Optimization-derived blood input function using a kernel method and its evaluation with total-body PET for brain parametric imaging.

Dynamic PET allows quantification of physiological parameters through tracer kinetic modeling. For dynamic imaging of brain or head and neck cancer on conventional PET scanners with a short axial field of view, the image-derived input function (ID-IF) from intracranial blood vessels such as the carotid artery (CA) suffers from severe partial volume effects. Alternatively, optimization-derived input function (OD-IF) by the simultaneous estimation (SIME) method does not rely on an ID-IF but derives the input function directly from the data. However, the optimization problem is often highly ill-posed. We proposed a new method that combines the ideas of OD-IF and ID-IF together through a kernel framework. While evaluation of such a method is challenging in human subjects, we used the uEXPLORER total-body PET system that covers major blood pools to provide a reference for validation. METHODS: The conventional SIME approach estimates an input function using a joint estimation together with kinetic parameters by fitting time activity curves from multiple regions of interests (ROIs). The input function is commonly parameterized with a highly nonlinear model which is difficult to estimate. The proposed kernel SIME method exploits the CA ID-IF as a priori information via a kernel representation to stabilize the SIME approach. The unknown parameters are linear and thus easier to estimate. The proposed method was evaluated using 18F-fluorodeoxyglucose studies with both computer simulations and 20 human-subject scans acquired on the uEXPLORER scanner. The effect of the number of ROIs on kernel SIME was also explored. RESULTS: The estimated OD-IF by kernel SIME showed a good match with the reference input function and provided more accurate estimation of kinetic parameters for both simulation and human-subject data. The kernel SIME led to the highest correlation coefficient (R = 0.97) and the lowest mean absolute error (MAE = 10.5 %) compared to using the CA ID-IF (R = 0.86, MAE = 108.2 %) and conventional SIME (R = 0.57, MAE = 78.7 %) in the human-subject evaluation. Adding more ROIs improved the overall performance of the kernel SIME method. CONCLUSION: The proposed kernel SIME method shows promise to provide an accurate estimation of the blood input function and kinetic parameters for brain PET parametric imaging.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy.

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

Multicenter PET image harmonization using generative adversarial networks.

PURPOSE: To improve reproducibility and predictive performance of PET radiomic features in multicentric studies by cycle-consistent generative adversarial network (GAN) harmonization approaches. METHODS: GAN-harmonization was developed to harmonize whole-body PET scans to perform image style and texture translation between different centers and scanners. GAN-harmonization was evaluated by application to two retrospectively collected open datasets and different tasks. First, GAN-harmonization was performed on a dual-center lung cancer cohort (127 female, 138 male) where the reproducibility of radiomic features in healthy liver tissue was evaluated. Second, GAN-harmonization was applied to a head and neck cancer cohort (43 female, 154 male) acquired from three centers. Here, the clinical impact of GAN-harmonization was analyzed by predicting the development of distant metastases using a logistic regression model incorporating first-order statistics and texture features from baseline 18F-FDG PET before and after harmonization. RESULTS: Image quality remained high (structural similarity: left kidney ≥ 0.800, right kidney ≥ 0.806, liver ≥ 0.780, lung ≥ 0.838, spleen ≥ 0.793, whole-body ≥ 0.832) after image harmonization across all utilized datasets. Using GAN-harmonization, inter-site reproducibility of radiomic features in healthy liver tissue increased at least by ≥ 5 ± 14% (first-order), ≥ 16 ± 7% (GLCM), ≥ 19 ± 5% (GLRLM), ≥ 16 ± 8% (GLSZM), ≥ 17 ± 6% (GLDM), and ≥ 23 ± 14% (NGTDM). In the head and neck cancer cohort, the outcome prediction improved from AUC 0.68 (95% CI 0.66-0.71) to AUC 0.73 (0.71-0.75) by application of GAN-harmonization. CONCLUSIONS: GANs are capable of performing image harmonization and increase reproducibility and predictive performance of radiomic features derived from different centers and scanners.

Biochemically recurrent prostate cancer: rationalisation of the approach to imaging.

