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International Journal of Computer Assisted Radiology and Surgery

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01-09-2016 | Original Article

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

Authors: A. Duménil, A. Kaladji, M. Castro, C. Göksu, A. Lucas, P. Haigron

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 9/2016

Abstract

Purpose

Augmented 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.

Methods

We 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.

Results

Registration 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 \({<}17\,\hbox {s}\) 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.

Conclusion

We presented a versatile 3D/2D rigid registration applicable to all intraoperative scenes and usable to guide an EVAR procedure by augmented reality.

United Kingdom EVAR Trial Investigators, Greenhalgh RM, Brown LC, Powell JT, Thompson SG, Epstein D, Sculpher MJ (2010) Endovascular versus open repair of abdominal aortic aneurysm. N Engl J Med 362(20):1863–1871

Kersten-Oertel M, Jannin P, Collins DL (2013) The state of the art of visualization in mixed reality image guided surgery. Comput Med Imaging Graph Off J Comput Med Imaging Soc 37(2):98–112CrossRef

Markelj P, Tomaževič D, Likar B, Pernuš F (2012) A review of 3D/2D registration methods for image-guided interventions. Med Image Anal 16(3):642–661PubMedCrossRef

Liao R, Zhang L, Sun Y, Miao S, Chefd’hotel C (2013) A review of recent advances in registration techniques applied to minimally invasive therapy. IEEE Trans Multimed 15(5):983–1000CrossRef

Kaladji A, Dumenil A, Castro M, Haigron P, Heautot J-F, Haulon S (2013) Endovascular aortic repair of a postdissecting thoracoabdominal aneurysm using intraoperative fusion imaging. J Vasc Surg 57(4):1109–1112PubMedCrossRef

Sailer AM, de Haan MW, Peppelenbosch AG, Jacobs MJ, Wildberger JE, Schurink GWH (2014) CTA with fluoroscopy image fusion guidance in endovascular complex aortic aneurysm repair. Eur J Vasc Endovasc Surg Off J Eur Soc Vasc Surg 47(4):349–356CrossRef

Hertault A, Maurel B, Sobocinski J, Gonzalez TM, Roux ML, Azzaoui R, Midulla M, Haulon S (2014) Impact of Hybrid Rooms with Image Fusion on Radiation Exposure during Endovascular Aortic Repair. Eur J Vasc Endovasc Surg 48(4):382–390

Tacher V, Lin M, Desgranges P, Deux J-F, Grünhagen T, Becquemin J-P, Luciani A, Rahmouni A, Kobeiter H (2013) Image guidance for endovascular repair of complex aortic aneurysms: comparison of two-dimensional and three-dimensional angiography and image fusion. J Vasc Interv Radiol 24(11):1698–1706PubMedPubMedCentralCrossRef

McNally MM, Scali ST, Feezor RJ, Neal D, Huber TS, Beck AW (2014) Three-dimensional fusion computed tomography decreases radiation exposure, procedure time, and contrast use during fenestrated endovascular aortic repair. J Vasc Surg 61(2):309–316PubMedPubMedCentralCrossRef

10.

Goksu C, Haigron P, Acosta O, Lucas A (2004) Endovascular navigation based on real/virtual environments cooperation for computer-assisted TEAM procedures. In: Proceedings of SPIE 5367, Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display, pp 257–266

11.

Penney G, Varnavas A, Dastur N, Carrell T (2011) An image-guided surgery system to aid endovascular treatment of complex aortic aneurysms: description and initial clinical experience. In: Taylor RH, Yang G-Z (eds) Information processing in computer-assisted interventions. Springer, Berlin, pp 13–24CrossRef

12.

Guyot A, Varnavas A, Carrell T, Penney G (2013) Non-rigid 2D–3D registration using anisotropic error ellipsoids to account for projection uncertainties during aortic surgery. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv 16(Pt 3):179–186

13.

Duménil A, Kaladji A, Castro M, Esneault S, Lucas A, Rochette M, Göksu C, Haigron P (2013) Finite-element-based matching of pre- and intraoperative data for image-guided endovascular aneurysm repair. IEEE Trans Biomed Eng 60(5):1353–1362PubMedCrossRef

14.

Miao S, Liao R, Pfister M (2013) Toward smart utilization of two X-ray images for 2-D/3-D registration applied to abdominal aortic aneurysm interventions. Comput Electr Eng 39(5):1485–1498CrossRef

15.

