In PET, partial-volume effects cause errors in estimation of size and activity for small objects with radiopharmaceutical uptake. Recent methods for image reconstruction, compared with traditional reconstruction techniques, include algorithms for resolution recovery that result in images with higher resolution and enable quantification of size and activity of smaller objects. The purpose of this study was to evaluate a combination of 2 algorithms for volume delineation and partial-volume correction on uptake volumes smaller than 0.7 mL using image reconstruction algorithms with and without resolution recovery.

METHODS: Volumes of interests (VOIs) were delineated using a threshold intensity calculated as a weighted sum of tumor and background intensities. These VOIs were used for calculating correction factors by convolving a tumor mask with the system point-spread function. The methods algorithms were evaluated using a phantom constructed from 5 small different-sized balloons filled with (18)F-FDG in background activity. Six different backgrounds were used. Data were acquired using a PET/CT scanner, and the images were reconstructed using 2 iterative algorithms, one of which used a resolution recovery algorithm.

RESULTS: For the images reconstructed using the resolution recovery algorithm, the method for volume delineation resulted in VOI sizes that were correct within 1 SD for all balloons of a volume of 0.35 mL (equivalent diameter, 8.8 mm) and larger, in all backgrounds. For the images reconstructed without resolution recovery, the VOI sizes were background-dependent and generally less accurate. Correct volume delineations generally led to accurate activity estimates.

CONCLUSION: The algorithms tested on the phantom developed for this study could, for this PET camera and these reconstruction algorithms, be used for accurate volume delineation and activity quantification of lesions 0.35 mL and larger.

Objective: The reference Logan plot is a tool for determining the non-displaceable binding potential for dynamic PET exams using tracers with reversible bindings. Dynamic frame protocols affect noise in PET images and short frames can lead to quantitative uncertainties and noise-induced reconstruction bias. The aim of this study was to analyze the effect of frame binning on ¹¹C-Raclopride striatal binding potential from reference Logan analysis. Methods: 12 healthy volunteers were scanned in list mode using ¹¹C-raclopride, and the image data were reconstructed into 9 different frame binning schemes whereof 3 clinical schemes. Reconstruction was performed with 3 different algorithms, one based on filtered back projection (FBP) and two based on ordered subset expectation maximization (OSEM); one including resolution recovery. Logan plots were used for calculating the non-displaceable binding potential. Variation in binding potential was evaluated using Students t-tests. Results: It was found that frame lengths of up to 60 s gave significantly different results compared to the reference clinical protocol for OSEM, both with and without resolution recovery (maximum deviation: 10.3 % for the 15 s protocol). For FBP, frame lengths of up to 30 s gave significantly different results with a maximum deviation of 2.8 %. The higher sampling dependence of OSEM compared to FBP is likely due to noise-dependent bias in the OSEM algorithm, most apparent at high noise levels. Conclusions: Bias related to OSEM reconstruction of high-noise data is an important factor for dynamic PET protocols. Time frames of 120 s or more generate the most stable values for the striatum binding potential with the reference Logan plot for ¹¹C-Raclopride brain PET.

Background: Attenuation correction of PET/MRI is a remaining problem for whole-body PET/MRI. The statistical decomposition algorithm (SDA) is a probabilistic atlas-based method that calculates synthetic CTs from T2-weighted MRI scans. In this study, we evaluated the application of SDA for attenuation correction of PET images in the pelvic region.

Materials and method: Twelve patients were retrospectively selected from an ongoing prostate cancer research study. The patients had same-day scans of [11C]acetate PET/MRI and CT. The CT images were non-rigidly registered to the PET/MRI geometry, and PET images were reconstructed with attenuation correction employing CT, SDA-generated CT, and the built-in Dixon sequence-based method of the scanner. The PET images reconstructed using CT-based attenuation correction were used as ground truth.

Results: The mean whole-image PET uptake error was reduced from - 5.4% for Dixon-PET to - 0.9% for SDA-PET. The prostate standardized uptake value (SUV) quantification error was significantly reduced from - 5.6% for Dixon-PET to - 2.3% for SDA-PET.

Conclusion: Attenuation correction with SDA improves quantification of PET/MR images in the pelvic region compared to the Dixon-based method.