Partial Volume Correction Techniques Research Articles

Partial volume correction in longitudinal tau PET studies: is it really needed?

Background[18F]flortaucipir (FTP) tau PET quantification is known to be affected by non-specific binding in off-target regions. Although partial volume correction (PVC) techniques partially account for this effect, their inclusion may also introduce noise and variability into the quantification process. While the impact of these effects has been studied in cross-sectional designs, the benefits and drawbacks of PVC on longitudinal FTP studies is still under scrutiny. The aim of this work was to study the performance of the most common PVC techniques for longitudinal FTP imaging. MethodsA cohort of 247 individuals from the Alzheimer's Disease Neuroimaging Initiative with concurrent baseline FTP-PET, amyloid-beta (Aβ) PET and structural MRI, as well as with follow-up FTP-PET and MRI were included in the study. FTP-PET scans were corrected for partial volume effects using Meltzer's, a simple and popular analytical PVC, and both the region-based voxel-wise (RBV) and the iterative Yang (iY) corrections. FTP SUVR values and their longitudinal rates of change were calculated for regions of interest (ROI) corresponding to Braak Areas I-VI, for a temporal meta-ROI and for regions typically displaying off-target FTP binding (caudate, putamen, pallidum, thalamus, choroid plexus, hemispheric white matter, cerebellar white matter, and cerebrospinal fluid). The longitudinal correlation between binding in off-target and target ROIs was analysed for the different PVCs. Additionally, group differences in longitudinal FTP SUVR rates of change between Aβ-negative (A-) and Aβ-positive (A+), and between cognitively unimpaired (CU) and cognitively impaired (CI) individuals, were studied. Finally, we compared the ability of different partial-volume-corrected baseline FTP SUVRs to predict longitudinal brain atrophy and cognitive decline. ResultsAmong off-target ROIs, hemispheric white matter showed the highest correlation with longitudinal FTP SUVR rates from cortical target ROIs (R2=0.28–0.82), with CSF coming in second (R2=0.28–0.42). Application of voxel-wise PVC techniques minimized this correlation, with RBV performing best (R2=0.00–0.07 for hemispheric white matter). PVC also increased group differences between CU and CI individuals in FTP SUVR rates of change across all target regions, with RBV again performing best (No PVC: Cohen's d = 0.26–0.66; RBV: Cohen's d = 0.43–0.74). These improvements were not observed for differentiating A- from A+ groups. Additionally, voxel-wise PVC techniques strengthened the correlation between baseline FTP SUVR and longitudinal grey matter atrophy and cognitive decline. ConclusionQuantification of longitudinal FTP SUVR rates of change is affected by signal from off-target regions, especially the hemispheric white matter and the CSF. Voxel-wise PVC techniques significantly reduce this effect. PVC provided a significant but modest benefit for tasks involving the measurement of group-level longitudinal differences. These findings are particularly relevant for the estimations of sample sizes and analysis methodologies of longitudinal group studies.

PARTIAL VOLUME CORRECTION TECHNIQUES FOR LONGITUDINAL TAU‐PET QUANTIFICATION: A COMPARISON STUDY

AbstractBackgroundThe selection of an appropriate Partial Volume Correction (PVC) is crucial for evaluating tau accumulation rates using 18F‐Flortaucipir (18F‐FTP). PVC can reduce the impact of off‐target binding, but it can also increase noise and variability. While these effects may be averaged on cross‐sectional studies, they might be of paramount importance when evaluating within‐subject longitudinal tau‐PET signal. The aim of this study is to evaluate the robustness of different PVCs for the evaluation of tau accumulation rates in longitudinal 18F‐FTP studies, as measured by their correlation with cognitive clinical progression.Method111 cognitively impaired subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with serial 18F‐FTP PET and T1 images, as well as cognitive performance evaluation available for a 2‐year follow‐up period, were included in the study. 18F‐FTP PET images were corrected by applying a traditional deconvolution PVC (Grey matter only), the reblurred Van‐Cittert (RVC) analytical PVC (grey + white matter), and 2 voxel‐based PVCs, the region‐based voxel‐wise correction (RBV) and the iterative Yang (iY). Longitudinal rates of change for the regional standard uptake value ratios (SUVR) of the temporal meta‐ROI were computed for the images corrected for the different PVCs, and their correlation with the rates of change of the ADAS‐Cog 11 cognitive performance metric was analyzed.ResultThe deconvolution PVC correction showed the strongest correlation between decreased cognitive performance and increased tau accumulation rates (p<0.001, ρ = 0.38), followed closely by the RBV (p<0.001, ρ = 0.36) and iY (p<0.001, ρ = 0.35) corrections (Fig. 1). In contrast, the RVC results (p = 0.03, ρ = 0.20) were comparable to not applying any PVC at all (p = 0.03, ρ = 0.21).ConclusionOur findings suggest that longitudinal FTP studies might benefit from the use of PVC techniques for the evaluation of tau accumulation rates. Tau uptake rates of change tracked the observed clinical progression more accurately after certain PVC corrections were applied. Moreover, a simple deconvolution PVC has been shown to perform similarly to more complex, voxel‐wise corrections such as the RBV and iY.

