Geometric Transfer Matrix Method Research Articles

Elevated neurofibrillary tau levels emerge with subthreshold Aβ accumulation in Down syndrome

AbstractBackgroundAdults with Down syndrome (DS) are genetically predisposed to Alzheimer’s disease (AD) and accumulate beta‐amyloid plaques (Aβ) early in life. The aim of this study was to evaluate neurofibrillary tau deposition in DS between groups of Aβ negative (A‐) and subthreshold Aβ accumulators (subthreshold A+).MethodA total of 130 adults with DS (age=36.5 [6.77] years) and 40 healthy, non‐DS sibling controls (43.2 [12.6] years) underwent T1w‐MRI, [C‐11]PiB and [F‐18]AV‐1451 PET scans. MRI images were processed using FreeSurfer v5.3.0 to generate ROI masks encompassing the Braak staging of tau pathology. PiB and AV‐1451 SUVr images were generated using a cerebellar gray matter reference region. Global Aβ burden was calculated using the amyloid load metric (AβL). Of the 130 DS adults, N=26 were classified as subthreshold A+ (13.3 < AβL < 20), and the remaining 104 were classified as A‐ (AβL < 13.3). AV‐1451 images were averaged for each group, and the difference was taken to generate a ΔSUVr image. Regional tau was assessed using AV‐1451 SUVr Z‐scores relative to the sibling control group. Partial volume correction was performed on AV‐1451 SUVrs in the Braak I‐II regions using the geometric transfer matrix method. Braak regional SUVr Z‐scores were then compared across the two groups using Student’s t‐tests while adjusting for imaging site. The analysis was then repeated using an age‐matched sample of A‐ (N=68) and subthreshold A+ (N=26) DS.ResultThe SUVr difference image revealed higher AV‐1451 uptake in Braak regions I‐III for the subthreshold A+ group (Figure 1). Student’s t‐tests revealed significantly higher AV‐1451 uptake in Braak regions I‐III for the subthreshold A+ group (Table 1). No difference in AV‐1451 uptake was observed between groups in Braak regions IV‐VI (Table 1). Higher AV‐1451 uptake in Braak regions I‐III was also observed in the subthreshold A+ group when compared to the age‐matched A‐ group (Table 2).ConclusionThese results show that subthreshold Aβ in DS is accompanied by elevated tau in the early Braak stage regions. These findings indicate that there is a short latency between the onset of Aβ and the spread of neurofibrillary tau in DS.

Association of white matter hyperintensities with sub‐threshold amyloid accumulation

AbstractBackgroundPrevious studies investigating the relationship between amyloid‐β (Aβ) pathology and white matter lesions have led to inconsistent results. A potential explanation for these disparities is the cross‐sectional design of most of these studies, which might have increased the confounding effect of vascular pathology. Here, we used a longitudinal design to investigate whether white matter lesion burden is associated with faster rates of longitudinal Aβ accumulation among cognitively normal older adults without PET‐evidenced Aβ pathology.MethodOne hundred fifty‐nine cognitively normal participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) who were Aβ‐negative at baseline were examined. All the participants had a T1 and FLAIR MRI scan at baseline, as well as baseline and at least one follow‐up [18F]florbetapir PET scans acquired in 2‐year intervals for up to 8 years. The Geometric Transfer Matrix method was used to correct for partial volume effects, including those coming from spill‐in counts from the white matter. A previously defined cortical summary region including frontal, parietal, cingulate, and temporal cortices was used to assess global amyloid burden. Standardized Uptake Value Ratios (SUVR) were computed using the cerebellar gray matter as reference region. The association between global and regional white matter hypertense (WMH) burden, and Aβ accumulation was assessed using linear mixed models adjusted by demographics and baseline SUVR.ResultPartial volume correction increased the measured annual rate of change of cortical SUVR (+2.4%) compared to non‐corrected data (+0.5%). There were no significant correlations between baseline WMH and baseline subthreshold cortical SUVR. In the longitudinal analysis, increased baseline cortical SUVR and increased baseline burden of global (p = 0.006), frontal (p = 0.006), and parietal WMH (p = 0.003) were associated with faster amyloid accumulation (Fig.1). WMH‐related Aβ accumulation occurred in parietal, frontal, and, to a lesser extent, cingulate cortices. These results remained unchanged after a sensitivity analysis excluding participants with the highest cortical SUVRs.ConclusionWe demonstrate that a specific spatial distribution of WMH is predictive of future Aβ accumulation among cognitively normal elderly without PET‐detectable Aβ pathology. These findings add to recent studies pointing to a direct relationship between WMH and Aβ pathology in early Alzheimer’s Disease.

