The overall aims of this competitive renewal are to continue the development, evaluation and validation of a novel magnetic resonance imaging (MRI) technique that has considerable potential as a sensitive indicator of the state of tumors before and after treatment, and which can provide unique information non-invasively on the microstructure of tissue. Previous studies have convincingly shown that diffusion weighted MRI (DW-MRI) can report on changes in tumors during growth and following treatment, and thus potentially provides a useful indicator of treatment response. However, detectable changes occur only after a critical time has elapsed, when cell density has altered sufficiently, and conventional DW-MRI is not sensitive to earlier or more subtle changes within cells. We have developed an alternative technique, oscillating gradient spin-echo (OGSE) DW- MRI, which is uniquely sensitive to microstructural features much smaller than a cell which restrict the free diffusion of tissue water. OGSE measurements may be sensitized selectively to features of different sizes, they appear to be able to detect changes within cells before there are changes in cell density, and they provide a new type of spectral data which can be analyzed to obtain quantitative structural information. We have shown that OGSE imaging reveals greater heterogeneity within tumors, and at higher contrast, that it should be sensitive to intra-cellular features such as nuclear size, and that it is more sensitive to earlier changes in tumors following treatment. Moreover, OGSE provides unique insights that allow a more complete understanding and interpretation of conventional DW-MRI. In the next phase we propose to apply optimized OGSE methods to measure changes that occur with the growth of tumors, and in response to different, specific treatments, in mouse models in vivo. We will compare the sensitivity of OGSE methods to conventional DWI measurements for detecting changes in tumors after treatment, and hypothesize that early changes are better revealed by OGSE methods than conventional approaches. We will establish how early OGSE methods can detect the response of tumors to treatments, how well these changes predict later outcomes, and which OGSE parameters correlate with changes in cellularity, apoptosis and proliferation. The OGSE data will be correlated with co-registered quantitative histological and immunohistochemical sections of the same tumor to verify the interpretation of the diffusion data. We will also further validate and assist the interpretation of OGSE measurements by performing elaborate computer simulations of water in compartmental systems of appropriate complexity. As a useful reduction technique for describing the data, we will fit OGSE data from in vivo images to models of water diffusing within and between compartments that will permit the extraction of parameters that reflect the sizes, intrinsic water diffusion rates and other structural features of water compartments. Our overall aim is to validate OGSE methods as an experimental tool for pre-clinical studies of tumors and to gain new insight into the causes of changes in water apparent diffusion rates in cancer.

Public Health Relevance

Reliable and sensitive methods for assessing the response of tumors to treatment are critical for the successful management of cancer and as investigational tools in pre-clinical research, but at present there are no accurate, non-invasive methods available to detect early response and predict the outcome of treatment. Repeatable, quantitative, non-invasive imaging methods which can reliably assess tumor response would aid the development of new treatments. The research proposed would provide a new MRI technique for non- invasive imaging of tumors which can be used to detect and assess their response to treatment sooner and more accurately than current methods, and which promises to become a useful tool in preclinical research and provide insights into how better to use current imaging methods.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
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Biomedical Imaging Technology Study Section (BMIT)
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Zhang, Huiming
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Vanderbilt University Medical Center
Schools of Medicine
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By, Samantha; Xu, Junzhong; Box, Bailey A et al. (2018) Multi-compartmental diffusion characterization of the human cervical spinal cord in vivo using the spherical mean technique. NMR Biomed 31:e3894
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