Brain partial volume correction with point spreading function reconstruction in high-resolution digital PET: comparison with an MR-based method in FDG imaging

ObjectiveIn quantitative positron emission tomography (PET) of the brain, partial volume effect due mainly to the finite spatial resolution of the PET scanner (> 3 mm full width at half maximum [FWHM]) is a primary source of error in the measurement of tracer uptake, especially in small structures such as the cerebral cortex (typically < 3 mm thickness). The aim of this study was to evaluate the partial volume correction (PVC) performance of point spread function-incorporated reconstruction (PSF reconstruction) in combination with the latest digital PET scanner. This evaluation was performed through direct comparisons with magnetic resonance imaging (MR)-based PVC (used as a reference method) in a human brain study.MethodsTen healthy subjects underwent brain 18F-FDG PET (30-min acquisition) on a digital PET/CT system (Siemens Biograph Vision, 3.5-mm FWHM scanner resolution at the center of the field of view) and anatomical T1-weighted MR imaging for MR-based PVC. PSF reconstruction was applied with a wide range of iterations (4 to 256; 5 subsets). FDG uptake in the cerebral cortex was evaluated using the standardized uptake value ratio (SUVR) and compared between PSF reconstruction and MR-based PVC.ResultsCortical structures were visualized by PSF reconstruction with several tens of iterations and were anatomically well matched with the MR-derived cortical segments. Higher numbers of iterations resulted in higher cortical SUVRs, which approached those of MR-based PVC (1.76), although even with the maximum number of iterations they were still smaller by 16% (1.47), corresponding to approximately 1.5-mm FWHM of the effective spatial resolution.ConclusionWith the latest digital PET scanner, PSF reconstruction can be used as a PVC technique in brain PET, albeit with suboptimal resolution recovery. A relative advantage of PSF reconstruction is that it can be applied not only to cerebral cortical regions, but also to various small structures such as small brain nuclei that are hardly visualized on anatomical T1-weighted imaging, and thus hardly recovered by MR-based PVC.

Impact of meningeal uptake and partial volume correction techniques on [18F]MK-6240 binding in aMCI patients and healthy controls

[18F]MK-6240 is a second-generation tau PET-tracer to quantify neurofibrillary tangles in-vivo. However, individually variable levels of meningeal uptake induce spill-in-effects into the cortex, complicating [18F]MK-6240 PET quantification. Group SUVR differences between age-matched HC subgroups with varying extracerebral uptake (EC-low/mixed/high), and between aMCI and each HC subgroup were assessed without and with partial volume correction (PVC). Both Müller-Gartner (MG-)PVC and region-based voxelwise (RBV-)PVC, with the latter also correcting for extracerebral spill-in-effects, were implemented. Between HC groups, where no differences are to be expected, HC EC-high showed spill-in differences compared to HC EC-low when no PVC was applied while for MG-PVC, differences were reduced and, for RBV-PVC, no statistically significant differences were observed. Between aMCI and HC, cortical SUVR differences were statistically significant, both without and with PVC, but modulated by the varying meningeal uptake in HC subgroups when no PVC was applied. After applying PVC, correlations to clinical parameters improved and effect sizes between HC and aMCI increased, independent of the HC-subgroup. Therefore, appropriate PVC with correction for extracerebral spill-in-effects is recommended to minimize the impact of varying meningeal uptake on cortical differences between HC and aMCI.