AIM: To assess the utility of magnetic resonance imaging (MRI) in addition to the additive benefit of the conventional imaging techniques, computed tomography (CT) and nuclear medicine (NM) bone scintigraphy, for investigation of biochemical recurrence (BCR) post-prostatectomy where access to prostate specific membrane antigen (PSMA) positron-emission tomography (PET)-CT is challenging. MATERIALS AND METHODS: Relevant imaging over a 5-year period was reviewed. Ethical approval was granted by the internal review board. All patients with suspected BCR, defined as a PSA ≥0.2 ng/ml on two separate occasions, underwent a retrospective imaging review. This was performed on PACS archive search database in a single centre using search terms "PSA" and "prostatectomy" in the three imaging methods; MRI, CT, and NM bone scintigraphy. All PSMA PET CT performed were recorded. RESULTS: One hundred and eighty-five patients were identified. Patients with an MRI pelvis that demonstrated distant metastases (i.e., pelvic bone metastases or lymph node involvement more cranial to the bifurcation of the common iliac arteries) were more likely to have a positive CT and/or NM bone scintigraphy. The Pearson correlation coefficient between the findings of M1 disease at MRI pelvis and the presence of distant metastases at CT thorax, abdomen, pelvis and NM bone scintigraphy was calculated at 0.81 (p<0.01) and 0.91 (p<0.01) respectively. CONCLUSION: An imaging strategy based on risk stratification and technique-specific selection criteria leads to more appropriate use of resources, and in turn, increases the yield of conventional imaging methods. MRI prostate findings can be used to predict the additive value of CT/NM bone scintigraphy allowing a more streamlined approach to their use.

Source-to-Target Automatic Rotating Estimation (STARE) - A publicly-available, blood-free quantification approach for PET tracers with irreversible kinetics: Theoretical framework and validation for [18F]FDG.

INTRODUCTION: Full quantification of positron emission tomography (PET) data requires an input function. This generally means arterial blood sampling, which is invasive, labor-intensive and burdensome. There is no current, standardized method to fully quantify PET radiotracers with irreversible kinetics in the absence of blood data. Here, we present Source-to-Target Automatic Rotating Estimation (STARE), a novel, data-driven approach to quantify the net influx rate (Ki) of irreversible PET radiotracers, that requires only individual-level PET data and no blood data. We validate STARE with human [18F]FDG PET scans and assess its performance using simulations. METHODS: STARE builds upon a source-to-target tissue model, where the tracer time activity curves (TACs) in multiple "target" regions are expressed at once as a function of a "source" region, based on the two-tissue irreversible compartment model, and separates target region Ki from source Ki by fitting the source-to-target model across all target regions simultaneously. To ensure identifiability, data-driven, subject-specific anchoring is used in the STARE minimization, which takes advantage of the PET signal in a vasculature cluster in the field of view (FOV) that is automatically extracted and partial volume-corrected. To avoid the need for any a priori determination of a single source region, each of the considered regions acts in turn as the source, and a final Ki is estimated in each region by averaging the estimates obtained in each source rotation. RESULTS: In a large dataset of human [18F]FDG scans (N = 69), STARE Ki estimates were correlated with corresponding arterial blood-based Ki estimates (r = 0.80), with an overall regression slope of 0.88, and were precisely estimated, as assessed by comparing STARE Ki estimates across several runs of the algorithm (coefficient of variation across runs=6.74 ± 2.48%). In simulations, STARE Ki estimates were largely robust to factors that influence the individualized anchoring used within its algorithm. CONCLUSION: Through simulations and application to [18F]FDG PET data, feasibility is demonstrated for STARE blood-free, data-driven quantification of Ki. Future work will include applying STARE to PET data obtained with a portable PET camera and to other irreversible radiotracers.

An optimized reference tissue method for quantification of tau protein depositions in diverse neurodegenerative disorders by PET with 18F-PM-PBB3 (18F-APN-1607).

