A versatile intensity-based 3D/2D rigid registration compatible with mobile C-arm for endovascular treatment of abdominal aortic aneurysm

PurposeAugmented reality-assisted surgery requires prior registration between preoperative and intraoperative data. In the context of the endovascular aneurysm repair (EVAR) of abdominal aortic aneurysm, no satisfactory solution exists at present for clinical use, in particular in the case of use with a mobile C-arm. The difficulties stem in particular from the diversity of intraoperative images, table movements and changes of C-arm pose.MethodsWe propose a fast and versatile 3D/2D registration method compatible with mobile C-arm that can be easily repeated during an EVAR procedure. Applicable to both vascular and bone structures, our approach is based on an optimization by reduced exhaustive search involving a multi-resolution scheme and a decomposition of the transformation to reduce calculation time.ResultsRegistration was performed between the preoperative CT-scan and fluoroscopic images for a group of 26 patients in order to confront our method in real conditions of use. The evaluation was completed by also performing registration between an intraoperative CBCT volume and fluoroscopic images for a group of 6 patients to compare registration results with reference transformations. The experimental results show that our approach allows obtaining accuracy of the order of 0.5 mm, a computation time of $${<}17\,\hbox {s}$$<17s and a higher rate of success in comparison with a classical optimization method. When integrated in an augmented reality navigation system, our approach shows that it is compatible with clinical workflow.ConclusionWe presented a versatile 3D/2D rigid registration applicable to all intraoperative scenes and usable to guide an EVAR procedure by augmented reality.

[1]  Rui Liao,et al.  Model-to-volume registration for endovascular aneurysm repair , 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

[2]  Maximilian Baust,et al.  Disocclusion-based 2D-3D registration for aortic interventions , 2013, Comput. Biol. Medicine.

[3]  Rui Liao,et al.  Toward smart utilization of two X-ray images for 2-D/3-D registration applied to abdominal aortic aneurysm interventions , 2013, Comput. Electr. Eng..

[4]  G W H Schurink,et al.  CTA with fluoroscopy image fusion guidance in endovascular complex aortic aneurysm repair. , 2014, European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery.

[5]  Daniel B. Russakoff,et al.  Intensity-based 2D-3D spine image registration incorporating a single fiducial marker. , 2005, Academic radiology.

[6]  Mark R. Pickering,et al.  A fast and robust technique for 3D-2D registration of CT to single plane X-ray fluoroscopy , 2014, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

[7]  D. Paulus,et al.  2D/3D image registration on the GPU , 2008, Pattern Recognition and Image Analysis.

[8]  Max Mignotte,et al.  3D/2D registration and segmentation of scoliotic vertebrae using statistical models. , 2003, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[9]  Pawel Lubniewski,et al.  3D/2D image registration by image transformation descriptors (ITDs) for thoracic aorta imaging , 2013, Electronic Imaging.

[10]  Kyehyun Kim,et al.  Fast 2D-3D registration using GPU-based preprocessing , 2005, Proceedings of 7th International Workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005..

[11]  Bostjan Likar,et al.  A protocol for evaluation of similarity measures for rigid registration , 2006, IEEE Transactions on Medical Imaging.

[12]  G. L. Moneta Endovascular versus Open Repair of Abdominal Aortic Aneurysm , 2010 .

[13]  Shigeru Eiho,et al.  Registration of Preoperative CTA and Intraoperative Fluoroscopic images for Assisting Aortic Stent Grafting , 2002, MICCAI.

[14]  Graeme P. Penney,et al.  An Image-Guided Surgery System to Aid Endovascular Treatment of Complex Aortic Aneurysms: Description and Initial Clinical Experience , 2011, IPCAI.

[15]  Pascal Haigron,et al.  Endovascular aortic repair of a postdissecting thoracoabdominal aneurysm using intraoperative fusion imaging. , 2013, Journal of vascular surgery.

[16]  Rui Liao,et al.  System and Method for 3-D/3-D Registration between Non-contrast-enhanced CBCT and Contrast-Enhanced CT for Abdominal Aortic Aneurysm Stenting , 2013, MICCAI.

[17]  A. Luciani,et al.  Image guidance for endovascular repair of complex aortic aneurysms: comparison of two-dimensional and three-dimensional angiography and image fusion. , 2013, Journal of vascular and interventional radiology : JVIR.

[18]  Ying Sun,et al.  A Review of Recent Advances in Registration Techniques Applied to Minimally Invasive Therapy , 2013, IEEE Transactions on Multimedia.