Deep-ASL enhancement technique in arterial spin labeling MRI – A novel approach for the error reduction of partial volume correction technique with linear regression algorithm

Arterial Spin Labelling MRI is a noninvasive quantitative imaging technique for measuring Cerebral Blood Flow (CBF) that plays a vital role in diagnosing different neurological disorders. Limited signal-to-noise ratio and significant partial volume effect due to the low resolution of ASL images make an accurate CBF estimation difficult. This work proposes a deep learning based ASL enhancement algorithm (Deep-ASL ENHANCE), based on the principle of single image super resolution and multi-loss joint strategy with two reconstruction modules and one weighted fusion module that employ residual dense block as the basic building block. Lack of huge amount of low quality and high quality images for training this deep learning network, is addressed by generating simulated ASL images from structural images of ADNI2. The experiment is conducted and results are evaluated on a simulated dataset in terms of different metrics such as RMSE, PSNR and SSIM. The model is also validated using clinical ASL images with the help of two independent radiologists and the results are compared using Visual Quality Score (VQS). The deep learning model trained by using simulated ASL images shows more promising results on clinical ASL data. The effectiveness of using Deep-ASL ENHANCE as a preprocessing step to the partial volume correction technique with Linear Regression algorithm (LR) has been investigated using RMSE score and it is found that CBF quantification accuracy is improved compared to the standalone LR algorithm.

Evaluation of amyloid and tau PET quantitation methods using a 3D‐printed anatomically accurate brain phantom

AbstractBackgroundA potential source of error in quantifying longitudinal changes in amyloid and tau imaging is the spatial resolution of PET. Partial volume correction (PVC) methods have been developed to account for this, but there remains a lack of consensus in the Alzheimer’s field on their use due to a lack of method evaluation relative to ground truth. The aim of this work was to evaluate various reconstruction and image‐based PVC techniques using an anatomically accurate 3D‐printed PET phantom with physiologically relevant radiotracer distributions.MethodsA lateral temporal phantom (Figure 1) with six fillable, thin‐walled (1.0 mm) chambers corresponding to inferior, middle, and superior temporal gray matter (GM) and white matter (WM) regions was constructed via 3D‐printing (Formlabs Form 3) using the FreeSurfer v5.3 segmented sample subject “bert” as a pattern. Inferior and superior temporal GM regions were filled with a 3.0 kBq/cc concentration of F‐18 solution and WM regions with 1.5 kBq/cc, simulating a high amyloid‐burden subject with a GM‐to‐WM radioactivity ratio of 2:1. The phantom was scanned on a Siemens Biograph mCT and reconstructed using three techniques: FBP; OSEM; and TrueX, an iterative method with system matrix modeling using a spatially variant point spread function. Image‐based geometric transfer matrix (GTM) PVC was applied to the FBP and OSEM images. Regional uncorrected and PVC radioactivity concentrations were compared to known ground truth.ResultsFBP, OSEM, and TrueX PET images are presented in Figure 2. Inferior and superior temporal GM and WM radioactivity concentrations for each of the reconstructions, uncorrected and PVC, are presented in Figure 3.ConclusionGTM PVC resulted in more accurate regional quantification relative to uncorrected data, regardless of reconstruction method. TrueX, which accounts for the system resolution during reconstruction, did not result in improved quantitative accuracy despite apparent differences in image quality. Optimization of TrueX parameters may result in improved quantitation accuracy. This study adhered to one fundamental assumption of the GTM technique: radioactivity uniformity within a region. This assumption may be violated in human imaging. Future studies will address this and will examine varying levels of amyloid and tau burden and cortical atrophy.

Analysis of partial volume correction on quantification and regional heterogeneity in cardiac PET

BackgroundThe partial volume correction (PVC) of cardiac PET datasets using anatomical side information during reconstruction is appealing but not straightforward. Other techniques, which do not make use of additional anatomical information, could be equally effective in improving the reconstructed myocardial activity. MethodsResolution modeling in combination with different noise suppressing priors was evaluated as a means to perform PVC. Anatomical priors based on a high-resolution CT are compared to non-anatomical, edge-preserving priors (relative difference and total variation prior). The study is conducted on ex vivo datasets from ovine hearts. A simulation study additionally clarifies the relationship between prior effectiveness and myocardial wall thickness. ResultsSimple resolution modeling during data reconstruction resulted in over- and underestimation of activity, which hampers the absolute left ventricular quantification when compared to the ground truth. Both the edge-preserving and the anatomy-based PVC techniques improve the absolute quantification, with comparable results (Student t-test, P = .17). The relative tracer distribution was preserved with any reconstruction technique (repeated ANOVA, P = .98). ConclusionsThe use of edge-preserving priors emerged as optimal choice for quantification of tracer uptake in the left ventricular wall of the available datasets. Anatomical priors visually outperformed edge-preserving priors when the thinnest structures were of interest.

Impact of partial volume correction on the regional correspondence between in vivo [C-11]PiB PET and postmortem measures of Aβ load.

