Sam Brusco, Associate Editor03.02.22
French radiological artificial intelligence (AI) company GLEAMER has gained U.S. Food and Drug Administration (FDA) clearance for its BoneView AI software to help diagnose fractures and traumatic injuries on X-rays. BoneView earned CE mark class 2a certification in the EU in March 2020.
BoneView was developed to aid all who read X-rays: radiologists, orthopedic surgeons, emergency physicians, rheumatologists, family physicians, and physician assistants. It spots fractures in X-ray images and submits them to radiologists for validation. It’s cleared by the FDA as a CADe/CADx (computer-assisted detection and diagnosis), highlighting regions with suspected fractures using bounding boxes to prioritize those X-rays.
Results from a July 2020 – January 2021 study showed BoneView AI assistance offered 10.4 percent fracture detection sensitivity improvement and shortened radiograph reading time by 6.3 seconds per patient. The combo of AI and clinician interpretation lowered false negative rates by 29 percent and reduced reading time by 15 percent on exams.
"BoneView can change everything about the way X-ray reading is done today," Christian Allouche, CEO and co-founder of GLEAMER told the press. "In the value-based U.S. healthcare system, providers tell us they want to improve the radiographic diagnostic process which accounts for a huge part of their workload and optimize patient management. We are delighted and proud to offer clinicians and patients BoneView AI for this state-of-the-art advancement in radiology and patient care."
Traumatic skeletal injuries represent a third of annual visits, and interpretation errors can account for up to 24 percent of harmful diagnostic errors in the ER.
"Radiologists' workload has doubled in the past two decades, and despite technological progress, they must analyze hundreds more images every day, requiring the readings to be highly reliable," explained Ali Guermazi, MD, Ph.D., Chief of Radiology at VA Boston Healthcare System and Professor of Radiology and medicine at Boston University School of Medicine, and leader of the U.S. study. "The assistance of AI should allow us to improve the specificity of the complementary exams prescribed after the radiography, to avoid delays in care, and to direct patients into the right therapeutic pathway. Our study was focused on fracture diagnosis, and a similar concept can be applied to other diseases and disorders."
BoneView was developed to aid all who read X-rays: radiologists, orthopedic surgeons, emergency physicians, rheumatologists, family physicians, and physician assistants. It spots fractures in X-ray images and submits them to radiologists for validation. It’s cleared by the FDA as a CADe/CADx (computer-assisted detection and diagnosis), highlighting regions with suspected fractures using bounding boxes to prioritize those X-rays.
Results from a July 2020 – January 2021 study showed BoneView AI assistance offered 10.4 percent fracture detection sensitivity improvement and shortened radiograph reading time by 6.3 seconds per patient. The combo of AI and clinician interpretation lowered false negative rates by 29 percent and reduced reading time by 15 percent on exams.
"BoneView can change everything about the way X-ray reading is done today," Christian Allouche, CEO and co-founder of GLEAMER told the press. "In the value-based U.S. healthcare system, providers tell us they want to improve the radiographic diagnostic process which accounts for a huge part of their workload and optimize patient management. We are delighted and proud to offer clinicians and patients BoneView AI for this state-of-the-art advancement in radiology and patient care."
Traumatic skeletal injuries represent a third of annual visits, and interpretation errors can account for up to 24 percent of harmful diagnostic errors in the ER.
"Radiologists' workload has doubled in the past two decades, and despite technological progress, they must analyze hundreds more images every day, requiring the readings to be highly reliable," explained Ali Guermazi, MD, Ph.D., Chief of Radiology at VA Boston Healthcare System and Professor of Radiology and medicine at Boston University School of Medicine, and leader of the U.S. study. "The assistance of AI should allow us to improve the specificity of the complementary exams prescribed after the radiography, to avoid delays in care, and to direct patients into the right therapeutic pathway. Our study was focused on fracture diagnosis, and a similar concept can be applied to other diseases and disorders."