Resolution enhancement, noise suppression, and joint T2* decay estimation in dual-echo sodium-23 MR imaging using anatomically guided reconstruction.

PURPOSE: Sodium MRI is challenging because of the low tissue concentration of the 23 Na nucleus and its extremely fast biexponential transverse relaxation rate. In this article, we present an iterative reconstruction framework using dual-echo 23 Na data and exploiting anatomical prior information (AGR) from high-resolution, low-noise, 1 H MR images. This framework enables the estimation and modeling of the spatially varying signal decay due to transverse relaxation during readout (AGRdm), which leads to images of better resolution and reduced noise resulting in improved quantification of the reconstructed 23 Na images. METHODS: The proposed framework was evaluated using reconstructions of 30 noise realizations of realistic simulations of dual echo twisted projection imaging (TPI) 23 Na data. Moreover, three dual echo 23 Na TPI brain datasets of healthy controls acquired on a 3T Siemens Prisma system were reconstructed using conventional reconstruction, AGR and AGRdm. RESULTS: Our simulations show that compared to conventional reconstructions, AGR and AGRdm show improved bias-noise characteristics in several regions of the brain. Moreover, AGR and AGRdm images show more anatomical detail and less noise in the reconstructions of the experimental data sets. Compared to AGR and the conventional reconstruction, AGRdm shows higher contrast in the sodium concentration ratio between gray and white matter and between gray matter and the brain stem. CONCLUSION: AGR and AGRdm generate 23 Na images with high resolution, high levels of anatomical detail, and low levels of noise, potentially enabling high-quality 23 Na MR imaging at 3T.

Regional glucose metabolic decreases with ageing are associated with microstructural white matter changes: a simultaneous PET/MR study.

PURPOSE: Human ageing is associated with a regional reduction in cerebral neuronal activity as assessed by numerous studies on brain glucose metabolism and perfusion, grey matter (GM) density and white matter (WM) integrity. As glucose metabolism may impact energetics to maintain myelin integrity, but changes in functional connectivity may also alter regional metabolism, we conducted a cross-sectional simultaneous FDG PET/MR study in a large cohort of healthy volunteers with a wide age range, to directly assess the underlying associations between reduced glucose metabolism, GM atrophy and decreased WM integrity in a single ageing cohort. METHODS: In 94 healthy subjects between 19.9 and 82.5 years (mean 50.1 ± 17.1; 47 M/47F, MMSE ≥ 28), simultaneous FDG-PET, structural MR and diffusion tensor imaging (DTI) were performed. Voxel-wise associations between age and grey matter (GM) density, RBV partial-volume corrected (PVC) glucose metabolism, white matter (WM) fractional anisotropy (FA) and mean diffusivity (MD), and age were assessed. Clusters representing changes in glucose metabolism correlating significantly with ageing were used as seed regions for tractography. Both linear and quadratic ageing models were investigated. RESULTS: An expected age-related reduction in GM density was observed bilaterally in the frontal, lateral and medial temporal cortex, striatum and cerebellum. After PVC, relative FDG uptake was negatively correlated with age in the inferior and midfrontal, cingulate and parietal cortex and subcortical regions, bilaterally. FA decreased with age throughout the entire brain WM. Four white matter tracts were identified connecting brain regions with declining glucose metabolism with age. Within these, relative FDG uptake in both origin and target clusters correlated positively with FA (0.32 ≤ r ≤ 0.71) and negatively with MD (- 0.75 ≤ r ≤ - 0.41). CONCLUSION: After appropriate PVC, we demonstrated that regional cerebral glucose metabolic declines with age and that these changes are related to microstructural changes in the interconnecting WM tracts. The temporal course and potential causality between ageing effects on glucose metabolism and WM integrity should be further investigated in longitudinal cohort PET/MR studies.

Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network.

