Deriving physiological information from PET images: from SUV to compartmental modelling

Recent developments and challenges in positron emission tomography imaging of gliosis in chronic neuropathic pain

ABSTRACT

Understanding the mechanisms that underpin the transition from acute to chronic pain is critical for the development of more effective and targeted treatments. There is growing interest in the contribution of glial cells to this process, with cross-sectional preclinical studies demonstrating specific changes in these cell types capturing targeted timepoints from the acute phase and the chronic phase. In vivo longitudinal assessment of the development and evolution of these changes in experimental animals and humans has presented a significant challenge. Recent technological advances in preclinical and clinical positron emission tomography, including the development of specific radiotracers for gliosis, offer great promise for the field. These advances now permit tracking of glial changes over time and provide the ability to relate these changes to pain-relevant symptomology, comorbid psychiatric conditions, and treatment outcomes at both a group and an individual level. In this article, we summarize evidence for gliosis in the transition from acute to chronic pain and provide an overview of the specific radiotracers available to measure this process, highlighting their potential, particularly when combined with ex vivo / in vitro techniques, to understand the pathophysiology of chronic neuropathic pain. These complementary investigations can be used to bridge the existing gap in the field concerning the contribution of gliosis to neuropathic pain and identify potential targets for interventions.

Dual-time-point dynamic 68Ga-PSMA-11 PET/CT for parametric imaging generation in prostate cancer

PURPOSE

To investigate the optimal dual-time-point (DTP) approaches using dynamic 68Ga-PSMA-11 PET/CT imaging to generate parametric images for prostate cancer patients.

METHODS

Fifteen patients with prostate cancer were intravenously administered 68Ga-PSMA-11 of 181.9 ± 47.2 MBq, followed by an immediate 60 min dynamic PET/CT scan. List-mode data were reconstructed into 25 timeframes (6 × 10 s, 8 × 30 s, and 11 × 300 s) and corrected for motion and partial volume effect. DTP parametric images were generated using different interval time points of 5 min and 10 min, with a minimum of 30 min time interval. Net influx rates (Ki) were calculated through the fitting of a single irreversible two-tissue compartmental model. Intraclass correlation coefficient (ICC) values between DTP protocols and 60 min Ki were obtained. Lesion-to-background ratios (LBRs) of Ki and standardized uptake value (SUV) images in each DTP protocol were determined.

RESULTS

The DTP protocol of 5-10 min with a 40-45 min interval showed the highest ICC of 0.988 compared with the 60 min Ki, whereas the ICC values for the intervals of 0-5 min with 55-60 min and 0-10 min with 50-60 min were 0.941. The LBRs of the 60 min Ki, 5-10 min with 40-45 min Ki, 0-5 min with 55-60 min Ki, 0-10 min with 50-60 min Ki, SUVmean, and SUVmax images were 29.53 ± 27.33, 13.05 ± 15.28, 45.15 ± 53.11, 45.52 ± 70.31, 19.77 ± 23.43, and 25.06 ± 30.07, respectively.

CONCLUSION

The 0-5 min with 55-60 min DTP parametric imaging exhibits a comparable Ki to 60 min parametric imaging and remarkable image quality and contrast than SUV imaging, enhancing prostate cancer diagnosis while maintaining time efficiency.

The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [18F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown. Here, using two multimodal datasets of healthy participants, we built a multivariable multilevel model of functional-metabolic associations, assessing multiple functional features, describing the 1) rs-fMRI signal, 2) hemodynamic response, 3) static and 4) time-varying functional connectivity, as predictors of the human brain's metabolic architecture. The full model was trained on one dataset and tested on the other to assess its reproducibility. We found that functional-metabolic spatial coupling is nonlinear and heterogeneous across the brain, and that local measures of rs-fMRI activity and synchrony are more tightly coupled to local metabolism. In the testing dataset, the degree of functional-metabolic spatial coupling was also related to peripheral metabolism. Overall, although a significant proportion of regional metabolic variability can be described by measures of spontaneous activity, additional efforts are needed to explain the remaining variance in the brain's 'dark energy'.

A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging

Introduction

Recent evidence suggests the blood-to-brain influx rate (K1 ) in TSPO PET imaging as a promising biomarker of blood-brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF).

Methods

The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test-retest dataset of [18F]DPA714 scans.

Results

Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra  = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03-0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans.

Discussion

This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers' unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal.

A Comparison of Arterial Input Function Interpolation Methods for Patlak Plot Analysis of 68Ga-PSMA-11 PET Prostate Cancer Studies

Positron emission tomography (PET) imaging enables quantitative assessment of tissue physiology. Dynamic pharmacokinetic analysis of PET images requires accurate estimation of the radiotracer plasma input function to derive meaningful parameter estimates, and small discrepancies in parameter estimation can mimic subtle physiologic tissue variation. This study evaluates the impact of input function interpolation method on the accuracy of Patlak kinetic parameter estimation through simulations modeling the pharmacokinetic properties of [68Ga]-PSMA-11. This study evaluated both trained and untrained methods. Although the mean kinetic parameter accuracy was similar across all interpolation models, the trained node weighting interpolation model estimated accurate kinetic parameters with reduced overall variability relative to standard linear interpolation. Trained node weighting interpolation reduced kinetic parameter estimation variance by a magnitude approximating the underlying physiologic differences between normal and diseased prostatic tissue. Overall, this analysis suggests that trained node weighting improves the reliability of Patlak kinetic parameter estimation for [68Ga]-PSMA-11 PET.

Single-voxel delay map from long-axial field-of-view PET scans

Objective

We present an algorithm to estimate the delay between a tissue time-activity curve and a blood input curve at a single-voxel level tested on whole-body data from a long-axial field-of-view scanner with tracers of different noise characteristics.

