The overall goals of the proposed research are to develop dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) methods for the simultaneous assessment of tumor perfusion, permeability and cellularity in cerebral and non-cerebral tumors and to evaluate their role as potential surrogate biomarkers of treatment response. As the biophysical basis of DSC-MRI signals acquired in the presence of contrast agent extravasation is more comprehensively characterized it is evident that they reflect additional underlying biological features such as the vascular integrity and/or cellularity, not unlike those interrogated with dynamic contrast enhanced (DCE) MRI and diffusion weighted (DW)-MRI. To this end we propose to develop a DSC- MRI method that enables the simultaneous acquisition of reliable blood flow and blood volume measures, DCE-MRI data and a new imaging metric, the extravascular susceptibility calibration factor, which we propose reflects cellular features such as density and/or spacing. To characterize and validate the proposed method we will compare DSC-MRI, DCE-MRI and quantitative autoradiography derived measures of perfusion (Aim 1) and permeability (Aim 2) in orthotopic brain and breast tumor models. The DSC-MRI based tumor cellularity metric will be characterized in cellular phantoms and tumor tissue, compared with DW-MRI and validated using histology (Aim 3). Finally, given the pre-clinical and clinical success of DCE-MRI and DW-MRI to assess treatment response, we will compare their sensitivity to that of the proposed imaging metrics to asses treatment induced changes in tumor vascular and cellular status (Aim 4). Significance: The validation of the proposed methods would enable the simultaneous acquisition of parameters reflecting perfusion, permeability and cellularity thereby reducing total MRI scan time and contrast agent dose. Such an approach could greatly enhance clinical care by providing an efficient and more comprehensive assessment of tumor treatment response and enabling the application of DSC-MRI methods to non-cerebral tumors.

Public Health Relevance

The proposed research focuses on the development of magnetic resonance imaging methods that provide a more efficient and complete assessment of a tumor's response to treatment. Such methods could decrease health care costs, contrast agent dose and improve the way treatments are planned and monitored.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA158079-04
Application #
8703037
Study Section
Medical Imaging Study Section (MEDI)
Program Officer
Zhang, Huiming
Project Start
2011-09-16
Project End
2016-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
4
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
City
Nashville
State
TN
Country
United States
Zip Code
37212
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Quarles, C Chad; Bell, Laura C; Stokes, Ashley M (2018) Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI. Neuroimage :
Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura et al. (2018) Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies. J Med Imaging (Bellingham) 5:011006
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Newitt, David C; Malyarenko, Dariya; Chenevert, Thomas L et al. (2018) Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network. J Med Imaging (Bellingham) 5:011003
Bell, L C; Does, M D; Stokes, A M et al. (2017) Optimization of DSC MRI Echo Times for CBV Measurements Using Error Analysis in a Pilot Study of High-Grade Gliomas. AJNR Am J Neuroradiol 38:1710-1715
Sorace, Anna G; Syed, Anum K; Barnes, Stephanie L et al. (2017) Quantitative [18F]FMISO PET Imaging Shows Reduction of Hypoxia Following Trastuzumab in a Murine Model of HER2+ Breast Cancer. Mol Imaging Biol 19:130-137
Bell, Laura C; Hu, Leland S; Stokes, Ashley M et al. (2017) Characterizing the Influence of Preload Dosing on Percent Signal Recovery (PSR) and Cerebral Blood Volume (CBV) Measurements in a Patient Population With High-Grade Glioma Using Dynamic Susceptibility Contrast MRI. Tomography 3:89-95
Semmineh, Natenael B; Stokes, Ashley M; Bell, Laura C et al. (2017) A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. Tomography 3:41-49
Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M et al. (2017) Radiogenomics to characterize regional genetic heterogeneity in glioblastoma. Neuro Oncol 19:128-137

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