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Realtime TRUS/MRI Fusion Targeted-Biopsy for Prostate Cancer: A Clinical Demonstration of Increased Positive Biopsy Rates

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Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention (Prostate Cancer Imaging 2010)

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Abstract

In this paper, a system for fusion of realtime transrectal ultrasound (TRUS) with pre-acquired 3D images of the prostate is presented with a clinical demonstration on a cohort of 101 patients with suspicion of prostate cancer. Electromagnetically tracked biopsy guides for endocavity ultrasound transducers were calibrated and used to fuse MRI-based suspicious lesion locations with ultrasound image coordinates. The prostate shape is segmented from MRI in a semi-automated fashion via a model-based approach, and intraoperative image registration is performed between MR and ultrasound image space to superimpose target fiducials markers on the ultrasound image. In order to align both modalities, a surface model is automatically extracted from 2D swept TRUS images using a partial active shape model, utilizing image features and prior statistics. An automatic prostate motion compensation algorithm can be triggered as needed. The results were used to display live TRUS images fused with spatially corresponding realtime multiplanar reconstructions (MPRs) of the MR image volume. In this study, all patients were scanned with 3T MRI and TRUS for biopsy. Clinical results show significant improvement of target visualization and of positive detection rates during TRUS-guided biopsies. It also demonstrates the feasibility of realtime MR/TRUS image fusion for out-of-gantry procedures.

This work was supported in part by the Intramural Research Program of the NIH Clinical Center and by a Collaborative Research and Development Agreement between NIH and Philips Healthcare.

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Kadoury, S. et al. (2010). Realtime TRUS/MRI Fusion Targeted-Biopsy for Prostate Cancer: A Clinical Demonstration of Increased Positive Biopsy Rates. In: Madabhushi, A., Dowling, J., Yan, P., Fenster, A., Abolmaesumi, P., Hata, N. (eds) Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention. Prostate Cancer Imaging 2010. Lecture Notes in Computer Science, vol 6367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15989-3_7

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  • DOI: https://doi.org/10.1007/978-3-642-15989-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15988-6

  • Online ISBN: 978-3-642-15989-3

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