Evaluation of a compartmental model for estimating tumor hypoxia via FMISO dynamic PET imaging Journal Article
| Authors: | Wang, W.; Georgi, J. C.; Nehmeh, S. A.; Narayanan, M.; Paulus, T.; Bal, M.; O'Donoghue, J.; Zanzonico, P. B.; Schmidtlein, C. R.; Lee, N. Y.; Humm, J. L. |
| Article Title: | Evaluation of a compartmental model for estimating tumor hypoxia via FMISO dynamic PET imaging |
| Abstract: | This paper systematically evaluates a pharmacokinetic compartmental model for identifying tumor hypoxia using dynamic positron emission tomography (PET) imaging with <sup>18</sup>F-fluoromisonidazole (FMISO). A generic irreversible one-plasma two-tissue compartmental model was used. A dynamic PET image dataset was simulated with three tumor regions - normoxic, hypoxic and necrotic - embedded in a normal-tissue background, and with an image-based arterial input function. Each voxelized tissue's time activity curve (TAC) was simulated with typical values of kinetic parameters, as deduced from FMISO-PET data from nine head-and-neck cancer patients. The dynamic dataset was first produced without any statistical noise to ensure that correct kinetic parameters were reproducible. Next, to investigate the stability of kinetic parameter estimation in the presence of noise, 1000 noisy samples of the dynamic dataset were generated, from which 1000 noisy estimates of kinetic parameters were calculated and used to estimate the sample mean and covariance matrix. It is found that a more peaked input function gave less variation in various kinetic parameters, and the variation of kinetic parameters could also be reduced by two region-of-interest averaging techniques. To further investigate how bias in the arterial input function affected the kinetic parameter estimation, a shift error was introduced in the peak amplitude and peak location of the input TAC, and the bias of various kinetic parameters calculated. In summary, mathematical phantom studies have been used to determine the statistical accuracy and precision of model-based kinetic analysis, which helps to validate this analysis and provides guidance in planning clinical dynamic FMISO-PET studies. © 2009 Institute of Physics and Engineering in Medicine. |
| Keywords: | positron emission tomography; methodology; sensitivity and specificity; radiopharmaceuticals; neoplasm; neoplasms; reproducibility; reproducibility of results; metabolism; biological model; models, biological; image analysis; image interpretation, computer-assisted; oxygen; algorithms; kinetics; diagnostic agent; algorithm; computer assisted diagnosis; image enhancement; head and neck cancer; tumors; positron-emission tomography; radiopharmaceutical agent; drug derivative; scintiscanning; computer simulation; 1 fluoro 3 (2 nitro 1 imidazolyl) 2 propanol f 18; 1 fluoro 3 (2 nitro 1 imidazolyl) 2 propanol; misonidazole; kinetic analysis; oxygen consumption; tumor hypoxia; data sets; head-and-neck cancer; arterial input function; averaging technique; compartmental model; dynamic pet; image-based; input functions; mathematical phantoms; model-based; peak amplitude; pet data; region of interest; statistical accuracy; statistical noise; time-activity curves; typical values; covariance matrix; kinetic parameters; military photography; parameter estimation; compartment model; mathematical parameters |
| Journal Title: | Physics in Medicine and Biology |
| Volume: | 54 |
| Issue: | 10 |
| ISSN: | 0031-9155 |
| Publisher: | IOP Publishing Ltd |
| Date Published: | 2009-05-21 |
| Start Page: | 3083 |
| End Page: | 3099 |
| Language: | English |
| DOI: | 10.1088/0031-9155/54/10/008 |
| PUBMED: | 19420418 |
| PROVIDER: | scopus |
| PMCID: | PMC2836924 |
| DOI/URL: | |
| Notes: | --- - "Cited By (since 1996): 5" - "Export Date: 30 November 2010" - "CODEN: PHMBA" - "Source: Scopus" |
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357Zanzonico
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