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Multimodal US–gamma imaging using collaborative robotics for cancer staging biopsies

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

The staging of female breast cancer requires detailed information about the level of cancer spread through the lymphatic system. Common practice to obtain this information for patients with early-stage cancer is sentinel lymph node (SLN) biopsy, where LNs are radioactively identified for surgical removal and subsequent histological analysis. Punch needle biopsy is a less invasive approach but suffers from the lack of combined anatomical and nuclear information. We present and evaluate a system that introduces live collaborative robotic 2D gamma imaging in addition to live 2D ultrasound to identify SLNs in the surrounding anatomy.

Methods

The system consists of a robotic arm equipped with both a gamma camera and a stereoscopic tracking system that monitors the position of an ultrasound probe operated by the physician. The arm cooperatively places the gamma camera parallel to the ultrasound imaging plane to provide live multimodal visualization and guidance. We validate the system by evaluating the target registration errors between fused nuclear and US image data in a phantom consisting of two spheres, one of which is filled with radioactivity. Medical experts perform punch biopsies on agar–gelatine phantoms with complex configurations of hot and cold lesions to provide a qualitative and quantitative evaluation of the system.

Results

The average point registration error for the overlay is \(1.12 \pm 0.57\) mm. The time of the entire procedure was reduced by 36 %, with 80v of the biopsies being successful. The users’ feedback was very positive, and the system was deemed to be very intuitive, with handling similar to classic US-guided needle biopsy.

Conclusion

We present and evaluate the first medical collaborative robotic imaging system. Feedback from potential users for SLN punch needle biopsy is encouraging. Ongoing work investigates the clinical feasibility with more complex and realistic phantoms.

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Authors and Affiliations

  1. Computer Aided Medical Procedures (CAMP), Technische Universität München, Munich, Germany

    Marco Esposito, Benjamin Busam, Christoph Hennersperger, Julia Rackerseder, Nassir Navab & Benjamin Frisch

  2. FRAMOS GmbH, Taufkirchen, Germany

    Benjamin Busam

  3. Computer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, US

    Nassir Navab

Authors
  1. Marco Esposito
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  2. Benjamin Busam
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  3. Christoph Hennersperger
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  4. Julia Rackerseder
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  5. Nassir Navab
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  6. Benjamin Frisch
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Corresponding author

Correspondence to Marco Esposito.

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Ethical disclosure

This article does not contain any studies with human participants or animals performed by any of the authors. This article does not contain patient data.

Funding

This work was partially funded by the Bayerische Forschungsstiftung award number AZ-1072-13 (project RoBildOR).

Conflict of interest

Benjamin Busam is an employee of FRAMOS GmbH, Taufkirchen, Germany. The other authors declare no conflict of interest.

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Esposito, M., Busam, B., Hennersperger, C. et al. Multimodal US–gamma imaging using collaborative robotics for cancer staging biopsies. Int J CARS 11, 1561–1571 (2016). https://doi.org/10.1007/s11548-016-1464-6

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  • DOI: https://doi.org/10.1007/s11548-016-1464-6

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