Benameur S, Mignotte M, Parent S, Labelle H, Skalli W, de Guise J (2003) 3D/2D registration and segmentation of scoliotic vertebrae using statistical models. Comput Med Imaging Graph Off J Comput Med Imaging Soc 27(5):321–337CrossRef

16.

Sundar H, Khamene A, Xu C, Sauer F, Davatzikos C (2006) A novel 2D-3D registration algorithm for aligning fluoro images with 3D Pre-op CT/MR images. In: Proceedings of SPIE 6141, Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, 61412K

17.

Imamura H, Ida N, Sugimoto N, Eiho S, Urayama S, Ueno K, Inoue K (2002) Registration of preoperative CTA and intraoperative fluoroscopic images for assisting aortic stent grafting. In: Dohi T, Kikinis R (eds) Med Image Comput Comput Assist Interv—MICCAI 2002. Springer, Berlin, pp 477–484

18.

Khamene A, Bloch P, Wein W, Svatos M, Sauer F (2006) Automatic registration of portal images and volumetric CT for patient positioning in radiation therapy. Med Image Anal 10(1):96–112PubMedCrossRef

19.

Gong RH, Stewart AJ, Abolmaesumi P (2006) A new method for CT to fluoroscope registration based on unscented Kalman filter. Med Image Comput Comput Assist Interv 9(Pt 1):891–898PubMed

20.

Dey J, Napel S (2006) Targeted 2D/3D registration using ray normalization and a hybrid optimizer. Med Phys 33(12):4730–4738PubMedCrossRef

21.

van der Bom IMJ, Klein S, Staring M, Homan R, Bartels LW, Pluim JPW (2011) Evaluation of optimization methods for intensity-based 2D–3D registration in X-ray guided interventions. In: Proceedings of SPIE 7962, Medical Imaging 2011: Image Processing, 796223

22.

Orchard J (2007) Efficient least squares multimodal registration with a globally exhaustive alignment search. IEEE Trans Image Process Publ IEEE Signal Process Soc 16(10):2526–2534CrossRef

23.

Russakoff DB, Rohlfing T, Adler JR, Maurer CR (2005) Intensity-based 2D–3D spine image registration incorporating a single fiducial marker. Acad Radiol 12(1):37–50PubMedCrossRef

24.

Rohlfing T, Russakoff DB, Denzler J, Mori K, Maurer CR (2005) Progressive attenuation fields: fast 2D–3D image registration without precomputation. Med Phys 32(9):2870–2880PubMedCrossRef

25.

Kubias A, Deinzer F, Feldmann T, Paulus D, Schreiber B, Brunner T (2008) 2D/3D image registration on the GPU. Pattern Recognit Image Anal 18(3):381–389CrossRef

26.

Dorgham OM, Laycock SD, Fisher MH (2012) GPU accelerated generation of digitally reconstructed radiographs for 2-D/3-D image registration. IEEE Trans Biomed Eng 59(9):2594–2603PubMedCrossRef

27.

Sarrut D, Clippe S (2001) Geometrical transformation approximation for 2D/3D intensity-based registration of portal images and CT scan. In: Niessen WJ, Viergever MA (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. Springer Berlin Heidelberg, pp 532–540

28.

Clippe S, Sarrut D, Malet C, Miguet S, Ginestet C, Carrie C (2003) Patient setup error measurement using 3D intensity-based image registration techniques. Int J Radiat Oncol Biol Phys 56(1):259–265

29.

Fu D, Kuduvalli G (2008) A fast, accurate, and automatic 2D–3D image registration for image-guided cranial radiosurgery. Med Phys 35(5):2180–2194PubMedCrossRef

30.

Kubias A, Deinzer F, Feldmann T, Paulus D (2007) Extended global optimization strategy for rigid 2D/3D image registration. In: Kropatsch WG, Kampel M, Hanbury A (eds) Computer analysis of images and patterns. Springer, Berlin, pp 759–767CrossRef

31.

Haque MN, Pickering MR, Al Muhit A, Frater MR, Scarvell JM, Smith PN (2014) A fast and robust technique for 3D–2D registration of CT to single plane X-ray fluoroscopy. Comput Methods Biomech Biomed Eng Imaging Vis 2(2):76–89

32.

