Image-derived input function for brain PET studies: many challenges and few opportunities

Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function

Cerebral blood flow (CBF) can be measured with dynamic positron emission tomography (PET) of 15O-labeled water by using tracer kinetic modelling. However, for quantification of regional CBF, an arterial input function (AIF), obtained from arterial blood sampling, is required. In this work we evaluated a novel, non-invasive approach for input function prediction based on machine learning (MLIF), against AIF for CBF PET measurements in human subjects.Twenty-five subjects underwent two 10 min dynamic 15O-water brain PET scans with continuous arterial blood sampling, before (baseline) and following acetazolamide medication. Three different image-derived time-activity curves were automatically segmented from the carotid arteries and used as input into a Gaussian process-based AIF prediction model, considering both baseline and acetazolamide scans as training data. The MLIF approach was evaluated by comparing AIF and MLIF curves, as well as whole-brain grey matter CBF values estimated by kinetic modelling derived with either AIF or MLIF.The results showed that AIF and MLIF curves were similar and that corresponding CBF values were highly correlated and successfully differentiated before and after acetazolamide medication. In conclusion, our non-invasive MLIF method shows potential to replace the AIF obtained from blood sampling for CBF measurements using 15O-water PET and kinetic modelling.

Minimally invasive quantification of cerebral P2X7R occupancy using dynamic [18F]JNJ-64413739 PET and MRA-driven image derived input function

[¹⁸F]JNJ-64413739 has been evaluated as PET-ligand for in vivo quantification of purinergic receptor subtype 7 receptor (P2X7R) using Logan graphical analysis with a metabolite-corrected arterial plasma input function. In the context of a P2X7R PET dose occupancy study, we evaluated a minimally invasive approach by limiting arterial sampling to baseline conditions. Meanwhile, post dose distribution volumes (V_T) under blocking conditions were estimated by combining baseline blood to plasma ratios and metabolite fractions with an MR angiography driven image derived input function (IDIF). Regional postdose V_T,IDIF values were compared with corresponding V_T,AIF estimates using a arterial input function (AIF), in terms of absolute values, test–retest reliability and receptor occupancy. Compared to an invasive AIF approach, postdose V_T,IDIF values and corresponding receptor occupancies showed only limited bias (Bland–Altman analysis: 0.06 ± 0.27 and 3.1% ± 6.4%) while demonstrating a high correlation (Spearman ρ = 0.78 and ρ = 0.98 respectively). In terms of test–retest reliability, regional intraclass correlation coefficients were 0.98 ± 0.02 for V_T,IDIF compared to 0.97 ± 0.01 for V_T,AIF. These results confirmed that a postdose IDIF, guided by MR angiography and using baseline blood and metabolite data, can be considered for accurate [¹⁸F]JNJ-64413739 PET quantification in a repeated PET study design, thus avoiding multiple invasive arterial sampling and increasing dosing flexibility.

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.

In vitro and In vivo Assessment of Suitable Reference Region and Kinetic Modelling for the mGluR1 Radioligand [11C]ITDM in Mice

PURPOSE

This study aimed at investigating binding specificity, suitability of reference region-based kinetic modelling, and pharmacokinetics of the metabotropic glutamate receptor 1 (mGluR1) radioligand [¹¹C]ITDM in mice.

PROCEDURES

We performed in vivo blocking as well as displacement of [¹¹C]ITDM during positron emission tomography (PET) imaging using the specific mGluR1 antagonist YM-202074. Additionally, we assessed in vitro blocking of [³H]ITDM at two different doses of YM-202074. As an alternative to reference region models, we validated the use of a noninvasive image-derived input function (IDIF) compared to an arterial input function measured with an invasive arteriovenous (AV) shunt using a population-based curve for radiometabolite correction and characterized the pharmacokinetic modelling of [¹¹C]ITDM in the mouse brain. Finally, we also assessed semi-quantitative approaches.

RESULTS

In vivo blocking with YM-202074 resulted in a decreased [¹¹C]ITDM binding, ranging from - 35.8 ± 8.0 % in pons to - 65.8 ± 3.0 % in thalamus. Displacement was also markedly observed in all tested regions. In addition, in vitro [³H]ITDM binding could be blocked in a dose-dependent manner. The volume of distribution (V_T) based on the noninvasive IDIF (V_{T (IDIF)}) showed excellent agreement with the V_T values based on the metabolite-corrected plasma input function regardless of the metabolite correction (r² > 0.943, p < 0.0001). Two-tissue compartmental model (2TCM) was found to be the preferred model and showed optimal agreement with Logan plot (r² > 0.960, p < 0.0001). A minimum scan duration of 80 min was required for proper parameter estimation. SUV was not reliable (r² = 0.379, p = 0.0011), unlike the SUV ratio to the SUV of the input function, which showed to be a valid approach.

CONCLUSIONS

No suitable reference region could be identified for [¹¹C]ITDM as strongly supported by in vivo and in vitro evidence of specific binding in all brain regions. However, by applying appropriate kinetic models, [¹¹C]ITDM PET imaging represents a promising tool to visualize mGluR1 in the mouse brain.

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 (V_T) in 11 regions across the brain (r = 0.95, p<0.001). IDIF+venous V_T 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 V_T 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 V_T (mean bias -20.9%), and produced V_T 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 V_T.

Measurement of PET Quantitative Bias In Vivo

Quantitative imaging biomarkers are widely used in PET for both research and clinical applications, yet bias in the underlying image data has not been well characterized. In the absence of a readily available reference standard for in vivo quantification, bias in PET images has been inferred using physical phantoms, even though arrangements of this sort provide only a poor approximation of the imaging environment in real patient examinations. In this study, we used data acquired from patient volunteers to assess PET quantitative bias in vivo. Image-derived radioactivity concentrations in the descending aorta were compared with blood samples counted on a calibrated γ-counter. Methods: Ten patients with prostate cancer were studied using 2-(3-(1-carboxy-5-[(6-¹⁸F-fluoro-pyridine-3-carbonyl)-amino]-pentyl)-ureido)-pentanedioic acid PET/CT. For each patient, 3 whole-body PET/CT image series were acquired after a single administration of the radiotracer: shortly after injection as well as approximately 1 and 4 h later. Venous blood samples were obtained at 8 time points over an 8-h period, and whole blood was counted on a NaI γ-counter. A 10-mm-diameter, 20-mm-long cylindric volume of interest was positioned in the descending thoracic aorta to estimate the PET-derived radioactivity concentration in blood. A triexponential function was fit to the γ-counter blood data and used to estimate the radioactivity concentration at the time of each PET acquisition. Results: The PET-derived and γ-counter-derived radioactivity concentrations were linearly related, with an R ² of 0.985, over a range of relevant radioactivity concentrations. The mean difference between the PET and γ-counter data was 4.8% ± 8.6%, with the PET measurements tending to be greater. Conclusion: Human image data acquired on a conventional whole-body PET/CT system with a typical clinical protocol differed by an average of around 5% from blood samples counted on a calibrated γ-counter. This bias may be partly attributable to residual uncorrected scatter or attenuation correction error. These data offer an opportunity for the assessment of PET bias in vivo and provide additional support for the use of quantitative imaging biomarkers.

Kinetic analysis and optimisation of 18F-rhPSMA-7.3 PET imaging of prostate cancer

Purpose

This phase 1 open-label study evaluated the uptake kinetics of a novel theranostic PET radiopharmaceutical, ¹⁸F-rhPSMA-7.3, to optimise its use for imaging of prostate cancer.

Methods

Nine men, three with high-risk localised prostate cancer, three with treatment-naïve hormone-sensitive metastatic disease and three with castration-resistant metastatic disease, underwent dynamic 45-min PET scanning of a target area immediately post-injection of 300 MBq ¹⁸F-rhPSMA-7.3, followed by two whole-body PET/CT scans acquired from 60 and 90 min post-injection. Volumes of interest (VoIs) corresponding to prostate cancer lesions and reference tissues were recorded. Standardised uptake values (SUV) and lesion-to-reference ratios were calculated for 3 time frames: 35–45, 60–88 and 90–118 min. Net influx rates (K_i) were calculated using Patlak plots.

