By Erik L. Ridley, staff writer
    November 15, 2010

    Sunday, November 28 | 11:55 a.m.-12:05 p.m. | SSA10-08 | Room E353B
    Researchers from the University of Chicago will describe the potential for their prototype computer-aided detection (CAD) software in prostate MRI in this Sunday scientific session.

    Despite its limitations, multiparametric MRI (including T2-weighted imaging, diffusion-weighted imaging, dynamic contrast-enhanced MRI, and MR spectroscopy) is currently the best imaging modality for imaging the prostate and prostate cancer, according to presenter Aytekin Oto, MD. But the burden of analyzing a huge amount of data can be overwhelming for a single radiologist.

    As a result, the researchers sought to develop and test prototype CAD software that allowed for analysis of all MRI parameters using a Bayesian neural network. They found that combining multiple quantitative parameters improves upon the performance of any single parameter in predicting tumor Gleason score.

    Offering a "virtual biopsy" method, computerized analysis of prostate MRI can potentially integrate multiprotocol MR image information and aid in clinical decision making, according to Oto.

    "We expect CAD will allow a more standardized and automated analysis of multiparametric MR data, thereby improving cancer detection results and the reproducibility of the interpretation of MRI data," Oto told "Accurate localization information using CAD-assisted multiparametric MRI may be used to improve the yield and accuracy of prostate biopsies either by performing biopsies under MR guidance or using real-time [transrectal ultrasound] guidance with fusion of the information from multiparametric MRI."

    Last Updated np 11/12/2010 10:37:46 AM

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