Precision targeting of liver lesions with a needle-based soft tissue navigation system

  • Authors:

  • L. Maier-Hein;F. Pianka;A. Seitel;S. A. Müller;A. Tekbas;M. Seitel;I. Wolf;B. M. Schmied;H.-P. Meinzer

  • Affiliations:

  • German Cancer Research Center, Div. Medical and Biological Informatics, Heidelberg;University of Heidelberg, Dept. of General, Abdominal and Transplant Surgery, Heidelberg, Germany;German Cancer Research Center, Div. Medical and Biological Informatics, Heidelberg;University of Heidelberg, Dept. of General, Abdominal and Transplant Surgery, Heidelberg, Germany;University of Heidelberg, Dept. of General, Abdominal and Transplant Surgery, Heidelberg, Germany;German Cancer Research Center, Div. Medical and Biological Informatics, Heidelberg;German Cancer Research Center, Div. Medical and Biological Informatics, Heidelberg;University of Heidelberg, Dept. of General, Abdominal and Transplant Surgery, Heidelberg, Germany;German Cancer Research Center, Div. Medical and Biological Informatics, Heidelberg

  • Venue:
  • MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
  • Year:
  • 2007

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Abstract

In this study, we assessed the targeting precision of a previously reported needle-based soft tissue navigation system. For this purpose, we implanted 10 2-ml agar nodules into three pig livers as tumor models, and two of the authors used the navigation system to target the center of gravity of each nodule. In order to obtain a realistic setting, we mounted the livers onto a respiratory liver motion simulator that models the human body. For each targeting procedure, we simulated the liver biopsy workflow, consisting of four steps: preparation, trajectory planning, registration, and navigation. The lesions were successfully hit in all 20 trials. The final distance between the applicator tip and the center of gravity of the lesion was determined from control computed tomography (CT) scans and was 3.5 ± 1.1 mm on average. Robust targeting precision of this order of magnitude would significantly improve the clinical treatment standard for various CT-guided minimally invasive interventions in the liver.