Dedicated to Professor Rüdiger Lange on the occasion of his 65th birthdaySeveral inexpensive zeolites such as ZSM-5 (MFI), zeolite Y (FAU), and SAPO-34 (CHA) were developed from kaolin clay and applied for CO 2 capture from air. These molecular sieves were functionalized with tetraethylenepentamine (TEPA) in order to further improve their CO 2 capacity. The obtained kaolin-based zeolites exhibited similar properties than those of zeolites prepared with other sources. They also revealed a bimodal pore network consisting of both micropores and mesopores. The effect of amine loading on CO 2 capture was investigated and the results demonstrated that TEPA-modified zeolite Y with 10 wt % TEPA had a higher capacity than other zeolites due to its larger mesopore volume. The presence of mesopores in the zeolite Y framework facilitated a better accessibility of CO 2 molecules to the amine sites.

Objective: Dead time correction (DTC) is an important factor in ensuring accurate quantification in PET measurements. This is currently often achieved using a global DTC method, i.e., an average DTC factor is computed. For PET scanners designed to image dedicated organs, e.g., those used in brain imaging or positron emission mammography (PEM), a substantial amount of the administered radioactivity is located outside of the PET field-of-view (FOV). This activity contributes to the dead time (DT) of the scintillation detectors. Moreover, the count rates of the individual scintillation detectors are potentially very inhomogeneous due to the specific irradiation of each detector, especially for combined MR/PET systems, where radiation shields cannot be applied. Approach: We have developed a block-pairwise DTC method for our Siemens 3T MR BrainPET insert by extending a previously published method that uses the delayed random coincidence count rate to estimate the DT in the individual scans and planes (i.e., scintillation pixel rings). The method was validated in decay experiments using phantoms with a homogenous activity concentration and with and without out-of-FOV activity. Based on a three-compartment phantom, we compared the accuracy and noise properties of the block-pairwise DTC and the global DTC method. Main results: The currently used global DTC led to a substantial positive bias in regions with high activity; the block-pairwise DTC resulted in substantially less bias. The noise level for the block-pairwise DTC was comparable to the global DTC and image reconstructions without any DTC. Finally, we tested the block-pairwise DTC with a data set obtained from volunteer measurements using the mGluR5 (metabotropic glutamate receptor subtype 5) antagonist [11C]ABP688. When the relative differences in activity concentrations obtained with global DTC and block-pairwise DTC for the ACC and the cerebellum GM were compared, the ratios differed by a factor of up to 1.4 at the beginning – when the first injection is administered as a bolus with high radioactivity. Significance: In this work, global DTC was shown to have the potential to introduce quantification bias, while better quantitation accuracy was achieved with the presented block-pairwise DTC method. The method can be implemented in all systems that use the delayed window technique and is particulary expected to improve the quantiation accuracy of dedicated brain PET scanners due to their geometry.

Iterative image reconstruction is widely used in positron emission tomography. However, it is known to contribute to quantitation bias and is particularly pronounced during dynamic studies with 11C-labeled radiotracers where count rates become low towards the end of the acquisition. As the strength of the quantitation bias depends on the counts in the reconstructed frame, it can differ from frame to frame of the acquisition. This is especially relevant in the case of neuro-receptor studies with simultaneous PET/MR when a bolus-infusion protocol is applied to allow the comparison of pre- and post-task effects. Here, count dependent changes in quantitation bias may interfere with task changes. We evaluated the impact of different framing schemes on quantitation bias and its propagation into binding potential (BP) using a phantom decay study with 11C and 3D OP-OSEM. Further, we propose a framing scheme that keeps the true counts per frame constant over the acquisition time as constant framing schemes and conventional increasing framing schemes are unlikely to achieve stable bias values during the acquisition time range. For a constant framing scheme with 5 minutes frames, the BP bias was 7.13±2.01% (10.8% to 3.8%) compared to 5.63±2.85% (7.8% to 4.0%) for conventional increasing framing schemes. Using the proposed constant true counts framing scheme, a stabilization of the BP bias was achieved at 2.56±3.92% (3.5% to 1.7%). The change in BP bias was further studied by evaluating the linear slope during the acquisition time interval. The lowest slope values were observed in the constant true counts framing scheme. The constant true counts framing scheme was effective for BP bias stabilization at relevant activity and time ranges. The mean BP bias under these conditions was 2.56±3.92%, which represents the lower limit for the detection of changes in BP during equilibrium and is especially important in the case of cognitive tasks where the expected changes are low.

