Positron emission tomography (PET) is an inherently quantitative medical imaging technique. When combined with radiopharmaceuticals that provide valuable information on the state of malignancies, PET is a potentially powerful imaging modality for assessing response to new cancer therapies in multi-center clinical trials. Manufacturers of commercial PET scanner systems, however, understandably strive to generate higher quality diagnostic (i.e. detection task optimized) images to achieve market differentiation, but not necessarily the most accurate quantitative data. Recent advances in image reconstruction algorithms enhance image quality, but have paradoxically increased quantitative differences between PET scanners. The resulting variations in quantitative accuracy confound the comparisons of data within multi-center clinical trials. National and international efforts have been initiated to standardize protocols that impact PET quantitation. However, there has been limited effort to harmonize image reconstruction methodologies and parameters to resolve the problem of the substantial variability in PET image accuracy in multi-center trials. This size- and scanner-dependent variability degrades the quality of clinical trials by requiring more patient accrual and/or leading to inconclusive results in tests of badly needed cancer therapies. The proposed project will solve this problem through a combination of rigorous NIST traceable calibration standards combined with the development of an industry-supported harmonized PET image reconstruction paradigm providing quantitatively accurate and reproducible measurements with known errors characteristics. The project is supported by all three major PET/CT scanner manufacturers, facilitated through the Society of Nuclear Medicine's Clinical Trials Network, and will be primarily performed by three leading PET/CT academic institutions with extensive experience in quantitative imaging and established track records of substantial collaboration with the three manufacturers. Data will also be collected from other PET centers as needed to provide representative data and harmonized reconstruction solutions for the full range of 17 different current vintage PET/CT scanners.

Public Health Relevance

There is considerable interest in the medical and cancer community to use the information provided by Positron Emission Tomography (PET) imaging to help decrease the cost of drug development and the time it takes to bring these new drugs safely and effectively into the hands of physicians and patients. To perform the necessary scientifically rigorous clinical trials, the PET scanners must generate accurate, reproducible, and harmonious quantitative data, regardless of the manufacturer and model PET scanner being used. This project brings together the PET imaging programs of three major universities with the major PET scanner manufacturers and several major medical imaging professional societies to work on a non-competitive solution to this problem by identifying a method to generate quantitatively identical images for use in clinical trials.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA169072-04
Application #
8856169
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Zhang, Yantian
Project Start
2012-09-01
Project End
2016-06-30
Budget Start
2015-07-01
Budget End
2016-06-30
Support Year
4
Fiscal Year
2015
Total Cost
Indirect Cost
Name
University of Iowa
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52246
Ulrich, Ethan J; Sunderland, John J; Smith, Brian J et al. (2018) Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans. Med Phys 45:258-276
Beichel, Reinhard R; Smith, Brian J; Bauer, Christian et al. (2017) Multi-site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data. Med Phys 44:479-496
Panetta, Joseph V; Daube-Witherspoon, Margaret E; Karp, Joel S (2017) Validation of phantom-based harmonization for patient harmonization. Med Phys 44:3534-3544
Pierce II, Larry A; Byrd, Darrin W; Elston, Brian F et al. (2016) An algorithm for automated ROI definition in water or epoxy-filled NEMA NU-2 image quality phantoms. J Appl Clin Med Phys 17:440–456
Vaquero, Juan José; Kinahan, Paul (2015) Positron Emission Tomography: Current Challenges and Opportunities for Technological Advances in Clinical and Preclinical Imaging Systems. Annu Rev Biomed Eng 17:385-414
Pierce 2nd, Larry A; Elston, Brian F; Clunie, David A et al. (2015) A Digital Reference Object to Analyze Calculation Accuracy of PET Standardized Uptake Value. Radiology 277:538-45
Nyflot, Matthew J; Yang, Fei; Byrd, Darrin et al. (2015) Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards. J Med Imaging (Bellingham) 2:041002