Abstract
Purpose
Radiofrequency ablation for liver tumors (liver RFA) is widely performed under ultrasound guidance. However, discriminating between the tumor and the needle is often difficult because of cavitation caused by RFA-induced coagulation. An unclear ultrasound image can lead to complications and tumor residue. Therefore, image-guided navigation systems based on fiducial registration have been developed. Fiducial points are usually set on a patient’s skin. But the use of internal fiducial points can improve the accuracy of navigation. In this study, a new device is introduced to use internal fiducial points using 2D US.
Methods
3D Slicer as the navigation software, Polaris Vicra as the position sensor, and two target tumors in a 3D abdominal phantom as puncture targets were used. Also, a new device that makes it possible to obtain tracking coordinates in the body was invented. First, two-dimensional reslice images from the CT images using 3D Slicer were built. A virtual needle was displayed on the two-dimensional reslice image, reflecting the movement of the actual needle after fiducial registration. A phantom experiment using three sets of fiducial point configurations: one conventional case using only surface points, and two cases in which the center of the target tumor was selected as a fiducial point was performed. For each configuration, one surgeon punctured each target tumor ten times under guidance from the 3D Slicer display. Finally, a statistical analysis examining the puncture error was performed.
Results
The puncture error for each target tumor decreased significantly when the center of the target tumor was included as one of the fiducial points, compared with when only surface points were used.
Conclusion
This study introduces a new device to use internal fiducial points and suggests that the accuracy of image-guided navigation systems for liver RFA can be improved by using the new device.
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References
McGahan JP, Browning PD, Brock JM, Tesluk H (1990) Hepatic ablation using radiofrequency electrocautery. lnvest Radiol 25:267–270
Rossi S, Fornari F, Pathies C (1990) Thermal lesions induced by 480 KHz localized current. Field in gunea pig and pig liver. Tumori 76:54–57
Rossi S, Di Stasi M, Buscarini E (1995) Percutaneous radiofrequency interstitial thermal ablation in the treatment of small hepatocellular carcinoma. Cancer J Sci Am 1:73–81
Hasegawa K, Kokudo N, Makuuchi M, Izumi N, Ichida T, Kudo M, Ku Y, Sakamoto M, Nakashima O, Matsui O (2013) Comparison of resection and ablation for hepatocellular carcinoma: a cohort study based on a Japanese nationwide survey. J Hepatol 58:724–729
Livraghi T, Solbiati L, Meloni MF, Gazelle GS, Halpern EF, Goldberg SN (2003) Treatment of focal liver tumors with percutaneous radio frequency ablation: complications encountered in a multicenter study. Radiology 226:441–451
Nakazawa T, Kokubu S, Shibuya A, Ono K, Watanabe M, Hidaka H (2007) Radiofrequency ablation of hepatocellular carcinoma: correlation between local tumor progression after ablation and ablative margin. Am J Roentgenol 188:480–488
Livraghi T, Goldberg SN, Lazzaroni S, Meloni F, Ierace T, Solbiati L (2000) Hepatocellular carcinoma: radiofrequency ablation of medium and large lesions. Radiology 214:761–768
Stoll J, Ren H, Dupont PE (2012) Passive markers for tracking surgical instruments in real-time 3D ultrasound imaging. IEEE Trans Med Imaging 31(3):563–575
Banovac F, Tang J, Xu S (2005) Precision targeting of liver lesions using a novel electromagnetic navigation device in physiologic phantom and swine. Med Phys 32:2698–705
Krücker J, Xu S, Glossop N (2007) Electromagnetic tracking for thermal ablation and biopsy guidance: clinical evaluation of spatial accuracy. J Vasc Interv Radiol 18:1141–1150
Krücker J, Xu S, Venkatesan A, Locklin JK, Amalo H, Glossop N, Wood BJ (2011) Clinical utility of real-time fusion guidance for biopsy and ablation. J Vasc Interv Radiol 22:515–524
Nicolau SA, Pennec X, Soler L (2009) An augmented reality system for liver thermal ablation: design and evaluation on clinical cases. Med Image Anal 13:494–506
Hong J, Nakashima H, Konishi K (2006) Interventional navigation for abdominal therapy based on simultaneous use of MRI and ultrasound. Med Biol Eng Comput 44:1127–1134
Marescaux J, Diana M, Soler L (2013) Augmented reality and minimally invasive surgery. J Gastroenterol Hepatol Res 2(5):555–560
Ren H, Campos-Nanez E, Yaniv Z, Banovac F, Abeledo H, Hata N, Cleary K (2014) Treatment planning and image guidance for radiofrequency ablation of large tumors. IEEE J Biomed Health Inform 18(3):920–928
Fitzpatrick JM, West JB, Maurer CR Jr (1998) Predicting error in rigid-body point-based registration. IEEE Trans Med Imaging 17:694–702
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin JC, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward S, Miller JV, Pieper S, Kikinis R (2012) 3D Slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30(9):1323–1341. doi:10.1016/j.mri.2012.05.001
Lasso A, Heffter T, Rankin A, Pinter C, Fichtinger G (2014) PLUS: open-source toolkit for ultrasound-guided intervention systems. IEEE Trans Biomed Eng 61(10):2527–2537
Tokuda J, Fischer GS, Papademetris X, Yaniv Z, Ibanez L, Cheng P, Liu H, Blevins J, Arata J, Golby AJ, Kapur T, Pieper S, Burdette EC, Fichtinger G, Tempany CM, Hata N (2009) OpenlGTLink: an open network protocol for image-guided therapy environment. Int J Med Robot Comput Assist Surg 5(4):423–434
Ordas S, Yaniv Z, Cheng P, Tokuda J, Liu H, Hata N, Cleary K (2009) Interfacing proprietary hardware with the Image-Guided Surgery Toolkit (IGSTK): a case for the OpenIGTLink protocol. In: Proceedings of SPIE medical imaging, image processing, p 7264
Wiles AD, Thompson DG, Donald D (2004) Accuracy assessment and interpretation for optical tracking systems. Proc SPIE 5367:421–432
Porter BC, Rubens DJ, Strang JG, Smith J, Totterma S, Parker KJ (2001) Three-dimensional registration and fusion of ultrasound and MRI using major vessels as fiducial markers. IEEE Trans Med Imaging 20(4):354–359
Penney GP, Blackall JM, Hamady MS, Sabharwal T, Adam A, Hawkes DJ (2004) Registration of freehand 3D ultrasound and magnetic resonance liver images. Med Image Anal 8(1):81–91
Wein W, Brunke S, Khamene A, Callstrom MR, Navab N (2008) Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention. Med Image Anal 12(5):577–585
Lange T, Papenberg N, Heldmann S, Modersitzki J, Fischer B, Lamecker H (2009) Schlag PM.3D ultrasound-CT registration of the liver using combined landmark-intensity. Information 4(1):79–88
Weon C, Hyun Nam W, Lee D, Lee JY, Ra JB (2015) Position tracking of moving liver lesion based on real-time registration between 2D ultrasound and 3D preoperative images. Med Phys 42(1):335–347
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Doba, N., Fukuda, H., Numata, K. et al. A new device for fiducial registration of image-guided navigation system for liver RFA. Int J CARS 13, 115–124 (2018). https://doi.org/10.1007/s11548-017-1647-9
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DOI: https://doi.org/10.1007/s11548-017-1647-9