Methods

Whole-body scans of 15 patients divided equally among three tracers, namely [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, which were used in development and testing of the algorithm. Delay times were estimated by fitting the cumulatively summed input function and tissue time-activity curve with special considerations for noise. To evaluate the performance of the algorithm, it was compared against two other algorithms also commonly applied in delay estimation: name cross-correlation and a one-tissue compartment model with incorporated delay. All algorithms were tested on both synthetic time-activity curves produced with the one-tissue compartment model with increasing levels of noise and delays between the tissue activity curve and the blood input curve. Whole-body delay maps were also calculated for each of the three tracers with data acquired on a long-axial field-of-view scanner with high time resolution.

Results

Our proposed model performs better for low signal-to-noise ratio time-activity curves compared to both cross-correlation and the one-tissue compartment models for non-[15O]H2O tracers. Testing on synthetically produced time-activity curves showed only a small and even residual delay, while the one-tissue compartment model with included delay showed varying residual delays.

Conclusion

The algorithm is robust to noise and proves applicable on a range of tracers as tested on [15O]H2O, [18F]FDG and [64Cu]Cu-DOTATATE, and hence is a viable option offering the ability for delay correction across various organs and tracers in use with kinetic modeling.

Automated extraction of the arterial input function from brain images for parametric PET studies

BACKGROUND

Accurate measurement of the arterial input function (AIF) is crucial for parametric PET studies, but the AIF is commonly derived from invasive arterial blood sampling. It is possible to use an image-derived input function (IDIF) obtained by imaging a large blood pool, but IDIF measurement in PET brain studies performed on standard field of view scanners is challenging due to lack of a large blood pool in the field-of-view. Here we describe a novel automated approach to estimate the AIF from brain images.

RESULTS

Total body 18F-FDG PET data from 12 subjects were split into a model adjustment group (n = 6) and a validation group (n = 6). We developed an AIF estimation framework using wavelet-based methods and unsupervised machine learning to distinguish arterial and venous activity curves, compared to the IDIF from the descending aorta. All of the automatically extracted AIFs in the validation group had similar shape to the IDIF derived from the descending aorta IDIF. The average area under the curve error and normalised root mean square error across validation data were - 1.59 ± 2.93% and 0.17 ± 0.07.

CONCLUSIONS

Our automated AIF framework accurately estimates the AIF from brain images. It reduces operator-dependence, and could facilitate the clinical adoption of parametric PET.

Clinical feasibility study of early 30-minute dynamic FDG-PET scanning protocol for patients with lung lesions

PURPOSE

This study aimed to evaluate the clinical feasibility of early 30-minute dynamic 2-deoxy-2-[18F]fluoro-D-glucose (18F-FDG) positron emission tomography (PET) scanning protocol for patients with lung lesions in comparison to the standard 65-minute dynamic FDG-PET scanning as a reference.

METHODS

Dynamic 18F-FDG PET images of 146 patients with 181 lung lesions (including 146 lesions confirmed by histology) were analyzed in this prospective study. Dynamic images were reconstructed into 28 frames with a specific temporal division protocol for the scan data acquired 65 min post-injection. Ki images and quantitative parameters Ki based on two different acquisition durations [the first 30 min (Ki-30 min) and 65 min (Ki-65 min)] were obtained by applying the irreversible two-tissue compartment model using in-house Matlab software. The two acquisition durations were compared for Ki image quality (including visual score analysis and number of lesions detected) and Ki value (including accuracy of Ki, the value of differential diagnosis of lung lesions and prediction of PD-L1 status) by Wilcoxon's rank sum test, Spearman's rank correlation analysis, receiver operating characteristic (ROC) curve, and the DeLong test. The significant testing level (alpha) was set to 0.05.

RESULTS

The quality of the Ki-30 min images was not significantly different from the Ki-65 min images based on visual score analysis (P > 0.05). In terms of Ki value, among 181 lesions, Ki-65 min was statistically higher than Ki-30 min (0.027 ± 0.017 ml/g/min vs. 0.026 ± 0.018 ml/g/min, P < 0.05), while a very high correlation was obtained between Ki-65 min and Ki-30 min (r = 0.977, P < 0.05). In the differential diagnosis of lung lesions, ROC analysis was performed on 146 histologically confirmed lesions, the area under the curve (AUC) of Ki-65 min, Ki-30 min, and SUVmax was 0.816, 0.816, and 0.709, respectively. According to the Delong test, no significant differences in the diagnostic accuracies were found between Ki-65 min and Ki-30 min (P > 0.05), while the diagnostic accuracies of Ki-65 min and Ki-30 min were both significantly higher than that of SUVmax (P < 0.05). In 73 (NSCLC) lesions with definite PD-L1 expression results, the Ki-65 min, Ki-30 min, and SUVmax in PD-L1 positivity were significantly higher than that in PD-L1 negativity (P < 0.05). And no significant differences in predicting PD-L1 positivity were found among Ki-65 min, Ki-30 min, and SUVmax (AUC = 0.704, 0.695, and 0.737, respectively, P > 0.05), according to the results of ROC analysis and Delong test.

CONCLUSIONS

This study indicates that an early 30-minute dynamic FDG-PET acquisition appears to be sufficient to provide quantitative images with good-quality and accurate Ki values for the assessment of lung lesions and prediction of PD-L1 expression. Protocols with a shortened early 30-minute acquisition time may be considered for patients who have difficulty with prolonged acquisitions to improve the efficiency of clinical acquisitions.

Assessing dynamic metabolic heterogeneity in prostate cancer patients via total-body [68Ga]Ga-PSMA-11 PET/CT imaging: quantitative analysis of [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs

PURPOSE

This study aimed to quantitatively assess [68Ga]Ga-PSMA-11 uptake in pathological lesions and normal organs in prostate cancer using the total-body [68Ga]Ga-PSMA-11 PET/CT and to characterize the dynamic metabolic heterogeneity of prostate cancer.