Positron emission tomography (PET) with 18F-PM-PBB3 (18F-APN-1607, 18F-Florzolotau) enables high-contrast detection of tau depositions in various neurodegenerative dementias, including Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD). A simplified method for quantifying radioligand binding in target regions is to employ the cerebellum as a reference (CB-ref) on the assumption that the cerebellum has minimal tau pathologies. This procedure is typically valid in AD, while FTLD disorders exemplified by progressive supranuclear palsy (PSP) are characterized by occasional tau accumulations in the cerebellum, hampering the application of CB-ref. The present study aimed to establish an optimal method for defining reference tissues on 18F-PM-PBB3-PET images of AD and non-AD tauopathy brains. We developed a new algorithm to extract reference voxels with a low likelihood of containing tau deposits from gray matter (GM-ref) or white matter (WM-ref) by a bimodal fit to an individual, voxel-wise histogram of the radioligand retentions and applied it to 18F-PM-PBB3-PET data obtained from age-matched 40 healthy controls (HCs) and 23 CE, 40 PSP, and five other tau-positive FTLD patients. PET images acquired at 90-110 min after injection were averaged and co-registered to corresponding magnetic resonance imaging space. Subsequently, we generated standardized uptake value ratio (SUVR) images estimated by CB-ref, GM-ref and WM-ref, respectively, and then compared the diagnostic performances. GM-ref and WM-ref covered a broad area in HCs and were free of voxels located in regions known to bear high tau burdens in AD and PSP patients. However, radioligand retentions in WM-ref exhibited age-related declines. GM-ref was unaffected by aging and provided SUVR images with higher contrast than CB-ref in FTLD patients with suspected and confirmed corticobasal degeneration. The methodology for determining reference tissues as optimized here improves the accuracy of 18F-PM-PBB3-PET measurements of tau burdens in a wide range of neurodegenerative illnesses.

Metabolic connectivity-based single subject classification by multi-regional linear approximation in the rat.

Metabolic connectivity patterns on the basis of [18F]-FDG positron emission tomography (PET) are used to depict complex cerebral network alterations in different neurological disorders and therefore may have the potential to support diagnostic decisions. In this study, we established a novel statistical classification method taking advantage of differential time-dependent states of whole-brain metabolic connectivity following unilateral labyrinthectomy (UL) in the rat and explored its classification accuracy. The dataset consisted of repeated [18F]-FDG PET measurements at baseline and 1, 3, 7, and 15 days (= maximum of 5 classes) after UL with 17 rats per measurement day. Classification in different stages after UL was performed by determining connectivity patterns for the different classes by Pearson's correlation between uptake values in atlas-based segmented brain regions. Connections were fitted with a linear function, with which different thresholds on the correlation coefficient (r = [0.5, 0.85]) were investigated. Rats were classified by determining the congruence of their PET uptake pattern with the fitted connectivity patterns in the classes. Overall, the classification accuracy with this method was 84.3% for 3 classes, 75.0% for 4 classes, and 54.1% for 5 classes and outperformed random classification as well as machine learning classification on the same dataset. The optimal classification thresholds of the correlation coefficient and distance-to-fit were found to be |r| > 0.65 and d = 4 when using Siegel's slope estimator for fitting. This connectivity-based classification method can compete with machine learning classification and may have methodological advantages when applied to support PET-based diagnostic decisions in neurological network disorders (such as neurodegenerative syndromes).

Validation of a combined image derived input function and venous sampling approach for the quantification of [18F]GE-179 PET binding in the brain.

Blood-based kinetic analysis of PET data relies on an accurate estimate of the arterial plasma input function (PIF). An alternative to invasive measurements from arterial sampling is an image-derived input function (IDIF). However, an IDIF provides the whole blood radioactivity concentration, rather than the required free tracer radioactivity concentration in plasma. To estimate the tracer PIF, we corrected an IDIF from the carotid artery with estimates of plasma parent fraction (PF) and plasma-to-whole blood (PWB) ratio obtained from five venous samples. We compared the combined IDIF+venous approach to gold standard data from arterial sampling in 10 healthy volunteers undergoing [18F]GE-179 brain PET imaging of the NMDA receptor. Arterial and venous PF and PWB ratio estimates determined from 7 patients with traumatic brain injury (TBI) were also compared to assess the potential effect of medication. There was high agreement between areas under the curves of the estimates of PF (r = 0.99, p<0.001), PWB ratio (r = 0.93, p<0.001), and the PIF (r = 0.92, p<0.001) as well as total distribution volume (VT) in 11 regions across the brain (r = 0.95, p<0.001). IDIF+venous VT had a mean bias of -1.7% and a comparable regional coefficient of variation (arterial: 21.3 ± 2.5%, IDIF+venous: 21.5 ± 2.0%). Simplification of the IDIF+venous method to use only one venous sample provided less accurate VT estimates (mean bias 9.9%; r = 0.71, p<0.001). A version of the method that avoids the need for blood sampling by combining the IDIF with population-based PF and PWB ratio estimates systematically underestimated VT (mean bias -20.9%), and produced VT estimates with a poor correlation to those obtained using arterial data (r = 0.45, p<0.001). Arterial and venous blood data from 7 TBI patients showed high correlations for PF (r = 0.92, p = 0.003) and PWB ratio (r = 0.93, p = 0.003). In conclusion, the IDIF+venous method with five venous samples provides a viable alternative to arterial sampling for quantification of [18F]GE-179 VT.