The positron emission tomography (PET) radiotracer Pittsburgh Compound B ([C-11]PiB) demonstrates a high affinity for fibrillary amyloid-beta (Aβ) aggregates. However, [C-11]PiB's in vivo sensitivity and specificity is an ongoing area of investigation in correlation studies with postmortem measures of Aβ pathology. One potential confound in PET-to-postmortem correlation studies is the limited spatial resolution of PET and resulting partial volume effects (PVEs). In this work, we evaluated the impact of three partial volume correction (PVC) techniques – the Meltzer, the modified Müller-Gärtner, and the Region-Based Voxel-Wise – on correlations between region-matched in vivo [C-11]PiB standardized uptake value ratios (SUVRs) and postmortem measures of Aβ pathology in a unique cohort of nine subjects. Postmortem Aβ pathology was assessed histologically as percent area coverage of 6-CN-PiB positive and Aβ immunoreactive (4G8 antibody) deposits. The application of all three PVC techniques resulted in minimally reduced PET-to-postmortem correlations relative to no PVC. However, correlations to both 6-CN-PiB and 4G8 percent area across all PVC techniques and no PVC were statistically significant at p < 0.01, suggesting that PVC is of minimal importance in understanding the relationship between Aβ PET and neuropathologically assessed Aβ. Thus, the utility of PVC in Aβ PET imaging should continue to be examined on an application-specific basis.

PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography

Positron emission tomography (PET) images are degraded by a phenomenon known as the partial volume effect (PVE). Approaches have been developed to reduce PVEs, typically through the utilisation of structural information provided by other imaging modalities such as MRI or CT. These methods, known as partial volume correction (PVC) techniques, reduce PVEs by compensating for the effects of the scanner resolution, thereby improving the quantitative accuracy. The PETPVC toolbox described in this paper comprises a suite of methods, both classic and more recent approaches, for the purposes of applying PVC to PET data.Eight core PVC techniques are available. These core methods can be combined to create a total of 22 different PVC techniques. Simulated brain PET data are used to demonstrate the utility of toolbox in idealised conditions, the effects of applying PVC with mismatched point-spread function (PSF) estimates and the potential of novel hybrid PVC methods to improve the quantification of lesions.All anatomy-based PVC techniques achieve complete recovery of the PET signal in cortical grey matter (GM) when performed in idealised conditions. Applying deconvolution-based approaches results in incomplete recovery due to premature termination of the iterative process. PVC techniques are sensitive to PSF mismatch, causing a bias of up to 16.7% in GM recovery when over-estimating the PSF by 3 mm. The recovery of both GM and a simulated lesion was improved by combining two PVC techniques together.The PETPVC toolbox has been written in C++, supports Windows, Mac and Linux operating systems, is open-source and publicly available.

Establishment of an open database of realistic simulated data for evaluation of partial volume correction techniques in brain PET/MR.

The Partial Volume (PV) effect in Positron Emission Tomography (PET) imaging leads to loss in quantification accuracy, which manifests in PV effects (small objects occupy partially the sensitive volume of the imaging instrument, resulting in blurred images). Simultaneous acquisition of PET and Magnetic Resonance Imaging (MRI) produces concurrent metabolic and anatomical information. The latter has proved to be very helpful for the correction of PV effects. Currently, there are several techniques used for PV correction. They can be applied directly during the reconstruction process or as a post-processing step after image reconstruction. In order to evaluate the efficacy of the different PV correction techniques in brain- PET, we are constructing a database of simulated data. Here we present the framework and steps involved in constructing this database. Static 18F-FDG epilepsy and 18F-Florbetapir amyloid dementia PET/MR were selected because of their very different characteristics. The methodology followed was based on four main steps: Image pre-processing, Ground Truth (GT) generation, MRI and PET data simulation and reconstruction. All steps used Open Source software and can therefore be repeated at any centre. The framework as well as the database will be freely accessible. Tools used included GIF, FSL, POSSUM, GATE and STIR. The final data obtained after simulation, involving raw or reconstructed PET data together with corresponding MRI datasets, were close to the original patient data. Besides, there is the advantage that data can be compared with the GT. We indicate several parameters that can be improved and optimized.

