E.S,C., the director of the Perioperative Cardiology Cardiovascular Imaging Department at Centro Cardiologico Monzino in Milano, Italy.
“Sonic DL emerges as a game-changer in the field of cardiac imaging. By capturing images within a single heartbeat, this cutting-edge technology addresses the unique needs of patients who face challenges in breath-holding, suffer from advanced heart failure, or have arrhythmias,” noted Dr. Pontone. “The significance of this capability cannot be overstated as it ensures a smoother and more comfortable experience for patients during MRI exams.”
(Editor’s note: For related content, see “FDA Clears AI Software That May Lead to 30-Minute Full-Body MRI Exams,” “Emerging AI Advances in Cardiac Imaging” and “Can Emerging AI-Guided Software Rein in Scan Times for Cardiac MRI?”)
Leading Breast Radiologists Discuss the USPSTF Breast Cancer Screening Recommendations
May 17th 2024In recognition of National Women’s Health Week, Dana Bonaminio, MD, Amy Patel, MD, and Stacy Smith-Foley, MD, shared their thoughts and perspectives on the recently updated breast cancer screening recommendations from the United States Preventive Services Task Force (USPSTF).
CT Study: AI Algorithm Comparable to Radiologists in Differentiating Small Renal Masses
May 14th 2024An emerging deep learning algorithm had a lower AUC and sensitivity than urological radiologists for differentiating between small renal masses on computed tomography (CT) scans but had a 21 percent higher sensitivity rate than non-urological radiologists, according to new research.
Current Insights and Emerging Roles for Contrast-Enhanced Mammography
May 10th 2024In a recent lecture at the 2024 ARRS Annual Meeting, Jordana Phillips, MD, discussed the role of contrast-enhanced mammography in staging breast cancer, evaluating response to neoadjuvant chemotherapy and recalls from screening.
ACR Collaborative Model Achieves 20 Percent Improvement in PI-QUAL Scores for Prostate MRI
May 9th 2024Using a learning network model to discuss challenges and share insights among radiology departments from five different organizations, researchers noted that 87 percent of audited prostate MRI exams had PI-QUAL scores > 4 at the conclusion of the collaborative program.