A high-resolution in vivo atlas of the human brain's benzodiazepine binding site of GABAA receptors.

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the human brain and plays a key role in several brain functions and neuropsychiatric disorders such as anxiety, epilepsy, and depression. For decades, several in vivo and ex vivo techniques have been used to highlight the mechanisms of the GABA system, however, no studies have currently combined the techniques to create a high-resolution multimodal view of the GABA system. Here, we present a quantitative high-resolution in vivo atlas of the human brain benzodiazepine receptor sites (BZR) located on postsynaptic ionotropic GABAA receptors (GABAARs), generated on the basis of in vivo [11C]flumazenil Positron Emission Tomography (PET) data. Next, based on ex vivo autoradiography data, we transform the PET-generated atlas from binding values into BZR protein density. Finally, we examine the brain regional association between BZR protein density and ex vivo mRNA expression for the 19 subunits in the GABAAR, including an estimation of the minimally required expression of mRNA levels for each subunit to translate into BZR protein. This represents the first publicly available quantitative high-resolution in vivo atlas of the spatial distribution of BZR densities in the healthy human brain. The atlas provides a unique neuroscientific tool as well as novel insights into the association between mRNA expression for individual subunits in the GABAAR and the BZR density at each location in the brain.

Identifying brain networks in synaptic density PET (11C-UCB-J) with independent component analysis.

BACKGROUND: The human brain is inherently organized into distinct networks, as reported widely by resting-state functional magnetic resonance imaging (rs-fMRI), which are based on blood-oxygen-level-dependent (BOLD) signal fluctuations. 11C-UCB-J PET maps synaptic density via synaptic vesicle protein 2A, which is a more direct structural measure underlying brain networks than BOLD rs-fMRI. METHODS: The aim of this study was to identify maximally independent brain source networks, i.e., "spatial patterns with common covariance across subjects", in 11C-UCB-J data using independent component analysis (ICA), a data-driven analysis method. Using a population of 80 healthy controls, we applied ICA to two 40-sample subsets and compared source network replication across samples. We examined the identified source networks at multiple model orders, as the ideal number of maximally independent components (IC) is unknown. In addition, we investigated the relationship between the strength of the loading weights for each source network and age and sex. RESULTS: Thirteen source networks replicated across both samples. We determined that a model order of 18 components provided stable, replicable components, whereas estimations above 18 were not stable. Effects of sex were found in two ICs. Nine ICs showed age-related change, with 4 remaining significant after correction for multiple comparison. CONCLUSION: This study provides the first evidence that human brain synaptic density can be characterized into organized covariance patterns. Furthermore, we demonstrated that multiple synaptic density source networks are associated with age, which supports the potential utility of ICA to identify biologically relevant synaptic density source networks.

Modeling [11C]yohimbine PET human brain kinetics with test-retest reliability, competition sensitivity studies and search for a suitable reference region.