[19]  Graeme P. Penney,et al.  Non-Rigid 2D-3D Registration Using Anisotropic Error Ellipsoids to Account for Projection Uncertainties during Aortic Surgery , 2013, MICCAI.

[20]  Graeme P. Penney,et al.  Increasing the Automation of a 2D-3D Registration System , 2013, IEEE Transactions on Medical Imaging.

[21]  Joyoni Dey,et al.  Targeted 2D/3D registration using ray normalization and a hybrid optimizer. , 2006, Medical physics.

[22]  Frank Deinzer,et al.  Extended Global Optimization Strategy for Rigid 2D/3D Image Registration , 2007, CAIP.

[23]  Miguel Castro,et al.  Finite-Element-Based Matching of Pre- and Intraoperative Data for Image-Guided Endovascular Aneurysm Repair , 2013, IEEE Transactions on Biomedical Engineering.

[24]  Stephen D. Laycock,et al.  GPU Accelerated Generation of Digitally Reconstructed Radiographs for 2-D/3-D Image Registration , 2012, IEEE Transactions on Biomedical Engineering.

[25]  M. Viergever,et al.  Robust initialization of 2D-3D image registration using the projection-slice theorem and phase correlation. , 2010, Medical physics.

[26]  D. Louis Collins,et al.  The state of the art of visualization in mixed reality image guided surgery , 2013, Comput. Medical Imaging Graph..

[27]  Max A. Viergever,et al.  Image registration by maximization of combined mutual information and gradient information , 2000, IEEE Transactions on Medical Imaging.

[28]  A. James Stewart,et al.  A New Method for CT to Fluoroscope Registration Based on Unscented Kalman Filter , 2006, MICCAI.

[29]  M. Midulla,et al.  Impact of hybrid rooms with image fusion on radiation exposure during endovascular aortic repair. , 2014, European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery.

[30]  Josien P. W. Pluim,et al.  Evaluation of optimization methods for intensity-based 2D-3D registration in x-ray guided interventions , 2011, Medical Imaging.

[31]  Maximilien Vermandel,et al.  Intrinsic 2D/3D registration based on a hybrid approach: use in the radiosurgical imaging process. , 2007, Cellular and molecular biology.

[32]  Rui Liao,et al.  Automatic pose initialization for accurate 2D/3D registration applied to abdominal aortic aneurysm endovascular repair , 2012, Medical Imaging: Image-Guided Procedures.

[33]  Pramod K. Varshney,et al.  A pyramid approach for multimodality image registration based on mutual information , 2000, Proceedings of the Third International Conference on Information Fusion.

[34]  Frank Sauer,et al.  Automatic registration of portal images and volumetric CT for patient positioning in radiation therapy , 2006, Medical Image Anal..

[35]  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.

[36]  G. Kuduvalli,et al.  A fast, accurate, and automatic 2D-3D image registration for image-guided cranial radiosurgery. , 2008, Medical physics.

[37]  Pascal Haigron,et al.  Endovascular navigation based on real/virtual environments cooperation for computer-assisted TEAM procedures , 2004, Medical Imaging: Image-Guided Procedures.

[38]  Serge Miguet,et al.  Patient setup error measurement using 3D intensity-based image registration techniques. , 2003, International journal of radiation oncology, biology, physics.

[39]  Christos Davatzikos,et al.  A novel 2D-3D registration algorithm for aligning fluoro images with 3D pre-op CT/MR images , 2006, SPIE Medical Imaging.

[40]  Joachim Denzler,et al.  Progressive attenuation fields: Fast 2D‐3D image registration without precomputation , 2005 .

[41]  Fang-Fang Yin,et al.  Comparison of Similarity Measures for Rigid-body CT/Dual X-ray Image Registrations , 2007, Technology in cancer research & treatment.

[42]  Jeff Orchard Efficient Least Squares Multimodal Registration With a Globally Exhaustive Alignment Search , 2007, IEEE Transactions on Image Processing.

[43]  David Sarrut,et al.  Geometrical Transformation Approximation for 2D/3D Intensity-Based Registration of Portal Images and CT Scan , 2001, MICCAI.

[44]  Bostjan Likar,et al.  A review of 3D/2D registration methods for image-guided interventions , 2012, Medical Image Anal..

[45]  Pascal Haigron,et al.  Sizing for endovascular aneurysm repair: clinical evaluation of a new automated three-dimensional software. , 2010, Annals of vascular surgery.

[46]  T. Huber,et al.  Three-dimensional fusion computed tomography decreases radiation exposure, procedure time, and contrast use during fenestrated endovascular aortic repair. , 2015, Journal of vascular surgery.