A new integrated dual time-point amyloid PET/MRI data analysis method.

In the initial evaluation of patients with suspected dementia and Alzheimer's disease, there is no consensus on how to perform semiquantification of amyloid in such a way that it: (1) facilitates visual qualitative interpretation, (2) takes the kinetic behaviour of the tracer into consideration particularly with regard to at least partially correcting for blood flow dependence, (3) analyses the amyloid load based on accurate parcellation of cortical and subcortical areas, (4) includes partial volume effect correction (PVEC), (5) includes MRI-derived topographical indexes, (6) enables application to PET/MRI images and PET/CT images with separately acquired MR images, and (7) allows automation. A method with all of these characteristics was retrospectively tested in 86 subjects who underwent amyloid (18F-florbetaben) PET/MRI in a clinical setting (using images acquired 90-110min after injection, 53 were classified visually as amyloid-negative and 33 as amyloid-positive). Early images after tracer administration were acquired between 0 and 10min after injection, and later images were acquired between 90 and 110min after injection. PVEC of the PET data was carried out using the geometric transfer matrix method. Parametric images and some regional output parameters, including two innovative "dual time-point" indexes, were obtained. Subjects classified visually as amyloid-positive showed a sparse tracer uptake in the primary sensory, motor and visual areas in accordance with the isocortical stage of the topographic distribution of the amyloid plaque (Braak stages V/VI). In patients classified visually as amyloid-negative, the method revealed detectable levels of tracer uptake in the basal portions of the frontal and temporal lobes, areas that are known to be sites of early deposition of amyloid plaques that probably represented early accumulation (Braak stage A) that is typical of normal ageing. There was a strong correlation between age and the indexes of the new dual time-point amyloid imaging method in amyloid-negative patients. The method can be considered a valuable tool in both routine clinical practice and in the research setting as it will standardize data regarding amyloid deposition. It could potentially also be used to identify early amyloid plaque deposition in younger subjects in whom treatment could theoretically be more effective.

PETPVE12: an SPM toolbox for Partial Volume Effects correction in brain PET – Application to amyloid imaging with AV45-PET

Positron emission tomography (PET) allows detecting molecular brain changes in vivo. However, the accuracy of PET is limited by partial volume effects (PVE) that affects quantitative analysis and visual interpretation of the images. Although PVE-correction methods have been shown to effectively increase the correspondence of the measured signal with the true regional tracer uptake, these procedures are still not commonly applied, neither in clinical nor in research settings. Here, we present an implementation of well validated PVE-correction procedures as a SPM toolbox, PETPVE12, for automated processing. We demonstrate its utility by a comprehensive analysis of the effects of PVE-correction on amyloid-sensitive AV45-PET data from 85 patients with Alzheimer's disease (AD) and 179 cognitively normal (CN) elderly. Effects of PVE-correction on global cortical standard uptake value ratios (SUVR) and the power of diagnostic group separation were assessed for the region-wise geometric transfer matrix method (PVEc-GTM), as well as for the 3-compartmental voxel-wise “Müller-Gärtner” method (PVEc-MG). Both PVE-correction methods resulted in decreased global cortical SUVRs in the low to middle range of SUVR values, and in increased global cortical SUVRs at the high values. As a consequence, average SUVR of the CN group was reduced, whereas average SUVR of the AD group was increased by PVE-correction. These effects were also reflected in increased accuracies of group discrimination after PVEc-GTM (AUC=0.86) and PVEc-MG (AUC=0.89) compared to standard non-corrected SUVR (AUC=0.84). Voxel-wise analyses of PVEc-MG corrected data also demonstrated improved detection of regionally increased AV45 SUVR values in AD patients. These findings complement the growing evidence for a beneficial effect of PVE-correction in quantitative analysis of amyloid-sensitive PET data. The novel PETPVE12 toolbox significantly facilitates the application of PVE-correction, particularly within SPM-based processing pipelines. This is expected to foster the use of PVE-correction in brain PET for more widespread use. The toolbox is freely available at http://www.fil.ion.ucl.ac.uk/spm/ext/#PETPVE12.