In the last two decades, it has been shown that anatomically-guided PET reconstruction can lead to improved bias-noise characteristics in brain PET imaging. However, despite promising results in simulations and first studies, anatomically-guided PET reconstructions are not yet available for use in routine clinical because of several reasons. In light of this, we investigate whether the improvements of anatomically-guided PET reconstruction methods can be achieved entirely in the image domain with a convolutional neural network (CNN). An entirely image-based CNN post-reconstruction approach has the advantage that no access to PET raw data is needed and, moreover, that the prediction times of trained CNNs are extremely fast on state of the art GPUs which will substantially facilitate the evaluation, fine-tuning and application of anatomically-guided PET reconstruction in real-world clinical settings. In this work, we demonstrate that anatomically-guided PET reconstruction using the asymmetric Bowsher prior can be well-approximated by a purely shift-invariant convolutional neural network in image space allowing the generation of anatomically-guided PET images in almost real-time. We show that by applying dedicated data augmentation techniques in the training phase, in which 16 [18F]FDG and 10 [18F]PE2I data sets were used, lead to a CNN that is robust against the used PET tracer, the noise level of the input PET images and the input MRI contrast. A detailed analysis of our CNN in 36 [18F]FDG, 18 [18F]PE2I, and 7 [18F]FET test data sets demonstrates that the image quality of our trained CNN is very close to the one of the target reconstructions in terms of regional mean recovery and regional structural similarity.

Impact of left bundle branch block on myocardial perfusion and metabolism: A positron emission tomography study.

BACKGROUND: Better understanding of pathophysiological changes, induced by left bundle branch block (LBBB), may improve patient selection for cardiac resynchronization therapy (CRT). Therefore, we assessed the effect of LBBB on regional glucose metabolism, 13N-NH3-derived absolute and semiquantitative myocardial blood flow (MBF), and their relation in non-ischemic CRT candidates. METHODS: Twenty-five consecutive non-ischemic patients with LBBB underwent 18F-FDG and resting dynamic 13N-NH3 PET/CT prior to CRT implantation. Regional 18F-FDG uptake, absolute MBF, and late 13N-NH3 uptake were analyzed and corresponding septal-to-lateral wall ratios (SLR) were calculated. Segmental analysis was performed to evaluate "reverse mismatch," "mismatch," and "match" patterns, based on late 13N-NH3/18F-FDG uptake ratios. RESULTS: A significantly lower 18F-FDG uptake was observed in the septum compared to the lateral wall (SLR 0.53 ± 0.17). A similar pattern was observed for MBF (SLR 0.68 ± 0.18), whereas late 13N-NH3 uptake showed a homogeneous distribution (SLR 0.96 ± 0.13). 13N-NH3/18F-FDG "mismatch" and "reverse mismatch" segments were predominantly present in the lateral (52%) and septal wall (61%), respectively. CONCLUSIONS: Non-ischemic CRT candidates with LBBB demonstrate lower glucose uptake and absolute MBF in the septum compared to the lateral wall. However, late static 13N-NH3 uptake showed a homogenous distribution, reflecting a composite measure of altered regional MBF and metabolism, induced by LBBB.

Combined brain and spinal FDG PET allows differentiation between ALS and ALS mimics.

PURPOSE: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder with on average a 1-year delay between symptom onset and diagnosis. Studies have demonstrated the value of [18F]-FDG PET as a sensitive diagnostic biomarker, but the discriminatory potential to differentiate ALS from patients with symptoms mimicking ALS has not been investigated. We investigated the combination of brain and spine [18F]-FDG PET-CT for differential diagnosis between ALS and ALS mimics in a real-life clinical diagnostic setting. METHODS: Patients with a suspected diagnosis of ALS (n = 98; 64.8 ± 11 years; 61 M) underwent brain and spine [18F]-FDG PET-CT scans. In 62 patients, ALS diagnosis was confirmed (67.8 ± 10 years; 35 M) after longitudinal follow-up (average 18.1 ± 8.4 months). In 23 patients, another disease was diagnosed (ALS mimics, 60.9 ± 12.9 years; 17 M) and 13 had a variant motor neuron disease, primary lateral sclerosis (PLS; n = 4; 53.6 ± 2.5 years; 2 M) and progressive muscular atrophy (PMA; n = 9; 58.4 ± 7.3 years; 7 M). Spine metabolism was determined after manual and automated segmentation. VOI- and voxel-based comparisons were performed. Moreover, a support vector machine (SVM) approach was applied to investigate the discriminative power of regional brain metabolism, spine metabolism and the combination of both. RESULTS: Brain metabolism was very similar between ALS mimics and ALS, whereas cervical and thoracic spine metabolism was significantly different (in standardised uptake values; cervical: ALS 2.1 ± 0.5, ALS mimics 1.9 ± 0.4; thoracic: ALS 1.8 ± 0.3, ALS mimics 1.5 ± 0.3). As both brain and spine metabolisms were very similar between ALS mimics and PLS/PMA, groups were pooled for accuracy analyses. Mean discrimination accuracy was 65.4%, 80.0% and 81.5%, using only brain metabolism, using spine metabolism and using both, respectively. CONCLUSION: The combination of brain and spine FDG PET-CT with SVM classification is useful as discriminative biomarker between ALS and ALS mimics in a real-life clinical setting.

