"The system may be able to assist residents, radiologists or other physicians by acting either as a first or second reader, or as a triage tool that helps prioritize worklists, potentially reducing the risk of missing a fracture," Hendrix said.
Such assistance could prevent delayed therapy and reduce complications that may lead to a subpar clinical outcome, according to Hendrix.
"The convolutional neural network may also reduce unnecessary wrist immobilization, performed out of precaution, in more than half of the patients with clinical suspicion for having a scaphoid fracture," he said.
The class activation maps were found to overlap with fracture lines in the scaphoid, suggesting they could be used for localizing potential fractures.
Hendrix and colleagues plan to expand the scaphoid fracture detection system so that it can combine multiple X-ray views for its predictions. They are also conducting an experimental study in which radiologists are asked to identify scaphoid fractures on X-rays with and without the aid of the fracture detection system.
The researchers hope to extend the system to fracture detection in other bone structures.
"Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs." Collaborating with Nils Hendrix were Ernst Scholten, M.D., Ph.D., Bastiaan Vernhout, M.D., Stefan Bruijnen, M.D., Ph.D., Bas Maresch, M.D., Mathijn de Jong, M.D., Suzanne Diepstraten, M.D., Stijn Bollen, M.D., Steven Schalekamp, M.D., Maarten de Rooij, M.D., Ph.D., Alexander Scholtens, M.D., Ward Hendrix, M.Sc., Tijs Samson, M.Sc., Lee-Ling Sharon Ong, Ph.D., Eric Postma, Ph.D., Bram van Ginneken, Ph.D., and Matthieu Rutten, M.D., Ph.D.
About RSNA
RSNA is an association of radiologists, radiation oncologists, medical physicists and related scientists promoting excellence in patient care and health care delivery through education, research and technologic innovation. The Society is based in Oak Brook, Illinois.
Back to HCB News