Objective: The positron range is a fundamental, detector-independent physical limitation to spatial resolution in positron emission tomography (PET) as it causes a significant blurring of underlying activity distribution in the reconstructed images. A major challenge for positron range correction methods is to provide accurate range kernels that inherently incorporate the generally inhomogeneous stopping power, especially at tissue boundaries. In this work, we propose a novel approach to generate accurate three-dimensional (3-D) blurring kernels both in homogenous and heterogeneous media to improve PET spatial resolution. Approach: In the proposed approach, positron energy deposition was approximately tracked along straight paths, depending on the positron stopping power of the underlying material. The positron stopping power was derived from the attenuation coefficient of 511keV gamma photons according to the available PET attenuation maps. Thus, the history of energy deposition is taken into account within the range of kernels. Special emphasis was placed on facilitating the very fast computation of the positron annihilation probability in each voxel. Results: Positron path distributions of 18F in low-density polyurethane were in high agreement with Geant4 simulation at an annihilation probability larger than 10-2~10-3 of the maximum annihilation probability. The Geant4 simulation was further validated with measured 18F depth profiles in these polyurethane phantoms. The tissue boundary of water with cortical bone and lung was correctly modeled. Residual artifacts from the numerical computations were in the range of 1%. The calculated annihilation probability in voxels shows an overall difference of less than 20% compared to the Geant4 simulation. Significance: The proposed method is expected to significantly improve spatial resolution for non-standard isotopes by providing sufficiently accurate range kernels, even in the case of significant tissue inhomogeneities.

Background For positron emission tomography (PET) ligands, such as [11C]ABP688, to be able to provide more evidence about the glutamatergic hypothesis in schizophrenia (SZ), quantification bias during dynamic PET studies and its propagation into the estimated values of non-displaceable binding potential (BPND) must be addressed. This would enable more accurate quantification during bolus + infusion (BI) neuroreceptor studies and further our understanding of neurological diseases. Previous studies have shown BPND-related biases can often occur due to overestimated cerebellum activity (reference region). This work investigates whether an alternative framing scheme can minimize quantification biases propagated into BPND, whether confounders, such as smoking status, need to be controlled for during the study, and what the consequences for the data interpretation following analysis are. A group of healthy controls (HC) and a group of SZ patients (balanced and unbalanced number of smokers) were investigated with [11C]ABP688 and a BI protocol. Possible differences in BPND quantification as a function of smoking status were tested with constant 5 min (‘Const 5 min’) and constant true counts (‘Const Trues’) framing schemes. In order to find biomarkers for SZ, the differences in smoking effects were compared between groups. The normalized BPND and the balanced number of smokers and non-smokers for both framing schemes were evaluated. Results When applying F-tests to the ‘Const 5 min’ framing scheme, effect sizes (η2p) and brain regions which showed significant effects fluctuated considerably with F = 50.106 ± 54.948 (9.389 to 112.607), P-values 0.005 to < 0.001 and η2p = 0.514 ± 0.282 (0.238 to 0.801). Conversely, when the ‘Const Trues’ framing scheme was applied, the results showed much smaller fluctuations with F = 78.038 ± 8.975 (86.450 to 68.590), P < 0.001 for all conditions and η2p = 0.730 ± 0.017 (0.742 to 0.710), and regions with significant effects were more robustly reproduced. Further, differences, which would indicate false positive identifications between HC and SZ groups in five brain regions when using the ‘Const 5 min’ framing scheme, were not observed with the ‘Const Trues’ framing. Conclusions Based on an [11C]ABP688 PET study in SZ patients, the results show that non-consistent BPND outcomes can be propagated by the framing scheme and that potential bias can be minimized using ‘Const Trues’ framing.