Whole liver segmentation based on deep learning and manual adjustment for clinical use in SIRT.

PURPOSE: In selective internal radiation therapy (SIRT), an accurate total liver segmentation is required for activity prescription and absorbed dose calculation. Our goal was to investigate the feasibility of using automatic liver segmentation based on a convolutional neural network (CNN) for CT imaging in SIRT, and the ability of CNN to reduce inter-observer variability of the segmentation. METHODS: A multi-scale CNN was modified for liver segmentation for SIRT patients. The CNN model was trained with 139 datasets from three liver segmentation challenges and 12 SIRT patient datasets from our hospital. Validation was performed on 13 SIRT datasets and 12 challenge datasets. The model was tested on 40 SIRT datasets. One expert manually delineated the livers and adjusted the liver segmentations from CNN for 40 test SIRT datasets. Another expert performed the same tasks for 20 datasets randomly selected from the 40 SIRT datasets. The CNN segmentations were compared with the manual and adjusted segmentations from the experts. The difference between the manual segmentations was compared with the difference between the adjusted segmentations to investigate the inter-observer variability. Segmentation difference was evaluated through dice similarity coefficient (DSC), volume ratio (RV), mean surface distance (MSD), and Hausdorff distance (HD). RESULTS: The CNN segmentation achieved a median DSC of 0.94 with the manual segmentation and of 0.98 with the manually corrected CNN segmentation, respectively. The DSC between the adjusted segmentations is 0.98, which is 0.04 higher than the DSC between the manual segmentations. CONCLUSION: The CNN model achieved good liver segmentations on CT images of good image quality, with relatively normal liver shapes and low tumor burden. 87.5% of the 40 CNN segmentations only needed slight adjustments for clinical use. However, the trained model failed on SIRT data with low dose or contrast, lesions with large density difference from their surroundings, and abnormal liver position and shape. The abovementioned scenarios were not adequately represented in the training data. Despite this limitation, the current CNN is already a useful clinical tool which improves inter-observer agreement and therefore contributes to the standardization of the dosimetry. A further improvement is expected when the CNN will be trained with more data from SIRT patients.

Synthesis and Kinetic Characterisation of Water-Soluble Fluorogenic Acyl Donors for Transglutaminase†2.

Small glutamate-containing peptides bearing coumarin derivatives as fluorescent leaving groups attached to the γ-carboxylic acid group of the Glu residue were synthesised and investigated with regard to their potential to act as substrates for transglutaminase 2 (TGase 2). Their synthesis was accomplished by an efficient solid-phase approach. The excellent water solubility of the compounds enabled their extensive kinetic characterisation in the context of TGase 2-catalysed hydrolysis and aminolysis. The influence of the coumarin skeleton's substitution pattern on the kinetic properties was studied. Derivatives containing 7-hydroxy-4-methylcoumarin (HMC) revealed properties superior to those of their 7-hydroxycoumarin counterparts; analogous amides are not accepted as substrates. Z-Glu(HMC)-Gly-OH, which exhibited the best substrate properties out of the investigated derivatives, was selected for representative kinetic characterisation of acyl acceptor substrates and irreversible inhibitors.