Chen H, Varshney PK (2000) A pyramid approach for multimodality image registration based on mutual information. In: Proceedings of the third international conference on Information Fusion, 2000, vol 1. FUSION 2000, pp MOD3-9–MOD3-15

33.

Penney GP, Weese J, Little JA, Desmedt P, Hill DL, Hawkes DJ (1998) A comparison of similarity measures for use in 2-D–3-D medical image registration. IEEE Trans Med Imaging 17(4):586–595

34.

Skerl D, Likar B, Pernus F (2006) A protocol for evaluation of similarity measures for rigid registration. IEEE Trans Med Imaging 25(6):779–791PubMedCrossRef

35.

van der Bom MJ, Bartels LW, Gounis MJ, Homan R, Timmer J, Viergever MA, Pluim JPW (2010) Robust initialization of 2D–3D image registration using the projection-slice theorem and phase correlation. Med Phys 37(4):1884–1892PubMedCrossRef

36.

Miao S, Lucas J, Liao R (2012) Automatic pose initialization for accurate 2D/3D registration applied to abdominal aortic aneurysm endovascular repair. In: Proceedings of SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 83160Q

37.

Łubniewski PJ, Sarry L, Miguel B, Lohou C (2013) 3D/2D image registration by image transformation descriptors (ITDs) for thoracic aorta imaging. In: Proceedings of SPIE 8650, Three-Dimensional Image Processing (3DIP) and Applications 2013, 86500T

38.

Varnavas A, Carrell T, Penney G (2013) Increasing the automation of a 2D–3D registration system. IEEE Trans Med Imaging 32(2):387–399PubMedCrossRef

39.

Vermandel M, Betrouni N, Gauvrit J-Y, Pasquier D, Vasseur C, Rousseau J (2006) Intrinsic 2D/3D registration based on a hybrid approach: use in the radiosurgical imaging process. Cell Mol Biol (Noisy-le-Grand, France) 52(6):44–53

40.

Kaladji A, Lucas A, Kervio G, Haigron P, Cardon A (2010) Sizing for endovascular aneurysm repair: clinical evaluation of a new automated three-dimensional software. Ann Vasc Surg 24(7):912–920

41.

Kim K, Park S, Hong H, Shin YG (2005) Fast 2D-3D registration using GPU-based preprocessing. In: Proceedings of 7th international workshop on Enterprise networking and Computing in Healthcare Industry, 2005. HEALTHCOM 2005, pp 139–143

42.

Kim J, Li S, Pradhan D, Hammoud R, Chen Q, Yin F-F, Zhao Y, Kim JH, Movsas B (2007) Comparison of similarity measures for rigid-body CT/Dual X-ray image registrations. Technol Cancer Res Treat 6(4):337–346

43.

Pluim JP, Maintz JB, Viergever MA (2000) Image registration by maximization of combined mutual information and gradient information. IEEE Trans Med Imaging 19(8):809–814PubMedCrossRef

44.

Miao S, Liao R, Pfister M, Zhang L, Ordy V (2013) System and method for 3-D/3-D registration between non-contrast-enhanced CBCT and contrast-enhanced CT for abdominal aortic aneurysm stenting. In: Mori K, Sakuma I, Sato Y, Barillot C, Navab N (eds) Medical image computing and computer-assisted intervention—MICCAI 2013. Springer, Berlin, pp 380–387CrossRef

45.

Huynh T, Miao S, Liao R (2014) Model-to-volume registration for endovascular aneurysm repair. In: 2014 IEEE 11th international symposium on biomedical imaging (ISBI). pp 405–408

46.

Demirci S, Baust M, Kutter O, Manstad-Hulaas F, Eckstein H-H, Navab N (2013) Disocclusion-based 2D–3D registration for aortic interventions. Comput Biol Med 43(4):312–322PubMedCrossRef

Title: A versatile intensity-based 3D/2D rigid registration compatible with mobile C-arm for endovascular treatment of abdominal aortic aneurysm
Authors: A. Duménil
A. Kaladji
M. Castro
C. Göksu
A. Lucas
P. Haigron
Publication date: 01-09-2016
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 9/2016
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-016-1416-1

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Purpose

Methods

Results

Conclusion

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Purpose

Methods

Results

Conclusion

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