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Towards markerless navigation for percutaneous needle insertions

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Abstract

Purpose

Percutaneous needle insertions are increasingly used for diagnosis and treatment of abdominal lesions. The challenging part of computed tomography (CT)-guided punctures is the transfer of the insertion trajectory planned in the CT image to the patient. Conventionally, this often results in several needle repositionings and control CT scans. To address this issue, several navigation systems for percutaneous needle insertions have been presented; however, none of them has thus far become widely accepted in clinical routine. Their benefit for the patient could not exceed the additional higher costs and the increased complexity in terms of bulky tracking systems and specialized markers for registration and tracking.

Methods

We present the first markerless and trackerless navigation concept for real-time patient localization and instrument guidance. It has specifically been designed to be integrated smoothly into the clinical workflow and does not require markers or an external tracking system. The main idea is the utilization of a range imaging device that allows for contactless and radiation-free acquisition of both range and color information used for patient localization and instrument guidance.

Results

A first feasibility study in phantom and porcine models yielded a median targeting accuracy of 6.9 and 19.4 mm, respectively.

Conclusions

Although system performance remains to be improved for clinical use, expected advances in camera technology as well as consideration of respiratory motion and automation of the individual steps will make this approach an interesting alternative for guiding percutaneous needle insertions.

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Notes

  1. Note that the range data could as well be used to generate tracking information when post-processed with an instrument/object tracking algorithm (e.g., [39]). With the term tracking system, we refer to the widely applied definition where specialized hardware (cameras and tracking markers) are used for generating tracking information.

  2. This porcine trial was approved by the Committee for Animal Care and Research of the Karlsruhe regional council (G-83/12).

  3. The statistical power of these calculations (\(n = 10\)) may still not be sufficient to reliably detect significant differences.

    Fig. 8
    figure 8

    Targeting accuracies and registration error of the phantom study (“Phantom study’ section) with the markerless navigation system for PMD CamCube 3.0 and Microsoft Kinect for Xbox 360. The box plots show the targeting error divided into the overall error, the longitudinal error and the lateral error as well as the registration accuracy as the fiducial registration error (FRE) for all trials (\(N = 10\)) in mm (median, mininimum/maximum, upper/lower quartile)

    Full size image

  4. Note that one trial was not considered in the error calculation due to an erroneous visualization of the implemented prototype which can easily be fixed in future versions.

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Acknowledgments

This work was conducted within the settings of Research Training Group 1126: “Intelligent Surgery” funded by the German Research Foundation (DFG) and was partly supported by the DFG grant PD 15577. The authors would further like to thank Martina Jochim from the Department of Radiology at the German Cancer Research Center (DKFZ) for the assistance during the CT acquisitions, Adrian Winterstein for his help during the porcine trial and Christian Stock from the University Hospital Heidelberg for his statistical advise.

Conflict of interest

A. Seitel, N. Bellemann, M. Hafezi, A. Franz, M. Servatius, A. Saffari, T. Kilgus, H.-P. Schlemmer, A. Mehrabi, B. Radeleff and L. Maier-Hein declare that they have no conflict of interest.

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Author notes

  1. Alexander Seitel

    Present address: The Robotics and Control Laboratory, University of British Columbia, Vancouver, Canada

Authors and Affiliations

  1. Junior Group: Computer-Assisted Interventions, German Cancer Research Center (DKFZ), Heidelberg, Germany

    Alexander Seitel, Alfred M. Franz, Thomas Kilgus & Lena Maier-Hein

  2. Department of Diagnostic and Interventional Radiology, University Clinic Heidelberg, Heidelberg, Germany

    Nadine Bellemann, Mark Servatius & Boris A. Radeleff

  3. Department of General, Visceral and Transplant Surgery, University Clinic Heidelberg, Heidelberg, Germany

    Mohammadreza Hafezi, Arash Saffari & Arianeb Mehrabi

  4. Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

    Heinz-Peter Schlemmer

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  1. Alexander Seitel
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Correspondence to Alexander Seitel.

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Seitel, A., Bellemann, N., Hafezi, M. et al. Towards markerless navigation for percutaneous needle insertions. Int J CARS 11, 107–117 (2016). https://doi.org/10.1007/s11548-015-1156-7

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