A fundamental need exists to determine whether pulmonary lesions detected on a cancer patient's high- resolution CT scan are metastatic disease. While CT has extraordinary sensitivity, it lacks the specificity to make this critical distinction. The long-term goal of our research, therefore, is to develop a new tomographic imaging method to non-invasively tag and detect cancer cells in the lungs with molecular specificity and high resolution. Our approach uses hyperpolarized (HP) gas MR imaging to visualize cancer cells that have been targeted by tumor-specific functionalized Iron Oxide Nanoparticles (SPIONs). The objective of this application is to optimize this demonstrated method in mouse models of metastatic cancer, establish its theoretical and practical detection limits, and directly compare this method to micro-CT, while using histology to establish ground truth. The central hypothesis is that this new imaging method will surpass the sensitivity of CT, while adding the molecular specificity needed to distinguish metastatic from benign lesion. The rationale for the proposed research is that development of a technique that can non-invasively characterize pulmonary nodules with high sensitivity and specificity will not only improve patient outcomes, but also drive progress in lung cancer research. Thus, the proposed research is relevant to that part of the NIH Mission that pertains to improving health by developing and accelerating the application of biomedical technologies. Guided by strong preliminary data, the central hypothesis will be tested by pursuing three Specific Aims: 1) Establish the theoretical and practical detection limits, 2) Optimize the image acquisition, SPION delivery, and tumor visualization methods, and 3) Directly compare the method's sensitivity and specificity against CT. Completion of these aims will position this technology for clinical translation.
The first aim establishes a theoretical model of SPION image contrast and validates the model by imaging HP gas flowing through a phantom containing well- characterized, and progressively smaller distributions of SPIONs.
The second aim will develop and test an image acquisition strategy to increase sensitivity, optimize intravenous delivery of SPIONs to enable imaging pre- and post-SPION targeting, and implement an enhanced image analysis approach to further increase the detection sensitivity of the method.
The final aim compares the fully optimized method against micro-CT to image mouse models of metastatic cancer mixed with non-cancerous lesions. The proposed approach is innovative because it combines two cutting-edge technologies to take a potential quantum leap in molecular imaging of cancer cells in the lung-an organ that has historically posed enormous imaging challenges. The proposed research is significant because the imaging method being developed opens up an entirely new capacity for sensitive detection and molecular characterization of pulmonary metastases, and more broadly enables high-resolution molecular imaging in the lung to become feasible.

Public Health Relevance

The proposed studies will develop a minimally invasive imaging technique to enable physicians to determine whether pulmonary lesions detected on a cancer patient's x-ray CT scan are metastases. Such information permits the physician to administer the right therapy at the earliest possible stage in the patient's treatment. The proposed research has relevance to public health because new tools in imaging pulmonary cancers will not only improve patient treatment, but will also accelerate research to develop better therapies.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA142842-01A1
Application #
7899668
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Tandon, Pushpa
Project Start
2010-04-01
Project End
2015-01-31
Budget Start
2010-04-01
Budget End
2011-01-31
Support Year
1
Fiscal Year
2010
Total Cost
$332,089
Indirect Cost
Name
Duke University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
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