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Journal of Endourology
Aid to Percutaneous Renal Access by Virtual Projection of the Ultrasound Puncture Tract onto Fluoroscopic Images

To cite this article:
Pierre Mozer, Pierre Conort, Antoine Leroy, Michael Baumann, Yohan Payan, Jocelyne Troccaz, Emmanuel Chartier-Kastler, François Richard. Journal of Endourology. May 2007, 21(5): 460-465. doi:10.1089/end.2006.0168.

Published in Volume: 21 Issue 5: May 24, 2007

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Pierre Mozer, M.D.
Service d'Urologie, Groupe Hospitalier Pitié-Salpétrière, Paris, France.
Pierre Conort, M.D.
Service d'Urologie, Groupe Hospitalier Pitié-Salpétrière, Paris, France.
Antoine Leroy, Ph.D.
Laboratoire TIMC/IMAG, Université Joseph Fourier, La Tronche, France.
Michael Baumann, M.sc.
Laboratoire TIMC/IMAG, Université Joseph Fourier, La Tronche, France.
Yohan Payan, Ph.D.
Laboratoire TIMC/IMAG, Université Joseph Fourier, La Tronche, France.
Jocelyne Troccaz, Ph.D.
Laboratoire TIMC/IMAG, Université Joseph Fourier, La Tronche, France.
Emmanuel Chartier-Kastler, M.D., Ph.D.
Service d'Urologie, Groupe Hospitalier Pitié-Salpétrière, Paris, France.
François Richard, M.D.
Service d'Urologie, Groupe Hospitalier Pitié-Salpétrière, Paris, France.

Background and Purpose: Percutaneous renal access in the context of percutaneous nephrolithotomy (PCNL) is a difficult technique, requiring rapid and precise access to a particular calix. We present a computerized system designed to improve percutaneous renal access by projecting the ultrasound puncture tract onto fluoroscopic images.

Materials and Methods: The system consists of a computer and a localizer allowing spatial localization of the position of the various instruments. Without any human intervention, the ultrasound nephrostomy tract is superimposed in real time onto fluoroscopic images acquired in various views.

Results: We tested our approach by laboratory experiments on a phantom. Also, after approval by our institution's Ethics Committee, we validated this technique in the operating room during PCNL in one patient.

Conclusion: Our system is reliable, and the absence of image-processing procedures makes it robust. We have initiated a prospective study to validate this technique both for PCNL specialists and as a learning tool.

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