Previous work introduced the [11C]yohimbine as a suitable ligand of central α2-adrenoreceptors (α2-ARs) for PET imaging. However, reproducibility of [11C]yohimbine PET measurements in healthy humans estimated with a simplified modeling method with reference region, as well as sensitivity of [11C]yohimbine to noradrenergic competition were not evaluated. The objectives of the present study were therefore to fill this gap. METHODS: Thirteen healthy humans underwent two [11C]yohimbine 90-minute dynamic scans performed on a PET-MRI scanner. Seven had arterial blood sampling with metabolite assessment and plasmatic yohimbine free fraction evaluation at the first scan to have arterial input function and test appropriate kinetic modeling. The second scan was a simple retest for 6 subjects to evaluate the test-retest reproducibility. For the remaining 7 subjects the second scan was a challenge study with the administration of a single oral dose of 150 µg of clonidine 90 min before the PET scan. Parametric images of α2-ARs distribution volume ratios (DVR) were generated with two non-invasive models: Logan graphical analysis with Reference (LREF) and Simplified Reference Tissue Method (SRTM). Three reference regions (cerebellum white matter (CERWM), frontal white matter (FLWM), and corpus callosum (CC)) were tested. RESULTS: We showed high test-retest reproducibility of DVR estimation with LREF and SRTM regardless of reference region (CC, CERWM, FLWM). The best fit was obtained with SRTMCC (r2=0.94). Test-retest showed that the SRTMCC is highly reproducible (mean ICC>0.7), with a slight bias (-1.8%), whereas SRTMCERWM had lower bias (-0.1%), and excellent ICC (mean>0.8). Using SRTMCC, regional changes have been observed after clonidine administration with a significant increase reported in the amygdala and striatum as well as in several posterior cortical areas as revealed with the voxel-based analysis. CONCLUSION: The results add experimental support for the suitability of [11C]yohimbine PET in the quantitative assessment of α2-ARs occupancy in vivo in the human brain. Trial registration EudraCT 2018-000380-82.

Uncertainty analysis of MR-PET image registration for precision neuro-PET imaging.

Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated. For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.

Cerebrovascular reactivity measurements using simultaneous 15O-water PET and ASL MRI: Impacts of arterial transit time, labeling efficiency, and hematocrit.

Cerebrovascular reactivity (CVR) reflects the capacity of the brain to meet changing physiological demands and can predict the risk of cerebrovascular diseases. CVR can be obtained by measuring the change in cerebral blood flow (CBF) during a brain stress test where CBF is altered by a vasodilator such as acetazolamide. Although the gold standard to quantify CBF is PET imaging, the procedure is invasive and inaccessible to most patients. Arterial spin labeling (ASL) is a non-invasive and quantitative MRI method to measure CBF, and a consensus guideline has been published for the clinical application of ASL. Despite single post labeling delay (PLD) pseudo-continuous ASL (PCASL) being the recommended ASL technique for CBF quantification, it is sensitive to variations to the arterial transit time (ATT) and labeling efficiency induced by the vasodilator in CVR studies. Multi-PLD ASL controls for the changes in ATT, and velocity selective ASL is in theory insensitive to both ATT and labeling efficiency. Here we investigate CVR using simultaneous 15O-water PET and ASL MRI data from 19 healthy subjects. CVR and CBF measured by the ASL techniques were compared using PET as the reference technique. The impacts of blood T1 and labeling efficiency on ASL were assessed using individual measurements of hematocrit and flow velocity data of the carotid and vertebral arteries measured using phase-contrast MRI. We found that multi-PLD PCASL is the ASL technique most consistent with PET for CVR quantification (group mean CVR of the whole brain = 42±19% and 40±18% respectively). Single-PLD ASL underestimated the CVR of the whole brain significantly by 15±10% compared with PET (p<0.01, paired t-test). Changes in ATT pre- and post-acetazolamide was the principal factor affecting ASL-based CVR quantification. Variations in labeling efficiency and blood T1 had negligible effects.

Validation of kinetic modeling of [15O]H2O PET using an image derived input function on hybrid PET/MRI.