Modeling magnetization transfer effects of Q2TIPS bolus saturation in multi-TI pulsed arterial spin labeling.

PURPOSE: To estimate the relaxation time changes during Q2TIPS bolus saturation caused by magnetization transfer effects and to propose and evaluate an extended model for perfusion quantification which takes this into account. METHOD: Three multi inversion-time pulsed arterial spin labeling sequences with different bolus saturation duration were acquired for five healthy volunteers. Magnetization transfer exchange rates in tissue and blood were obtained from control image saturation recovery. Cerebral blood flow (CBF) obtained using the extended model and the standard model was compared. RESULTS: A decrease of obtained CBF of 6% (10%) was observed in grey matter when the duration of bolus saturation increased from 600 to 900 ms (1200 ms). This decrease was reduced to 1.6% (2.8%) when the extended quantification model was used. Compared with the extended model, the standard model underestimated CBF in grey matter by 9.7, 15.0, and 18.7% for saturation durations 600, 900, and 1200 ms, respectively. Results for simulated single inversion-time data showed 5-16% CBF underestimation depending on blood arrival time and bolus saturation duration. CONCLUSION: Magnetization transfer effects caused by bolus saturation pulses should not be ignored when performing quantification as they can cause appreciable underestimation of the CBF.

Quantitative assessment of the asphericity of pretherapeutic FDG uptake as an independent predictor of outcome in NSCLC.

BACKGROUND: The aim of the present study was to evaluate the predictive value of a novel quantitative measure for the spatial heterogeneity of FDG uptake, the asphericity (ASP) in patients with non-small cell lung cancer (NSCLC). METHODS: FDG-PET/CT had been performed in 60 patients (15 women, 45 men; median age, 65.5 years) with newly diagnosed NSCLC prior to therapy. The FDG-PET image of the primary tumor was segmented using the ROVER 3D segmentation tool based on thresholding at the volume-reproducing intensity threshold after subtraction of local background. ASP was defined as the relative deviation of the tumor's shape from a sphere. Univariate and multivariate Cox regression as well as Kaplan-Meier (KM) analysis and log-rank test with respect to overall (OAS) and progression-free survival (PFS) were performed for clinical variables, SUVmax/mean, metabolically active tumor volume (MTV), total lesion glycolysis (TLG), ASP and "solidity", another measure of shape irregularity. RESULTS: ASP, solidity and "primary surgical treatment" were significant independent predictors of PFS in multivariate Cox regression with binarized parameters (HR, 3.66; p<0.001, HR, 2.11; p=0.05 and HR, 2.09; p=0.05), ASP and "primary surgical treatment" of OAS (HR, 3.19; p=0.02 and HR, 3.78; p=0.01, respectively). None of the other semi-quantitative PET parameters showed significant predictive value with respect to OAS or PFS. Kaplan-Meier analysis revealed a probability of 2-year PFS of 52% in patients with low ASP compared to 12% in patients with high ASP (p<0.001). Furthermore, it showed a higher OAS rate in the case of low versus high ASP (1-year-OAS, 91% vs. 67%: p=0.02). CONCLUSIONS: The novel parameter asphericity of pretherapeutic FDG uptake seems to provide better prognostic value for PFS and OAS in NCSLC compared to SUV, metabolic tumor volume, total lesion glycolysis and solidity.

Exact parameter identification in PET pharmacokinetic modeling using the irreversible two tissue compartment model.

