Multiparametric Cardiac ¹⁸F-FDG PET in Humans: Kinetic Model Selection and Identifiability Analysis

Abstract

Cardiac 18 F-FDG PET has been used in clinics to assess myocardial glucose metabolism. Its ability for imaging myocardial glucose transport, however, has rarely been exploited in clinics. Using the dynamic FDG-PET scans of ten patients with coronary artery disease, we investigate in this paper appropriate dynamic scan and kinetic modeling protocols for efficient quantification of myocardial glucose transport. Three kinetic models and the effect of scan duration were evaluated by using statistical fit quality, assessing the impact on kinetic quantification, and analyzing the practical identifiability. The results show that the kinetic model selection depends on the scan duration. The reversible two-tissue model was needed for a one-hour dynamic scan. The irreversible two-tissue model was optimal for a scan duration of around 10-15 minutes. If the scan duration was shortened to 2-3 minutes, a one-tissue model was the most appropriate. For global quantification of myocardial glucose transport, we demonstrated that an early dynamic scan with a duration of 10-15 minutes and irreversible kinetic modeling was comparable to the full one-hour scan with reversible kinetic modeling. Myocardial glucose transport quantification provides an additional physiological parameter on top of the existing assessment of glucose metabolism and has the potential to enable single tracer multiparametric imaging in the myocardium.

Multiparametric cardiac 18F-FDG PET in humans: pilot comparison of FDG delivery rate with 82Rb myocardial blood flow

“…The maximum Pearson's r between MBF and FDG K 1 by the 2T6P model was reached when the scan duration is one hour, while the scan duration was 10-20 minutes for the 2T5P model and 2-3 minutes for the 1T4P model. These results are consistent with our previous analysis of the identifiability of FDG K 1 [25]. The results for the IHD group are shown in Figure 3(d-f), demonstrating different temporal patterns from the all-patient group.…”

“…Image-derived time activity curves (TACs) of different regions of interest (ROI) were extracted from the left ventricle (LV) cavity, right ventricle (RV) cavity, and myocardium, denoted by C LV (t), C RV (t), and C T (t), respectively. Based on the analysis in our previous work [25], a two-tissue compartmental model was used to model the one-hour dynamic FDG-PET data:…”

“…In addition to the aforementioned 2T6P model, we also studied two simplified models: (1) 2T5P model: the 2T6P model with k 4 =0, and (2) 1T4P model: the one-tissue (1T) model which is equivalent to the 2T6P model with both k 3 and k 4 set at 0. Our previous study [25] showed that these models are respectively required for modeling the dynamic FDG-PET data of different scan durations. For each model, the unknown kinetic parameters were estimated using nonlinear least-square curve fitting, see [25] for more details.…”

“…Our previous study [25] showed that these models are respectively required for modeling the dynamic FDG-PET data of different scan durations. For each model, the unknown kinetic parameters were estimated using nonlinear least-square curve fitting, see [25] for more details.…”

“…This is corresponding to the same 1T4P model for FDG kinetic analysis. All the 82 Rb kinetic parameters (v LV , v RV , K 1 , k 2 ) were estimated using nonlinear least-square curve fitting in a way similar [25].…”