METHODS

Dynamic total-body [68Ga]Ga-PSMA-11 PET/CT scans were performed on ten prostate cancer patients. Manual delineation of volume-of-interests (VOIs) was performed on multiple normal organs displaying high [68Ga]Ga-PSMA-11 uptake, as well as pathological lesions. Time-to-activity curves (TACs) were generated, and the four compartment models including one-tissue compartmental model (1T1k), reversible one-tissue compartmental model (1T2k), irreversible two-tissue compartment model (2T3k) and reversible two-tissue compartmental model (2T4k) were fitted to each tissue TAC. Various rate constants, including K1 (forward transport rate from plasma to the reversible compartment), k2 (reverse transport rate from the reversible compartment to plasma), k3 (tracer binding on the PSMA-receptor and its internalization), k4 (the externalization rate of the tracer) and Ki (net influx rate), were obtained. The selection of the optimal model for describing the uptake of both lesions and normal organs was determined using the Akaike information criteria (AIC). Receiver operating characteristic (ROC) curve analysis was performed to determine the cut-off values for differentiating physiological and pathological [68Ga]Ga-PSMA-11 uptake.

RESULTS

Both 1T1k and 1T2k models showed relatively high AIC values compared to the 2T3k and 2T4k models in both pathological lesions and normal organs. The kinetic behavior of pathological lesions was better described by the 2T3k model compared to the 2T4k model, while the normal organs were better described by the 2T4k model. Significant variations in kinetic metrics, such as K1, k2, and k3, and Ki, were observed among normal organs with high [68Ga]Ga-PSMA-11 uptake and pathological lesions. The high Ki value in normal organs was primarily determined by elevated K1 and low k3, rather than k2. Conversely, the high Ki value in pathological lesions, ranking second to the kidney and similar to salivary glands and spleen, was predominantly determined by the highest k3 value. Notably, k3 exhibited the highest performance in distinguishing between physiological and pathological [68Ga]Ga-PSMA-11 uptake, with an area under the curve (AUC) of 0.844 (95% CI, 0.773-0.915), sensitivity of 82.9%, and specificity of 74.1%. The k3 values showed better performance than SUVmean (AUC, 0.659), SUVmax (AUC, 0.637), and other kinetic parameter including K1 (AUC, 0.604), k2 (AUC, 0.634), and Ki (AUC, 0.651).

CONCLUSIONS

Significant discrepancies in kinetic metrics were detected between pathological lesions and normal organs, despite their shared high uptake of [68Ga]Ga-PSMA-11. Notably, the k3 value exhibits a noteworthy capability to distinguish between pathological lesions and normal organs with elevated [68Ga]Ga-PSMA-11 uptake. This discovery implies that k3 holds promise as a prospective imaging biomarker for distinguishing between pathologic and non-specific [68Ga]Ga-PSMA-11 uptake in patients with prostate cancer.

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET

BACKGROUND

In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an 18F-fluorodeoxyglucose (18F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24-min imaging window and an input function modeled using measurements from a region of interest placed over the left ventricle.

METHODS

To test the protocol in 6 healthy participants, we examined the quality of voxel-based maps of kinetic parameters in the brain generated using the two-tissue compartment model and compared estimated parameter values with previously published values. We also utilized data from a 36-min validation imaging window to compare (1) the modeled AIF against the input function measured in the validation window; and (2) the net influx rate ([Formula: see text]) computed using parameter estimates from the short imaging window against the net influx rate obtained using Patlak analysis in the validation window.

RESULTS

Compared to the AIF measured in the validation window, the input function estimated from the short imaging window achieved a mean area under the curve error of 9%. The voxel-wise Pearson's correlation between [Formula: see text] estimates from the short imaging window and the validation imaging window exceeded 0.95.

CONCLUSION

The proposed 24-min triple injection protocol enables parametric 18F-FDG neuroimaging with noninvasive estimation of the AIF from cardiac images using a standard field of view PET scanner.

Comparison of parametric imaging and SUV imaging with [68 Ga]Ga-PSMA-11 using dynamic total-body PET/CT in prostate cancer

PURPOSE

Standardized uptake value (SUV) has been prevalently used to measure [68 Ga]Ga-PSMA-11 activity in prostate cancer, but it is susceptible to multiple factors. Parametric imaging allows for absolute quantification of tracer uptake and provides a better diagnostic accuracy that is crucial for lesion detection. However, the clinical significance of total-body parametric imaging of [68 Ga]Ga-PSMA-11 remains to be fully assessed. Therefore, the aim of our study is to delve into the diagnostic implications of total-body parametric imaging of [68 Ga]Ga-PSMA-11 PET/CT for patients with prostate cancer.

METHODS

Twenty prostate cancer patients were included and underwent a dynamic total-body [68 Ga]Ga-PSMA-11 PET/CT scan. An irreversible two-tissue compartment model (2T3k) was fitted for each tissue time-to-activity curve, and the net influx rate (Ki) was obtained. The image quality and semi-quantitative analysis of lesion-to-background ratio (LBR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between parametric images and SUV images.

RESULTS

Kinetic modeling using 2T3k demonstrated favorable model fitting in both normal organs and lesions. All of the lesions detected on SUV images (55-60 min) could be detected on Ki images. The correlation between Ki, SUVmean, and SUVmax in both normal organs and pathological lesions was found to be positive and statistically significant. Conversely, a moderate positive correlations were found between Ki and K1 (R = 0.69, P < 0.001; R = 0.61, P < 0.001) and Ki and k3 (R = 0.69, P < 0.001; R = 0.62, P < 0.001), in normal organs and pathological lesions, respectively. Visual assessment in Ki images showed less image noise and higher lesions conspicuity compared to SUV images. Ki image-derived LBR, SNR, and CBR of pathological lesions including primary tumors (PTs), lymph node metastases (LNMs) and bone metastases (BMs), exhibited remarkably higher folds (1.4-3.6 folds) compared to those derived from SUV of corresponding lesions.

CONCLUSIONS

Total-body parametric imaging of [68 Ga]Ga-PSMA-11 enhanced lesion contrast and improved lesion detectability compared to SUV images. This may potentially serve as an imaging biomarker and theranostic tool for precise diagnosis and treatment evaluation in prostate cancer patients.

