Comparisons of surface vs. volumetric model-based registration methods using single-plane vs. bi-plane fluoroscopy in measuring spinal kinematics.

Several 2D-to-3D image registration methods are available for measuring 3D vertebral motion but their performance has not been evaluated under the same experimental protocol. In this study, four major types of fluoroscopy-to-CT registration methods, with different use of surface vs. volumetric models, and single-plane vs. bi-plane fluoroscopy, were evaluated: STS (surface, single-plane), VTS (volumetric, single-plane), STB (surface, bi-plane) and VTB (volumetric, bi-plane). Two similarity measures were used: 'Contour Difference' for STS and STB and 'Weighted Edge-Matching Score' for VTS and VTB. Two cadaveric porcine cervical spines positioned in a box filled with paraffin and embedded with four radiopaque markers were CT scanned to obtain vertebral models and marker coordinates, and imaged at ten static positions using bi-plane fluoroscopy for subsequent registrations using different methods. The registered vertebral poses were compared to the gold standard poses defined by the marker positions determined using CT and Roentgen stereophotogrammetry analysis. The VTB was found to have the highest precision (translation: 0.4mm; rotation: 0.3°), comparable with the VTS in rotations (0.3°), and the STB in translations (0.6mm). The STS had the lowest precision (translation: 4.1mm; rotation: 2.1°).

[1]  Guoyan Zheng,et al.  Scaled, patient-specific 3D vertebral model reconstruction based on 2D lateral fluoroscopy , 2011, International Journal of Computer Assisted Radiology and Surgery.

[2]  Gang Li,et al.  Measurement of Vertebral Kinematics Using Noninvasive Image Matching Method–Validation and Application , 2008, Spine.

[3]  Guoan Li,et al.  Comments on "validation of a non-invasive fluoroscopic imaging technique for the measurement of dynamic knee joint motion". , 2008 .

[4]  Michael J Bey,et al.  Three-dimensional dynamic in vivo motion of the cervical spine: assessment of measurement accuracy and preliminary findings. , 2010, The spine journal : official journal of the North American Spine Society.

[5]  Richard D. Komistek,et al.  A robust method for registration of three-dimensional knee implant models to two-dimensional fluoroscopy images , 2003, IEEE Transactions on Medical Imaging.

[6]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  R. Siddon Fast calculation of the exact radiological path for a three-dimensional CT array. , 1985, Medical physics.

[8]  P Bifulco,et al.  Advanced template matching method for estimation of intervertebral kinematics of lumbar spine. , 2011, Medical engineering & physics.

[10]  Tung-Wu Lu,et al.  Effects of soft tissue artifacts on the calculated kinematics and kinetics of the knee during stair-ascent. , 2011, Journal of biomechanics.

[11]  Tung-Wu Lu,et al.  In vivo three-dimensional kinematics of the normal knee during active extension under unloaded and loaded conditions using single-plane fluoroscopy. , 2008, Medical engineering & physics.

[12]  M M Panjabi,et al.  The Basic Kinematics of the Human Spine: A Review of Past and Current Knowledge , 1978, Spine.

[13]  G. Selvik Roentgen stereophotogrammetry. A method for the study of the kinematics of the skeletal system. , 1989, Acta orthopaedica Scandinavica. Supplementum.

[14]  Daniel Rueckert,et al.  Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration , 2005, IEEE Transactions on Medical Imaging.

[15]  James D. Kang,et al.  Validation of a Noninvasive Technique to Precisely Measure In Vivo Three-Dimensional Cervical Spine Movement , 2011, Spine.

[16]  Luigi Paura,et al.  X-ray fluoroscopy noise modeling for filter design , 2013, International Journal of Computer Assisted Radiology and Surgery.

[17]  Maria Romano,et al.  A continuous description of intervertebral motion by means of spline interpolation of kinematic data extracted by videofluoroscopy. , 2012, Journal of biomechanics.

[18]  M. Panjabi,et al.  Functional Radiographic Diagnosis of the Lumbar Spine: Flexion—Extension and Lateral Bending , 1991, Spine.

