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Proceedings Paper

Multi-parametric MRI-pathologic correlation of prostate cancer using tracked biopsies
Author(s): Sheng Xu; Baris Turkbey; Jochen Kruecker; Pingkun Yan; Julia Locklin; Peter Pinto; Peter Choyke; Bradford Wood
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Paper Abstract

MRI is currently the most promising imaging modality for prostate cancer diagnosis due to its high resolution and multiparametric nature. However, currently there is no standard for integration of diagnostic information from different MRI sequences. We propose a method to increase the diagnostic accuracy of MRI by correlating biopsy specimens with four MRI sequences including T2 weighted MRI, Diffusion Weight Imaging, Dynamic Contrast Enhanced MRI and MRI spectroscopy. This method uses device tracking and image fusion to determine the specimen's position on MRI images. The proposed method is unbiased and cost effective. It does not substantially interfere with the standard biopsy workflow, allowing it to be easily accepted by physicians. A study of 41 patients was carried out to validate the approach. The performance of all four MRI sequences in various combinations is reported. Guidelines are given for multi-parametric imaging and tracked biopsy of prostate cancer.

Paper Details

Date Published: 23 February 2010
PDF: 8 pages
Proc. SPIE 7625, Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, 76252R (23 February 2010); doi: 10.1117/12.844051
Show Author Affiliations
Sheng Xu, Philips Research North America (United States)
Baris Turkbey, National Institutes of Health (United States)
Jochen Kruecker, Philips Research North America (United States)
Pingkun Yan, Philips Research North America (United States)
Julia Locklin, National Institutes of Health (United States)
Peter Pinto, National Institutes of Health (United States)
Peter Choyke, National Institutes of Health (United States)
Bradford Wood, National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 7625:
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; Michael I. Miga, Editor(s)

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