Quantification of PET infusion studies without true equilibrium: A tissue clearance correction.
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ABSTRACT:
SUBMITTER: Hillmer AT
PROVIDER: S-EPMC7168787 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The quantification of dynamic positron emission tomography studies performed with arterial sampling usually requires correcting the input function for the presence of radiometabolites by using a model of the plasma parent fraction (PPf). Here, we show how to include the duration of radioligand injection in the PPf model formulations to achieve a more physiologic description of the plasma measurements. This formulation (here called convoluted model) was tested on simulated data and on three datasets with different parent kinetics: [(11)C]NOP-1A, [(11)C]MePPEP, and [(11)C](R)-rolipram. Results showed that convoluted PPf models better described the fraction of unchanged parent in the plasma compared with standard models for all three datasets (weighted residuals sum of squares up to 25% lower). When considering the effect on tissue quantification, the overall impact on the total volume of distribution (VT) was low. However, the impact was significant and radioligand-dependent on the binding potential (BP) and the microparameters (K1, k2, k3, and k4). Simulated data confirmed that quantification is sensitive to different degrees to PPf model misspecification. Including the injection duration allows obtaining a more accurate correction of the input function for the presence of radiometabolites and this yields a more reliable quantification of the tissue parameters.
| S-EPMC4640335 | biostudies-literature
Project description:UNLABELLED:Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVRs) in ligand-receptor dynamic PET studies. The objective of this study was to use a recently developed relative equilibrium-based graphical (RE) plot method to improve and simplify the 2 commonly used methods for quantification of (11)C-Pittsburgh compound B ((11)C-PiB) PET. METHODS:The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight (11)C-PiB dynamic PET scans (66 from controls and 12 from participants with mild cognitive impaired [MCI] from the Baltimore Longitudinal Study of Aging) were acquired over 90 min. Regions of interest (ROIs) were defined on coregistered MR images. Both the ROI and the pixelwise time-activity curves were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI time-activity curves were used as a reference for comparison of DVR estimates. RESULTS:Results from the theoretic analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI time-activity curves. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, and cingulate regions and the striatum were underestimated by the Logan plot (controls, 4%-12%; MCI, 9%-16%) and overestimated by the SUVR (controls, 8%-16%; MCI, 16%-24%). This bias was higher in the MCI group than in controls (P < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR. CONCLUSION:The RE plot improves pixelwise quantification of (11)C-PiB dynamic PET, compared with the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates than of SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of (11)C-PiB studies.
| S-EPMC3449083 | biostudies-literature
Project description:BACKGROUND:Subject motion in positron emission tomography (PET) studies leads to image blurring and artifacts; simultaneously acquired magnetic resonance imaging (MRI) data provides a means for motion correction (MC) in integrated PET/MRI scanners. PURPOSE:To assess the effect of realistic head motion and MR-based MC on static [18 F]-fluorodeoxyglucose (FDG) PET images in dementia patients. STUDY TYPE:Observational study. POPULATION:Thirty dementia subjects were recruited. FIELD STRENGTH/SEQUENCE:3T hybrid PET/MR scanner where EPI-based and T1 -weighted sequences were acquired simultaneously with the PET data. ASSESSMENT:Head motion parameters estimated from high temporal resolution MR volumes were used for PET MC. The MR-based MC method was compared to PET frame-based MC methods in which motion parameters were estimated by coregistering 5-minute frames before and after accounting for the attenuation-emission mismatch. The relative changes in standardized uptake value ratios (SUVRs) between the PET volumes processed with the various MC methods, without MC, and the PET volumes with simulated motion were compared in relevant brain regions. STATISTICAL TESTS:The absolute value of the regional SUVR relative change was assessed with pairwise paired t-tests testing at the P?=?0.05 level, comparing the values obtained through different MR-based MC processing methods as well as across different motion groups. The intraregion voxelwise variability of regional SUVRs obtained through different MR-based MC processing methods was also assessed with pairwise paired t-tests testing at the P?=?0.05 level. RESULTS:MC had a greater impact on PET data quantification in subjects with larger amplitude motion (higher than 18% in the medial orbitofrontal cortex) and greater changes were generally observed for the MR-based MC method compared to the frame-based methods. Furthermore, a mean relative change of ?4% was observed after MC even at the group level, suggesting the importance of routinely applying this correction. The intraregion voxelwise variability of regional SUVRs was also decreased using MR-based MC. All comparisons were significant at the P?=?0.05 level. DATA CONCLUSION:Incorporating temporally correlated MR data to account for intraframe motion has a positive impact on the FDG PET image quality and data quantification in dementia patients. LEVEL OF EVIDENCE:3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1288-1296.
