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. We have shown that 2-3 PET tracers can be reliably imaged in a single scan, where imaging results for each tracer are recovered using """"""""signal-separation"""""""" image processing algorithms. These new technologies have now advanced to the point where they are ready to be translated and distributed to end users for widespread research use. This translation will require advances and refinements that make the new imaging techniques easy to use by PET technologists on a routine basis, and moreover the algorithms must be incorporated into software medical devices that meet regulatory and industry requirements. This project will address these issues through continued scientific study closely coupled with software product development through a partnership between the University of Utah and MultiFunctional Imaging (MFI). Scientific advances and algorithm refinements will be performed under documented design and quality control systems, enabling immediate and rapid incorporation of these technologies into a software medical device package (MFI-Oncology). Successful translation of these emerging technologies will be demonstrated by transitioning ongoing clinical research studies at Huntsman Cancer Institute to single-scan multi-tracer imaging. The new MFI-Oncology software will then be widely distributed for research use under end user's IRB-approved protocols. Ultimately, this will enable clinical research studies at multiple institutions to use rapid multi-tracer PET/CT scanning, establishing this new research tool and accumulating data on efficacy for future clinical use.

Public Health Relevance

Transformative advances in cancer care will require personalized treatments that have been optimized for individual patients based on imaging results. This project will develop new and improved methods of characterizing tumors using a specially-designed imaging technique called multi-tracer PET/CT, and these techniques will be made available to hospitals throughout the country by distributing them through our industrial partner, MultiFunctional Imaging.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-SBIB-J (57))
Program Officer
Menkens, Anne E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Utah
Schools of Medicine
Salt Lake City
United States
Zip Code
Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J (2016) Application of separable parameter space techniques to multi-tracer PET compartment modeling. Phys Med Biol 61:1238-58
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
Enslow, Michael S; Zollinger, Lauren V; Morton, Kathryn A et al. (2012) Comparison of 18F-fluorodeoxyglucose and 18F-fluorothymidine PET in differentiating radiation necrosis from recurrent glioma. Clin Nucl Med 37:854-61
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
Rondina, Matthew T; Lam, Uyen T; Pendleton, Robert C et al. (2012) (18)F-FDG PET in the evaluation of acuity of deep vein thrombosis. Clin Nucl Med 37:1139-45
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

Showing the most recent 10 out of 11 publications