A new framework for metabolic connectivity mapping using bolus [18F]FDG PET and kinetic modeling

Metabolic connectivity (MC) has been previously proposed as the covariation of static [18F]FDG PET images across participants, i.e., across-individual MC (ai-MC). In few cases, MC has been inferred from dynamic [18F]FDG signals, i.e., within-individual MC (wi-MC), as for resting-state fMRI functional connectivity (FC). The validity and interpretability of both approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel wi-MC methodology; 2) compare ai-MC maps from standardized uptake value ratio (SUVR) vs. [18F]FDG kinetic parameters fully describing the tracer behavior (i.e., Ki, K1, k3); 3) assess MC interpretability in comparison to structural connectivity and FC. We developed a new approach based on Euclidean distance to calculate wi-MC from PET time-activity curves. The across-individual correlation of SUVR, Ki, K1, k3 produced different networks depending on the chosen [18F]FDG parameter (k3 MC vs. SUVR MC, r = 0.44). We found that wi-MC and ai-MC matrices are dissimilar (maximum r = 0.37), and that the match with FC is higher for wi-MC (Dice similarity: 0.47-0.63) than for ai-MC (0.24-0.39). Our analyses demonstrate that calculating individual-level MC from dynamic PET is feasible and yields interpretable matrices that bear similarity to fMRI FC measures.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Brain connectomics: time for a molecular imaging perspective?

In the past two decades brain connectomics has evolved into a major concept in neuroscience. However, the current perspective on brain connectivity and how it underpins brain function relies mainly on the hemodynamic signal of functional magnetic resonance imaging (MRI). Molecular imaging provides unique information inaccessible to MRI-based and electrophysiological techniques. Thus, positron emission tomography (PET) has been successfully applied to measure neural activity, neurotransmission, and proteinopathies in normal and pathological cognition. Here, we position molecular imaging within the brain connectivity framework from the perspective of timeliness, validity, reproducibility, and resolution. We encourage the neuroscientific community to take an integrative approach whereby MRI-based, electrophysiological techniques, and molecular imaging contribute to our understanding of the brain connectome.

Quantitative assessment of translocator protein (TSPO) in the non-human primate brain and clinical translation of [18F]LW223 as a TSPO-targeted PET radioligand

OBJECTIVES

Translocator protein 18 kDa (TSPO) positron emission tomography (PET) can be harnessed for the non-invasive detection of macrophage-driven inflammation. [¹⁸F]LW223, a newly reported TSPO PET tracer which was insensitive to rs6971 polymorphism, showed favorable performance characteristics in a recent imaging study involving a rat myocardial infarction model. To enable quantitative neuroimaging with [¹⁸F]LW223, we conducted kinetic analysis in the non-human primate (NHP) brain. Further, we sought to assess the utility of [¹⁸F]LW223-based TSPO imaging in a first-in-human study.

METHODS

Radiosynthesis of [¹⁸F]LW223 was accomplished on an automated module, whereas molar activities, stability in formulation, lipophilicity and unbound free fraction (f_u) of the probe were measured. Brain penetration and target specificity of [¹⁸F]LW223 in NHPs were corroborated by PET-MR imaging under baseline and pre-blocking conditions using the validated TSPO inhibitor, (R)-PK11195, at doses ranging from 5 to 10 mg/kg. Kinetic modeling was performed using one-tissue compartment model (1TCM), two-tissue compartment model (2TCM) and Logan graphical analyses, using dynamic PET data acquisition, arterial blood collection and metabolic stability testing. Clinical PET scans were performed in two healthy volunteers (HVs). Regional brain standard uptake value ratio (SUVr) was assessed for different time intervals.

RESULTS

[¹⁸F]LW223 was synthesized in non-decay corrected radiochemical yields (n.d.c. RCYs) of 33.3 ± 6.5% with molar activities ranging from 1.8 ± 0.7 Ci/µmol (n = 11). [¹⁸F]LW223 was stable in formulation for up to 4 h and LogD_7.4 of 2.31 ± 0.13 (n = 6) and f_u of 5.80 ± 1.42% (n = 6) were determined. [¹⁸F]LW223 exhibited good brain penetration in NHPs, with a peak SUV value of ca. 1.79 in the whole brain. Pre-treatment with (R)-PK11195 substantially accelerated the washout and attenuated the area under the time-activity curve, indicating in vivo specificity of [¹⁸F]LW223 towards TSPO. Kinetic modeling demonstrated that 2TCM was the most suitable model for [¹⁸F]LW223-based neuroimaging. Global transfer rate constants (K₁) and total volumes of distribution (V_T) were found to be 0.10 ± 0.01 mL/cm³/min and 2.30 ± 0.17 mL/cm³, respectively. Dynamic PET data analyses across distinct time windows revealed that the V_T values were relatively stable after 60 min post-injection. In a preliminary clinical study with two healthy volunteers, [¹⁸F]LW223 exhibited good brain uptake and considerable tracer retention across all analyzed brain regions. Of note, an excellent correlation between SUVr with V_T was obtained when assessing the time interval from 20 to 40 min post tracer injection (SUVr_(20-40 min), R² = 0.94, p < 0.0001), suggesting this time window may be suitable to estimate specific binding to TSPO in human brain.

CONCLUSION

Our findings indicate that [¹⁸F]LW223 is suitable for quantitative TSPO-targeted PET imaging in higher species. Employing state-of-the-art kinetic modeling, we found that [¹⁸F]LW223 was effective in mapping TSPO throughout the NHP brain, with best model fits obtained from 2TCM and Logan graphical analyses. Overall, our results indicate that [¹⁸F]LW223 exhibits favorable tracer performance characteristics in higher species, and this novel imaging tool may hold promise to provide effective neuroinflammation imaging in patients with neurological disease.

