Mobile augmented reality for computer-assisted percutaneous nephrolithotomy - Abstract

PURPOSE: Percutaneous nephrolithotomy (PCNL) plays an integral role in treatment of renal stones.

Creating percutaneous renal access is the most important and challenging step in the procedure. To facilitate this step, we evaluated our novel mobile augmented reality (AR) system for its feasibility of use for PCNL.

METHODS: A tablet computer, such as an iPad®, is positioned above the patient with its camera pointing toward the field of intervention. The images of the tablet camera are registered with the CT image by means of fiducial markers. Structures of interest can be superimposed semi-transparently on the video images. We present a systematic evaluation by means of a phantom study. An urological trainee and two experts conducted 53 punctures on kidney phantoms.

RESULTS: The trainee performed best with the proposed AR system in terms of puncturing time (mean: 99 s), whereas the experts performed best with fluoroscopy (mean: 59 s). iPad assistance lowered radiation exposure by a factor of 3 for the inexperienced physician and by a factor of 1.8 for the experts in comparison with fluoroscopy usage. We achieve a mean visualization accuracy of 2.5 mm.

CONCLUSIONS: The proposed tablet computer-based AR system has proven helpful in assisting percutaneous interventions such as PCNL and shows benefits compared to other state-of-the-art assistance systems. A drawback of the system in its current state is the lack of depth information. Despite that, the simple integration into the clinical workflow highlights the potential impact of this approach to such interventions.

Written by:
Müller M, Rassweiler MC, Klein J, Seitel A, Gondan M, Baumhauer M, Teber D, Rassweiler JJ, Meinzer HP, Maier-Hein L.   Are you the author?
Department of Medical and Biological Informatics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.

Reference: Int J Comput Assist Radiol Surg. 2013 Mar 23. Epub ahead of print.
doi: 10.1007/s11548-013-0828-4


PubMed Abstract
PMID: 23526436

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