GE HealthCare Gets FDA Clearance for AI-Powered MRI
GE HealthCare has received FDA clearance for its next-generation SIGNA MRI systems, which feature an integrated AI workflow ecosystem to automate tasks and reduce scan times. Social media discussions highlighted how similar AI reconstruction technology is cutting some MRI scan times by nearly half, alongside separate clearance for a next-gen portable bedside brain MRI system.
- The FDA clearance includes three main components: the SIGNA Sprint with Freelium (a 1.5T system), the SIGNA Bolt (a 3T system), and SIGNA One, the AI-powered workflow platform that drives both scanners. The SIGNA Sprint with Freelium is a sealed magnet system that uses less than 1% of the helium compared to conventional magnets, a key feature for mobile imaging and sites with siting constraints. - The AI-driven workflow of SIGNA One automates several steps of the imaging process, including patient setup through AI-enabled landmark localization and verification, which can help reduce training time and variability between technologists. This automation is a direct response to challenges like workforce burnout and rising demand for imaging procedures. - GE HealthCare's deep learning technology, Sonic DL, which is integrated into the new systems, has been shown in other applications to reduce cardiac MRI scan times by as much as 83% and can acquire images up to 12 times faster than conventional methods. This allows for capturing images in a single heartbeat, which is particularly beneficial for patients who have difficulty holding their breath. - This clearance comes as the U.S. outpatient imaging market continues to grow, now accounting for 47% of the total radiology IT market spend and projected to be over 50% by 2028. This shift is driven by the cost-effectiveness and convenience of freestanding imaging centers. Projections indicate a 14% growth in advanced outpatient imaging over the next decade. - The mobile medical imaging services market is forecasted to grow from $16.63 billion in 2025 to $21.13 billion by 2031. North America holds the largest market share at over 40%. The competitive landscape is moderately fragmented, with regional specialists competing with national networks and a trend of vertical integration, such as RadNet's acquisition of AI vendor iCAD. - Reimbursement policies continue to influence the shift to outpatient settings, with ongoing pushes for site-neutral payments that would equalize reimbursement between hospital outpatient departments and freestanding imaging centers. The 2026 Hospital Outpatient Prospective Payment System (HOPPS) final rule included a 2.6% increase to the conversion factor but also saw a 57% reimbursement reduction for a specific SPECT scan code, frustrating some industry advocates. - For radiology departments, AI and machine learning are key strategies for improving workflow and productivity, a top priority for hospitals. AI tools help mitigate staffing shortages and improve consistency by automating tasks like patient positioning, which can reduce setup time and the need for repeat scans. - Major competitors like Siemens Healthineers and Philips are also heavily investing in AI. Siemens has its AI-Rad Companion platform, while GE HealthCare's strategy centers on its Edison platform and collaborations with companies like NVIDIA and AWS to expand its AI ecosystem. In 2023, 50% of sites planning to purchase a new MRI were considering GE HealthCare, just behind Siemens at 53%.
