Elsevier

NeuroImage

Volume 132, 15 May 2016, Pages 334-343
NeuroImage

Different partial volume correction methods lead to different conclusions: An 18F-FDG-PET study of aging

https://doi.org/10.1016/j.neuroimage.2016.02.042Get rights and content

Highlights

  • A study of partial volume correction (PVC) methods for FDG of aging is performed.

  • Methods: no PVC, Meltzer, Müller-Gärtner, symmetric geometric transfer matrix

  • Testing was performed with and without modeling of cerebral spinal fluid (CSF).

  • Different methods yielded a wide range of results for the same data.

  • CSF had a surprisingly high FDG signal and strongly influenced PVC.

Abstract

A cross-sectional group study of the effects of aging on brain metabolism as measured with 18F-FDG-PET was performed using several different partial volume correction (PVC) methods: no correction (NoPVC), Meltzer (MZ), Müller-Gärtner (MG), and the symmetric geometric transfer matrix (SGTM) using 99 subjects aged 65–87 years from the Harvard Aging Brain study. Sensitivity to parameter selection was tested for MZ and MG. The various methods and parameter settings resulted in an extremely wide range of conclusions as to the effects of age on metabolism, from almost no changes to virtually all of cortical regions showing a decrease with age. Simulations showed that NoPVC had significant bias that made the age effect on metabolism appear to be much larger and more significant than it is. MZ was found to be the same as NoPVC for liberal brain masks; for conservative brain masks, MZ showed few areas correlated with age. MG and SGTM were found to be similar; however, MG was sensitive to a thresholding parameter that can result in data loss. CSF uptake was surprisingly high at about 15% of that in gray matter. The exclusion of CSF from SGTM and MG models, which is almost universally done, caused a substantial loss in the power to detect age-related changes. This diversity of results reflects the literature on the metabolism of aging and suggests that extreme care should be taken when applying PVC or interpreting results that have been corrected for partial volume effects. Using the SGTM, significant age-related changes of about 7% per decade were found in frontal and cingulate cortices as well as primary visual and insular cortices.

Introduction

Positron emission tomography (PET) suffers from the partial volume effect (PVE) in which limited scanner resolution causes the activity to appear to spill out of one region and into another. This makes it difficult to quantify the effect in a given region because of loss of its own signal and contamination from nearby regions. The size of the PVE depends on many factors, including the size and shape of the region and the size, shape of, and activity in nearby regions. This create a confound when studying aging or neurodegenerative diseases because it becomes unclear whether a difference between groups or across time is due to differences in tissue properties or is simply a side effect of changes in size and shape due to atrophy. Atrophy-induced bias has been documented in simulations of an 18F-FDG aging study (Meltzer et al., 1999); those simulations showed that the atrophic effects of aging caused a false enhancement of the decrease in measured 18F-FDG uptake with age. It is therefore imperative that the PVEs be resolved before attempting to draw conclusions about neurodegenerative diseases.

Partial volume correction (PVC) methods have been developed to remove PVEs. The most popular are Meltzer (MZ, Meltzer et al., 1999), Müller-Gärtner (MG, Meltzer et al., 1996, Müller-Gärtner et al., 1992, Rousset et al., 1998b), and the geometric transfer matrix (GTM, Rousset et al., 1998a) and symmetric GTM (SGTM, Labbé et al., 1998, Sattarivand et al., 2012); see Erlandsson et al. (2012) for a general review of PVC methods. These methods require a second image of the brain from a modality that has substantially reduced PVEs compared to PET, such as MRI or CT. The GTM/SGTM is strictly for region-of-interest (ROI) analysis; MG and MZ provide voxel-wise results, which can then be used in ROI analysis. All analyses performed in this paper are ROI-based using 3D PVC. The application of PVC to group 18F-FDG studies of aging has produced conflicting results in terms of the biological conclusions about aging and metabolism. Some studies find regions with significant changes when not using PVC (NoPVC), few or none of which survive after applying PVC (Curiati et al., 2011, Ibanez et al., 2004, Kochunov et al., 2009, Yanase et al., 2005, Yoshii et al., 1988). Others report strong effects both with and without PVC (Knopman et al., 2014). Still others report strong aging results when using PVC without reporting the uncorrected results (Kalpouzos et al., 2009, Nugent et al., 2014a, Nugent et al., 2014b). Even the studies that do not correct at all are conflicting. For example, de Leon et al., 1987, Hawkins et al., 1983, and Kuhl et al., 1982 found no changes with age, while Herholz et al., 2002, Loessner et al., 1995, Moeller et al., 1996, Petit-Taboue et al., 1998, and Yoshizawa et al., 2014 found change with age. The studies that did not find a change were performed when PET scanner resolutions were very poor which may account for the lack of results.

