Estimation of image derived input functions using a reconstruction based partial volume correction algorithm: Methodology and evaluation in [11C]flumazenil studies

Introduction: The availability of image derived input functions (IDIF) obviates the need for arterial blood sampling and thereby facilitates clinical use of quantitative PET studies. The aim of this study was to develop a method for deriving IDIFs using reconstruction-based partial volume correction (PVC) [1]. Methods: PET and arterial blood data from nine dynamic [11C]flumazenil scans, acquired using an ECAT EXACT HR+ scanner and an on-line blood sampler, were used to develop and evaluate the method. Scans were reconstructed using both standard (no PVC) ordered subset expectation maximization (OSEM, 2 iterations, 16 subsets) and a PVC-OSEM algorithm, which corrects for the spatial resolution of the scanner. Number of iterations and width of PVC kernel were varied. The following regions of interest (ROIs) Methods: were evaluated for defining cerebral arteries: (a) pixel value threshold, (b) variable number of 'hottest' pixels per plane, (c) region growing, (d) cluster analysis, and (e) MR-based ROI. ROIs were defined on a pseudo blood volume image, generated by summation of early frames (<60s). ROIs were copied to all frames and IDIFs were extracted from both OSEM and PVC-OSEM images. For each IDIF the following parameters were derived: (a) area under the curve (AUC) for peak (1-2 min), (b) AUC for tail (2-60 min), (c) volume of distribution (Vd) obtained from parametric Logan images, and (d) Vd and K1 obtained from parametric basis function method (BFM) images. In each case, Results: were compared with those using on-line measured arterial input functions. Results: For PVC-OSEM, the optimal trade-off between computational time and signal-to-noise ratio was obtained for 4 iterations and 16 subsets. A 5.5 mm Gaussian resolution kernel gave optimal recovery correction. The best IDIF was obtained using the 'four hottest pixels per plane' over the blood pool in the region below the base of the skull. Compared with standard OSEM, use of PVC-OSEM improved mean (SD) AUC from 0.46 (0.06) to 1.15 (0.11) for the peak and from 0.82 (0.06) to 0.94 (0.12) for the tail part of the input function, respectively. Results: of the comparison between OSEM and PVC-OSEM for Vd and K1 are shown in Table 1 and Figure 1. Discussion and Conclusions: Excellent correlations were obtained between Vd and K1 values based on IDIFs and those based on on-line sampled input functions. Definition of an accurate IDIF may be sensitive to patient movement and future studies need to focus on motion correction Methods:. Nevertheless, this study shows the feasibility of deriving accurate IDIFs from dynamic PET scans using reconstruction-based PVC.