The AI-enabled software Rayvolve reportedly demonstrated a 96 percent sensitivity rate for diagnosing pediatric fractures in a recent study involving 3,000 patients.
The Food and Drug Administration (FDA) has granted an expanded (510)k clearance for the artificial intelligence (AI)-powered software Rayvolve for the detection of pediatric fractures.1
Noting a recent study examining the use of Rayvolve for diagnosing pediatric fractures on X-rays, AZMed, the manufacturer of Rayvolve, said the AI platform had a 96 percent sensitivity rate, 86 percent specificity and a 94 percent area under the curve (AUC).1
The Rayvolve software previously garnered FDA clearance for adult fracture detection on radiographs. At the 2023 RSNA conference, researchers found that Rayvolve could facilitate a sixfold reduction in turnaround time from image acquisition to the final radiology report.2
"The 510(k) clearance reflects our commitment to meeting the needs of health-care professionals," said Julien Vidal, the CEO of AZmed. "We are excited to extend our innovation to pediatric care, empowering clinicians with advanced tools to achieve the best outcomes for their patients."
References
1. AZMed. AZMed secures FDA 510(k) clearance for Rayvolve in pediatric fracture detection through study with SimonMed Imaging, expanding its AI-powered medical imaging solutions. PR Newswire. Available at: https://www.prnewswire.com/news-releases/azmed-secures-fda-510k-clearance-for-rayvolve-in-pediatric-fracture-detection-through-study-with-simonmed-imaging-expanding-its-ai-powered-medical-imaging-solutions-302236044.html . Published September 3, 2024. Accessed September 3, 2024.
2. Hall J. AI facilitates nearly 83 percent improvement in turnaround time for fracture X-rays. Available at: https://www.diagnosticimaging.com/view/ai-nearly-83-percent-improvement-turnaround-time-fracture-x-rays . Published December 19, 2023. Accessed September 3, 2024.
Multicenter Study Shows Merits of AI-Powered Ultrasound Assessment for Detecting Ovarian Cancer
January 3rd 2025Adjunctive AI offered greater than seven percent increases in sensitivity, specificity, and accuracy for ultrasound detection of ovarian cancer in comparison to unassisted clinicians who lacked ultrasound expertise, according to findings from new international multicenter research.
Study Examines Impact of Deep Learning on Fast MRI Protocols for Knee Pain
December 17th 2024Ten-minute and five-minute knee MRI exams with compressed sequences facilitated by deep learning offered nearly equivalent sensitivity and specificity as an 18-minute conventional MRI knee exam, according to research presented recently at the RSNA conference.
Can AI Facilitate Single-Phase CT Acquisition for COPD Diagnosis and Staging?
December 12th 2024The authors of a new study found that deep learning assessment of single-phase CT scans provides comparable within-one stage accuracies to multiphase CT for detecting and staging chronic obstructive pulmonary disease (COPD).