There are many differences in those studies that may account for the diversity of conclusions such as sample size, age ranges, scanner, PET reconstruction, scan duration, and whether kinetic modeling was performed or standardized uptake values used. However, the above studies also represent a diversity of PVC methods which may account for some of the variation. Several studies have compared PVC methods. Most have used simulations, phantoms, or just a few subjects (Boivin et al., 2014, Harri et al., 2007, Meltzer et al., 1999, Quarantelli et al., 2004, Rousset et al., 1998b) and do not address the question of whether different methods yield different biological conclusions. Uchida et al., 2011, studied aging and serotonin 2 A receptor density using NoPVC, MZ, MG, and GTM and found that NoPVC and MZ showed age effects across the brain which went away entirely with GTM; MG was somewhere in between. Thomas et al., 2011 found that AD subjects differed from controls in 18F-flumetamol uptake when MG was used but not with NoPVC or the GTM-derived region-based voxel-wise (RBV) method; their conclusions were limited to hippocampus.

Here we systematically study NoPVC, MZ, MG, and SGTM in 18F-FDG data from an adult cross-sectional aging study. Each method was tested under a range of parameters attempting to not only document the differences in biological conclusions but to explain why these differences occur. While MG and SGTM/GTM can accommodate the modeling of extracerebral tissue such as cerebral spinal fluid (CSF), in practice they are almost never implemented in this way because CSF is not metabolically active and so is assumed to have no 18F-FDG signal. Remarkably, this assumption does not appear to have ever been tested. Thus, a second aim of this study is to measure the signal in CSF and determine how its inclusion or exclusion in PVC affects the measured 18F-FDG uptake. All PVC methods were implemented under the FreeSurfer neuroimage analysis software package (surfer.nmr.mgh.harvard.edu) and will be released with version 6 of this software.

Section snippets

Subjects

Ninety-nine subjects were drawn from the Harvard Aging Brain (HAB) Study (Mormino et al., 2014). Study protocols were approved by the Partners Healthcare Institutional Review Board, and all participants provided written informed consent. Participants were included if they had a score of less than 11 on the Geriatric Depression Scale, had a score of 0 on the Clinical Dementia Rating Scale, had a score of greater than 25 on the Mini-Mental State Examination, performed within education-adjusted

Results

This section is divided into methodological results and neurobiological results. We first describe the tabulated results then investigate each method more fully. The reader is directed to Table 1 to help keep track of the methods, parameter settings, and overall results of each. We will use Fig. 2 to demonstrate how the performance metrics were computed. Fig. 2 shows a plot of rSUV versus age for SGTM-Full, NoPVC, and simulated NoPVC for the isthmus cingulate (IC) along with best-fit lines;

Discussion

The results presented here show that the way PVC is performed (i.e., the PVC method and parameters used) is critical to the conclusions that one draws about the effects of aging on metabolism. Depending upon the method, parameters, and anatomical modeling, one could report that nearly all brain areas have a significant drop in metabolism between the ages of 66 and 87 years or one could report that virtually no areas are affected or one could report that only frontal regions are affected. At some

Conclusions

We have analyzed the effects of aging on 18F-FDG uptake in a cross-sectional set of subjects aged 66–87 years without PVC and with three popular PVC methods (GTM/SGTM, MG, and MZ) to examine how the results changed with method and how sensitive the conclusions were to changes in method parameters. The results without PVC were highly contaminated by anatomical changes causing 18F-FDG in the entire brain to appear to drop with age; the results became consistent with PVC when this bias was removed.

Acknowledgments

Support for this research was provided in part by the National Institutes of Health grants 5R01EB006758-04, 5R01NS052585-05, 5R21NS072652-02, P41-RR14075, R01RR16594-01A1, 1R21EB018964-01, 1S10RR023043, and 1S10RR023401. This work was also supported by EU 7th Framework Program: INMiND (HEALTH-F2-2011-278850).

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