| S-EPMC6129224 | biostudies-literature
Project description:Hybrid PET and MR scanners have become a reality in recent years, with the benefits of reduced radiation exposure, reduction of imaging time, and potential advantages in quantification. Appropriate attenuation correction remains a challenge. Biases in PET activity measurements were demonstrated using the current MR-based attenuation-correction technique. We aimed to investigate the impact of using a standard MR-based attenuation correction technique on the clinical and research utility of a PET/MR hybrid scanner for amyloid imaging.Florbetapir scans were obtained for 40 participants on a hybrid scanner with simultaneous MR acquisition. PET images were reconstructed using both MR- and CT-derived attenuation maps. Quantitative analysis was performed for both datasets to assess the impact of MR-based attenuation correction to absolute PET activity measurements as well as target-to-reference ratio (SUVR). Clinical assessment was also performed by a nuclear medicine physician to determine amyloid status based on the criteria in the Food and Drug Administration prescribing information for florbetapir.MR-based attenuation correction led to underestimation of PET activity for most parts of the brain, with a small overestimation for deep brain regions. There was also an overestimation of SUVRs with cerebellar reference. SUVR measurements obtained from the 2 attenuation-correction methods were strongly correlated. Clinical assessment of amyloid status resulted in identical classification as positive or negative regardless of the attenuation-correction methods.MR-based attenuation correction causes biases in quantitative measurements. The biases may be accounted for by a linear model, although the spatial variation cannot be easily modeled. The quantitative differences, however, did not affect clinical assessment as positive or negative.
| S-EPMC4891225 | biostudies-literature
Project description:Combined MR∕PET is a relatively new, hybrid imaging modality. A human MR∕PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR∕PET for brain imaging.The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR∕PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [(11)C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods.For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%.MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR∕PET.
| S-EPMC3477199 | biostudies-other
Project description:BACKGROUND:The clinical impact of hypoxia in solid tumours is indisputable and yet questions about the sensitivity of hypoxia-PET imaging have impeded its uptake into routine clinical practice. Notably, the binding rate of hypoxia-sensitive PET tracers is slow, comparable to the rate of diffusive equilibration in some tissue types, including mucinous and necrotic tissue. This means that tracer uptake on the scale of a PET imaging voxel-large enough to include such tissue and hypoxic cells-can be as much determined by tissue transport properties as it is by hypoxia. Dynamic PET imaging of 20 patients with pancreatic ductal adenocarcinoma was used to assess the impact of transport on surrogate metrics of hypoxia: the tumour-to-blood ratio [TBR(t)] at time t post-tracer injection and the trapping rate k 3 inferred from a two-tissue compartment model. Transport quantities obtained from this model included the vascular influx and efflux rate coefficients, k 1 and k 2, and the distribution volume v d ?k 1/(k 2+k 3). RESULTS:Correlations between voxel- and whole tumour-scale k 3 and TBR values were weak to modest: the population average of the Pearson correlation coefficients (r) between voxel-scale k 3 and TBR (1 h) [TBR(2 h)] values was 0.10 [0.01] in the 20 patients, while the correlation between tumour-scale k 3 and TBR(2 h) values was 0.58. Using Patlak's formula to correct uptake for the distribution volume, correlations became strong (r=0.80[0.52] and r=0.93, respectively). The distribution volume was substantially below unity for a large fraction of tumours studied, with v d ranging from 0.68 to 1 (population average, 0.85). Surprisingly, k 3 values were strongly correlated with v d in all patients. A model was proposed to explain this in which k 3 is a combination of the hypoxia-sensitive tracer binding rate k b and the rate k eq of equilibration in slow-equilibrating regions occupying a volume fraction 1-v d of the imaged tissue. This model was used to calculate the proposed hypoxia surrogate marker k b. CONCLUSIONS:Hypoxia-sensitive PET tracers are slow to reach diffusive equilibrium in a substantial fraction of pancreatic tumours, confounding quantification of hypoxia using both static (TBR) and dynamic (k 3) PET imaging. TBR is reduced by distribution volume effects and k 3 is enhanced by slow equilibration. We proposed a novel model to quantify tissue transport properties and hypoxia-sensitive tracer binding in order to improve the sensitivity of hypoxia-PET imaging.
| S-EPMC5741574 | biostudies-literature
Project description:BACKGROUND:Accurate quantification of plaque imaging using 18F-NaF PET requires partial volume correction (PVC). METHODS:PVC of PET data was implemented by the use of a local projection (LP) method. LP-based PVC was evaluated with an image quality (NEMA) and with a thorax phantom with "plaque-type" lesions of 18-36 mL. The validated PVC method was then applied to a cohort of 17 patients, each with at least one plaque in the carotid or ascending aortic arteries. In total, 51 calcified (HU > 110) and 16 non-calcified plaque lesions (HU < 110) were analyzed. The lesion-to-background ratio (LBR) and the relative change of LBR (?LBR) were measured on PET. RESULTS:Following PVC, LBR of the spheres (NEMA phantom) was within 10% of the original values. LBR of the thoracic lesions increased by 155% to 440% when the LP-PVC method was applied to the PET images. In patients, PVC increased the LBR in both calcified [mean = 78% (-8% to 227%)] and non-calcified plaques [mean = 41%, (-9%-104%)]. CONCLUSIONS:PVC helps to improve LBR of plaque-type lesions in both phantom studies and clinical patients. Better results were obtained when the PVC method was applied to images reconstructed with point spread function modeling.