Partial volume effect estimation and correction in the aortic vascular wall in PET imaging

We evaluated the impact of partial volume effect (PVE) in the assessment of arterial diseases with 18FDG PET. An anthropomorphic digital phantom enabling the modeling of aorta related diseases like atherosclerosis and arteritis was used. Based on this phantom, we performed GATE Monte Carlo simulations to produce realistic PET images with a known organ segmentation and ground truth activity values. Images corresponding to 15 different activity-concentration ratios between the aortic wall and the blood and to 7 different wall thicknesses were generated. Using the PET images, we compared the theoretical wall-to-blood activity-concentration ratios (WBRs) with the measured WBRs obtained with five measurement methods: (1) measurement made by a physician (Expert), (2) automated measurement supposed to mimic the physician measurements (Max), (3) simple correction based on a recovery coefficient (Max-RC), (4) measurement based on an ideal VOI segmentation (Mean-VOI) and (5) measurement corrected for PVE using an ideal geometric transfer matrix (GTM) method. We found that Mean-VOI WBRs values were strongly affected by PVE. WBRs obtained by the physician measurement, by the Max method and by the Max-RC method were more accurate than WBRs obtained with the Mean-VOI approach. However Expert, Max and Max-RC WBRs strongly depended on the wall thickness. Only the GTM corrected WBRs did not depend on the wall thickness. Using the GTM method, we obtained more reproducible ratio values that could be compared across wall thickness. Yet, the feasibility of the implementation of a GTM-like method on real data remains to be studied.

Partial Volume Correction using Structural–Functional Synergistic Resolution Recovery: Comparison with Geometric Transfer Matrix Method

We validated the use of a novel image-based method for partial volume correction (PVC), structural-functional synergistic resolution recovery (SFS-RR) for the accurate quantification of dopamine synthesis capacity measured using [(18)F]DOPA positron emission tomography. The bias and reliability of SFS-RR were compared with the geometric transfer matrix (GTM) method. Both methodologies were applied to the parametric maps of [(18)F]DOPA utilization rates (ki(cer)). Validation was first performed by measuring repeatability on test-retest scans. The precision of the methodologies instead was quantified using simulated [(18)F]DOPA images. The sensitivity to the misspecification of the full-width-half-maximum (FWHM) of the scanner point-spread-function on both approaches was also assessed. In the in-vivo data, the ki(cer) was significantly increased by application of both PVC procedures while the reliability remained high (intraclass correlation coefficients >0.85). The variability was not significantly affected by either PVC approach (<10% variability in both cases). The corrected ki(cer) was significantly influenced by the FWHM applied in both the acquired and simulated data. This study shows that SFS-RR can effectively correct for partial volume effects to a comparable degree to GTM but with the added advantage that it enables voxelwise analyses, and that the FWHM used can affect the PVC result indicating the importance of accurately calibrating the FWHM used in the recovery model.