Patient-Adaptive Population-Based Modeling of Arterial Input Functions

Kinetic modeling of dynamic PET data requires knowledge of tracer concentration in blood plasma, described by the arterial input function (AIF). Arterial blood sampling is the gold standard for AIF measurement, but is invasive and labour intensive. A number of methods have been proposed to accurately estimate the AIF directly from blood sampling and/or imaging data. Here we consider fitting a patient-adaptive mixture of historical population time course profiles to estimate individual AIFs. Travel time of a tracer atom from the injection site to the right ventricle of the heart is modeled as a realization from a Gamma distribution, and the time this atom spends in circulation before being sampled is represented by a subject-specific linear mixture of population profiles. These functions are estimated from independent population data. Individual AIFs are obtained by projection onto this basis of population profile components. The model incorporates knowledge of injection duration into the fit, allowing for varying injection protocols. Analyses of arterial sampling data from 18F-FDG, 15O-H2O and 18F-FLT clinical studies show that the proposed model can outperform reference techniques. The statistically significant gain achieved by using population data to train the basis components, instead of fitting these from the single individual sampling data, is measured on the FDG cohort. Kinetic analyses of simulated data demonstrate the reliability and potential benefit of this approach in estimating physiological parameters. These results are further supported by numerical simulations that demonstrate convergence and stability of the proposed technique under varying training population sizes and noise levels.

FDG PET Scan Durations via Effective Data Processing

BACKGROUND

Total-body dynamic PET (dPET) imaging using ¹⁸ F-fluorodeoxyglucose (¹⁸ F-FDG) has received widespread attention in clinical oncology. However, the conventionally required scan duration of approximately 1 hour seriously limits the application and promotion of this imaging technique. In this study, we investigated the possibility and feasibility of shortening the total-body dynamic scan duration to 30 min post-injection (PI) with the help of a novel Patlak data processing algorithm for accurate K_i estimations of tumor lesions.

METHODS

Total-body dPET images acquired by uEXPLORER (United Imaging Healthcare Inc.) using ¹⁸ F-FDG of 15 patients with different tumor types were analyzed in this study. Dynamic images were reconstructed into 25 frames with a specific temporal dividing protocol for the scan data acquired 1 hour PI. Patlak analysis-based K_i parametric imaging was conducted based on the imaging data corresponding to the first 30 min PI, during which a Patlak data processing method based on cubit Hermite interpolation (THI) was applied. The resultant K_i images acquired by 30-min dynamic PET data and the standard 1-hour K_i images were compared in terms of visual imaging effect, region signal-to-noise ratio (SNR), and K_i estimation accuracy to evaluate the performance of the proposed K_i imaging method with a shortened scan duration.

RESULTS

With the help of Patlak data processing, acceptable K_i parametric images were obtained from dynamic PET data acquired with a scan duration of 30 min PI. Compared with K_i images obtained from unprocessed Patlak data, the resulting images from the proposed method performed better in terms of noise reduction. Moreover, Bland-Altman (BA) plot and Person correlation coefficient (PPC) analysis showed that that 30-min K_i images obtained from the processed Patlak data had higher accuracy for tumor lesions.

CONCLUSION

Satisfactory K_i parametric images with high tumor accuracy can be acquired from dynamic imaging data corresponding to the first 30 min PI. Patlak data processing can help achieve higher K_i imaging quality and higher accuracy regarding tumor lesion K_i values. Clinically, it is possible to shorten the dynamic scan duration of ¹⁸ F-FDG PET to 30 min to acquire an accurate tumor K_i and further effective tumor detection with uEXPLORER scanners. This article is protected by copyright. All rights reserved.

Image-derived Input Function in brain [18F]FDG PET data: which alternatives to the carotid siphons?

Quantification of brain [¹⁸F] fluorodeoxyglucose ([¹⁸F]FDG) positron emission tomography (PET) data requires an input function. A noninvasive alternative to gold-standard arterial sampling is the image-derived input function (IDIF), typically extracted from the internal carotid arteries (ICAs), which are however difficult to segment and subjected to spillover effects. In this work, we evaluated the feasibility of extracting the IDIF from two different vascular sites, i.e., 1) common carotids (CCA) and 2) superior sagittal sinus (SSS), other than 3) ICA in a large group of glioma patients undergoing a dynamic [¹⁸F]FDG PET acquisition on a hybrid PET/MR scanner. Comparisons are drawn between the different IDIFs in terms of peak amplitude and shape, as well as between the estimates of fractional uptake rate (Kr) obtained from the different extraction sites in terms of a) grey/white matter average absolute values, b) ratio of grey-to-white matter, and c) spatial patterns for the hemisphere contralateral to the lesion. Clinical Relevance - This work points towards new feasible IDIF extraction sites (CCA in particular) which could allow for fully noninvasive absolute PET quantification in clinical populations.

Hepatic Positron Emission Tomography: Applications in Metabolism, Haemodynamics and Cancer

Evaluating in vivo the metabolic rates of the human liver has been a challenge due to its unique perfusion system. Positron emission tomography (PET) represents the current gold standard for assessing non-invasively tissue metabolic rates in vivo. Here, we review the existing literature on the assessment of hepatic metabolism, haemodynamics and cancer with PET. The tracer mainly used in metabolic studies has been [¹⁸F]2-fluoro-2-deoxy-D-glucose (¹⁸F-FDG). Its application not only enables the evaluation of hepatic glucose uptake in a variety of metabolic conditions and interventions, but based on the kinetics of ¹⁸F-FDG, endogenous glucose production can also be assessed. 14(R,S)-[¹⁸F]fluoro-6-thia-Heptadecanoic acid (¹⁸F-FTHA), ¹¹C-Palmitate and ¹¹C-Acetate have also been applied for the assessment of hepatic fatty acid uptake rates (¹⁸F-FTHA and ¹¹C-Palmitate) and blood flow and oxidation (¹¹C-Acetate). Oxygen-15 labelled water (¹⁵O-H₂O) has been used for the quantification of hepatic perfusion. ¹⁸F-FDG is also the most common tracer used for hepatic cancer diagnostics, whereas ¹¹C-Acetate has also shown some promising applications in imaging liver malignancies. The modelling approaches used to analyse PET data and also the challenges in utilizing PET in the assessment of hepatic metabolism are presented.

