Prostate cancer is the most common malignancy and third leading cause of cancer-related mortality in American men. Due to the ageing "baby boomers", the number of men with localized prostate cancer will increase, as will the need for an accurate non-invasive imaging tool. Magnetic Resonance (MR) imaging has the ability to deliver precise anatomical mapping of tumor. Newer MR techniques allow for pharmacokinetic (PK) evaluation of prostate tissue. This functional aspect of MR imaging could contribute greatly to the accuracy of tumor detection and localization, and potentially serve as a guide for focal ablative therapy, or non-invasively assess functional aspects of prostate tissue microcirculation in response to neoadjuvant treatment. The objective of this study is therefore to determine if optimized MR analysis tools and algorithms can be used as a biomarker guide for targeted therapy and as a surrogate for disease recurrence in prostate cancer. We plan to achieve our objective through 4 specific aims: 1. To develop and implement imaging methodology and analysis tools for automated, robust quantitative assessment of prostate tumor volumetry and assessment of the functional properties (vascularity and permeability) using quantitative multi-parametric MR imaging (mpMRI). 2. To clinically validate the prostate mpMRI quantitative analysis tools described in Aim 1. We will perform a multivariate analysis of the results of the analyses tools, and patient-specific parameter maps for tumor localization (a summary statistic display) will be obtained and correlated with pathology at prostatectomy. 3. To determine the clinical use of the analysis tools as a biomarker guide for targeted therapy and as a surrogate for disease recurrence in low-risk prostate cancer patients. We will obtain mpMRI maps, detailing the index lesion and its margins, and register them with focal ablative therapy treatment planning images. Follow up mpMRI maps will be registered the pre-treatment maps to detect changes, and will be correlated with PSA to determine the "expected" treatment margin and untreated prostate mpMRI characteristics. 4. To determine the clinical use of the analysis tools in evaluating tumor response to treatment with neoadjuvant androgen deprivation therapy (ADT) in patients with high-risk prostate cancer. We will assess the changes in mpMRI maps after 12 weeks of ADT to determine if prostate tumor vascular permeability changes may be a suitable predictor of pathological response, by correlation with prostatectomy specimens.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA151261-04
Application #
8504789
Study Section
Special Emphasis Panel (ZCA1-SRLB-V (M1))
Program Officer
Nordstrom, Robert J
Project Start
2010-09-22
Project End
2015-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
4
Fiscal Year
2013
Total Cost
$321,752
Indirect Cost
$108,734
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Yankeelov, Thomas E; Mankoff, David A; Schwartz, Lawrence H et al. (2016) Quantitative Imaging in Cancer Clinical Trials. Clin Cancer Res 22:284-90
Huang, Wei; Chen, Yiyi; Fedorov, Andriy et al. (2016) The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge. Tomography 2:56-66
Fedorov, Andriy; Tuncali, Kemal; Panych, Lawrence P et al. (2016) Segmented diffusion-weighted imaging of the prostate: Application to transperineal in-bore 3T MR image-guided targeted biopsy. Magn Reson Imaging 34:1146-54
Glazer, Daniel I; Hassanzadeh, Elmira; Fedorov, Andriy et al. (2016) Diffusion-weighted endorectal MR imaging at 3T for prostate cancer: correlation with tumor cell density and percentage Gleason pattern on whole mount pathology. Abdom Radiol (NY) :
Fedorov, Andriy; Clunie, David; Ulrich, Ethan et al. (2016) DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research. PeerJ 4:e2057
Mehrtash, Alireza; Gupta, Sandeep N; Shanbhag, Dattesh et al. (2016) Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging. J Med Imaging (Bellingham) 3:014503
Ciris, Pelin Aksit; Balasubramanian, Mukund; Seethamraju, Ravi T et al. (2016) Characterization of gradient echo signal decays in healthy and cancerous prostate at 3T improves with a Gaussian augmentation of the mono-exponential (GAME) model. NMR Biomed 29:999-1009
Hassanzadeh, Elmira; Glazer, Daniel I; Dunne, Ruth M et al. (2016) Prostate imaging reporting and data system version 2 (PI-RADS v2): a pictorial review. Abdom Radiol (NY) :
Yamauchi, Fernando I; Penzkofer, Tobias; Fedorov, Andriy et al. (2015) Prostate cancer discrimination in the peripheral zone with a reduced field-of-view T(2)-mapping MRI sequence. Magn Reson Imaging 33:525-30
Penzkofer, Tobias; Tuncali, Kemal; Fedorov, Andriy et al. (2015) Transperineal in-bore 3-T MR imaging-guided prostate biopsy: a prospective clinical observational study. Radiology 274:170-80

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