In present study we aimed to validate the use of image-derived input functions (IDIF) in the kinetic modeling of cerebral blood flow (CBF) measured by [15O]H2O PET by comparing with the accepted reference standard arterial input function (AIF). Additional comparisons were made to mean cohort AIF and CBF values acquired by methodologically independent phase-contrast mapping (PCM) MRI. Using hybrid PET/MRI an IDIF was generated by measuring the radiotracer concentration in the internal carotid arteries and correcting for partial volume effects using the intravascular volume measured from MRI-angiograms. Seven patients with carotid steno-occlusive disease and twelve healthy controls were examined at rest, after administration of acetazolamide, and, in the control group, during hyperventilation. Agreement between the techniques was examined by linear regression and Bland-Altman analysis. Global CBF values modeled using IDIF correlated with values from AIF across perfusion states in both patients (p<10-6, R2=0.82, 95% limits of agreement (LoA)=[-11.3-9.9] ml/100 g/min) and controls (p<10-6, R2=0.87, 95% LoA=[-17.1-13.7] ml/100 g/min). The reproducibility of gCBF using IDIF was identical to AIF (15.8%). Values from IDIF and AIF had equally good correlation to measurements by PCM MRI, R2=0.86 and R2=0.84, (p<10-6), respectively. Mean cohort AIF performed substantially worse than individual IDIFs (p<10-6, R2=0.63, LoA=[-12.8-25.3] ml/100 g/min). In the patient group, use of IDIF provided similar reactivity maps compared to AIF. In conclusion, global CBF values modeled using IDIF correlated with values modeled by AIF and similar perfusion deficits could be established in a patient group.

Perfusion weighted imaging using combined gradient/spin echo EPIK: Brain tumour applications in hybrid MR-PET.

Advanced perfusion-weighted imaging (PWI) methods that combine gradient echo (GE) and spin echo (SE) data are important tools for the study of brain tumours. In PWI, single-shot, EPI-based methods have been widely used due to their relatively high imaging speed. However, when used with increasing spatial resolution, single-shot EPI methods often show limitations in whole-brain coverage for multi-contrast applications. To overcome this limitation, this work employs a new version of EPI with keyhole (EPIK) to provide five echoes: two with GEs, two with mixed GESE and one with SE; the sequence is termed "GESE-EPIK." The performance of GESE-EPIK is evaluated against its nearest relative, EPI, in terms of the temporal signal-to-noise ratio (tSNR). Here, data from brain tumour patients were acquired using a hybrid 3T MR-BrainPET scanner. GESE-EPIK resulted in reduced susceptibility artefacts, shorter TEs for the five echoes and increased brain coverage when compared to EPI. Moreover, compared to EPI, EPIK achieved a comparable tSNR for the first and second echoes and significantly higher tSNR for other echoes. A new method to obtain multi-echo GE and SE data with shorter TEs and increased brain coverage is demonstrated. As proposed here, the workflow can be shortened and the integration of multimodal clinical MR-PET studies can be facilitated.

Postoperative Surveillance in Older Adults With T1N0M0 Low-risk Papillary Thyroid Cancer.

BACKGROUND: The frequency and cost of postoperative surveillance for older adults (>65 y) with T1N0M0 low-risk papillary thyroid cancer (PTC) have not been well studied. METHODS: Using the SEER-Medicare (2006-2013) database, frequency and cost of surveillance concordant with American Thyroid Association (ATA) guidelines (defined as an office visit, ≥1 thyroglobulin measurement, and ultrasound 6- to 24-month postoperatively) were analyzed for the overall cohort of single-surgery T1N0M0 low-risk PTC, stratified by lobectomy versus total thyroidectomy. RESULTS: Majority of 2097 patients in the study were white (86.7%) and female (77.5%). Median age and tumor size were 72 y (interquartile range 68-76) and 0.6 cm (interquartile range 0.3-1.1 cm), respectively; 72.9% of patients underwent total thyroidectomy. Approximately 77.5% of patients had a postoperative surveillance visit; however, only 15.9% of patients received ATA-concordant surveillance. Patients who underwent total thyroidectomy as compared with lobectomy were more likely to undergo surveillance testing, thyroglobulin (61.7% versus 24.8%) and ultrasound (37.5% versus 29.2%) (all P < 0.01), and receive ATA-concordant surveillance (18.5% versus 9.0%, P < 0.001). Total surveillance cost during the study period was $621,099. Diagnostic radioactive iodine, ablation, and advanced imaging (such as positron emission tomography scans) accounted for 55.5% of costs ($344,692), whereas ATA-concordant care accounted for 44.5% of costs. After multivariate adjustment, patients who underwent total thyroidectomy as compared with lobectomy were twice as likely to receive ATA-concordant surveillance (adjusted odds ratio 2.0, 95% confidence interval: 1.5-2.8, P < 0.001). CONCLUSIONS: Majority of older adults with T1N0M0 low-risk PTC do not receive ATA-concordant surveillance; discordant care was costly. Total thyroidectomy was the strongest predictor of receiving ATA-concordant care.