Dynamic chaotic gravitational search algorithm-based kinetic parameter estimation of hepatocellular carcinoma on 18F-FDG PET/CT

Background

Kinetic parameters estimated with dynamic ¹⁸F-FDG PET/CT can help to characterize hepatocellular carcinoma (HCC). We aim to evaluate the feasibility of the gravitational search algorithm (GSA) for kinetic parameter estimation and to propose a dynamic chaotic gravitational search algorithm (DCGSA) to enhance parameter estimation.

Methods

Five-minute dynamic PET/CT data of 20 HCCs were prospectively enrolled, and the kinetic parameters k₁ ~ k₄ and the hepatic arterial perfusion index (HPI) were estimated with a dual-input three-compartment model based on nonlinear least squares (NLLS), GSA and DCGSA.

Results

The results showed that there were significant differences between the HCCs and background liver tissues for k₁, k₄ and the HPI of NLLS; k₁, k₃, k₄ and the HPI of GSA; and k₁, k₂, k₃, k₄ and the HPI of DCGSA. DCGSA had a higher diagnostic performance for k₃ than NLLS and GSA.

Conclusions

GSA enables accurate estimation of the kinetic parameters of dynamic PET/CT in the diagnosis of HCC, and DCGSA can enhance the diagnostic performance.

Correlation of the quantitative methods for the measurement of bone uptake and plasma clearance of 18F-NaF using positron emission tomography. Systematic review and meta-analysis

PURPOSE

¹⁸F-NaF PET is valuable for detecting bone metabolism through osteoblastic activity in the assessment of bone disease. Hawkins, Patlak, and standardised uptake value (SUV) are the most common quantitative measurements used to evaluate bone metabolism. This systematic review evaluates the correlation between quantitative positron emission tomography (PET) methods and to compare their precision.

METHODS

A systematic search in Medline, PubMed, SCOPUS, and Web of Science was undertaken to find relevant papers published from 2000. All studies with human adults undergoing ¹⁸F-NaF PET, PET/CT, or PET/MRI were included except for subjects diagnosed with non-diffuse metabolic bone disease or malignancy. Quality Assessment Tool for Studies of Diverse Designs (QATSDD) was used to assess risk of bias. A qualitative review and meta-analysis using Hedges random-effect model was used producing summary size effects of the correlation between methods in healthy and unhealthy bone sites and assessing study heterogeneity.

RESULTS

228 healthy and unhealthy participants were included across 12 studies resulted from the systematic search. One-third of studies had a moderate quality percentage while the rest had relatively high quality. The pooled correlation coefficient in meta-analysis showed a high correlation of more than 0.88 (0.71-1.05. 95 %CI) between SUV and Hawkins and more than 0.96 (0.88-1.03. 95 %CI) between Patlak and Hawkins within all subgroups, suggesting all methods yield similar results in healthy and unhealthy bone sites. SUV has the lowest precision error followed by Patlak while Hawkins method showed the highest precision error.

CONCLUSION

Patlak is the best within research and SUV is better within clinical practice.

Computational modeling of PET tracer distribution in solid tumors integrating microvasculature

BACKGROUND

We present computational modeling of positron emission tomography radiotracer uptake with consideration of blood flow and interstitial fluid flow, performing spatiotemporally-coupled modeling of uptake and integrating the microvasculature. In our mathematical modeling, the uptake of fluorodeoxyglucose F-18 (FDG) was simulated based on the Convection-Diffusion-Reaction equation given its high accuracy and reliability in modeling of transport phenomena. In the proposed model, blood flow and interstitial flow are solved simultaneously to calculate interstitial pressure and velocity distribution inside cancer and normal tissues. As a result, the spatiotemporal distribution of the FDG tracer is calculated based on velocity and pressure distributions in both kinds of tissues.

RESULTS

Interstitial pressure has maximum value in the tumor region compared to surrounding tissue. In addition, interstitial fluid velocity is extremely low in the entire computational domain indicating that convection can be neglected without effecting results noticeably. Furthermore, our results illustrate that the total concentration of FDG in the tumor region is an order of magnitude larger than in surrounding normal tissue, due to lack of functional lymphatic drainage system and also highly-permeable microvessels in tumors. The magnitude of the free tracer and metabolized (phosphorylated) radiotracer concentrations followed very different trends over the entire time period, regardless of tissue type (tumor vs. normal).

CONCLUSION

Our spatiotemporally-coupled modeling provides helpful tools towards improved understanding and quantification of in vivo preclinical and clinical studies.

Positron emission tomography in multiple sclerosis - straight to the target

Following the impressive progress in the treatment of relapsing-remitting multiple sclerosis (MS), the major challenge ahead is the development of treatments to prevent or delay the irreversible accumulation of clinical disability in progressive forms of the disease. The substrate of clinical progression is neuro-axonal degeneration, and a deep understanding of the mechanisms that underlie this process is a precondition for the development of therapies for progressive MS. PET imaging involves the use of radiolabelled compounds that bind to specific cellular and metabolic targets, thereby enabling direct in vivo measurement of several pathological processes. This approach can provide key insights into the clinical relevance of these processes and their chronological sequence during the disease course. In this Review, we focus on the contribution that PET is making to our understanding of extraneuronal and intraneuronal mechanisms that are involved in the pathogenesis of irreversible neuro-axonal damage in MS. We consider the major challenges with the use of PET in MS and the steps necessary to realize clinical benefits of the technique. In addition, we discuss the potential of emerging PET tracers and future applications of existing compounds to facilitate the identification of effective neuroprotective treatments for patients with MS.

Mathematical Models for FDG Kinetics in Cancer: A Review

Compartmental analysis is the mathematical framework for the modelling of tracer kinetics in dynamical Positron Emission Tomography. This paper provides a review of how compartmental models are constructed and numerically optimized. Specific focus is given on the identifiability and sensitivity issues and on the impact of complex physiological conditions on the mathematical properties of the models.