Results

Altogether, 44 lesions from the target area were identified. Optimal visual lesion detection started 60 min post-injection. The ¹⁸F-rhPSMA-7.3 signal from prostate cancer lesions increased over time, while reference tissue signals remained stable or decreased. The mean (SD) SUV (g/mL) at the 3 time frames were 8.4 (5.6), 10.1 (7) and 10.6 (7.5), respectively, for prostate lesions, 11.2 (4.3), 13 (4.8) and 14 (5.2) for lymph node metastases, and 4.6 (2.6), 5.7 (3.1) and 6.4 (3.5) for bone metastases. The mean (SD) lesion-to-reference ratio increases from the earliest to the 2 later time frames were 40% (10) and 59% (9), respectively, for the prostate, 65% (27) and 125% (47) for metastatic lymph nodes and 25% (19) and 32% (30) for bone lesions. Patlak plots from lesion VoIs signified almost irreversible uptake kinetics. K_i, SUV and lesion-to-reference ratio estimates showed good agreement.

Conclusion

¹⁸F-rhPSMA-7.3 uptake in prostate cancer lesions was high. Lesion-to-background ratios increased over time, with optimal visual detection starting from 60 min post-injection. Thus, ¹⁸F-rhPSMA-7.3 emerges as a very promising PET radiopharmaceutical for diagnostic imaging of prostate cancer.

Trial Registration

NCT03995888 (24 June 2019).

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05346-8.

Region- and voxel-based quantification in human brain of [18F]LSN3316612, a radioligand for O-GlcNAcase

Background

Previous studies found that the positron emission tomography (PET) radioligand [¹⁸F]LSN3316612 accurately quantified O-GlcNAcase in human brain using a two-tissue compartment model (2TCM). This study sought to assess kinetic model(s) as an alternative to 2TCM for quantifying [¹⁸F]LSN3316612 binding, particularly in order to generate good-quality parametric images.

Methods

The current study reanalyzed data from a previous study of 10 healthy volunteers who underwent both test and retest PET scans with [¹⁸F]LSN3316612. Kinetic analysis was performed at the region level with 2TCM using 120-min PET data and arterial input function, which was considered as the gold standard. Quantification was then obtained at both the region and voxel levels using Logan plot, Ichise's multilinear analysis-1 (MA1), standard spectral analysis (SA), and impulse response function at 120 min (IRF₁₂₀). To avoid arterial sampling, a noninvasive relative quantification (standardized uptake value ratio (SUVR)) was also tested using the corpus callosum as a pseudo-reference region. Venous samples were also assessed to see whether they could substitute for arterial ones.

Results

Logan and MA1 generated parametric images of good visual quality and their total distribution volume (V_T) values at both the region and voxel levels were strongly correlated with 2TCM-derived V_T (r = 0.96–0.99) and showed little bias (up to − 8%). SA was more weakly correlated to 2TCM-derived V_T (r = 0.93–0.98) and was more biased (~ 16%). IRF₁₂₀ showed a strong correlation with 2TCM-derived V_T (r = 0.96) but generated noisier parametric images. All techniques were comparable to 2TCM in terms of test–retest variability and reliability except IRF₁₂₀, which gave significantly worse results. Noninvasive SUVR values were not correlated with 2TCM-derived V_T, and arteriovenous equilibrium was never reached.

Conclusions

Compared to SA and IRF, Logan and MA1 are more suitable alternatives to 2TCM for quantifying [¹⁸F]LSN3316612 and generating good-quality parametric images.

Noninvasive quantification of nonhuman primate dynamic 18F-FDG PET imaging

¹⁸F-FDG uptake rate constant K_i is the main physiology parameter measured in dynamic PET studies. A model-independent graphical analysis using Patlak plot with plasma input function (PIF) is a standard approach used to estimate K_i . The PIF is the ¹⁸F-FDG time activity curve (TAC) in plasma that is obtained by serial arterial blood sampling. The purpose of the study is to evaluate a Patlak plot-based optimization approach with reduced blood samples for noninvasive quantification of dynamic ¹⁸F-FDG PET imaging. Eight 60 min rhesus monkey brain dynamic ¹⁸F-FDG PET scans with arterial blood samples were collected. The measured PIF (mPIF) was determined by arterial blood samples. TACs of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the population-based PIF (pPIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal sampling scheme with given blood sample size was determined by maximizing the correlations between the K_i estimated from pPIF and those obtained by mPIF. A leave-two-out cross-validation method was used for evaluation. The linear correlations between the K_i estimates from pPIF with optimal sampling schemes and those from mPIF were: K_i (pPIF 1 sample at 40 min) = 1.015 K_i (mPIF) - 0.000, R ² = 0.974; K_i (pPIF 2 samples at 35 and 50 min) = 1.052 K_i (mPIF) - 0.001, R ² = 0.976; K_i (pPIF 3 samples at 12, 40, and 50 min) = 1.030 K_i (mPIF) - 0.000, R ² = 0.985; and K_i (pPIF 4 samples at 10, 20, 40, and 50 min) = 1.016 K_i (mPIF)- 0.000, R ² = 0.993. As the sample size became greater or equal to 4, the K_i estimates from pPIF with the optimal protocol were almost identical to those from mPIF. The Patlak plot-based optimization approach is a reliable method to estimate PIF for noninvasive quantification of non-human primate dynamic ¹⁸F-FDG PET imaging and is potentially extendable to further translational human studies.

Quantitative PET in the 2020s: a roadmap

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

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.

GABAA Receptors in the Mongolian Gerbil: a PET Study Using [18F]Flumazenil to Determine Receptor Binding in Young and Old Animals

PURPOSE

Plastic changes in the central auditory system involving the GABAergic system accompany age-related hearing loss. Such processes can be investigated with positron emission tomography (PET) imaging using [¹⁸F]flumazenil ([¹⁸F]FMZ). Here, [¹⁸F]FMZ PET-based modeling approaches allow a simple and reliable quantification of GABA_A receptor binding capacity revealing regional differences and age-related changes.

PROCEDURES

Sixty-minute list-mode PET acquisitions were performed in 9 young (range 5-6 months) and 11 old (range 39-42 months) gerbils, starting simultaneously with the injection of [¹⁸F]FMZ via femoral vein. Non-displaceable binding potentials (BPnd) with pons as reference region were calculated for auditory cortex (AC), inferior colliculus (IC), medial geniculate body (MGB), somatosensory cortex (SC), and cerebellum (CB) using (i) a two-tissue compartment model (2TCM), (ii) the Logan plot with image-derived blood-input (Logan (BI)), (iii) a simplified reference tissue model (SRTM), and (iv) the Logan reference model (Logan (RT)). Statistical parametric mapping analysis (SPM) comparing young and old gerbils was performed using 3D parametric images for BPnd based on SRTM. Results were verified with in vitro autoradiography from five additional young gerbils. Model assessment included the Akaike information criterion (AIC). Hearing was evaluated using auditory brainstem responses.

RESULTS

BPnd differed significantly between models (p < 0.0005), showing the smallest mean difference between 2TCM as reference and SRTM as simplified procedure. SRTM revealed the lowest AIC values. Both volume of distribution (r² = 0.8793, p = 0.018) and BPnd (r² = 0.8216, p = 0.034) correlated with in vitro autoradiography data. A significant age-related decrease of receptor binding was observed in auditory (AC, IC, MGB) and other brain regions (SC and CB) (p < 0.0001, unpaired t test) being confirmed by SPM using pons as reference (p < 0.0001, uncorrected).

CONCLUSION

Imaging of GABA_A receptor binding capacity in gerbils using [¹⁸F]FMZ PET revealed SRTM as a simple and robust quantification method of GABA_A receptors. Comparison of BPnd in young and old gerbils demonstrated an age-related decrease of GABA_A receptor binding.

