U.S. Food and Drug Administration05.25.18
Today, the U.S. Food and Drug Administration permitted marketing of Imagen OsteoDetect, a type of computer-aided detection and diagnosis software designed to detect wrist fractures in adult patients.
“Artificial intelligence algorithms have tremendous potential to help health care providers diagnose and treat medical conditions,” said Robert Ochs, Ph.D., acting deputy director for radiological health, Office of In Vitro Diagnostics and Radiological Health in the FDA’s Center for Devices and Radiological Health. “This software can help providers detect wrist fractures more quickly and aid in the diagnosis of fractures.”
The OsteoDetect software is a computer-aided detection and diagnostic software that uses an artificial intelligence algorithm to analyze two-dimensional X-ray images for signs of distal radius fracture, a common type of wrist fracture. The software marks the location of the fracture on the image to aid the provider in detection and diagnosis.
OsteoDetect analyzes wrist radiographs using machine learning techniques to identify and highlight regions of distal radius fracture during the review of posterior-anterior (front and back) and medial-lateral (sides) X-ray images of adult wrists. OsteoDetect is intended to be used by clinicians in various settings, including primary care, emergency medicine, urgent care and specialty care, such as orthopedics. It is an adjunct tool and is not intended to replace a clinician’s review of the radiograph or his or her clinical judgment.
The company submitted a retrospective study of 1,000 radiograph images that assessed the independent performance of the image analysis algorithm for detecting wrist fractures and the accuracy of the fracture localization of OsteoDetect against the performance of three board certified orthopedic hand surgeons. Imagen also submitted a retrospective study of 24 providers who reviewed 200 patient cases. Both studies demonstrated that the readers’ performance in detecting wrist fractures was improved using the software, including increased sensitivity, specificity, positive and negative predictive values, when aided by OsteoDetect, as compared with their unaided performance according to standard clinical practice.
The FDA reviewed the OsteoDetect device through the De Novo premarket review pathway, a regulatory pathway for some low to moderate risk devices of a new type.
The FDA granted marketing authorization of the OsteoDetect device to Imagen.
“Artificial intelligence algorithms have tremendous potential to help health care providers diagnose and treat medical conditions,” said Robert Ochs, Ph.D., acting deputy director for radiological health, Office of In Vitro Diagnostics and Radiological Health in the FDA’s Center for Devices and Radiological Health. “This software can help providers detect wrist fractures more quickly and aid in the diagnosis of fractures.”
The OsteoDetect software is a computer-aided detection and diagnostic software that uses an artificial intelligence algorithm to analyze two-dimensional X-ray images for signs of distal radius fracture, a common type of wrist fracture. The software marks the location of the fracture on the image to aid the provider in detection and diagnosis.
OsteoDetect analyzes wrist radiographs using machine learning techniques to identify and highlight regions of distal radius fracture during the review of posterior-anterior (front and back) and medial-lateral (sides) X-ray images of adult wrists. OsteoDetect is intended to be used by clinicians in various settings, including primary care, emergency medicine, urgent care and specialty care, such as orthopedics. It is an adjunct tool and is not intended to replace a clinician’s review of the radiograph or his or her clinical judgment.
The company submitted a retrospective study of 1,000 radiograph images that assessed the independent performance of the image analysis algorithm for detecting wrist fractures and the accuracy of the fracture localization of OsteoDetect against the performance of three board certified orthopedic hand surgeons. Imagen also submitted a retrospective study of 24 providers who reviewed 200 patient cases. Both studies demonstrated that the readers’ performance in detecting wrist fractures was improved using the software, including increased sensitivity, specificity, positive and negative predictive values, when aided by OsteoDetect, as compared with their unaided performance according to standard clinical practice.
The FDA reviewed the OsteoDetect device through the De Novo premarket review pathway, a regulatory pathway for some low to moderate risk devices of a new type.
The FDA granted marketing authorization of the OsteoDetect device to Imagen.
