This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Ovarian cancer is the leading cause of death among women with gynecologic malignancies. An estimated 21,600 cases were diagnosed in 2008 and an estimated 15,500 women died from ovarian cancer that year. Clinical applications of MRI in cancer care have increased with the development of methods to determine cellular density through diffusion-sensitive sequences, and vascular information through dynamic contrast enhanced imaging. Combined with spectroscopy, these MR imaging methods provide a wealth of functional and anatomical information to help characterize tissue. This initial project is an exploratory study across the spectrum of the clinical setting to develop functional MR methods for characterizing ovarian cancer and to evaluate their clinical utility. We propose the following Specific Aim: to acquire anatomic, metabolic and functional data from 3T MRI scans in women with normal ovaries and women with benign or malignant ovarian tumors. This study will involve both anatomic and functional imaging in women with normal ovaries, benign and malignant ovarian tumors. Ovarian pathology results will be compared against pre-surgery imaging results with the purpose of determining if imaging data show tendencies to distinguish between malignant disease, benign disease and normal tissue. The novel and innovative research that we propose will be among the first ever to combine anatomic imaging, MR spectroscopy and dynamic contrast enhanced imaging from high-field MRI of the ovary. Successful completion of this preliminary work will allow us to use high-field MRI of the ovary to address many research questions that represent challenges in ovarian cancer diagnosis and management.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
5P41RR008079-19
Application #
8362861
Study Section
Special Emphasis Panel (ZRG1-SBIB-S (40))
Project Start
2011-06-01
Project End
2012-05-31
Budget Start
2011-06-01
Budget End
2012-05-31
Support Year
19
Fiscal Year
2011
Total Cost
$30,257
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