Feasibility of Longitudinal Brain PET with Real-Time Arterial Input Function in Rats

PURPOSE

Preclinical dynamic brain PET studies remain hampered by the limitations related to the measurement of the arterial input function (AIF). In this regard, the use of an arterial-venous shunt is a promising method for the generation of real-time AIFs, but its application in longitudinal studies is still impeded by the cumbersome surgeries and high failure rates. We studied the feasibility and reproducibility of double arterial-venous shunt strategies for conducting longitudinal PET studies with real-time AIFs in rats.

PROCEDURES

We studied the feasibility of double arterial-venous shunts in rats in the right/left inguinal region and evaluated inter-animal and intra-animal AIF reproducibilities. Image-derived input function (IDIF) was also obtained for comparison. Dynamic brain FDG PET studies were conducted to estimate kinetic constants and Cerebral Metabolic Rate of Glucose (CMR_glc) obtained from standard 2-tissue compartment (2TCM) and Patlak analysis.

RESULTS

We showed that longitudinal AIFs from double arterial-venous shunts can be obtained with very high success rate of the surgeries (88 %). Our results provided highly reproducible AIF measurements with low inter-animal variabilities (11 %) and intra-animal variabilities (5-10 %) that were included into the kinetic models, such that longitudinal rate constants and CMR_glc can be efficiently estimated without bias associated to the double shunt. Our results indicated that longitudinal IDIF can be also generated without bias along time but showing higher intra-animal uncertainties.

CONCLUSIONS

We have demonstrated the feasibility and high reproducibility of conducting longitudinal AIF measurements and consequently accurate kinetic modeling using arterial shunt method.

Pharmacokinetic modelling for the simultaneous assessment of perfusion and 18F-flutemetamol uptake in cerebral amyloid angiopathy using a reduced PET-MR acquisition time: Proof of concept

PURPOSE

Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease associated with perivascular β-amyloid deposition. CAA is also associated with strokes due to lobar intracerebral haemorrhage (ICH). ¹⁸F-flutemetamol amyloid ligand PET may improve the early detection of CAA. We performed pharmacokinetic modelling using both full (0-30, 90-120 min) and reduced (30 min) ¹⁸F-flutemetamol PET-MR acquisitions, to investigate regional cerebral perfusion and amyloid deposition in ICH patients.

METHODS

Dynamic¹⁸F-flutemetamol PET-MR was performed in a pilot cohort of sixteen ICH participants; eight lobar ICH cases with probable CAA and eight deep ICH patients. A model-based input function (mIF) method was developed for compartmental modelling. mIF 1-tissue (1-TC) and 2-tissue (2-TC) compartmental modelling, reference tissue models and standardized uptake value ratios were assessed in the setting of probable CAA detection.

RESULTS

The mIF 1-TC model detected perfusion deficits and ¹⁸F-flutemetamol uptake in cases with probable CAA versus deep ICH patients, in both full and reduced PET acquisition time (all P < 0.05). In the reduced PET acquisition, mIF 1-TC modelling reached the highest sensitivity and specificity in detecting perfusion deficits (0.87, 0.77) and ¹⁸F-flutemetamol uptake (0.83, 0.71) in cases with probable CAA. Overall, 52 and 48 out of the 64 brain areas with ¹⁸F-flutemetamol-determined amyloid deposition showed reduced perfusion for 1-TC and 2-TC models, respectively.

CONCLUSION

Pharmacokinetic (1-TC) modelling using a 30 min PET-MR time frame detected impaired haemodynamics and increased amyloid load in probable CAA. Perfusion deficits and amyloid burden co-existed within cases with CAA, demonstrating a distinct imaging pattern which may have merit in elucidating the pathophysiological process of CAA.

PET Imaging of Tumor Perfusion: A Potential Cancer Biomarker?

Perfusion, as measured by imaging, is considered a standard of care biomarker for the evaluation of many tumors. Measurements of tumor perfusion may be used in a number of ways, including improving the visual detection of lesions, differentiating malignant from benign findings, assessing aggressiveness of tumors, identifying ischemia and by extension hypoxia within tumors, and assessing treatment response. While most clinical perfusion imaging is currently performed with CT or MR, a number of methods for PET imaging of tumor perfusion have been described. The inert PET radiotracer 15O-water PET represents the recognized gold standard for absolute quantification of tissue perfusion in both normal tissue and a variety of pathological conditions including cancer. Other cancer PET perfusion imaging strategies include the use of radiotracers with high first-pass uptake, analogous to those used in cardiac perfusion PET. This strategy produces more visually pleasing high-contrast images that provide relative rather than absolute perfusion quantification. Lastly, multiple timepoint imaging of PET tracers such as 18F-FDG, are not specifically optimized for perfusion, but have advantages related to availability, convenience, and reimbursement. Multiple obstacles have thus far blocked the routine use of PET imaging for tumor perfusion, including tracer production and distribution, image processing, patient body coverage, clinical validation, regulatory approval and reimbursement, and finally feasible clinical workflows. Fortunately, these obstacles are being overcome, especially within larger imaging centers, opening the door for PET imaging of tumor perfusion to become standard clinical practice. In the foreseeable future, it is possible that whole-body PET perfusion imaging with 15O-water will be able to be performed in a single imaging session concurrent with standard PET imaging techniques such as 18F-FDG-PET. This approach could establish an efficient clinical workflow. The resultant ability to measure absolute tumor blood flow in combination with glycolysis will provide important complementary information to inform prognosis and clinical decisions.

PET Parametric Imaging: Past, Present, and Future

Positron emission tomography (PET) is actively used in a diverse range of applications in oncology, cardiology, and neurology. The use of PET in the clinical setting focuses on static (single time frame) imaging at a specific time-point post radiotracer injection and is typically considered as semi-quantitative; e.g. standardized uptake value (SUV) measures. In contrast, dynamic PET imaging requires increased acquisition times but has the advantage that it measures the full spatiotemporal distribution of a radiotracer and, in combination with tracer kinetic modeling, enables the generation of multiparametric images that more directly quantify underlying biological parameters of interest, such as blood flow, glucose metabolism, and receptor binding. Parametric images have the potential for improved detection and for more accurate and earlier therapeutic response assessment. Parametric imaging with dynamic PET has witnessed extensive research in the past four decades. In this paper, we provide an overview of past and present activities and discuss emerging opportunities in the field of parametric imaging for the future.

Human Positron Emission Tomography Neuroimaging

Neuroimaging with positron emission tomography (PET) is the most powerful tool for understanding pharmacology, neurochemistry, and pathology in the living human brain. This technology combines high-resolution scanners to measure radioactivity throughout the human body with specific, targeted radioactive molecules, which allow measurements of a myriad of biological processes in vivo. While PET brain imaging has been active for almost 40 years, the pace of development for neuroimaging tools, known as radiotracers, and for quantitative analytical techniques has increased dramatically over the past decade. Accordingly, the fundamental questions that can be addressed with PET have expanded in basic neurobiology, psychiatry, neurology, and related therapeutic development. In this review, we introduce the field of human PET neuroimaging, some of its conceptual underpinnings, and motivating questions. We highlight some of the more recent advances in radiotracer development, quantitative modeling, and applications of PET to the study of the human brain.