Background: Iterative image reconstruction algorithms are widely used in positron emission tomography (PET). However, they are known to contribute to quantitation bias, which is particularly pronounced during dynamic PET studies such as neuroreceptor binding studies with 11C-labelled radiotracers where count rates become low towards the end of the examination. This problem is relevant in case simultaneous PET/MR studies which apply a bolus-infusion protocol to allow the multimodal comparison between control or resting state and stimulation effects in a single session of e.g. 60 min, i.e. 3 half-lives of 11C. A quantitation bias may interfere with stimulation related changes. In this study, we evaluated the impact of the 3D ordinary Poisson OSEM (3D OP-OSEM) on quantitation accuracy reconstructions and the subsequent propagation into binding potential values using a decay study of a 11C filled phantom and a human brain data set. To evaluate the reconstruction bias, we tested different reconstruction framing schemes and propose a framing scheme that keeps the counts per time frame constant over the full acquisition time. We also compared the vendor’s 3D OP-OSEM image reconstruction method to an in-house developed reconstruction (PRESTO toolkit). Results: In general, a bias for low and high activity concentration regions was observed in the range of ± 3% and - 3% to 5%, respectively. Using the alternative proposed framing scheme, a lower bias was achieved for regions with low activity concentration using PRESTO, and a stabilization of the mean bias for the binding potential was achieved at around 5% with the vendor’s reconstruction throughout the relevant activity curve time interval. Conclusions: The bias in activity concentration propagated into the binding potential values leading to a mean bias of around 5%, thus allowing the detection of changes in binding values during equilibrium of > 5%.

Objective: The positron range is a fundamental, detector-independent physical limitation to special resolution in positron emission tomography (PET) as it causes a significant blurring of the reconstructed PET images. A major challenge for positron range correction methods is to provide accurate range kernels that inherently incorporate the generally inhomogeneous stopping power, especially at tissue boundaries. In this work, we propose a novel approach to generate accurate three-dimensional (3-D) blurring kernels both in homogenous and heterogeneous media to improve PET spatial resolution. Approach: In the proposed approach, positron energy deposition was approximately tracked along straight paths, depending on the positron stopping power of the underlying material. The positron stopping power was derived from the attenuation coefficient of 511keV gamma photons according to the available PET attenuation maps. Thus, the history of energy deposition is taken into account within the range of kernels. Special emphasis was placed on facilitating the very fast computation of the positron annihilation probability in each voxel. Results: Positron path distributions of 18F in low-density polyurethane were in high agreement with Geant4 simulation at an annihilation probability larger than 10-2~10-3 of the maximum annihilation probability. The Geant4 simulation was further validated with measured 18F depth profiles in these polyurethane phantoms. The tissue boundary of water with cortical bone and lung was correctly modeled. Residual artifacts from the numerical computations were in the range of 1%. The calculated annihilation probability in voxels shows an overall difference of less than 20% compared to the Geant4 simulation. Significance: The proposed method significantly improves spatial resolution for non-standard isotopes by providing accurate range kernels, even in the case of significant tissue inhomogeneities.

Dead time correction (DTC) is an important factor in ensuring accurate quantification in PET measurements. This is currently often achieved using a global DTC method, i.e., an average DTC factor is computed. For PET scanners designed to image dedicated organs, e.g., those used in brain imaging or positron emission mammography (PEM), a substantial amount of the administered radioactivity is located outside of the PET field-of-view (FOV). This activity contributes to the dead time (DT) of the scintillation detectors. Moreover, the count rates of the individual scintillation detectors are potentially very inhomogeneous due to the specific irradiation of each detector, especially for combined MR/PET systems, where radiation shields cannot be applied. We have developed a block-pairwise DTC method for our Siemens 3T MR BrainPET insert by extending a previously published method that uses the delayed random coincidence count rate to estimate the DT in the individual scans and planes (i.e., scintillation pixel rings). The method was validated in decay experiments using phantoms with a homogenous activity concentration and with and without out-of-FOV activity. Based on a three-compartment phantom, we compared the accuracy and noise properties of the block-pairwise DTC and the global DTC method. While the currently used global DTC led to a substantial positive bias in regions with high activity, the block-pairwise DTC resulted in substantially less bias. The noise level for the block-pairwise DTC was comparable to the global DTC and image reconstructions without any DTC. Finally, we tested the block-pairwise DTC with a data set obtained from volunteer measurements using the mGlu5R (metabotropic glutamate receptor subtype 5) antagonist [ 11 C]-ABP688, when comparing the time-activity curves (TACs) obtained with the global DTC with the block-pairwise DTC, relative differences in the anterior cingulate cortex (ACC) and the cerebellum of up to 25% were observed during the first 30 minutes of these measurements.