Imaging Biotin Trafficking In Vivo with Positron Emission Tomography

The water-soluble vitamin biotin is essential for cellular growth, development, and well-being, but its absorption, distribution, metabolism, and excretion are poorly understood. This paper describes the radiolabeling of biotin with the positron emission tomography (PET) radionuclide carbon-11 ([¹¹C]biotin) to enable the quantitative study of biotin trafficking in vivo. We show that intravenously administered [¹¹C]biotin is quickly distributed to the liver, kidneys, retina, heart, and brain in rodents-consistent with the known expression of the biotin transporter-and there is a surprising accumulation in the brown adipose tissue (BAT). Orally administered [¹¹C]biotin was rapidly absorbed in the small intestine and swiftly distributed to the same organs. Preadministration of nonradioactive biotin inhibited organ uptake and increased excretion. [¹¹C]Biotin PET imaging therefore provides a dynamic in vivo map of transporter-mediated biotin trafficking in healthy rodents. This technique will enable the exploration of biotin trafficking in humans and its use as a research tool for diagnostic imaging of obesity/diabetes, bacterial infection, and cancer.

Relevance of quantification in brain PET studies with 18F-FDG

The inclusion of ¹⁸F-FDG PET as a biomarker in the diagnostic criteria of neurodegenerative diseases and its indication in the presurgical assessment for drug-resistant epilepsies allow to improve specificity of these diagnosis. The traditional interpretation of neurological PET studies has been performed qualitatively, although in the last decade, several quantitative evaluation methods have emerged. This technical development has become relevant in clinical practice, improving specificity, reproducibility and reducing the interrater reliability derived from visual analysis. In this article we update/review the main imaging processing techniques currently used. This may allow the Nuclear Medicine physician to know their advantages and disadvantages when including these procedures in daily clinical practice.

Repurposing radiotracers for myelin imaging: a study comparing 18F-florbetaben, 18F-florbetapir, 18F-flutemetamol,11C-MeDAS, and 11C-PiB

PURPOSE

Drugs promoting myelin repair represent a promising therapeutic approach in multiple sclerosis and several candidate molecules are currently being evaluated, fostering the need of a quantitative method to specifically measure myelin content in vivo. PET using the benzothiazole derivative ¹¹C-PiB has been successfully used to quantify myelin content changes in humans. Stilbene derivatives, such as ¹¹C-MeDAS, have also been shown to bind to myelin in animals and are considered a promising radiopharmaceutical class for myelin imaging. Fluorinated compounds from both classes are now commercially available and thus should constitute clinically useful myelin radiotracers. The aim of this study is to provide a head-to-head comparison of ¹⁸F-florbetaben, ¹⁸F-florbetapir, ¹⁸F-flutemetamol, ¹¹C-MeDAS, and ¹¹C-PiB with regard to brain kinetics and binding in white matter (WM).

METHODS

Four baboons underwent a 90-min dynamic PET scan for each radioligand. Arterial blood samples were collected during the exam for each radiotracer, except for ¹⁸F-florbetapir, to obtain a radiometabolite-corrected input function. Standardized uptake value ratio between 75 at 90 min (SUVR_75-90), binding potential (BP) estimated with Logan method with input function, and distribution volume ratio (DVR) estimated with Logan reference method (using cerebellar gray matter as reference region) were calculated in WM and compared between tracers using mixed effect models.

RESULTS

In WM, ¹⁸F-florbetapir had the highest SUVR_75-90 (1.38 ± 0.03), followed by ¹⁸F-flutemetamol (1.34 ± 0.02), ¹⁸F-florbetaben (1.32 ± 0.07), ¹¹C-MeDAS (1.27 ± 0.04), and ¹¹C-PiB (1.25 ± 0.07). With regard to BP, ¹⁸F-florbetaben had the highest value (0.32 ± 0.06) compared with ¹⁸F-flutemetamol (0.20 ± 0.03), ¹¹C-MeDAS (0.17 ± 0.03), and ¹¹C-PiB (0.16 ± 0.03). No difference in DVR was detected between ¹⁸F-florbetaben (1.26 ± 0.06) and ¹⁸F-florbetapir (1.27 ± 0.03), but both were significantly higher in DVR than ¹⁸F-flutemetamol (1.17 ± 0.02), ¹¹C-MeDAS (1.16 ± 0.03), and ¹¹C-PiB (1.14 ± 0.02).

CONCLUSIONS

Given their higher binding and longer half-life, our study indicates that ¹⁸F-florbetapir and ¹⁸F-florbetaben are promising tracers for myelin imaging which are readily available for clinical application in demyelinating diseases.

Current advances in ligand design for inorganic positron emission tomography tracers 68Ga, 64Cu, 89Zr and 44Sc

A key part of the development of metal based Positron Emission Tomography probes is the chelation of the radiometal. In this review the recent developments in the chelation of four positron emitting radiometals, ⁶⁸Ga, ⁶⁴Cu, ⁸⁹Zr and ⁴⁴Sc, are explored. The factors that effect the chelation of each radio metal and the ideal ligand system will be discussed with regards to high in vivo stability, complexation conditions, conjugation to targeting motifs and complexation kinetics. A series of cyclic, cross-bridged and acyclic ligands will be discussed, such as CP256 which forms stable complexes with ⁶⁸Ga under mild conditions and PCB-TE2A which has been shown to form a highly stable complex with ⁶⁴Cu. ⁸⁹Zr and ⁴⁴Sc have seen significant development in recent years with a number of chelates being applied to each metal - eight coordinate di-macrocyclic terephthalamide ligands were found to rapidly produce more stable complexes with ⁸⁹Zr than the widely used DFO.