Validation and noninvasive kinetic modeling of [11C]UCB-J PET imaging in mice

Synaptic pathology is associated with several brain disorders, thus positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) using the radioligand [¹¹C]UCB-J may provide a tool to measure synaptic alterations. Given the pivotal role of mouse models in understanding neuropsychiatric and neurodegenerative disorders, this study aims to validate and characterize [¹¹C]UCB-J in mice. We performed a blocking study to verify the specificity of the radiotracer to SV2A, examined kinetic models using an image-derived input function (IDIF) for quantification of the radiotracer, and investigated the in vivo metabolism. Regional TACs during baseline showed rapid uptake of [¹¹C]UCB-J into the brain. Pretreatment with levetiracetam confirmed target engagement in a dose-dependent manner. V_{T (IDIF)} values estimated with one- and two-tissue compartmental models (1TCM and 2TCM) were highly comparable (r=0.999, p < 0.0001), with 1TCM performing better than 2TCM for K_{1 (IDIF)}. A scan duration of 60 min was sufficient for reliable V_{T (IDIF)} and K_{1 (IDIF)} estimations. In vivo metabolism of [¹¹C]UCB-J was relatively rapid, with a parent fraction of 22.5 ± 4.2% at 15 min p.i. In conclusion, our findings show that [¹¹C]UCB-J selectively binds to SV2A with optimal kinetics in the mouse representing a promising tool to noninvasively quantify synaptic density in comparative or therapeutic studies in neuropsychiatric and neurodegenerative disorder models.

Quantification of [18F]UCB-H Binding in the Rat Brain: From Kinetic Modelling to Standardised Uptake Value

PURPOSE

[¹⁸F]UCB-H is a specific positron emission tomography (PET) biomarker for the Synaptic Vesicle protein 2A (SV2A), the binding site of the antiepileptic drug levetiracetam. With a view to optimising acquisition time and simplifying data analysis with this radiotracer, we compared two parameters: the distribution volume (Vt) obtained from Logan graphical analysis using a Population-Based Input Function, and the Standardised Uptake Value (SUV).

PROCEDURES

Twelve Sprague Dawley male rats, pre-treated with three different doses of levetiracetam were employed to develop the methodology. Three additional kainic acid (KA) treated rats (temporal lobe epilepsy model) were also used to test the procedure. Image analyses focused on: (i) length of the dynamic acquisition (90 versus 60 min); (ii) correlations between Vt and SUV over 20-min consecutive time-frames; (iii) and (iv) evaluation of differences between groups using the Vt and the SUV; and (v) preliminary evaluation of the methodology in the KA epilepsy model.

RESULTS

A large correlation between the Vt issued from 60 to 90-min acquisitions was observed. Further analyses highlighted a large correlation (r > 0.8) between the Vt and the SUV. Equivalent differences between groups were detected for both parameters, especially in the 20-40 and 40-60-min time-frames. The same results were also obtained with the epilepsy model.

CONCLUSIONS

Our results enable the acquisition setting to be changed from a 90-min dynamic to a 20-min static PET acquisition. According to a better image quality, the 20-40-min time-frame appears optimal. Due to its equivalence to the Vt, the SUV parameter can be considered in order to quantify [¹⁸F]UCB-H uptake in the rat brain. This work, therefore, establishes a starting point for the simplification of SV2A in vivo quantification with [¹⁸F]UCB-H, and represents a step forward to the clinical application of this PET radiotracer.

Quantification of Positron Emission Tomography Data Using Simultaneous Estimation of the Input Function: Validation with Venous Blood and Replication of Clinical Studies

PURPOSE

To determine if one venous blood sample can substitute full arterial sampling in quantitative modeling for multiple positron emission tomography (PET) radiotracers using simultaneous estimation of the input function (SIME).

PROCEDURES

Participants underwent PET imaging with [¹¹C]ABP688, [¹¹C]CUMI-101, and [¹¹C]DASB. Full arterial sampling and additional venous blood draws were performed for quantification with the arterial input function (AIF) and SIME using one arterial or venous (vSIME) sample.

RESULTS

Venous and arterial metabolite-corrected plasma activities were within 6 % of each other at varying time points. vSIME- and AIF-derived outcome measures were in good agreement, with optimal sampling times of 12 min ([¹¹C]ABP688), 90 min ([¹¹C]CUMI-101), and 100 min ([¹¹C]DASB). Simulation-based power analyses revealed that SIME required fewer subjects than the AIF method to achieve statistical power, with significant reductions for [¹¹C]CUMI-101 and [¹¹C]DASB with vSIME. Replication of previous findings and test-retest analyses bolstered the simulation analyses.

CONCLUSIONS

We demonstrate the feasibility of AIF recovery using SIME with one venous sample for [¹¹C]ABP688, [¹¹C]CUMI-101, and [¹¹C]DASB. This method simplifies PET acquisition while allowing for fully quantitative modeling, although some variability and bias are present with respect to AIF-based quantification, which may depend on the accuracy of the single venous blood measurement.

Simulation study of a coincidence detection system for non-invasive determination of arterial blood time-activity curve measurements

Background

Arterial sampling in PET studies for the purposes of kinetic modeling remains an invasive, time-intensive, and expensive procedure. Alternatives to derive the blood time-activity curve (BTAC) non-invasively are either reliant on large vessels in the field of view or are laborious to implement and analyze as well as being prone to many processing errors. An alternative method is proposed in this work by the simulation of a non-invasive coincidence detection unit.

Results

We utilized GATE simulations of a human forearm phantom with a blood flow model, as well as a model for dynamic radioactive bolus activity concentration based on clinical measurements. A fixed configuration of 14 and, also separately, 8 detectors were employed around the phantom, and simulations were performed to investigate signal detection parameters. Bismuth germanate (BGO) crystals proved to show the highest count rate capability and sensitivity to a simulated BTAC with a maximum coincidence rate of 575 cps. Repeatable location of the blood vessels in the forearm allowed a half-ring design with only 8 detectors. Using this configuration, maximum coincident rates of 250 cps and 42 cps were achieved with simulation of activity concentration determined from ¹⁵O and ¹⁸F arterial blood sampling. NECR simulated in a water phantom at 3 different vertical positions inside the 8-detector system (Y = − 1 cm, Y = − 2 cm, and Y = −3 cm) was 8360 cps, 13,041 cps, and 20,476 cps at an activity of 3.5 MBq. Addition of extra axial detection rings to the half-ring configuration provided increases in system sensitivity by a factor of approximately 10.

Conclusions

Initial simulations demonstrated that the configuration of a single half-ring 8 detector of monolithic BGO crystals could describe the simulated BTAC in a clinically relevant forearm phantom with good signal properties, and an increased number of axial detection rings can provide increased sensitivity of the system. The system would find use in the derivation of the BTAC for use in the application of kinetic models without physical arterial sampling or reliance on image-based techniques.

Total Body PET: Why, How, What for?

PET instruments are now available with a long axial field-of-view (LAFOV) to enable imaging the total-body, or at least head and torso, simultaneously and without bed translation. This has two major benefits, a dramatic increase in system sensitivity and the ability to measure kinetics with wider axial coverage so as to include multiple organs. This manuscript presents a review of the technology leading up to the introduction of these new instruments, and explains the benefits of a LAFOV PET-CT instrument. To date there are two platforms developed for TB-PET, an outcome of the EXPLORER Consortium of the University of California at Davis (UC Davis) and the University of Pennsylvania (Penn). The uEXPLORER at UC Davis has an AFOV of 194 cm and was developed by United Imaging Healthcare. The PennPET EXPLORER was developed at Penn and is based on the digital detector from Philips Healthcare. This multi-ring system is scalable and has been tested with 3 rings but is now being expanded to 6 rings for 140 cm. Initial human studies with both EXPLORER systems have demonstrated the successful implementation and benefits of LAFOV scanners for both clinical and research applications. Examples of such studies are described in this manuscript.

PennPET Explorer: Human Imaging on a Whole-Body Imager

The PennPET Explorer, a prototype whole-body imager currently operating with a 64-cm axial field of view, can image the major body organs simultaneously with higher sensitivity than that of commercial devices. We report here the initial human imaging studies on the PennPET Explorer, with each study designed to test specific capabilities of the device. Methods: Healthy subjects were imaged with FDG on the PennPET Explorer. Subsequently, clinical subjects with disease were imaged with ¹⁸F-FDG and ⁶⁸Ga-DOTATATE, and research subjects were imaged with experimental radiotracers. Results: We demonstrated the ability to scan for a shorter duration or, alternatively, with less activity, without a compromise in image quality. Delayed images, up to 10 half-lives with ¹⁸F-FDG, revealed biologic insight and supported the ability to track biologic processes over time. In a clinical subject, the PennPET Explorer better delineated the extent of ¹⁸F-FDG–avid disease. In a second clinical study with ⁶⁸Ga-DOTATATE, we demonstrated comparable diagnostic image quality between the PennPET scan and the clinical scan, but with one fifth the activity. Dynamic imaging studies captured relatively noise-free input functions for kinetic modeling approaches. Additional studies with experimental research radiotracers illustrated the benefits from the combination of large axial coverage and high sensitivity. Conclusion: These studies provided a proof of concept for many proposed applications for a PET scanner with a long axial field of view.