| S-EPMC6153866 | biostudies-other
Project description:The impact of a method for MR-based respiratory motion correction of PET data on lesion visibility and quantification in patients with oncologic findings in the lung was evaluated. Twenty patients with one or more lesions in the lung were included. Hybrid imaging was performed on an integrated PET/MR system using 18F-FDG as radiotracer. The standard thoracic imaging protocol was extended by a free-breathing self-gated acquisition of MR data for motion modelling. PET data was acquired simultaneously in list-mode for 5-10 mins. One experienced radiologist and one experienced nuclear medicine specialist evaluated and compared the post-processed data in consensus regarding lesion visibility (scores 1-4, 4 being best), image noise levels (scores 1-3, 3 being lowest noise), SUVmean and SUVmax. Motion-corrected (MoCo) images were additionally compared with gated images. Non-motion-corrected free-breathing data served as standard of reference in this study. Motion correction generally improved lesion visibility (3.19 ± 0.63) and noise ratings (2.95 ± 0.22) compared to uncorrected (2.81 ± 0.66 and 2.95 ± 0.22, respectively) or gated PET data (2.47 ± 0.93 and 1.30 ± 0.47, respectively). Furthermore, SUVs (mean and max) were compared for all methods to estimate their respective impact on the quantification. Deviations of SUVmax were smallest between the uncorrected and the MoCo lesion data (average increase of 9.1% of MoCo SUVs), while SUVmean agreed best for gated and MoCo reconstructions (MoCo SUVs increased by 1.2%). The studied method for MR-based respiratory motion correction of PET data combines increased lesion sharpness and improved lesion activity quantification with high signal-to-noise ratio in a clinical setting. In particular, the detection of small lesions in moving organs such as the lung and liver may thus be facilitated. These advantages justify the extension of the PET/MR imaging protocol by 5-10 minutes for motion correction.
| S-EPMC7272064 | biostudies-literature
Project description:Several factors have to be considered for implementing an accurate attenuation-correction (AC) method in a combined MR-PET scanner. In this work, some of these challenges were investigated, and an AC method based entirely on the MRI data obtained with a single dedicated sequence was developed and used for neurologic studies performed with the MR-PET human brain scanner prototype.The focus was on the problem of bone-air segmentation, selection of the linear attenuation coefficient for bone, and positioning of the radiofrequency coil. The impact of these factors on PET data quantification was studied in simulations and experimental measurements performed on the combined MR-PET scanner. A novel dual-echo ultrashort echo time (DUTE) MRI sequence was proposed for head imaging. Simultaneous MR-PET data were acquired, and the PET images reconstructed using the proposed DUTE MRI-based AC method were compared with the PET images that had been reconstructed using a CT-based AC method.Our data suggest that incorrectly accounting for the bone tissue attenuation can lead to large underestimations (>20%) of the radiotracer concentration in the cortex. Assigning a linear attenuation coefficient of 0.143 or 0.151 cm(-1) to bone tissue appears to give the best trade-off between bias and variability in the resulting images. Not identifying the internal air cavities introduces large overestimations (>20%) in adjacent structures. On the basis of these results, the segmented CT AC method was established as the silver standard for the segmented MRI-based AC method. For an integrated MR-PET scanner, in particular, ignoring the radiofrequency coil attenuation can cause large underestimations (i.e., <or=50%) in the reconstructed images. Furthermore, the coil location in the PET field of view has to be accurately known. High-quality bone-air segmentation can be performed using the DUTE data. The PET images obtained using the DUTE MRI- and CT-based AC methods compare favorably in most of the brain structures.A DUTE MRI-based AC method considering all these factors was implemented. Preliminary results suggest that this method could potentially be as accurate as the segmented CT method and could be used for quantitative neurologic MR-PET studies.
| S-EPMC3801218 | biostudies-literature
Project description:Amyloid positron emission tomography (PET) imaging is a valuable tool for research and diagnosis in Alzheimer's disease (AD). Partial volume effects caused by the limited spatial resolution of PET scanners degrades the quantitative accuracy of PET image. In this study, we have applied a method to evaluate the impact of a joint-entropy based partial volume correction (PVC) technique on brain networks learned from a clinical dataset of AV-45 PET image and compare network properties of both uncorrected and corrected image-based brain networks. We also analyzed the region-wise SUVRs of both uncorrected and corrected images. We further performed classification tests on different groups using the same set of algorithms with same parameter settings. PVC has sometimes been avoided due to increased noise sensitivity in image registration and segmentation, however, our results indicate that appropriate PVC may enhance the brain network structure analysis for AD progression and improve classification performance.
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