Symmetric geometric transfer matrix partial volume correction for PET imaging: principle, validation and robustness

Limited spatial resolution of positron emission tomography (PET) often requires partial volume correction (PVC) to improve the accuracy of quantitative PET studies. Conventional region-based PVC methods use co-registered high resolution anatomical images (e.g. computed tomography (CT) or magnetic resonance images) to identify regions of interest. Spill-over between regions is accounted for by calculating regional spread functions (RSFs) in a geometric transfer matrix (GTM) framework. This paper describes a new analytically derived symmetric GTM (sGTM) method that relies on spill-over between RSFs rather than between regions. It is shown that the sGTM is mathematically equivalent to Labbe's method; however it is a region-based method rather than a voxel-based method and it avoids handling large matrices. The sGTM method was validated using two three-dimensional (3D) digital phantoms and one physical phantom. A 3D digital sphere phantom with sphere diameters ranging from 5 to 30 mm and a sphere-to-background uptake ratio of 3-to-1 was used. A 3D digital brain phantom was used with four different anatomical regions and a background region with different activities assigned to each region. A physical sphere phantom with the same geometry and uptake as the digital sphere phantom was manufactured and PET-CT images were acquired. Using these three phantoms, the performance of the sGTM method was assessed against that of the GTM method in terms of accuracy, precision, noise propagation and robustness. The robustness was assessed by applying mis-registration errors and errors in estimates of PET point spread function (PSF). In all three phantoms, the results showed that the sGTM method has accuracy similar to that of the GTM method and within 5%. However, the sGTM method showed better precision and noise propagation than the GTM method, especially for spheres smaller than 13 mm. Moreover, the sGTM method was more robust than the GTM method when mis-registration errors or errors in estimates of PSF occur. The improved robustness was more pronounced for smaller objects. In conclusion, the sGTM method was analytically derived and validated. The noise characteristics and robustness of the sGTM method were better than the conventional GTM method.

Sci-Fri AM: Imaging - 07: Symmetric geometric transfer matrix partial volume correction technique for emission tomography: Principle, validation, and robustness.

Partial volume correction (PVC) is often needed to correct for limited spatial resolution in quantitative Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) studies. In conventional region-based PVC methods, spill over between regions segmented from coregistered computed tomography (CT) or magnetic resonance (MR) images is accounted for by calculating regional spread functions (RSFs) in a geometric transfer matrix (GTM) framework. This paper describes a new analytically derived symmetric GTM (sGTM) method that considers spill over between RSFs rather than between regions. The sGTM is mathematically equivalent to Labbe's method, however it is region-based rather than voxel-based and it avoids handling large matrices. The sGTM method was validated using an MR-based 3D digital brain phantom and a physical phantom containing spheres 5 mm to 30 mm in diameter. The sGTM method was compared to the GTM method in terms of accuracy, precision, noise propagation, and robustness, i.e. effects of mis-registration or point spread function (PSF) estimation errors. The results showed that the sGTM method has accuracy similar to that of the GTM method, and within 5% of the true value. However, the sGTM method showed better precision and noise propagation than the GTM method, especially for spheres smaller than 13 mm. Moreover, the sGTM method was more robust than the GTM method when misregistration or errors in estimates of PSF occurred. In conclusion, the sGTM method was analytically derived and validated and shown to exhibit better noise characteristics and robustness compared to the GTM method.

Characterisation of partial volume effect and region-based correction in small animal positron emission tomography (PET) of the rat brain