Substitution of venous for arterial blood sampling in the determination of regional rates of cerebral protein synthesis with L-[1-11C]leucine PET: A validation study

We developed and validated a method to estimate input functions for determination of regional rates of cerebral protein synthesis (rCPS) with L-[1-¹¹C]leucine PET without arterial sampling. The method is based on a population-derived input function (PDIF) approach, with venous samples for calibration. Population input functions were constructed from arterial blood data measured in 25 healthy 18-24-year-old males who underwent L-[1-¹¹C]leucine PET scans while awake. To validate the approach, three additional groups of 18-27-year-old males underwent L-[1-¹¹C]leucine PET scans with both arterial and venous blood sampling: 13 awake healthy volunteers, 10 sedated healthy volunteers, and 5 sedated subjects with fragile X syndrome. Rate constants of the L-[1-¹¹C]leucine kinetic model were estimated voxel-wise with measured arterial input functions and with venous-calibrated PDIFs. Venous plasma leucine measurements were used with venous-calibrated PDIFs for rCPS computation. rCPS determined with PDIFs calibrated with 30-60 min venous samples had small errors (RMSE: 4-9%), and no statistically significant differences were found in any group when compared to rCPS determined with arterial input functions. We conclude that in young adult males, PDIFs calibrated with 30-60 min venous samples can be used in place of arterial input functions for determination of rCPS with L-[1-¹¹C]leucine PET.

Towards quantitative [18F]FDG-PET/MRI of the brain: Automated MR-driven calculation of an image-derived input function for the non-invasive determination of cerebral glucose metabolic rates

Absolute quantification of PET brain imaging requires the measurement of an arterial input function (AIF), typically obtained invasively via an arterial cannulation. We present an approach to automatically calculate an image-derived input function (IDIF) and cerebral metabolic rates of glucose (CMRGlc) from the [18F]FDG PET data using an integrated PET/MRI system. Ten healthy controls underwent test-retest dynamic [18F]FDG-PET/MRI examinations. The imaging protocol consisted of a 60-min PET list-mode acquisition together with a time-of-flight MR angiography scan for segmenting the carotid arteries and intermittent MR navigators to monitor subject movement. AIFs were collected as the reference standard. Attenuation correction was performed using a separate low-dose CT scan. Assessment of the percentage difference between area-under-the-curve of IDIF and AIF yielded values within ±5%. Similar test-retest variability was seen between AIFs (9 ± 8) % and the IDIFs (9 ± 7) %. Absolute percentage difference between CMRGlc values obtained from AIF and IDIF across all examinations and selected brain regions was 3.2% (interquartile range: (2.4-4.3) %, maximum < 10%). High test-retest intravariability was observed between CMRGlc values obtained from AIF (14%) and IDIF (17%). The proposed approach provides an IDIF, which can be effectively used in lieu of AIF.

Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC)

OBJECTIVE

To obtain attenuation-corrected PET images directly from non-attenuation-corrected images using a convolutional encoder-decoder network.

METHODS

Brain PET images from 129 patients were evaluated. The network was designed to map non-attenuation-corrected (NAC) images to pixel-wise continuously valued measured attenuation-corrected (MAC) PET images via an encoder-decoder architecture. Image quality was evaluated using various evaluation metrics. Image quantification was assessed for 19 radiomic features in 83 brain regions as delineated using the Hammersmith atlas (n30r83). Reliability of measurements was determined using pixel-wise relative errors (RE; %) for radiomic feature values in reference MAC PET images.

RESULTS

Peak signal-to-noise ratio (PSNR) and structural similarity index metric (SSIM) values were 39.2 ± 3.65 and 0.989 ± 0.006 for the external validation set, respectively. RE (%) of SUV_mean was - 0.10 ± 2.14 for all regions, and only 3 of 83 regions depicted significant differences. However, the mean RE (%) of this region was 0.02 (range, - 0.83 to 1.18). SUV_max had mean RE (%) of - 3.87 ± 2.84 for all brain regions, and 17 regions in the brain depicted significant differences with respect to MAC images with a mean RE of - 3.99 ± 2.11 (range, - 8.46 to 0.76). Homogeneity amongst Haralick-based radiomic features had the highest number (20) of regions with significant differences with a mean RE (%) of 7.22 ± 2.99.

CONCLUSIONS

Direct AC of PET images using deep convolutional encoder-decoder networks is a promising technique for brain PET images. The proposed deep learning method shows significant potential for emission-based AC in PET images with applications in PET/MRI and dedicated brain PET scanners.

KEY POINTS

• We demonstrate direct emission-based attenuation correction of PET images without using anatomical information. • We performed radiomics analysis of 83 brain regions to show robustness of direct attenuation correction of PET images. • Deep learning methods have significant promise for emission-based attenuation correction in PET images with potential applications in PET/MRI and dedicated brain PET scanners.

Towards Improved Pharmacokinetic Models for the Analysis of Transporter-Mediated Hepatic Disposition of Drug Molecules with Positron Emission Tomography

Positron emission tomography (PET) imaging with radiolabeled drugs holds great promise to assess the influence of membrane transporters on hepatobiliary clearance of drugs. To exploit the full potential of PET, quantitative pharmacokinetic models are required. In this study, we evaluated the suitability of different compartment models to describe the hepatic disposition of [11C]erlotinib as a small-molecule model drug which undergoes transporter-mediated hepatobiliary excretion. We analyzed two different, previously published data sets in healthy volunteers, in which a baseline [11C]erlotinib PET scan was followed by a second PET scan either after oral intake of unlabeled erlotinib (300 mg) or after intravenous infusion of the prototypical organic anion-transporting polypeptide inhibitor rifampicin (600 mg). We assessed a three-compartment (3C) and a four-compartment (4C) model, in which either a sampled arterial blood input function or a mathematically derived dual input function (DIF), which takes the contribution of the portal vein to the liver blood supply into account, was used. Both models provided acceptable fits of the observed PET data in the liver and extrahepatic bile duct and gall bladder. Changes in model outcome parameters between scans were consistent with the involvement of basolateral hepatocyte uptake and canalicular efflux transporters in the hepatobiliary clearance of [11C]erlotinib. Our results demonstrated that inclusion of a DIF did not lead to substantial improvements in model fits. The models developed in this work represent a step forward in applying PET as a tool to assess the impact of hepatic transporters on drug disposition and their involvement in drug-drug interactions.

No significant difference found in PET/MRI CBF values reconstructed with CT-atlas-based and ZTE MR attenuation correction

Background

Accurate attenuation correction (AC) is one of the most important issues to be addressed in quantitative brain PET/MRI imaging. Atlas-based MRI AC (AB-MRAC), one of the representative MRAC methods, has been used to estimate the skull attenuation in brain scans. The zero echo time (ZTE) pulse sequence is also expected to provide a better MRAC estimation in brain PET scans. The difference in quantitative measurements of cerebral blood flow (CBF) using H₂¹⁵O-PET/MRI was compared between the two MRAC methods, AB and ZTE.

Method

Twelve patients with cerebrovascular disease (4 males, 43.2 ± 11.7 years) underwent H₂¹⁵O-PET/MRI studies with a 3-min PET scan and MRI scans including the ZTE sequence. Eleven of them were also studied under the conditions of baseline and 10 min after acetazolamide administration, and 2 of them were followed up after several months interval. A total of 25 PET images were reconstructed as dynamic data using 2 sets of reconstruction parameters to obtain the image-derived input function (IDIF), the time-activity curves of the major cerebral artery extracted from images, and CBF images. The CBF images from AB- and ZTE-MRAC were then compared for global and regional differences.

