Novel magnetic resonance technique for characterizing mesoscale structure of trabecular bone
Osteoporosis, characterized by increased fracture risk and bone fragility, impacts millions of adults worldwide, but effective, non invasive and easily accessible diagnostic tests of the disease remain elusive. We present a magnetic resonance (MR) technique that overcomes the motion limitations of traditional MR imaging to acquire high resolution frequency domain data to characterize the texture of biological tissues. This technique does not involve obtaining full two dimensional or three dimensional images, but can probe scales down to the order of 40 mm and in particular uncover structural information in trabecular bone. Using micro computed tomography data of vertebral trabecular bone, we computationally validate this MR technique by simulating MR measurements of a 'ratio metric' determined from a few k space values corresponding to trabecular thickness and spacing. We train a support vector machine classifier on ratio metric values determined from healthy and simulated osteoporotic bone data, which we use to accurately classify osteoporotic bone.
Royal Society Open Science