In a large number of men in whom prostate cancer has been newly discovered, the standard evaluations in current clincal practice primarily serve as a counseling tool regarding the probability of their tumor being a specific pathologic stage, rather than as a strict decision-making tool for the individual. Key elements for guiding appropriate treatments in the individual include, distinction of organ-confined disease from extracapsular extension (ECE), a determination of total tumor burden and a determination of tumor grade, none of which are satisfactory accomplished in today's pre-treatment paradigm. A more comprehensive and objective means to characterize prostate cancer after its detection and prior to therapy would be very useful for clinical practice. This proposal introduces 3T endorectal coil MRI, both for structure and function, to provide a non-invasive pre-treatment tool that can 1) detect extra-capsular spread, 2) detect and quantify specific areas within the prostate that harbor cancer, 3) determine the aggressiveness of the cancer. The imaging strategy we are proposing acquires higher-resolution images with smaller voxel sizes than has been possible with prior MR technology and more comprehensive tissue sampling compared to other pre- surgical assessments. The results of pre-operative T2-weighted imaging, dynamic contrast-enhanced 3D imaging and MR spectroscopy will be compared to whole mount pathology specimens. Our long-term goal is to provide a non-invasive, pre-treatment evaluation of patients with prostate cancer that can more fully characterize the disease to assist clinicians in their efforts to more objectively and rationally select appropriate treatments. Furthermore, such a capacity can aid in the assessment of new treatment strategies and has the potential to assist in the management of important clinical scenarios such as: a) patients electing a 'watchful waiting' approach to their disease and b) those patients with elevated PSAs and repeat negative biopsies. Ultimately, we hope to further improve the numbers and percentage of cancers that receive curative therapy and maximize the quality of life during and following therapy. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA116465-03
Application #
7482199
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Zhang, Huiming
Project Start
2006-09-26
Project End
2010-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
3
Fiscal Year
2008
Total Cost
$366,158
Indirect Cost
Name
Beth Israel Deaconess Medical Center
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02215
Costa, Daniel N; Bloch, B Nicolas; Yao, David F et al. (2013) Diagnosis of relevant prostate cancer using supplementary cores from magnetic resonance imaging-prompted areas following multiple failed biopsies. Magn Reson Imaging 31:947-52
Bloch, B Nicolas; Genega, Elizabeth M; Costa, Daniel N et al. (2012) Prediction of prostate cancer extracapsular extension with high spatial resolution dynamic contrast-enhanced 3-T MRI. Eur Radiol 22:2201-10
Bulman, Julie C; Toth, Robert; Patel, Amish D et al. (2012) Automated computer-derived prostate volumes from MR imaging data: comparison with radiologist-derived MR imaging and pathologic specimen volumes. Radiology 262:144-51
Eyal, Erez; Bloch, B Nicolas; Rofsky, Neil M et al. (2010) Principal component analysis of dynamic contrast enhanced MRI in human prostate cancer. Invest Radiol 45:174-81
McMahon, Colm J; Bloch, B Nicolas; Lenkinski, Robert E et al. (2009) Dynamic contrast-enhanced MR imaging in the evaluation of patients with prostate cancer. Magn Reson Imaging Clin N Am 17:363-83
Lenkinski, Robert E; Bloch, B Nicolas; Liu, Fangbing et al. (2008) An illustration of the potential for mapping MRI/MRS parameters with genetic over-expression profiles in human prostate cancer. MAGMA 21:411-21
Bloch, B Nicolas; Lenkinski, Robert E; Rofsky, Neil M (2008) The role of magnetic resonance imaging (MRI) in prostate cancer imaging and staging at 1.5 and 3 Tesla: the Beth Israel Deaconess Medical Center (BIDMC) approach. Cancer Biomark 4:251-62
Viswanath, Satish; Bloch, B Nicolas; Genega, Elisabeth et al. (2008) A comprehensive segmentation, registration, and cancer detection scheme on 3 Tesla in vivo prostate DCE-MRI. Med Image Comput Comput Assist Interv 11:662-9