[19]  Chung-Ming Chen,et al.  A volumetric model-based 2D to 3D registration method for measuring kinematics of natural knees with single-plane fluoroscopy. , 2010, Medical physics.

[20]  H. van Mameren,et al.  Cervical spine motion in the sagittal plane (I) range of motion of actually performed movements, an X-ray cinematographic study. , 1990, European journal of morphology.

[21]  E KALLIO,et al.  Injuries of the thoraco-lumbar spine with paraplegia. , 1963, Acta orthopaedica Scandinavica. Supplementum.

[22]  F. Veldpaus,et al.  A least-squares algorithm for the equiform transformation from spatial marker co-ordinates. , 1988, Journal of biomechanics.

[23]  G. Jull,et al.  Normal kinematics of the upper cervical spine during the Flexion-Rotation Test - In vivo measurements using magnetic resonance imaging. , 2011, Manual therapy.

[24]  Hideki Yoshikawa,et al.  Kinematics of the Cervical Spine in Lateral Bending: In Vivo Three-Dimensional Analysis , 2006, Spine.

[25]  Benjamin J Fregly,et al.  Theoretical accuracy of model-based shape matching for measuring natural knee kinematics with single-plane fluoroscopy. , 2005, Journal of biomechanical engineering.

[26]  S-W Hong,et al.  A method for measuring three-dimensional mandibular kinematics in vivo using single-plane fluoroscopy. , 2013, Dento maxillo facial radiology.

[27]  Graeme P. Penney,et al.  Standardized evaluation methodology for 2-D-3-D registration , 2005, IEEE Transactions on Medical Imaging.

[28]  S.A. Banks,et al.  Accurate measurement of three-dimensional knee replacement kinematics using single-plane fluoroscopy , 1996, IEEE Transactions on Biomedical Engineering.

[29]  Markus Hadwiger,et al.  Real-time volume graphics , 2006, Eurographics.

[30]  K. Shelburne,et al.  A comparison of calibration methods for stereo fluoroscopic imaging systems. , 2011, Journal of biomechanics.

[31]  Minho Kim,et al.  Evaluation of similarity measures for use in the intensity-based rigid 2D-3D registration for patient positioning in radiotherapy. , 2009, Medical physics.

[32]  Jürgen Weese,et al.  A comparison of similarity measures for use in 2-D-3-D medical image registration , 1998, IEEE Transactions on Medical Imaging.

[33]  Maria Romano,et al.  2D-3D Registration of CT Vertebra Volume to Fluoroscopy Projection: A Calibration Model Assessment , 2010, EURASIP J. Adv. Signal Process..

[34]  M. Levoy,et al.  Fast volume rendering using a shear-warp factorization of the viewing transformation , 1994, SIGGRAPH.

[35]  Peter Kazanzides,et al.  Intraoperative Image-based Multiview 2D/3D Registration for Image-Guided Orthopaedic Surgery: Incorporation of Fiducial-Based C-Arm Tracking and GPU-Acceleration , 2012, IEEE Transactions on Medical Imaging.

[36]  M M Panjabi,et al.  Clinical Validation of Functional Flexion‐Extension Roentgenograms of the Lumbar Spine , 1991, Spine.

[37]  Alberto Leardini,et al.  A model-based method for the reconstruction of total knee replacement kinematics , 1999, IEEE Transactions on Medical Imaging.

[38]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[39]  Zhonglin Zhu,et al.  An automatic 2D–3D image matching method for reproducing spatial knee joint positions using single or dual fluoroscopic images , 2012, Computer methods in biomechanics and biomedical engineering.

[40]  M M Panjabi,et al.  Functional Radiographic Diagnosis of the Cervical Spine: Flexion/Extension , 1988, Spine.

[41]  Paolo Bifulco,et al.  A comparison of denoising methods for X-ray fluoroscopic images , 2012, Biomed. Signal Process. Control..

[42]  H. Hatze,et al.  High-precision three-dimensional photogrammetric calibration and object space reconstruction using a modified DLT-approach. , 1988, Journal of biomechanics.