Partial volume correction in quantitative amyloid imaging

Amyloid imaging is a valuable tool for research and diagnosis in dementing disorders. As positron emission tomography (PET) scanners have limited spatial resolution, measured signals are distorted by partial volume effects. Various techniques have been proposed for correcting partial volume effects, but there is no consensus as to whether these techniques are necessary in amyloid imaging, and, if so, how they should be implemented. We evaluated a two-component partial volume correction technique and a regional spread function technique using both simulated and human Pittsburgh compound B (PiB) PET imaging data. Both correction techniques compensated for partial volume effects and yielded improved detection of subtle changes in PiB retention. However, the regional spread function technique was more accurate in application to simulated data. Because PiB retention estimates depend on the correction technique, standardization is necessary to compare results across groups. Partial volume correction has sometimes been avoided because it increases the sensitivity to inaccuracy in image registration and segmentation. However, our results indicate that appropriate PVC may enhance our ability to detect changes in amyloid deposition.

Decomposing cerebral blood flow MRI into functional and structural components: A non-local approach based on prediction

We present RIPMMARC (Rotation Invariant Patch-based Multi-Modality Analysis aRChitecture), a flexible and widely applicable method for extracting information unique to a given modality from a multi-modal data set. We use RIPMMARC to improve the interpretation of arterial spin labeling (ASL) perfusion images by removing the component of perfusion that is predicted by the underlying anatomy. Using patch-based, rotation invariant descriptors derived from the anatomical image, we learn a predictive relationship between local neuroanatomical structure and the corresponding perfusion image. This relation allows us to produce an image of perfusion that would be predicted given only the underlying anatomy and a residual image that represents perfusion information that cannot be predicted by anatomical features. Our learned structural features are significantly better at predicting brain perfusion than tissue probability maps, which are the input to standard partial volume correction techniques. Studies in test–retest data show that both the anatomically predicted and residual perfusion signals are highly replicable for a given subject. In a pediatric population, both the raw perfusion and structurally predicted images are tightly linked to age throughout adolescence throughout the brain. Interestingly, the residual perfusion also shows a strong correlation with age in selected regions including the hippocampi (corr=0.38, p-value <10−6), precuneus (corr=−0.44, p<10−5), and combined default mode network regions (corr=−0.45, p<10−8) that is independent of global anatomy-perfusion trends. This finding suggests that there is a regionally heterogeneous pattern of functional specialization that is distinct from that of cortical structural development.

Partial volume correction for approximating crack opening displacements in CFRP material obtained from micro-focus X-ray CT scans

This paper presents a partial volume correction technique that applies a measurement weighting based on grey scale intensity values, allowing crack opening displacements (CODs) to be better estimated in micro-focus computed tomography (μCT) scans. These were tested on 3D data obtained from two separate μCT scanners on particle toughened and non-particle toughened carbon fibre material subjected to low velocity impact. Direct comparisons of COD estimations were made with higher resolution measurements obtained using synchrotron radiation computed tomography (SRCT) scans taken at the European Synchrotron Radiation Facility (ESRF). In this study, partial volume correction is reported to improve the accuracy of these measurements to within 20% of SRCT measurements, whereas measurements based on counting interconnected voxels representing a detectable crack are reported to consistently overestimate crack openings by up to 500%. Scatter in estimations was dependent on material type, noise, and artefacts associated with μCT volumes.

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.

The importance of appropriate partial volume correction for PET quantification in Alzheimer’s disease

Alzheimer's disease (AD) is the most common form of dementia. Clinically, it is characterized by progressive cognitive and functional impairment with structural hallmarks of cortical atrophy and ventricular expansion. Amyloid plaque aggregation is also known to occur in AD subjects. In-vivo imaging of amyloid plaques is now possible with positron emission tomography (PET) radioligands. PET imaging suffers from a degrading phenomenon known as the partial volume effect (PVE). The quantitative accuracy of PET images is reduced by PVEs primarily due to the limited spatial resolution of the scanner. The degree of PVE is influenced by structure size, with smaller structures tending to suffer from more severe PVEs such as atrophied grey matter regions. The aims of this paper were to investigate the effect of partial volume correction (PVC) on the quantification of amyloid PET and to highlight the importance of selecting an appropriate PVC technique. An improved PVC technique, region-based voxel-wise (RBV) correction, was compared against existing Van-Cittert (VC) and Müller-Gärtner (MG) methods using amyloid PET imaging data. Digital phantom data were produced using segmented MRI scans from a control subject and an AD subject. Typical tracer distributions were generated for each of the phantom anatomies. Also examined were 70 clinical PET scans acquired using [(18)F]flutemetamol. Volume of interest (VOI) analysis was performed for corrected and uncorrected images. PVC was shown to improve the quantitative accuracy of regional analysis performed on amyloid PET images. Of the corrections applied, VC deconvolution demonstrated the worst recovery of grey matter values. MG PVC was shown to induce biases in some grey matter regions due to grey matter variability. In addition, white matter variability was shown to influence the accuracy of MG PVC in cortical grey matter and also cerebellar grey matter, a typical reference region for amyloid PET normalization in sporadic AD. RBV was shown to be more accurate than MG in terms of grey matter and white matter uptake. An increase in within-group variability after PVC was observed and is believed to be a genuine, more accurate representation of the data rather than a correction-induced error. The standardized uptake value ratio (SUVR) threshold for classifying subjects as either amyloid-positive or amyloid-negative was found to be 1.64 in the uncorrected dataset, rising to 2.25 after PVC. Care should be taken when applying PVC to amyloid PET images. Assumptions made in existing PVC strategies can induce biases that could lead to erroneous inferences about uptake in certain regions. The proposed RBV PVC technique accounts for within-compartment variability, with the potential to reduce errors of this kind.

