A computer deep learning model can accurately screen for osteoporosis based on x-rays of the hand and wrist, according to pilot study results published in The Journal of Hand Surgery.
Computer algorithms designed to classify images have been applied to medical treatment and diagnosis in several ways, such as in spinal surgery and assessment of coronary angiograms. With regard to screening for bone loss, researchers have developed a mobile-based technology to predict the presence of osteopenia or osteoporosis based on hand x-rays, using second metacarpal cortical percentage as a proxy for global bone mineral density. Although this technology is simpler and notably more cost-effective than dual-energy x-ray absorptiometry, it is limited by inconsistencies in interpretations, measurements, and standardization, which may be improved with computer learning.
Based on this research, investigators explored whether a convolutional neural network, a deep learning technique for analyzing visual images, could be used to predict osteoporosis on plain hand and wrist x-rays.
Read more at Rheumatology Advisor and find the study in the Journal of Hand Surgery.
