Dataset Information

Pitfalls in quantitative myocardial PET perfusion I: Myocardial partial volume correction.

ABSTRACT: BACKGROUND:PET quantitative myocardial perfusion requires correction for partial volume loss due to one-dimensional LV wall thickness smaller than scanner resolution. METHODS:We aimed to assess accuracy of risk stratification for death, MI, or revascularization after PET using partial volume corrections derived from two-dimensional ACR and three-dimensional NEMA phantoms for 3987 diagnostic rest-stress perfusion PETs and 187 MACE events. NEMA, ACR, and Tree phantoms were imaged with Rb-82 or F-18 for size-dependent partial volume loss. Perfusion and Coronary Flow Capacity were recalculated using different ACR- and NEMA-derived partial volume corrections compared by Kolmogorov-Smirnov statistics to standard perfusion metrics with established correlations with MACE. RESULTS:Partial volume corrections based on two-dimensional ACR rods (two equal radii) and three-dimensional NEMA spheres (three equal radii) over estimate partial volume corrections, quantitative perfusion, and Coronary Flow Capacity by 50% to 150% over perfusion metrics with one-dimensional partial volume correction, thereby substantially impairing correct risk stratification. CONCLUSIONS:ACR (2-dimensional) and NEMA (3-dimensional) phantoms overestimate partial volume corrections for 1-dimensional LV wall thickness and myocardial perfusion that are corrected with a simple equation that correlates with MACE for optimal risk stratification applicable to most PET-CT scanners for quantifying myocardial perfusion.

SUBMITTER: Lance Gould K

PROVIDER: S-EPMC7174249 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Pitfalls in quantitative myocardial PET perfusion I: Myocardial partial volume correction.

Lance Gould K K Bui Linh L Kitkungvan Danai D Pan Tinsu T Roby Amanda E AE Nguyen Tung T TT Johnson Nils P NP

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology 20200224 2

<h4>Background</h4>PET quantitative myocardial perfusion requires correction for partial volume loss due to one-dimensional LV wall thickness smaller than scanner resolution.<h4>Methods</h4>We aimed to assess accuracy of risk stratification for death, MI, or revascularization after PET using partial volume corrections derived from two-dimensional ACR and three-dimensional NEMA phantoms for 3987 diagnostic rest-stress perfusion PETs and 187 MACE events. NEMA, ACR, and Tree phantoms were imaged wi ...[more]

PMID: 32095938

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Project description:BackgroundAccurate quantification of PET studies depends on the spatial resolution of the PET data. The commonly limited PET resolution results in partial volume effects (PVE). Iterative deconvolution methods (IDM) have been proposed as a means to correct for PVE. IDM improves spatial resolution of PET studies without the need for structural information (e.g. MR scans). On the other hand, deconvolution also increases noise, which results in lower signal-to-noise ratios (SNR). The aim of this study was to implement IDM in combination with HighlY constrained back-PRojection (HYPR) denoising to mitigate poor SNR properties of conventional IDM.MethodsAn anthropomorphic Hoffman brain phantom was filled with an [18F]FDG solution of ~25 kBq mL-1 and scanned for 30 min on a Philips Ingenuity TF PET/CT scanner (Philips, Cleveland, USA) using a dynamic brain protocol with various frame durations ranging from 10 to 300 s. Van Cittert IDM was used for PVC of the scans. In addition, HYPR was used to improve SNR of the dynamic PET images, applying it both before and/or after IDM. The Hoffman phantom dataset was used to optimise IDM parameters (number of iterations, type of algorithm, with/without HYPR) and the order of HYPR implementation based on the best average agreement of measured and actual activity concentrations in the regions. Next, dynamic [11C]flumazenil (five healthy subjects) and [11C]PIB (four healthy subjects and four patients with Alzheimer's disease) scans were used to assess the impact of IDM with and without HYPR on plasma input-derived distribution volumes (V T) across various regions of the brain.ResultsIn the case of [11C]flumazenil scans, Hypr-IDM-Hypr showed an increase of 5 to 20% in the regional V T whereas a 0 to 10% increase or decrease was seen in the case of [11C]PIB depending on the volume of interest or type of subject (healthy or patient). References for these comparisons were the V Ts from the PVE-uncorrected scans.ConclusionsIDM improved quantitative accuracy of measured activity concentrations. Moreover, the use of IDM in combination with HYPR (Hypr-IDM-Hypr) was able to correct for PVE without increasing noise.

Project description:Partial volume effect in positron emission tomography (PET) can cause incorrect quantification of radiopharmaceutical uptake in functional imaging. A PET partial volume correction method is presented to attenuate partial volume blurring and to yield voxel-based corrected PET images.By modeling partial volume effect as a convolution of point spread function of the PET scanner, the reconstructed PET images are corrected by iterative deconvolution with an edge-preserving smoothness constraint. The constraint is constructed to restore discontinuities extracted from coregistered MR images but maintains the smoothness in radioactivity distribution. The correction is implemented in a Bayesian deconvolution framework and is solved by a conjugate gradient method. The performance of the method was compared with the geometric transfer matrix (GTM) method on a simulated dataset. The method was evaluated on synthesized brain FDG-PET data and phantom MRI-PET experiments.The true PET activity of objects with a size of greater than the full-width at half maximum of the point spread function has been effectively restored in the simulated data. The partial volume correction method is quantitatively comparable to the GTM method. For synthesized FDG-PET with true activity 0 μci/cc for cerebrospinal fluid (CSF), 228 μci/cc for white matter (WM), and 621 μci/cc for gray matter (GM), the method has improved the radioactivity quantification from 186 ± 16 μci/cc to 30 ± 7 μci/cc in CSF, 317 ± 15 μci/cc to 236 ± 10 μci/cc for WM, 438 ± 4 μci/cc to 592 ± 5 μci/cc for GM. Both visual and quantitative assessments show improvement of partial volume correction in the synthesized and phantom experiments.The partial volume correction method improves the quantification of PET images. The method is comparable to the GTM method but does not need MR image segmentation or prior tracer distribution information. The voxel-based method can be particularly useful for combined PET/MRI studies.

Dataset Information

Pitfalls in quantitative myocardial PET perfusion I: Myocardial partial volume correction.

Publications

Pitfalls in quantitative myocardial PET perfusion I: Myocardial partial volume correction.

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