OBJECTIVE: In quantitative dynamic positron emission tomography (PET), time series of images, reflecting the tissue response to the arterial tracer supply, are reconstructed. This response is described by kinetic parameters, which are commonly determined on basis of the tracer concentration in tissue and the arterial input function. In clinical routine the latter is estimated by arterial blood sampling and analysis, which is a challenging process and thus, attempted to be derived directly from reconstructed PET images. However, a mathematical analysis about the necessity of measurements of the common arterial whole blood activity concentration, and the concentration of free non-metabolized tracer in the arterial plasma, for a successful kinetic parameter identification does not exist. Here we aim to address this problem mathematically. Approach: We consider the identification problem in simultaneous pharmacokinetic modeling of multiple regions of interests of dynamic PET data using the irreversible two-tissue compartment model analytically. In addition to this consideration, the situation of noisy measurements is addressed using Tikhonov regularization. Furthermore, numerical simulations with a regularization approach are carried out to illustrate the analytical results in a synthetic application example. Main results: We provide mathematical proofs showing that, under reasonable assumptions, all metabolic tissue parameters can be uniquely identified without requiring additional blood samples to measure the arterial input function. A connection to noisy measurement data is made via a consistency result, showing that exact reconstruction of the ground-truth tissue parameters is stably maintained in the vanishing noise limit. Furthermore, our numerical experiments suggest that an approximate reconstruction of kinetic parameters according to our analytic results is also possible in practice for moderate noise levels. Significance: The analytical result, which holds in the idealized, noiseless scenario, suggests that for irreversible tracers, fully quantitative dynamic PET imaging is in principle possible without costly arterial blood sampling and metabolite analysis.

Comparison of a 3D CZT and conventional SPECT/CT system for quantitative Lu-177 SPECT imaging.

PURPOSE: Next-generation SPECT/CT systems with CdZnTe (CZT) digital detectors in a ring-like setup are emerging to perform quantitative Lu-177 SPECT imaging in clinical routine. It is essential to assess how the shorter acquisition time might affect the image quality and uncertainty on the mean absorbed dose of the tumors and organs at risk compared to a conventional system. METHODS: A NEMA Image Quality phantom was scanned with a 3D CZT SPECT/CT system (Veriton, by Spectrum Dynamics) using 6 min per bed position and with a conventional SPECT/CT system (Symbia T16, by Siemens) using 16 min per bed position. The sphere-to-background ratio was 12:1 and the background activity concentration ranged from 0.52 to 0.06 MBq/mL. A clinical reconstruction protocol for dosimetry purposes was determined for both systems by maximizing the sphere-to-background ratio while keeping the coefficient of variation of the background as low as possible. The corresponding image resolution was determined by the matching filter method and used for a dose uncertainty assessment of both systems following an established uncertainty model.. RESULTS: The optimized iterative reconstruction protocol included scatter and attenuation correction for both systems and detector response modeling for the Siemens system. For the 3D CZT system, 6 iterations and 8 subsets were combined with a Gaussian post-filter of 3 mm Full Width Half Maximum (FWHM) for post-smoothing. For the conventional system, 16 iterations and 16 subsets were applied with a Gaussian post-smoothing filter of 1 mm FWHM. For these protocols, the sphere-to-background ratio was 18.5% closer to the true ratio for the conventional system compared to the 3D CZT system when considering the four largest spheres. Meanwhile, the background coefficient of variation was very similar for both systems. These protocols resulted in SPECT image resolution of 14.8 mm and 13.6 mm for the 3D CZT and conventional system respectively. Based on these resolution estimates, a 50% dose uncertainty corresponded to a lesion volume of 28 mL for the conventional system and a lesion volume of 33 mL for the 3D CZT system. CONCLUSIONS: An optimized reconstruction protocol for a Veriton system with 6 min of acquisition time per bed position resulted in slightly higher dose uncertainties than a conventional Symbia system using 16 min of acquisition time per bed position. Therefore, a 3D CZT SPECT/CT allows to significantly reduce the acquisition times with only a very limited impact on dose uncertainties such that quantitative Lu-177 SPECT/CT imaging becomes much more accessible for treatment concurrent dosimetry. Nevertheless, the uncertainty of SPECT-based dose estimates remains high.

Partial volume correction in arterial spin labeling using a Look-Locker sequence.

PURPOSE: Partial volume (PV) effects are caused by limited spatial resolution and significantly affect cerebral blood flow investigations with arterial spin labeling. Therefore, accurate PV correction (PVC) procedures are required. PVC is commonly based on PV maps obtained from segmented high-resolution T1 -weighted images. Segmentation of these images is error-prone, and it can be difficult to coregister these images accurately with the single-shot ASL images such as those created by echo-planar imaging (EPI). In this paper, an alternative method for PV map generation is proposed. METHODS: The Look-Locker EPI (LL-EPI) acquisition is used for analyzing the T1 -recovery curve and for subsequent PV map generation. The new method was evaluated in five healthy volunteers (mean age 30 ± 3.7 years). RESULTS: By applying a linear regression method for PVC, a 12% decrease in regression error was reached with the new method. CONCLUSION: PV maps extraction from LL-EPI is a viable, possibly superior alternative to the standard approach based on segmentation of high-resolution T1 -weighted images.