Results

The mean differences of IDIF curves at each point obtained from AB- and ZTE-MRAC dynamic data were less than 5%, and the differences in time-activity curves were very small. The means of CBF from AB- and ZTE-MRAC reconstructions calculated using each IDIF showed differences of less than 5% for all cortical regions. CBF images from AB-MRAC tended to show greater values in the parietal region and smaller values in the skull base region.

Conclusion

The CBF images from AB- and ZTE-MRAC reconstruction showed no significant differences in regional values, although the parietal region tended to show greater values in AB-MRAC reconstruction. Quantitative values in the skull base region were very close, and almost the same IDIFs were obtained.

Automatic Extraction of a Reference Region for the Noninvasive Quantification of Translocator Protein in Brain Using 11C-PBR28

Brain inflammation is associated with various types of neurodegenerative diseases, including Alzheimer disease (AD). Quantifying inflammation with PET is a challenging and invasive procedure, especially in frail patients, because it requires blood sampling from an arterial catheter. A widely used alternative to arterial sampling is a supervised clustering algorithm (SVCA), which identifies the voxels with minimal specific binding in the PET images, thus extracting a reference region for noninvasive kinetic modeling. Methods: We tested this algorithm on a large population of subjects injected with the translocator protein radioligand ¹¹C-PBR28 and compared the kinetic modeling results obtained with the gold standard of arterial input function (V _T/f _p) with those obtained by SVCA (distribution volume ratio [DVR] with Logan plot). The study comprised 57 participants (21 healthy controls, 11 mild cognitive impairment patients, and 25 AD patients). Results: We found that V _T/f _p was greater in AD patients than in controls in the inferior parietal, combined middle and inferior temporal, and entorhinal cortices. SVCA-DVR identified increased binding in the same regions and in an additional one, the parahippocampal region. We noticed however that the average amplitude of the reference curve obtained from subjects with genetic high-affinity binding for ¹¹C-PBR28 was significantly larger than that from subjects with moderate affinity. This suggests that the reference curve extracted by SVCA was contaminated by specific binding. Conclusion: SVCA allows the noninvasive quantification of inflammatory biomarker translocator protein measured with ¹¹C-PBR28 but without the need of arterial sampling. Although the reference curves were contaminated with specific binding, the decreased variance of the outcome measure, SVCA DVR, allowed for an apparent greater sensitivity to detect regional abnormalities in brains of patients with AD.

Hybrid PET/MR Kernelised Expectation Maximisation Reconstruction for Improved Image-Derived Estimation of the Input Function from the Aorta of Rabbits

Positron emission tomography (PET) provides simple noninvasive imaging biomarkers for multiple human diseases which can be used to produce quantitative information from single static images or to monitor dynamic processes. Such kinetic studies often require the tracer input function (IF) to be measured but, in contrast to direct blood sampling, the image-derived input function (IDIF) provides a noninvasive alternative technique to estimate the IF. Accurate estimation can, in general, be challenging due to the partial volume effect (PVE), which is particularly important in preclinical work on small animals. The recently proposed hybrid kernelised ordered subsets expectation maximisation (HKEM) method has been shown to improve accuracy and contrast across a range of different datasets and count levels and can be used on PET/MR or PET/CT data. In this work, we apply the method with the purpose of providing accurate estimates of the aorta IDIF for rabbit PET studies. In addition, we proposed a method for the extraction of the aorta region of interest (ROI) using the MR and the HKEM image, to minimise the PVE within the rabbit aortic region-a method which can be directly transferred to the clinical setting. A realistic simulation study was performed with ten independent noise realisations while two, real data, rabbit datasets, acquired with the Biograph Siemens mMR PET/MR scanner, were also considered. For reference and comparison, the data were reconstructed using OSEM, OSEM with Gaussian postfilter and KEM, as well as HKEM. The results across the simulated datasets and different time frames show reduced PVE and accurate IDIF values for the proposed method, with 5% average bias (0.8% minimum and 16% maximum bias). Consistent results were obtained with the real datasets. The results of this study demonstrate that HKEM can be used to accurately estimate the IDIF in preclinical PET/MR studies, such as rabbit mMR data, as well as in clinical human studies. The proposed algorithm is made available as part of an open software library, and it can be used equally successfully on human or animal data acquired from a variety of PET/MR or PET/CT scanners.

Semi-quantitative cerebral blood flow parameters derived from non-invasive [15O]H2O PET studies

Quantification of regional cerebral blood flow (CBF) using [¹⁵O]H₂O positron emission tomography (PET) requires the use of an arterial input function. Arterial sampling, however, is not always possible, for example in ill-conditioned or paediatric patients. Therefore, it is of interest to explore the use of non-invasive methods for the quantification of CBF. For validation of non-invasive methods, test-retest normal and hypercapnia data from 15 healthy volunteers were used. For each subject, the data consisted of up to five dynamic [¹⁵O]H₂O brain PET studies of 10 min and including arterial sampling. A measure of CBF was estimated using several non-invasive methods earlier reported in literature. In addition, various parameters were derived from the time-activity curve (TAC). Performance of these methods was assessed by comparison with full kinetic analysis using correlation and agreement analysis. The analysis was repeated with normalization to the whole brain grey matter value, providing relative CBF distributions. A reliable, absolute quantitative estimate of CBF could not be obtained with the reported non-invasive methods. Relative (normalized) CBF was best estimated using the double integration method.

Feasibility and robustness of dynamic 18F-FET PET based tracer kinetic models applied to patients with recurrent high-grade glioma prior to carbon ion irradiation

The aim of this study was to analyze the robustness and diagnostic value of different compartment models for dynamic 18F-FET PET in recurrent high-grade glioma (HGG). Dynamic 18F-FET PET data of patients with recurrent WHO grade III (n:7) and WHO grade IV (n: 9) tumors undergoing re-irradiation with carbon ions were analyzed by voxelwise fitting of the time-activity curves with a simplified and an extended one-tissue compartment model (1TCM) and a two-tissue compartment model (2TCM), respectively. A simulation study was conducted to assess robustness and precision of the 2TCM. Parameter maps showed enhanced detail on tumor substructure. Neglecting the blood volume VB in the 1TCM yields insufficient results. Parameter K1 from both 1TCM and 2TCM showed correlation with overall patient survival after carbon ion irradiation (p = 0.043 and 0.036, respectively). The 2TCM yields realistic estimates for tumor blood volume, which was found to be significantly higher in WHO IV compared to WHO III (p = 0.031). Simulations on the 2TCM showed that K1 yields good accuracy and robustness while k2 showed lowest stability of all parameters. The 1TCM provides the best compromise between parameter stability and model accuracy; however application of the 2TCM is still feasible and provides a more accurate representation of tracer-kinetics at the cost of reduced robustness. Detailed tracer kinetic analysis of 18F-FET PET with compartment models holds valuable information on tumor substructures and provides additional diagnostic and prognostic value.

Noninvasive PK11195-PET Image Analysis Techniques Can Detect Abnormal Cerebral Microglial Activation in Parkinson's Disease

BACKGROUND AND PURPOSE

Neuroinflammation has been implicated in the pathophysiology of Parkinson's disease (PD), which might be influenced by successful neuroprotective drugs. The uptake of [11 C](R)-PK11195 (PK) is often considered to be a proxy for neuroinflammation, and can be quantified using the Logan graphical method with an image-derived blood input function, or the Logan reference tissue model using automated reference region extraction. The purposes of this study were (1) to assess whether these noninvasive image analysis methods can discriminate between patients with PD and healthy volunteers (HVs), and (2) to establish the effect size that would be required to distinguish true drug-induced changes from system variance in longitudinal trials.

