Abstract
Background: Patlak’s graphical analysis can provide tracer net influx constant (Ki) with limitation of assuming irreversible tracer trapping, that is, release rate constant (k b ) set to zero. We compared linear Patlak’s analysis to non-linear three-compartment three-parameter kinetic model analysis (3P-KMA) providing Ki, k b , and fraction of free 18 F-FDG in blood and interstitial volume (V b ). Methods: Dynamic PET data of 21 lung cancer patients were retrospectively analyzed, yielding for each patient an 18 F-FDG input function (IF) and a tissue time-activity curve. The former was fitted with a three-exponentially decreasing function, and the latter was fitted with an analytical formula involving the fitted IF data (11 data points, ranging 7.5–57.5 min post-injection). Bland-Altman analysis was used for Ki comparison between Patlak’s analysis and 3P-KMA. Additionally, a three-compartment five-parameter KMA (5P-KMA) was implemented for comparison with Patlak’s analysis and 3P-KMA. Results: We found that 3P-KMA Ki was significantly greater than Patlak’s Ki over the whole patient series, + 6.0% on average, with limits of agreement of ± 17.1% (95% confidence). Excluding 8 out of 21 patients with k b > 0 deleted this difference. A strong correlation was found between Ki ratio (=3P-KMA/Patlak) and k b (R = 0.801; P < 0.001). No significant difference in Ki was found between 3P-KMA versus 5P-KMA, and between 5P-KMA versus Patlak’s analysis, with limits of agreement of ± 23.0 and ± 31.7% (95% confidence), respectively. Conclusions: Comparison between 3P-KMA and Patlak’s analysis significantly showed that the latter underestimates Ki because it arbitrarily set k b to zero: the greater the k b value, the greater the Ki underestimation. This underestimation was not revealed when comparing 5P-KMA and Patlak’s analysis. We suggest that further studies are warranted to investigate the 3P-KMA efficiency in various tissues showing greater 18 F-FDG trapping reversibility than lung cancer lesions.
| Original language | English |
|---|---|
| Pages (from-to) | 24-31 |
| Number of pages | 8 |
| Journal | EJNMMI Research |
| Volume | 8 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Radiology Nuclear Medicine and imaging
Keywords
- 18
- F-FDG PET
- Patlak’s analysis
- Reversible trapping
- Uptake/release rate constant
- lung cancer
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