Impact of tissue kinetic heterogeneity on PET quantification: case study with the L-[1-11C]leucine PET method for cerebral protein synthesis rates

Functional quantification with PET is generally based on modeling that assumes tissue regions are kinetically homogeneous. Even in regions sufficiently small to approach homogeneity, spillover due to resolution limitations of PET scanners may introduce heterogeneous kinetics into measured data. Herein we consider effects of kinetic heterogeneity at the smallest volume accessible, the single image voxel. We used L-[1-¹¹C]leucine PET and compared rates of cerebral protein synthesis (rCPS) estimated voxelwise with methods that do (Spectral Analysis Iterative Filter, SAIF) and do not (Basis Function Method, BFM) allow for kinetic heterogeneity. In high resolution PET data with good counting statistics BFM produced estimates of rCPS comparable to SAIF, but at lower computational cost; thus the simpler, less costly method can be applied. With poorer counting statistics (lower injected radiotracer doses), BFM estimates were more biased. In data smoothed to simulate lower resolution PET, BFM produced estimates of rCPS 9-14% higher than SAIF, overestimation consistent with applying a homogeneous tissue model to kinetically heterogeneous data. Hence with lower resolution data it is necessary to account for kinetic heterogeneity in the analysis. Kinetic heterogeneity may impact analyses of other tracers and scanning protocols differently; assessments should be made on a case by case basis.

Spectral Analysis of Dynamic PET Studies: A Review of 20 Years of Method Developments and Applications

In Positron Emission Tomography (PET), spectral analysis (SA) allows the quantification of dynamic data by relating the radioactivity measured by the scanner in time to the underlying physiological processes of the system under investigation. Among the different approaches for the quantification of PET data, SA is based on the linear solution of the Laplace transform inversion whereas the measured arterial and tissue time-activity curves of a radiotracer are used to calculate the input response function of the tissue. In the recent years SA has been used with a large number of PET tracers in brain and nonbrain applications, demonstrating that it is a very flexible and robust method for PET data analysis. Differently from the most common PET quantification approaches that adopt standard nonlinear estimation of compartmental models or some linear simplifications, SA can be applied without defining any specific model configuration and has demonstrated very good sensitivity to the underlying kinetics. This characteristic makes it useful as an investigative tool especially for the analysis of novel PET tracers. The purpose of this work is to offer an overview of SA, to discuss advantages and limitations of the methodology, and to inform about its applications in the PET field.

Parametric Method Performance for Dynamic 3'-Deoxy-3'-18F-Fluorothymidine PET/CT in Epidermal Growth Factor Receptor-Mutated Non-Small Cell Lung Carcinoma Patients Before and During Therapy

The objective of this study was to validate several parametric methods for quantification of 3'-deoxy-3'-¹⁸F-fluorothymidine (¹⁸F-FLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic ¹⁸F-FLT PET/CT to assess the robustness of these methods. Methods: Ten NSCLC patients underwent dynamic ¹⁸F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (V_T) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy (R² ≥ 0.94; intraclass correlation coefficient > 0.97). SA-based V_T images were most robust to increased noise on a voxel-level (repeatability coefficient, 16% vs. >26%). Yet BFM generated the most accurate K₁ values (R² = 0.94; intraclass correlation coefficient, 0.96). Parametric K₁ data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric ¹⁸F-FLT V_T images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K₁ data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic ¹⁸F-FLT PET/CT studies; however, SA can also be used.

Modelling arterial input functions in positron emission tomography dynamic studies

The quantification of dynamic positron emission tomography (PET) images often requires the invasive measures of the arterial plasma tracer concentration to be used as arterial input function (AIF). In several situations, a mathematical model is fit to the hematic data to obtain a continuous and noise-free description of the AIF. In common practice, the tri-exponential and Feng's models are generally adopted. Despite their general applicability, often these approximations of blood tracer activity do not properly describe the complex behavior of the AIF (e.g. different clearance rates of the tracers) as well as they do not account for the length of the radiotracer injection. Here we propose two models able to include the injection duration as additional information in the AIF modeling and we compare their performances in eight different datasets acquired from different PET facilities.

Variability of [18F]FDG administered activities among patients undergoing PET examinations: an international multicenter survey

Given the large number of [(18)F]fluorodeoxyglucose (FDG) PET examinations performed annually throughout the world, reduction of the administered activity without compromise of the clinical information being sought is encouraged. Guidelines issued by the SNMMI and European Association of Nuclear Medicine (EANM) differ greatly on the choice of the activity that should be administered to patients: the EANM suggests a personalised activity based on the patient's body weight, whereas the SNMMI recommends the administration of fixed activities. The authors analysed a database of 24 716 [(18)F]FDG administrations performed worldwide in 15 PET centres to assess the degree of heterogeneity, in relation to available technology, operational protocols and reference guidelines. Median activities based on the patients' body weight were 43 % lower than fixed-activity administrations (p < 0.001). When TOF scanners are available, the median activity is lowered, but when comparing centres with the same technology or those that use the same operational protocols, weight-based activities are still significantly lower than fixed activities.

Quantification of [(11)C]PIB PET for imaging myelin in the human brain: a test-retest reproducibility study in high-resolution research tomography

An accurate in vivo measure of myelin content is essential to deepen our insight into the mechanisms underlying demyelinating and dysmyelinating neurological disorders, and to evaluate the effects of emerging remyelinating treatments. Recently [(11)C]PIB, a positron emission tomography (PET) tracer originally conceived as a beta-amyloid marker, has been shown to be sensitive to myelin changes in preclinical models and humans. In this work, we propose a reference-region methodology for the voxelwise quantification of brain white-matter (WM) binding for [(11)C]PIB. This methodology consists of a supervised procedure for the automatic extraction of a reference region and the application of the Logan graphical method to generate distribution volume ratio (DVR) maps. This approach was assessed on a test-retest group of 10 healthy volunteers using a high-resolution PET tomograph. The [(11)C]PIB PET tracer binding was shown to be up to 23% higher in WM compared with gray matter, depending on the image reconstruction. The DVR estimates were characterized by high reliability (outliers <1%) and reproducibility (intraclass correlation coefficient (ICC) >0.95). [(11)C]PIB parametric maps were also found to be significantly correlated (R(2)>0.50) to mRNA expressions of the most represented proteins in the myelin sheath. On the contrary, no correlation was found between [(11)C]PIB imaging and nonmyelin-associated proteins.