SCOTTSDALE, Ariz., Dec. 12th, 2024 – SimonMed Imaging (“SimonMed”), one of the largest outpatient medical imaging providers and radiology practices in the United States, recently revealed two new study datasets at the 2024 Radiological Society of North America’s Radiology (RSNA) Conference and Annual meeting. The studies both consist of artificial intelligence models in fracture detection in both geriatric and pediatric patients to improve detection by reducing turnaround time and enhancing radiologist reader performance.
The first study evaluated the effectiveness of implementing an enterprisewide artificial intelligence (AI) system for fracture detection from radiographs across SimonMed’s 200 imaging centers. SimonMed’s goal was to assess the impact of AI-powered worklist prioritization on reducing turnaround time. 26,690 MSK (musculoskeletal) radiographs detecting fractures were assessed, ultimately finding that 10.6% were detected during the pre-AI period and 14.7% during the post-AI period, ultimately shortening turnaround time while improving quality.
“The integration of AI into fracture detection at SimonMed showcases the transition of innovative technology from concept to real-world application,” said Dr. Sean Raj, Chief Innovation Officer and study Principal Investigator. “These studies demonstrate how AI-powered tools not only enhance detection accuracy but also streamline workflows, leading to faster and more reliable patient care. At SimonMed, we remain dedicated to turning cutting-edge ideas into practical solutions that improve outcomes for patients of all ages, from children to seniors.”
The second study focuses on pediatric fracture detection and assessing the efficacy of AI models and their impact on performance purposes. This study evaluated two implication phases of AI models amongst 3,016 pediatric radiographs and 189 cases, overall finding that the AI model incorporated into pediatric fracture tests exhibited high accuracy in detecting fractures, and its integration significantly enhanced reader performance.
“At SimonMed Imaging, our mission is to provide diagnostic advancements that enhance patient care. The integration of AI in fracture detection represents a transformative leap forward, allowing faster and more accurate diagnoses. By using this technology, we can deliver earlier interventions, reduce errors, and improve outcomes, providing our patients with the highest standard of care.” said Dr. John Simon, CEO and Founder of SimonMed Imaging.
While both of these studies exhibit AI assistance in bone fraction detection in patients, allowing for quicker turnaround time, and enhancing radiologists’ reader performance, SimonMed’s team continues to work to incorporate the highest technology and use it as a reliable tool for detecting fractures in pediatric patients in a real-world clinical setting, overall bettering patient care and trust.