PET/MRI in head and neck cancer: initial experience.

PURPOSE: To evaluate the feasibility of PET/MRI (positron emission tomography/magnetic resonance imaging) with FDG ((18)F-fluorodeoxyglucose) for initial staging of head and neck cancer. METHODS: The study group comprised 20 patients (16 men, 4 women) aged between 52 and 81 years (median 64 years) with histologically proven squamous cell carcinoma of the head and neck region. The patients underwent a PET scan on a conventional scanner and a subsequent PET/MRI examination on a whole-body hybrid system. FDG was administered intravenously prior to the conventional PET scan (267-395 MBq FDG, 348 MBq on average). The maximum standardized uptake values (SUV(max)) of the tumour and of both cerebellar hemispheres were determined for both PET datasets. The numbers of lymph nodes with increased FDG uptake were compared between the two PET datasets. RESULTS: No MRI-induced artefacts where observed in the PET images. The tumour was detected by PET/MRI in 17 of the 20 patients, by PET in 16 and by MRI in 14. The PET/MRI examination yielded significantly higher SUV(max) than the conventional PET scanner for both the tumour (p < 0.0001) and the cerebellum (p = 0.0009). The number of lymph nodes with increased FDG uptake detected using the PET dataset from the PET/MRI system was significantly higher the number detected by the stand-alone PET system (64 vs. 39, p = 0.001). CONCLUSION: The current study demonstrated that PET/MRI of the whole head and neck region is feasible with a whole-body PET/MRI system without impairment of PET or MR image quality.

Quantitative accuracy of attenuation correction in the Philips Ingenuity TF whole-body PET/MR system: a direct comparison with transmission-based attenuation correction.

OBJECTIVE: Evaluation of the quantitative accuracy of MR-based attenuation correction (MRAC) in the Philips Ingenuity TF whole-body PET/MR. MATERIALS AND METHODS: In 13 patients, PET emission data from the PET/MR were reconstructed using two different methods for attenuation correction. In the first reconstruction, the vendor-provided standard MRAC was used. In the second reconstruction, a coregistered transmission-based attenuation map from a second immediately preceding investigation with a stand-alone Siemens ECAT EXACT HR(+) PET scanner was used (TRAC). The two attenuation maps were compared regarding occurrence of segmentation artifacts in the MRAC procedure. Standard uptake values (SUVs) of multiple VOIs (liver, cerebellum, hot focal structures at various locations in the trunk) were compared between both reconstructed data sets. Furthermore, a voxel-wise intensity correlation analysis of both data sets in the lung and trunk was performed. RESULTS: VOI averaged SUV differences between MRAC and TRAC were as follows (relative differences, mean ± standard deviation): (+12 ± 6) % cerebellum, (-4 ± 9) % liver, (-2 ± 11) % hot focal structures. The fitted slopes of the voxel-wise correlations in the lung and trunk were 0.87 ± 0.17 and 0.95 ± 0.10 with averaged adjusted R (2) values of 0.96 and 0.98, respectively. These figures include two instances with partially erroneous lung segmentation due to artifacts in the underlying MR images. CONCLUSION: The MR-based attenuation correction implemented on the Philips Ingenuity PET/MR provides reasonable quantitative accuracy. On average, deviations from TRAC-based results are small (on the order of 10% or below) across the trunk, but due to interindividual variability of the segmentation quality, deviations of more than 20% can occur. Future improvement of the segmentation quality would help to increase the quantitation accuracy further and to reduce the inter-subject variability.

PET/MR for therapy response evaluation in malignant lymphoma: initial experience.

