This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Current diagnostic tests cannot reliably determine prostate cancer extent (volume and location) or biological aggressiveness. The main goal of this research is to realize the full potential of 3 Tesla MRI to generate cancer probability maps by combining the multi-parametric data generated from anatomic and functional studies within a new statistical model. This goal will be accomplished by realizing the following four specific aims: 1) generate parametric maps from MRI data acquired and processed with novel techniques;2) develop and validate a 3-dimensional (3D) strategy to spatially co-register MRI images to histopathology sections from prostatectomy;3) develop a classifier based on 3T MRI data to produce a 3D probability map of cancer;and 4) identify MRI features that predict histological and molecular markers of aggressiveness. Our expected outcome is the development of a novel MRI-based imaging method to non-invasively and reliably determine both the extent and aggressiveness of prostate cancer. It is our hope that the methods developed in this study may permit doctors and their patients to make better treatment decisions and reduce morbidity and mortality due to prostate cancer.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR008079-17
Application #
7954984
Study Section
Special Emphasis Panel (ZRG1-SBIB-S (40))
Project Start
2009-06-01
Project End
2010-05-31
Budget Start
2009-06-01
Budget End
2010-05-31
Support Year
17
Fiscal Year
2009
Total Cost
$25,670
Indirect Cost
Name
University of Minnesota Twin Cities
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
555917996
City
Minneapolis
State
MN
Country
United States
Zip Code
55455
Herzberg, Max P; Hodel, Amanda S; Cowell, Raquel A et al. (2018) Risk taking, decision-making, and brain volume in youth adopted internationally from institutional care. Neuropsychologia 119:262-270
U?urbil, Kamil (2018) Imaging at ultrahigh magnetic fields: History, challenges, and solutions. Neuroimage 168:7-32
Foell, Jens; Palumbo, Isabella M; Yancey, James R et al. (2018) Biobehavioral threat sensitivity and amygdala volume: A twin neuroimaging study. Neuroimage 186:14-21
Magnitsky, Sergey; Pickup, Stephan; Garwood, Michael et al. (2018) Imaging of a high concentration of iron labeled cells with positive contrast in a rat knee. Magn Reson Med :
Lee, Byeong-Yeul; Zhu, Xiao-Hong; Woo, Myung Kyun et al. (2018) Interleaved 31 P MRS imaging of human frontal and occipital lobes using dual RF coils in combination with single-channel transmitter-receiver and dynamic B0 shimming. NMR Biomed 31:
Wilson, Sylia; Malone, Stephen M; Hunt, Ruskin H et al. (2018) Problematic alcohol use and hippocampal volume in a female sample: disentangling cause from consequence using a co-twin control study design. Psychol Med 48:1673-1684
Bolan, Patrick J; Kim, Eunhee; Herman, Benjamin A et al. (2017) MR spectroscopy of breast cancer for assessing early treatment response: Results from the ACRIN 6657 MRS trial. J Magn Reson Imaging 46:290-302
Nelson, Brent G; Bassett, Danielle S; Camchong, Jazmin et al. (2017) Comparison of large-scale human brain functional and anatomical networks in schizophrenia. Neuroimage Clin 15:439-448
Lyzinski, Vince; Fishkind, Donniell E; Fiori, Marcelo et al. (2016) Graph Matching: Relax at Your Own Risk. IEEE Trans Pattern Anal Mach Intell 38:60-73
Ugurbil, Kamil (2016) What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging. Philos Trans R Soc Lond B Biol Sci 371:

Showing the most recent 10 out of 493 publications