(782.4) A New Method for Quantifying 3D Skeletal Morphology in Living Subjects Using Low-Dose Stereo Radiographs

Poster Board Number: C54
Introduction: AAA has separate poster presentation times for odd and even posters.
Odd poster #s – 10:15 am – 11:15 am
Even poster #s – 11:15 am – 12:15 pm

Austin Lawrence (University of Missouri), Melanie Boeyer (University of Missouri), Kevin Middleton (University of Missouri)

Accurate and repeatable assessments of three-dimensional (3D) skeletal morphology are critical to interpretations of vertebrate functional anatomy. In skeletal specimens, these goals can be accomplished using in-silico models derived from 3D laser scan, photogrammetry, or computed tomography (CT) data. Assessments of skeletal morphology in living subjects, especially humans, are more challenging and are often either cost-prohibitive (e.g., magnetic resonance) or expose subjects to high doses of ionizing radiation (e.g., CT). Here, we present a new, open-source method for assessing 3D skeletal morphology using ultra-low dose biplanar radiographs. Biplanar radiographs were obtained using an EOS Imaging System (EOS Imaging, Inc., Paris, France). A custom-built calibration frame with radiopaque markers was scanned using this system on multiple days in multiple positions inside the scanning space. We quantified the 3D coordinates of markers by placing landmarks at the center of each marker in both anterior-posterior and lateral radiographs. Landmark data for each scan were collected independently by two observers to determine inter-observer error. 3D coordinates of landmarks in each scan differed by lt;1 mm between observers, suggesting strong repeatability in assessing morphology of living subjects. To assess distortion in EOS images, we constructed a second calibration device, a flat plate with radiopaque markers at the corners of three squares with 10 cm, 20 cm, and 30 cm sides, respectively, surrounding an origin point. The calibration plate was scanned with the origin point at the center of the scan area and the sides of the squares parallel to the detectors. We identified distortion at the edges of EOS images which could significantly impact measurements on skeletal features near the margins of the scan area (i.e., hips, pelvis, lower limbs) and developed a method to mathematically correct for resulting distortion in landmark data. Finally, we demonstrate this method using measurements of iliac blade and spinous process orientation in a sample of living human participants. This method will be applicable to studies of multiple human cohorts, including symptomatic and asymptomatic groups, as well as to other biplanar radiograph platforms and study organisms.

This study received funding support from the Department of Pathology and Anatomical Sciences at the University of Missouri School of Medicine.