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Virtual reality navigation system for prostate biopsy

Published:08 November 2017Publication History

ABSTRACT

Prostate cancer is the most common non-cutaneous cancer in America. Tumor detection involves non-invasive screening tests, but positive results must be confirmed by a prostate biopsy. About twelve random samples are obtained during the biopsy, which is a systematic procedure traditionally performed with trans-rectal ultrasound (TRUS) guidance to determine prostate location. Recently, methods of fusion between TRUS and preoperative MRI have been introduced in order to perform targeted biopsies aimed to reduce the number of samples to few suspicious areas. Since the TRUS displaces the prostate during the procedure, the preoperative MRI does not match patient anatomy. Therefore, complex MRI deformation algorithms are needed. However, despite the substantial increase in complexity and cost, there is no strong evidence that the TRUS-MRI fusion actually improves accuracy and surgical outcomes.

This paper presents an innovative virtual reality surgical navigation system for performing targeted prostate biopsies, without the need of the uncomfortable TRUS. Both biopsy needle and patient anatomy are constantly tracked by an electromagnetic tracking system that provides their 3D position and orientation with respect to the surgical bed. Multiple fiducial markers are placed on the patient skin (at the iliac crest and pubic bone) during MRI scanning. Once in the operative room, the surgeon is presented a stereoscopic 3D volumetric rendering and multiple orthogonal views of the patient anatomy, as well as a virtual representation of the tracked needle. After a simple registration process between the MRI and the tracker coordinate system, the navigation system guides the needle insertion in the patient perineum through several anatomical layers towards the biopsy targets.

References

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        cover image ACM Conferences
        VRST '17: Proceedings of the 23rd ACM Symposium on Virtual Reality Software and Technology
        November 2017
        437 pages
        ISBN:9781450355483
        DOI:10.1145/3139131

        Copyright © 2017 ACM

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        Publication History

        • Published: 8 November 2017

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