Accurate quantification of PET imaging data is required for a useful interpretation of the measured radioactive tracer concentrations. The partial volume effect (PVE) describes signal dilution and mixing due to spatial resolution and sampling limitations, which introduces bias in quantitative results. In the present study we investigated the magnitude of PVE for volumes of interest (VOIs) in the rat brain and the effect of positron range. In simulated 11C-raclopride studies we examined the influence of PVE on time activity curves in striatal and cerebellar VOIs and binding potential estimation. The performance of partial volume correction (PVC) was studied using the region-based geometric transfer matrix (GTM) method including the question of whether a spatially variant point spread function (PSF) is necessary for PVC of a rat brain close to the centre of the field of view. Furthermore, we determined the effect of spillover from activity outside the brain.The results confirmed that PVE is significant in rat brain PET and showed that positron range is an important factor that needs to be included in the PSF. There was considerable bias in time activity curves for the simulated 11C-raclopride studies and significant underestimation of binding potential even for very small centred VOIs. Good activity recovery was achieved with the GTM PVC using a spatially invariant simulated PSF when no activity was present outside the brain. PVC using a simple Gaussian fit point spread function was not sufficiently accurate. Spillover from regions outside the brain had a significant impact on measured activity concentrations and reduced the accuracy of PVC with the GTM method using rat brain regions alone, except for the smallest VOI size but at the cost of increased noise. Voxel-based partial volume correction methods which inherently compensate for spillover from outside the brain might be a more suitable choice.

An MR image-guided, voxel-based partial volume correction method for PET images.

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.

TU‐G‐211‐06: Partial Volume Correction for Noninvasive PET Image‐Derived Simplified Kinetic Analysis

Purpose: To assess a partial volume correction (PVC) method for a non‐invasive PET image based simplified kinetic analysis.Methods and Materials: A phantom was designed with a cylinder tank and six fillable cylinders to simulate vessels with a range of inner diameters from 4.8 to 28.6mm. F‐18 in aqueous solution was injected into the vessels and the tank with an activity concentration ratio of 1.5 to 1. The PET FOV was 576mm and voxel size 4×4×4mm. CT images of this phantom were used to create a digital 3D PET phantom model. The inner and outer vessel cylinders and the tank were automatically contoured and the known true F‐18 activities were assigned to the vessels and tank volume. The CT‐based model was then convolved with a 3D Gaussian PET point spread function to create the simulated phantom. For both simulated and physical phantoms, PVC was applied to recover the F‐18 uptakes using a 3×3 geometric transfer matrix (GTM) method. Recovery coefficients of the vessels were calculated before and after PVC. Results: Severe underestimations in vessel uptake were observed for both simulated and physical phantoms before PVC. After PVC the vessel uptakes recovered closer to the true uptake values. For the simulated phantom, complete PVC recovery was achieved for all vessel sizes with an accuracy &lt;0.2%. For the physical phantom, the PVC recovery was &lt;5% for all vessel sizes except for the smallest vessel (4.8mm) where the vessel uptake was overestimated by 20%. Conclusions: Non‐invasive PET image based simplified kinetic analysis is feasible provided that partial volume corrections are applied to recover vessel tracer uptake. Blood activity may be corrected for partial volume error with better than 5% accuracy using the GTM method for vessels larger than 10mm in diameter. A patient study is needed to confirm these results in clinical settings.

Partial volume effect compensation for quantitative brain SPECT imaging

Partial volume (PV) effects degrade the quantitative accuracy of SPECT brain images. In this paper, we extended a PV compensation (PVC) method originally developed for brain PET, the geometric transfer matrix (GTM) method, to brain SPECT using iterative reconstruction-based compensations. In the GTM method a linear transform between the true regional activities and the measured results was assumed. Elements of the GTM were calculated by projecting and reconstructing maps with uniform regions representing different structures. However, with iterative reconstruction methods, especially when reconstruction-based compensation for detector response was applied, we found that it was important to treat the region maps as a perturbation to the reconstructed image in the estimation of the GTM. This modified method, termed perturbation-based GTM (pGTM) was evaluated using Monte Carlo (MC) simulated and experimentally acquired data. Results showed great improvement of the quantitative accuracy in brain SPECT imaging. For MC simulated data, PVC using pGTM reduced the underestimation of striatal activities from 30% to less than 1.2%. For experimental data, PVC using pGTM reduced the underestimation of striatal activities from 36% to less than 7.8%. The underestimation of the striatum to background activity ratio was also improved from 31% to 2.7%.