One of the greatest strengths of positron emission tomography (PET) is the ability to image any of a number of molecular or physiologic targets using different radiotracers. The clinical utility of PET is well- established for cancer detection and staging. The development of new tracers for imaging metabolism, proliferation, blood flow and numerous other molecular targets offers almost unlimited potential for image- guided personalized medicine. However, much of this potential remains unrealized because current technology permits only one PET tracer to be imaged at a time-multiple scanning sessions need to be scheduled, often on different days, resulting in high costs, image alignment issues, and a long and onerous experience for the patient. Recent advances have shown that it is technically feasible to image 2-3 PET tracers in a single scan using staggered injections and dynamic imaging. Measures of each tracer can be recovered using "signal-separation" algorithms based on kinetic constraints for each tracer. This project will continue development of such rapid multi-tracer imaging technologies, with emphasis on developing specific methods of immediate value and translation to clinical patient imaging. Four tracers will be studied: 18F-fluorodeoxyglucose (FDG) as a marker for glucose metabolism;18F-fluorothymidine (FLT) for proliferation;11C-acetate (ACE) for lipid synthesis and related growth;and 15O-water (H2O) for blood flow and volume of distribution.
Aim 1 will develop and test methods for rapid dual- and triple-tracer imaging of FDG, FLT, and ACE in a single scan, targeting total scan times of ~70 min. for dual-tracer, and 90-120 min. for triple-tracer imaging. These methods will be evaluated in large animal tumor models and in patients with primary brain tumors.
Aim 2 will develop improved multi-tracer algorithms, emphasizing robust algorithms suitable for routine use. Rapid multi-tracer imaging also provides unique opportunities for determining inter-linked physiologic parameters.
Aim 3 will investigate methods of measuring tumor blood from derived from the first-pass uptake of all tracers present, using H2O PET as the standard measure of flow. This will potentially provide reliable measures of blood flow without the need for a focused blood flow tracer. The overall project is designed to translate multi-tracer PET technologies to clinical tumor imaging, which will be expressly accomplished through Aim 4. Twenty patients with primary brain tumors will undergo multi-tracer PET imaging prior to any therapy, after 6 weeks chemoradiotherapy, and at the time of tumor recurrence. These data will validate the new methods of Aims 1-3, and will begin to explore the clinical value of multi-tracer PET biomarkers for predicting tumor aggressiveness, assigning patients to personalized treatment regimens, and assessing response to therapy.
Advances in cancer treatment have provided a host of therapeutic drugs, radiation treatments, and targeted agents that provide a vast array of weapons for treating cancer. Rational methods are needed for selecting which treatment will be the best for each individual patient, such as tumor imaging with positron emission tomography (PET). This project will develop new and improved methods of characterizing tumors by PET imaging with multiple tracers, providing a new and greatly improved means of selecting the best treatment option for individual patients.
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|Kadrmas, Dan J; Rust, Thomas C; Hoffman, John M (2013) Single-scan dual-tracer FLT+FDG PET tumor characterization. Phys Med Biol 58:429-49|
|Kadrmas, Dan J; Oktay, M Bugrahan (2013) Generalized separable parameter space techniques for fitting 1K-5K serial compartment models. Med Phys 40:072502|
|Kadrmas, Dan J; Hoffman, John M (2013) Methodology for quantitative rapid multi-tracer PET tumor characterizations. Theranostics 3:757-73|
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|Zeng, Gengsheng L; Kadrmas, Dan J; Gullberg, Grant T (2012) Fourier domain closed-form formulas for estimation of kinetic parameters in reversible multi-compartment models. Biomed Eng Online 11:70|
|Zeng, Gengsheng L; Gullberg, Grant T (2012) Null-space function estimation for the interior problem. Phys Med Biol 57:1873-87|
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|Zeng, Gengsheng L; Hernandez, Andrew; Kadrmas, Dan J et al. (2012) Kinetic parameter estimation using a closed-form expression via integration by parts. Phys Med Biol 57:5809-21|
|Zeng, Gengsheng L; Gullberg, Grant T; Kadrmas, Dan J (2010) Closed-form kinetic parameter estimation solution to the truncated data problem. Phys Med Biol 55:7453-68|
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