SU-GG-I-137: Effects of Background Activity On Partial Volume Correction (PVC) in PET Imaging

Purpose: PVC techniques based on a‐priori knowledge of object size have been previously proposed and evaluated. The aim of this abstract is to investigate the effect of background activity (BA) correction on the accuracy of PVC. Method and Materials: An IEC phantom containing six spheres (1–3.7cm) was scanned using GE DRX PET/CT scanner. The sphere to background ratio (SBR) was (4:1, 6.5:1, 11.1:1) while keeping BA concentration constant. BA was set to that found in the thorax of clinical PET studies. PET data was acquired in 3D mode for 3 minutes. ROIs were drawn on all spheres. PVC was then applied with and without background subtraction (BS) while using the scanner's point spread function (PSF) and the sphere size obtained from CT. Care was taken to include the effects of reconstruction filter on the PSF. For PVC with BS, the BA was first subtracted from the mean sphere activity concentration (AC) and then divided by the convolution of the PSF with a binary map of the true sphere size obtained from CT. Finally, BA was then added to give the corrected sphere AC. Plots of mean AC with and without BS versus sphere size were generated and differences between the two corrections were calculated. Results: PVC with BS was consistently better than without BS for different SBR and sphere sizes. This effect was more pronounced as SBR and sphere size decreased. PVC with BS was on average 6.7% different than the true value while that without BS was 28.5% different. The smallest sphere had the biggest discrepancy with a difference of 64.3% and 13.9% for PVC without and with BS respectively. Conclusion: Background effects can impact the accuracy of PVC in PETimages, especially for small SBR and tumor size. BS should be implemented with PVC to insure accurate lesion quantification.

TH‐C‐351‐09: Partial Volume Correction of PET‐Imaged Tumor Heterogeneity Using Expectation Maximization

Purpose: Due to the limited spatial resolution of PET imaging, small objects experience partial volume effects which impact the quantification and spatial distribution of imaged tumor heterogeneities. This study examines the ability of an iterative partial volume correction (PVC) method to restore imaged heterogeneity to an object heterogeneity map using expectation maximization. Method and Materials: Treating PET as a linear system, images obtained through the convolution of a true object's radioactivity distribution and the system's point spread function (PSF) may be used to uncover the true object's activity distribution. The presented method uses iterative expectation maximization with the measured system PSF to determine the true object activity distribution. The three‐dimensional spatially dependent PSF was obtained by Gaussian fitting point objects imaged on a Discovery LS PET/CT scanner radially in single plane. The technique was tested on dual‐tracer heterogeneity phantoms using spheres of 10 and 15 mm diameter as both hot and cold heterogeneities relative to the phantoms' uniform tumor activity. The method was also applied to clinical studies to observe the impact of quantitative changes. Results: The observed PVC showed dependencies on heterogeneity size and contrast with surrounding regions. This PVC technique successfully recovered phantom heterogeneities hotter than uniform tumor activity, but experienced difficulty with cold heterogeneity. Quantitative image accuracy was restored as heterogeneities experienced shifts of 25 and 35% for diameters of 15 and 10 mm, respectively. Using changes in the image correction matrix proved a successful stopping criteria for determining the optimal number of iterations for PVC in phantoms. Changes as large as ±20% were frequently observed in patient heterogeneities. Conclusion: The expectation maximization PVC method successfully recovers tumor heterogeneity lost through PET imaging. Inclusion of PET information into treatment planning or treatment assessment would greatly benefit from the quantitative accuracy gains shown in this PVC method.