Abstract
In the United States, unenhanced CT is currently the most common imaging modality used to guide percutaneous biopsy and tumor ablation. The majority of liver tumors such as hepatocellular carcinomas are visible on contrast-enhanced CT or MRI obtained prior to the procedure. Yet, these tumors may not be visible or may have poor margin conspicuity on unenhanced CT images acquired during the procedure. Non-rigid registration has been used to align images accurately, even in the presence of organ motion. However, to date, it has not been used clinically for radiofrequency ablation (RFA), since it requires significant computational infrastructure and often these methods are not sufficient robust. We have already introduced a novel finite element based method (FEM) that is demonstrated to achieve good accuracy and robustness for the problem of brain shift in neurosurgery. In this current study, we adapt it to fuse pre-procedural MRI with intra-procedural CT of liver. We also compare its performance with conventional rigid registration and two non-rigid registration methods: b-spline and demons on 13 retrospective datasets from patients that underwent RFA at our institution. FEM non-rigid registration technique was significantly better than rigid (p<10-5), non-rigid b-spline (p<10-4) and demons (p<10-4) registration techniques. The results of our study indicate that this novel technology may be used to optimize placement of RF applicator during CT-guided ablations.
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Silverman, S.G., Tuncali, K., Morrison, P.: MR Imaging-guided percutaneous tumor ablation(1). Acad. Radiol. 12(9), 1100–1109 (2005)
Rohr, K.: Elastic Registration of Multimodal Medical Images: A Survey 14(3) (2000)
Fei, B., Duerk, J.L., Boll, D.T., Lewin, J.S., Wilson, D.: Slice-to-volume registration and its potential application to interventional MRI-guided radio-frequency thermal ablation of prostate cancer. IEEE Trans. Med. Imaging 22(4), 515–525 (2003)
Carrillo, A., Duerk, J.L., Lewin, J.S., Wilson, D.L.: Semiautomatic 3-D image registration as applied to interventional MRI liver cancer treatment. IEEE TMI 19(3) (2000)
Penney, G.P., et al.: Registration of freehand 3D ultrasound and magnetic resonance liver images. Med. Image. Anal. 8(1), 81–91 (2004)
Bao, P., Warmath, J., Galloway, R., Herline Jr, A.: Ultrasound-to-computer-tomography registration for image-guided laparoscopic liver surgery. Surg. Endosc. 19(3), 424–429 (2005)
Rohlfing, T., Maurer Jr., C.R., O’Dell, W.G., Zhong, J.: Modeling liver motion and deformation during the respiratory cycle using intensity-based nonrigid registration of gated MR images. Med. Phys. 31(3), 427–432 (2004)
Banovac, F., Wilson, E., Zhang, H., Cleary, K.: Needle biopsy of anatomically unfavorable liver lesions with an electromagnetic navigation assist device in a computed tomography environment. J. Vasc. Interv. Radiol. 17(10) (2006)
Clatz, O., Delingette, H., Talos, I.F., Golby, A.J., Kikinis, R., Jolesz, F.A., Ayache, N., Warfield, S.K.: Robust nonrigid registration to capture brain shift from intraoperative MRI. IEEE Trans. Med. Imaging 24(11), 1417–1427 (2005)
Archip, N., Clatz, O., Whalen, S., Kacher, D., Fedorov, A., Kot, A., Chrisochoides, N., Jolesz, F., Golby, A., Black, P.M., Warfield, S.: Non-rigid alignment of pre-operative MRI, fMRI, and DT-MRI with intra-operative MRI for enhanced visualization and navigation in image-guided neurosurgery. Neuroimage (2007)
Chrisochoides, N., Fedorov, A., Kot, A., Archip, N., Black, P., Clatz, O., Golby, A., Kikinis, R., Warfield, S.K.: Toward Real-Time, Image Guided Neurosurgery Using Distributed and Grid Computing. In: Löwe, W., Südholt, M. (eds.) SC 2006. LNCS, vol. 4089, Springer, Heidelberg (2006)
Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L., Leach, M.O., Hawkes, D.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Trans. Med. Imaging 18(8), 712–721 (1999)
Thirion, J.P.: Image matching as a diffusion process: an analogy with Maxwell’s demons. Med. Image. Anal. 2(3), 243–260 (1998)
Studholme, C., Hill, D.L.G., Hawkes, D.J.: An overelap invariant entropy measure of 3D medical image alignment. Pattern Recognition 32(1) (1999)
Soza, G., Grosso, R., Nimsky, C., Hastreiter, P., Fahlbusch, R., Greiner, G.: Determination of the Elasticity Parameters of Brain Tissue with Combined Simulation and Registration. Int. J. Medical Robotics and Computer Assisted Surgery (1, Nr. 3)
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Archip, N., Tatli, S., Morrison, P., Jolesz, F., Warfield, S.K., Silverman, S. (2007). Non-rigid Registration of Pre-procedural MR Images with Intra-procedural Unenhanced CT Images for Improved Targeting of Tumors During Liver Radiofrequency Ablations. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75759-7_117
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DOI: https://doi.org/10.1007/978-3-540-75759-7_117
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