Assessing the downstream value of first-line cardiac positron emission tomography (PET) imaging using real world Medicare fee-for-service claims data.

BACKGROUND: Higher imaging quality makes cardiac positron emission tomography (PET) desirable for evaluation of suspected coronary artery disease (CAD). High cost of PET imaging may be offset by reduced utilization and/or improved outcomes. METHODS: This retrospective observational study utilized Medicare fee-for-service dataset. Study participants had no CAD diagnosis within 1 year prior to initial imaging. The PET group (PET imaging) and propensity score matched comparison group (single photon emission computed tomography or stress echocardiography) underwent index imaging between January 2014 and December 2016. Outcomes were analyzed using generalized linear models. RESULTS: Among 144,503 study subjects, 4619 (3.2%) had PET and 139,884 (96.8%) had conventional imaging. After matching, each group had 4619 patients (mean age 74 years, 59% female). The PET group had lower radiation exposure (3.8 milliSievert less per year, 95% CI - 3.96 to - 3.64, P < .0001) and unstable coronary syndrome (incidence rate ratio (IRR) 0.77, 95% CI 0.64-0.94, P = .008). The PET group experienced more hospital admissions (IRR 1.10, 95% CI 1.06-1.15, P < .0001), more use of percutaneous coronary intervention (IRR 1.24, 95% CI 1.02-1.50, P = 0.03), while similar mortality rate (hazard ratio 0.95, 95% CI 0.78-1.14, P = 0.55). The PET group had higher medical spending ($2358.2 vs $1774.3, difference = $583.9 per patient per month, P < .0001). CONCLUSIONS: First-line PET imaging was not associated with reduced levels of utilization and spending. Clinical outcomes were mostly similar.

AMYQ: An index to standardize quantitative amyloid load across PET tracers.

INTRODUCTION: Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations. METHODS: We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance. RESULTS: AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs. DISCUSSION: AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology.

PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice. In parallel, the integration of PET imaging with radionuclide therapy, also known as radiolabeled theranostics, has paved the way towards highly sensitive radionuclide-based precision medicine, with major breakthroughs emerging in neuroendocrine tumors and prostate cancer. PET imaging of tumor immunity and beyond is also emerging, emphasizing the unique capabilities of PET molecular imaging to constantly adapt to emerging oncological challenges. However, these new horizons face the growing complexity of multidimensional data. In the era of precision medicine, statistical and computer sciences are currently revolutionizing image-based decision making, paving the way for more holistic cancer molecular imaging analyses at the whole-body level.

Response assessment in paediatric low-grade glioma: recommendations from the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working group.

Paediatric low-grade gliomas (also known as pLGG) are the most common type of CNS tumours in children. In general, paediatric low-grade gliomas show clinical and biological features that are distinct from adult low-grade gliomas, and the developing paediatric brain is more susceptible to toxic late effects of the tumour and its treatment. Therefore, response assessment in children requires additional considerations compared with the adult Response Assessment in Neuro-Oncology criteria. There are no standardised response criteria in paediatric clinical trials, which makes it more difficult to compare responses across studies. The Response Assessment in Pediatric Neuro-Oncology working group, consisting of an international panel of paediatric and adult neuro-oncologists, clinicians, radiologists, radiation oncologists, and neurosurgeons, was established to address issues and unique challenges in assessing response in children with CNS tumours. We established a subcommittee to develop consensus recommendations for response assessment in paediatric low-grade gliomas. Final recommendations were based on literature review, current practice, and expert opinion of working group members. Consensus recommendations include imaging response assessments, with additional guidelines for visual functional outcomes in patients with optic pathway tumours. As with previous consensus recommendations, these recommendations will need to be validated in prospective clinical trials.