OBJECT: To evaluate the feasibility of positron emission tomography/magnetic resonance imaging (PET/MR) with (18)fluoro-2-deoxyglucose (FDG) for therapy response evaluation of malignant lymphoma. MATERIALS AND METHODS: Nine patients with malignant lymphoma who underwent FDG-PET/MR before and after chemotherapy were included in this retrospective study. Average time between the two scans was 70 days. The scans were evaluated independently by two nuclear medicine physicians. The Ann Arbor classification was used to describe lymphoma stage. Furthermore, the readers also rated PET image quality using a five point scale. Weighted kappa (κ) was used to calculate interrater agreement. RESULTS: The initial scan showed foci of increased FDG uptake in all patients, with Ann Arbor stage varying between I and IV. In the follow-up examination, all but one patient showed complete response to chemotherapy. PET image quality was rated as very good or excellent for all scans. Interrater agreement was excellent regarding Ann Arbor stage (κ = 0.97) and good regarding image quality (κ = 0.41). CONCLUSION: PET/MR shows promising initial results for therapy response evaluation in lymphoma patients.

Fast and memory-efficient reconstruction of sparse Poisson data in listmode with non-smooth priors with application to time-of-flight PET.

Objective.Complete time of flight (TOF) sinograms of state-of-the-art TOF PET scanners have a large memory footprint. Currently, they contain ∼4 · 109data bins which amount to ∼17 GB in 32 bit floating point precision. Moreover, their size will continue to increase with advances in the achievable detector TOF resolution and increases in the axial field of view. Using iterative algorithms to reconstruct such enormous TOF sinograms becomes increasingly challenging due to the memory requirements and the computation time needed to evaluate the forward model for every data bin. This is especially true for more advanced optimization algorithms such as the stochastic primal-dual hybrid gradient (SPDHG) algorithm which allows for the use of non-smooth priors for regularization using subsets with guaranteed convergence. SPDHG requires the storage of additional sinograms in memory, which severely limits its application to data sets from state-of-the-art TOF PET systems using conventional computing hardware.Approach.Motivated by the generally sparse nature of the TOF sinograms, we propose and analyze a new listmode (LM) extension of the SPDHG algorithm for image reconstruction of sparse data following a Poisson distribution. The new algorithm is evaluated based on realistic 2D and 3D simulationsn, and a real data set acquired on a state-of-the-art TOF PET/CT system. The performance of the newly proposed LM SPDHG algorithm is compared against the conventional sinogram SPDHG and the listmode EM-TV algorithm.Main results.We show that the speed of convergence of the proposed LM-SPDHG is equivalent the original SPDHG operating on binned data (TOF sinograms). However, we find that for a TOF PET system with 400 ps TOF resolution and 25 cm axial FOV, the proposed LM-SPDHG reduces the required memory from approximately 56 to 0.7 GB for a short dynamic frame with 107prompt coincidences and to 12.4 GB for a long static acquisition with 5·108prompt coincidences.Significance.In contrast to SPDHG, the reduced memory requirements of LM-SPDHG enables a pure GPU implementation on state-of-the-art GPUs-avoiding memory transfers between host and GPU-which will substantially accelerate reconstruction times. This in turn will allow the application of LM-SPDHG in routine clinical practice where short reconstruction times are crucial.

Can nuclear imaging accurately detect scar in ischemic cardiac resynchronization therapy candidates?

BACKGROUND: Accurate scar assessment is crucial in cardiac resynchronization therapy (CRT) candidates, since its presence is a negative predictor for CRT response. Therefore, we assessed the performance of different PET parameters to detect scar in CRT candidates. METHODS: Twenty-nine CRT candidates underwent 18F-fluorodeoxyglucose (18F-FDG)-PET/computed tomography (CT), resting 13N-NH3-PET/CT and cardiac magnetic resonance (CMR) prior to CRT implantation. Segmental 18F-FDG uptake, late 13N-NH3 uptake and absolute myocardial blood flow (MBF) were evaluated for scar detection using late gadolinium enhancement (LGE) CMR as reference. A receiver operator characteristic (ROC) area under the curve (AUC) ≥0.8 indicated a good accuracy of the methods evaluated. RESULTS: Scar was present in 111 of 464 segments. None of the approaches could reliably identify segments with nontransmural scar, except for 18F-FDG uptake in the lateral wall (AUC 0.83). Segmental transmural scars could be detected with all methods (AUC ≥ 0.8), except for septal 18F-FDG uptake and MBF in the inferior wall (AUC < 0.8). Late 13N-NH3 uptake was the best parameter for transmural scar detection, independent of its location, with a sensitivity of 80% and specificity of 92% using a cutoff of 66% of the maximum tracer activity. CONCLUSIONS: Late 13N-NH3 uptake is superior to 13N-NH3 MBF and 18F-FDG in detecting transmural scar, independently of its location. However, none of the tested PET parameters was able to accurately detect nontransmural scar.