METHODS

The sample consisted of 20 participants with PD and 19 HVs. Two independent teams analyzed the data to compare the volume of distribution calculated using image-derived input functions (IDIFs), and binding potentials calculated using the Logan reference region model.

RESULTS

With all methods, the higher signal-to-background in patients resulted in lower variability and better repeatability than in controls. We were able to use noninvasive techniques showing significantly increased uptake of PK in multiple brain regions of participants with PD compared to HVs.

CONCLUSION

Although not necessarily reflecting absolute values, these noninvasive image analysis methods can discriminate between PD patients and HVs. We see a difference of 24% in the substantia nigra between PD and HV with a repeatability coefficient of 13%, showing that it will be possible to estimate responses in longitudinal, within subject trials of novel neuroprotective drugs.

Practical Clinical Measurement of Radiotracer Concentration in Blood: Initial Device Concept and Feasibility Testing

Kinetic analysis of PET data requires continuous measurement of radioactivity in the arterial blood throughout the acquisition time, termed the arterial input function. The arterial input function is used as an input to compartmental modeling, which can be a better predictor of disease progression than SUV measurements from static PET images. Current common methods of measuring blood concentrations include image-derived, population-based, and manual sampling. These all have challenges due to logistical and technologic issues, as well as patient burden. The aim of this study was to design, develop, and assess a device that is practical and effective for the routine measurement of β-emitting radiotracer concentration in blood without the drawbacks of current methods and for which metabolite analysis is not required. Methods: Designs that integrated a scintillating fiber and a silicon photomultiplier with a general-purpose venous access catheter for in vivo measurement were considered. Other design requirements included miniaturization, high sampling rates, and stopping power for β-particles. Preliminary prototypes were designed to test the feasibility of the concept. Phantom tests were developed to mimic human vasculature. Tests of linearity, sensitivity, signal-to-noise ratios, the impact of vein diameter, and the influence of γ-radiation were conducted. Results: Prototype sensors were constructed using 2 different diameters of polystyrene-based scintillating fibers. Fibers were custom-polished and fixed to a silicon photomultiplier. Sensor output was linear, with R ² = 0.999 over the range from 0.037 to 9.25 MBq/mL. Absolute sensitivity was approximately 450 counts per second per MBq/mL. Measured signal-to-noise ratios ranged from 1.2:1 to 3.2:1 using a blood-to-tissue concentration ratio of 1:1. Sensor output increased with vein diameter and showed no sensitivity to γ-radiation. Conclusion: In experiments with phantom models, the prototype provided accurate measurements of β-emitting radiotracer concentration. The design will be refined for in vivo testing. The ability to routinely gather blood input function data would facilitate the adoption of kinetic modeling of PET data.

TSPO-PET imaging using [18F]PBR06 is a potential translatable biomarker for treatment response in Huntington's disease: preclinical evidence with the p75NTR ligand LM11A-31

Huntington's disease (HD) is an inherited neurodegenerative disorder that has no cure. HD therapeutic development would benefit from a non-invasive translatable biomarker to track disease progression and treatment response. A potential biomarker is using positron emission tomography (PET) imaging with a translocator protein 18 kDa (TSPO) radiotracer to detect microglial activation, a key contributor to HD pathogenesis. The ability of TSPO-PET to identify microglial activation in HD mouse models, essential for a translatable biomarker, or therapeutic efficacy in HD patients or mice is unknown. Thus, this study assessed the feasibility of utilizing PET imaging with the TSPO tracer, [18F]PBR06, to detect activated microglia in two HD mouse models and to monitor response to treatment with LM11A-31, a p75NTR ligand known to reduce neuroinflammation in HD mice. [18F]PBR06-PET detected microglial activation in striatum, cortex and hippocampus of vehicle-treated R6/2 mice at a late disease stage and, notably, also in early and mid-stage symptomatic BACHD mice. After oral administration of LM11A-31 to R6/2 and BACHD mice, [18F]PBR06-PET discerned the reductive effects of LM11A-31 on neuroinflammation in both HD mouse models. [18F]PBR06-PET signal had a spatial distribution similar to ex vivo brain autoradiography and correlated with microglial activation markers: increased IBA-1 and TSPO immunostaining/blotting and striatal levels of cytokines IL-6 and TNFα. These results suggest that [18F]PBR06-PET is a useful surrogate marker of therapeutic efficacy in HD mice with high potential as a translatable biomarker for preclinical and clinical HD trials.

Comparison of two different methods of image analysis for the assessment of microglial activation in patients with multiple sclerosis using (R)-[N-methyl-carbon-11]PK11195

Chronic active multiple sclerosis (MS) lesions have a rim of activated microglia/macrophages (m/M) leading to ongoing tissue damage, and thus represent a potential treatment target. Activation of this innate immune response in MS has been visualized and quantified using PET imaging with [¹¹C]-(R)-PK11195 (PK). Accurate identification of m/M activation in chronic MS lesions requires the sensitivity to detect lower levels of activity within a small tissue volume. We assessed the ability of kinetic modeling of PK PET data to detect m/M activity in different central nervous system (CNS) tissue regions of varying sizes and in chronic MS lesions. Ten patients with MS underwent a single brain MRI and two PK PET scans 2 hours apart. Volume of interest (VOI) masks were generated for the white matter (WM), cortical gray matter (CGM), and thalamus (TH). The distribution volume (V_T) was calculated with the Logan graphical method (LGM-V_T) utilizing an image-derived input function (IDIF). The binding potential (BP_ND) was calculated with the reference Logan graphical method (RLGM) utilizing a supervised clustering algorithm (SuperPK) to determine the non-specific binding region. Masks of varying volume were created in the CNS to assess the impact of region size on the various metrics among high and low uptake regions. Chronic MS lesions were also evaluated and individual lesion masks were generated. The highest PK uptake occurred the TH and lowest within the WM, as demonstrated by the mean time activity curves. In the TH, both reference and IDIF based methods resulted in estimates that did not significantly depend on VOI size. However, in the WM, the test-retest reliability of BP_ND was significantly lower in the smallest VOI, compared to the estimates of LGM-V_T. These observations were consistent for all chronic MS lesions examined. In this study, we demonstrate that BP_ND and LGM-V_T are both reliable for quantifying m/M activation in regions of high uptake, however with blood input function LGM-V_T is preferred to assess longitudinal m/M activation in regions of relatively low uptake, such as chronic MS lesions.

Accelerated PET kinetic maps estimation by analytic fitting method

In this work, we propose and test a new approach for non-linear kinetic parameters' estimation from dynamic PET data. A technique is discussed, to derive an analytical closed-form expression of the compartmental model used for kinetic parameters' evaluation, using an auxiliary parameter set, with the aim of reducing the computational burden and speeding up the fitting of these complex mathematical expressions to noisy TACs. Two alternative algorithms based on numeric calculations are considered and compared to the new proposal. We perform a simulation study aimed at (i) assessing agreement between the proposed method and other conventional ways of implementing compartmental model fitting, and (ii) quantifying the reduction in computational time required for convergence. It results in a speed-up factor of ∼120 when compared to a fully numeric version, or ∼38, with respect to a more conventional implementation, while converging to very similar values for the estimated model parameters. The proposed method is also tested on dynamic 3D PET clinical data of four control subjects. The results obtained supported those of the simulation study, and provided input and promising perspectives for the application of the proposed technique in clinical practice.

Assessment of brain beta-amyloid deposition in transgenic mouse models of Alzheimer's disease with PET imaging agents 18F-flutemetamol and 18F-florbetaben

BACKGROUND

Although amyloid beta (Aβ) imaging is widely used for diagnosing and monitoring Alzheimer's disease in clinical fields, paralleling comparison between 18F-flutemetamol and 18F-florbetaben was rarely attempted in AD mouse model. We performed a comparison of Aβ PET images between 18F-flutemetamol and 18F-florbetaben in a recently developed APPswe mouse model, C57BL/6-Tg (NSE-hAPPsw) Korl.

