Predicting spinal profile using 3D non-contact surface scanning: Changes in surface topography as a predictor of internal spinal alignment

RESEARCH ARTICLE Predicting spinal profile using 3D non-contact surface scanning: Changes in surface topography as a predictor of internal spinal alignment J. Paige Little ID1*, Lionel Rayward1, Mark J. Pearcy ID1, Maree T. Izatt ID1, Daniel Green2, Robert D. Labrom1,3, Geoffrey N. Askin1,4 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 1 Biomechanics and Spine Research Group, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Australia, 2 Sealy of Australia, Wacol, Australia, 3 Wesley Hospital, Brisbane, Australia, 4 Mater Health Services, Brisbane, Australia * Abstract OPEN ACCESS Citation: Little JP, Rayward L, Pearcy MJ, Izatt MT, Green D, Labrom RD, et al. (2019) Predicting spinal profile using 3D non-contact surface scanning: Changes in surface topography as a predictor of internal spinal alignment. PLoS ONE 14(9): e0222453. https://doi.org/10.1371/journal. pone.0222453 Editor: David Fyhrie, University of California Davis, UNITED STATES Received: April 12, 2019 Accepted: August 29, 2019 Published: September 26, 2019 Copyright: © 2019 Little et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The minimal anonymized data set is available from the QUT Research Data Finder (https://data. researchdatafinder.qut.edu.au/dataset/3dss-vsmri). Funding: This work was supported by Sealy of Australia who provided support in the form of salary for authors [JPL, DG], and a student scholarship [LR], but did not have any additional role in the study design, data collection and Introduction 3D non-contact surface scanners capture highly accurate, calibrated images of surface topography for 3D structures. This study sought to establish the efficacy and accuracy of using 3D surface scanning to characterise spinal curvature and sagittal plane contour. Methods 10 healthy female adults with a mean age of 25 years, (standard deviation: 3.6 years) underwent both MRI and 3D surface scanning (3DSS) (Artec Eva, Artec Group Inc., Luxembourg) while lying in the lateral decubitus position on a rigid substrate. Prior to 3DSS, anatomical landmarks on the spinous processes of each participant were demarcated using stickers attached to the skin surface. Following 3DSS, oil capsules (fiducial markers) were overlaid on the stickers and the subject underwent MRI. MRI stacks were processed to measure the thoracolumbar spinous process locations, providing an anatomical reference. 3D coordinates for the markers (surface stickers and MRI oil capsules) and for the spinous processes mapped the spinal column profiles and were compared to assess the quality of fit between the 3DSS and MRI marker positions. Results The RMSE for the polynomials fit to the spinous process, fiducial and surface marker profiles ranged from 0.17–1.15mm for all subjects. The MRI fiducial marker location was well aligned with the spinous process profile in the thoracic and upper lumbar spine for nine of the subjects. Over the 10 subjects, the mean RMSE between the MRI and 3D scan sagittal profiles for all surface markers was 9.8mm (SD 4.2mm). Curvature was well matched for seven of the subjects, with two showing differing curvatures across the lumbar spine due to inconsistent subject positioning. PLOS ONE | https://doi.org/10.1371/journal.pone.0222453 September 26, 2019 1 / 15 Predicting spinal profile using 3D non-contact surface scanning analysis, decision to publish, or preparation of the manuscript. Competing interests: Sealy of Australia provide support for research projects within the QUT Biomechanics and Spine Research Group, which funds staff salary, student scholarships and equipment. This does not alter our adherence to PLOS ONE policies on sharing data and materials. Conclusion Comparison of the observed trends for vertebral position measured from MRI and 3DSS, suggested the surface markers may provide a useful method for measuring internal changes in sagittal curvature or skeletal changes. Nomenclature For the purpose of this study, the term profile refers to quantitative marker locations and curvature or contour refers to spinal shape. Introduction Non- contact surface scanners capture 3D images of surface topography and shape. In doing so, they enable the virtual analysis of real objects to be conducted in order to gather qualitative and quantitative data on shape, size and colour of the object. From this, virtual reconstructions of a 3D object can be created with a high level of accuracy (in the order of a micron, depending on the scanner) to generate a dimensionally accurate, calibrated reconstruction. Such calibrated reconstructions provide a dimensionally accurate record of the object of interest at a particular point in time. 3D non-contact scanning using optical or light-based scanners has been utilised since the 1980s [1]. The technology has seen broad application in fields including reverse engineering and design of machinery parts, spatial reconstructions to capture accurate 3D representation of crime scenes for forensic investigations [2], computer graphics applications for gaming and movie production (www.artec3d.com/applications), and artistic or historically-driven reconstructions of physical artefacts (eg. paleantology) [3]. In terms of clinical applications, much interest surrounds the use of non-contact scanners to capture physical surface anatomy, whether this be for application in creating orthotic devices [4], in creating bespoke reconstructions for plastic surgery or in measuring surface contours [5] for anatomy such as the torso and spine. In recent years, there’s been an interest in using 3D scanning to measure spinal shape for biomechanical or ergonomic assessments of spinal posture during various activities [6]. Clinically, surface scanning is used to evaluate torso shape in patients with deformity [7, 8] or to reverse engineer torso geometry when manufacturing spinal braces [4, 9–12]. However, the uptake of this technology is still to some degree hampered by conflicting results relating to the correlation between surface topography and clinically relevant spinal parameters [7]. In a review of prior studies utilising metrics acquired using surface topography to evaluate spinal deformity indices for scoliosis, Patias et al [13] stated that surface metrics cannot be used to describe radiological measurements of spinal deformity in these patients. However, Goldberg et al [7] found a strong correlation between spinal deformity angles measured using the Quantec surface measurement system and the coronal Cobb angle measured radiographically for scoliosis patients. These surface parameters were calculated using a line demarcating the spinal column on the topographic image of the patient’s back. 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