Use of Micro-Computed Tomography to Visualize and Quantify COVID-19 Vaccine Efficiency in Free-Breathing Hamsters.

The SARS-CoV-2 pandemic has impacted the health of humanity after the outbreak in Hubei, China in late December 2019. Ever since, it has taken unprecedented proportions and rapidity causing over a million fatal cases. Recently, a robust Syrian golden hamster model recapitulating COVID-19 was developed in search for effective therapeutics and vaccine candidates. However, overt clinical disease symptoms were largely absent despite high levels of virus replication and associated pathology in the respiratory tract. Therefore, we used micro-computed tomography (µCT) to longitudinally visualize lung pathology and to preclinically assess candidate vaccines. µCT proved to be crucial to quantify and noninvasively monitor disease progression, to evaluate candidate vaccine efficacy, and to improve screening efforts by allowing longitudinal data without harming live animals. Here, we give a comprehensive guide on how to use low-dose high-resolution µCT to follow-up SARS-CoV-2-induced disease and test the efficacy of COVID-19 vaccine candidates in hamsters. Our approach can likewise be applied for the preclinical assessment of antiviral and anti-inflammatory drug treatments in vivo.

Cerebral glucose changes after chemotherapy and their relation to long-term cognitive complaints and fatigue.

Purpose: To investigate the short-term cerebral metabolic effects of intravenous chemotherapy and their association with long-term fatigue/cognitive complaints. Experimental design: Using [18F]-FDG-PET/CT whole-body scans, we retrospectively quantified relative cerebral glucose metabolism before and after neoadjuvant chemotherapy in a cohort of patients treated for non-metastatic breast cancer (2009-2019). Self-report of cognitive complaints and fatigue were prospectively assessed 7 ± 3 years after therapy. Metabolic changes were estimated with i) robust mixed-effects modelling in regions-of-interest (frontal, parietal, temporal, occipital, and insular cortex) and ii) general-linear modelling of whole-brain voxel-wise outcomes. iii) The association between metabolic changes and self-reported outcomes was evaluated using linear regression-analysis. Results: Of the 667 screened patients, 263 underwent PET/CT before and after chemotherapy and 183 (48 ± 9 years) met the inclusion criteria. After chemotherapy, decreased frontal and increased parietal and insular metabolism were observed (|ß|>0.273, pFDR <0.008). Separately, additional increased occipital metabolism after epiribucin+ cyclophosphamide (EC) and temporal metabolism after EC+ fluorouracil chemotherapy were observed (ß>0.244, pFDR ≤0.048). Voxel-based analysis (pcluster-FWE <0.001) showed decreased metabolism in the paracingulate gyrus (-3.2 ± 3.9%) and putamen (3.1 ± 4.1%) and increased metabolism in the lateral cortex (L=2.9 ± 3.1%) and pericentral gyri (3.0 ± 4.4%). Except for the central sulcus, the same regions showed changes in EC, but not in FEC patients. Of the 97 self-reported responders, 23% and 27% experienced extreme fatigue and long-term cognitive complaints, respectively, which were not associated with metabolic changes. Conclusion: Both hyper- and hypometabolism were observed after chemotherapy for breast cancer. Combined with earlier findings, this study could support inflammatory mechanisms resulting in relative hypermetabolism, mainly in the parietal/occipital cortices. As early metabolic changes did not precede long-term complaints, further research is necessary to identify vulnerable patients.