RESULTS

After an injection (0.23 mCi) of 18F-flutemetamol and 18F-florbetaben at a time interval of 2-3 days, we compared group difference of SUVR and kinetic parameters between the AD (n = 7) and control (n = 7) mice, as well as between 18F-flutemetamol and 18F-florbetaben image. In addition, bio-distribution and histopathology were conducted. With visual image and VOI-based SUVR analysis, the AD group presented more prominent uptake than did the control group in both the 18F-florbetaben and 18F-flutemetamol images. With kinetic analysis, the 18F-florbetaben images showed differences in K1 and k4 between the AD and control groups, although 18F-flutemetamol images did not show significant difference. 18F-florbetaben images showed more prominent cortical uptake and matched well to the thioflavin S staining images than did the 18F-flutemetamol image. In contrast, 18F-flutemetamol images presented higher K1, k4, K1/k2 values than those of 18F-florbetaben images. Also, 18F-flutemetamol images presented prominent uptake in the bowel and bladder, consistent with higher bio-distribution in kidney, lung, blood and heart.

CONCLUSIONS

Compared with 18F-flutemetamol images, 18F-florbetaben images showed prominent visual uptake intensity, SUVR, and higher correlations with the pathology. In contrast, 18F-flutemetamol was more actively metabolized than was 18F-florbetaben (Son et al. in J Nucl Med 58(Suppl 1):S278, 2017].

Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11C-SB201745

Background

Kinetic analysis of dynamic PET data requires an accurate knowledge of available PET tracer concentration within blood plasma over time, known as the arterial input function (AIF). The gold standard method used to measure the AIF requires serial arterial blood sampling over the course of the PET scan, which is an invasive procedure and makes this method less practical in clinical settings. Traditional image-derived methods are limited to specific tracers and are not accurate if metabolites are present in the plasma.

Results

In this work, we utilise an image-derived whole blood curve measurement to reduce the computational complexity of the simultaneous estimation method (SIME), which is capable of estimating the AIF directly from tissue time activity curves (TACs). This method was applied to data obtained from a serotonin receptor study (¹¹C-SB207145) and estimated parameter results are compared to results obtained using the original SIME and gold standard AIFs derived from arterial samples. Reproducibility of the method was assessed using test-retest data. It was shown that the incorporation of image-derived information increased the accuracy of total volume of distribution (V _T) estimates, averaged across all regions, by 40% and non-displaceable binding potential (BP _ND) estimates by 16% compared to the original SIME. Particular improvements were observed in K₁ parameter estimates. BP _ND estimates, based on the proposed method and the gold standard arterial sample-derived AIF, were not significantly different (P=0.7).

Conclusions

The results of this work indicate that the proposed method with prior AIF information obtained from a partial volume corrected image-derived whole blood curve, and modelled parent fraction, has the potential to be used as an alternative non-invasive method to perform kinetic analysis of tracers with metabolite products.

Noninvasive method for measurement of cerebral blood flow using O-15 water PET/MRI with ASL correlation

PURPOSE

A noninvasive image derived input function (IDIF) method was applied to estimate arterial input function from brain H₂¹⁵O-PET/MRI images for the measurement of cerebral blood flow (CBF) because of difficulty in arterial blood sampling during PET/MRI scans. To evaluate accuracy and reproducibility of radioactivity in the internal carotid arteries (ICA) for the IDIF method, a new phantom using a skull bone was applied in the cross-calibration process between the scanner and a gamma-well counter.

METHODS

Eleven healthy volunteers (9 males, 43.9 ± 10.9y) underwent PET/MRI studies with a 3-min H₂¹⁵O-PET and several MRI scans including arterial spin labeling (ASL) perfusion MRI. PET images were reconstructed as dynamic data using two sets of reconstruction parameters, which were determined by basic assessment of radioactivity concentration reproducibility in the tubes of the phantom. The IDIF method extracted the time-activity curves of the ICA from several image slices in the PET data. CBF images were calculated using the autoradiographic (ARG) method and a one-tissue compartment model (1-TCM).

RESULTS

The global means of CBF from the ARG, 1-TCM, and ASL-MRI were 44.8 ± 4.3, 47.9 ± 5.9 and 57.9 ± 8.6 (mL/min/100 g), respectively. CBF from ASL-MRI was significantly greater compared with CBF from H₂¹⁵O-PET (P < 0.001). However, these CBF values were significantly correlated with each other in the scatter plots (P < 0.05).

CONCLUSIONS

Noninvasive measurement of CBF using H₂¹⁵O-PET/MRI and IDIF with the cross-calibration method with a skull phantom experiment provided reasonable quantitative values. The IDIF method allowed reliable estimation of arterial radioactivity concentration, which is useful for clinical application. The ASL-MRI perfusion image from the simultaneous acquisition tended to overestimate CBF.

Noninvasive quantitation of rat cerebral blood flow using 99mTc-HMPAO-assessment of input function with dynamic chest planar imaging

BACKGROUND

Cerebral blood flow (CBF) quantitation using technetium-99m hexamethylpropyleneamine oxime (^99mTc-HMPAO) generally requires assessment of input function by arterial blood sampling, which would be invasive for small animals. We therefore performed chest dynamic planar imaging, instead of arterial blood sampling, to estimate the input function and establish noninvasive quantitation method of rat CBF using the image-derived input function.

RESULTS

Integrated radioactivity concentration in the heart-blood pool on planar images (AUC_Blood-planar) was identical to that in arterial blood samples (AUC_Blood-sampling). Radioactivity concentration in the brain determined by SPECT imaging (C_Brain-SPECT) was identical to that using brain sampling (C_Brain-sampling). Noninvasively calculated CBF obtained by dividing C_Brain-SPECT by AUC_Blood-planar was well correlated with conventionally estimated CBF obtained by dividing C_Brain-sampling by AUC_Blood-sampling.

CONCLUSION

Rat CBF could be noninvasively quantitated using ^99mTc-HMPAO chest dynamic planar imaging and head SPECT imaging without arterial blood sampling.

MR-based motion correction for cardiac PET parametric imaging: a simulation study

BACKGROUND

Both cardiac and respiratory motions bias the kinetic parameters measured by dynamic PET. The aim of this study was to perform a realistic positron emission tomography-magnetic resonance (PET-MR) simulation study using 4D XCAT to evaluate the impact of MR-based motion correction on the estimation of PET myocardial kinetic parameters using PET-MR. Dynamic activity distributions were obtained based on a one-tissue compartment model with realistic kinetic parameters and an arterial input function. Realistic proton density/T1/T2 values were also defined for the MRI simulation. Two types of motion patterns, cardiac motion only (CM) and both cardiac and respiratory motions (CRM), were generated. PET sinograms were obtained by the projection of the activity distributions. PET image for each time frame was obtained using static (ST), gated (GA), non-motion-corrected (NMC), and motion-corrected (MC) methods. Voxel-wise unweighted least squares fitting of the dynamic PET data was then performed to obtain K₁ values for each study. For each study, the mean and standard deviation of K₁ values were computed for four regions of interest in the myocardium across 25 noise realizations.

RESULTS

Both cardiac and respiratory motions introduce blurring in the PET parametric images if the motion is not corrected. Conventional cardiac gating is limited by high noise level on parametric images. Dual cardiac and respiratory gating further increases the noise level. In contrast to GA, the MR-based MC method reduces motion blurring in parametric images without increasing noise level. It also improves the myocardial defect delineation as compared to NMC method. Finally, the MR-based MC method yields lower bias and variance in K₁ values than NMC and GA, respectively. The reductions of K₁ bias by MR-based MC are 7.7, 5.1, 15.7, and 29.9% in four selected 0.18-mL myocardial regions of interest, respectively, as compared to NMC for CRM. MR-based MC yields 85.9, 75.3, 71.8, and 95.2% less K₁ standard deviation in the four regions, respectively, as compared to GA for CRM.

CONCLUSIONS

This simulation study suggests that the MR-based motion-correction method using PET-MR greatly reduces motion blurring on parametric images and yields less K₁ bias without increasing noise level.