Image-derived Input Function Research Articles

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 (VT) 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 VT,IDIF values were compared with corresponding VT,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 VT,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 VT,IDIF compared to 0.97 ± 0.01 for VT,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.

Modelling [18F]LW223 PET data using simplified imaging protocols for quantification of TSPO expression in the rat heart and brain

PurposeTo provide a comprehensive assessment of the novel 18 kDa translocator protein (TSPO) radiotracer, [18F]LW223, kinetics in the heart and brain when using a simplified imaging approach.MethodsNaive adult rats and rats with surgically induced permanent coronary artery ligation received a bolus intravenous injection of [18F]LW223 followed by 120 min PET scanning with arterial blood sampling throughout. Kinetic modelling of PET data was applied to estimated rate constants, total volume of distribution (VT) and binding potential transfer corrected (BPTC) using arterial or image-derived input function (IDIF). Quantitative bias of simplified protocols using IDIF versus arterial input function (AIF) and stability of kinetic parameters for PET imaging data of different length (40–120 min) were estimated.ResultsPET outcome measures estimated using IDIF significantly correlated with those derived with invasive AIF, albeit with an inherent systematic bias. Truncation of the dynamic PET scan duration to less than 100 min reduced the stability of the kinetic modelling outputs. Quantification of [18F]LW223 uptake kinetics in the brain and heart required the use of different outcome measures, with BPTC more stable in the heart and VT more stable in the brain.ConclusionModelling of [18F]LW223 PET showed the use of simplified IDIF is acceptable in the rat and the minimum scan duration for quantification of TSPO expression in rats using kinetic modelling with this radiotracer is 100 min. Carefully assessing kinetic outcome measures when conducting a systems level as oppose to single-organ centric analyses is crucial. This should be taken into account when assessing the emerging role of the TSPO heart-brain axis in the field of PET imaging.

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

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

Greater reductions in blood flow after anti-angiogenic treatment in non-small cell lung cancer patients are associated with shorter progression-free survival

To evaluate tumor blood flow using 15O-water positron emission tomography (PET) in patients with non-small cell lung cancer (NSCLC) before and after chemotherapy with bevacizumab, and to investigate the effects of bevacizumab on tumor blood flow changes and progression-free survival (PFS). Twelve patients with NSCLC were enrolled. Six patients underwent chemotherapy with bevacizumab and the other six without bevacizumab. 15O-water dynamic PET scans were performed within 1 week before the start of chemotherapy and within 1 week after the first day of chemotherapy. Tumor blood flow was analyzed quantitatively using a single one-tissue compartment model with the correction of pulmonary circulation blood volume and arterial blood volume via an image-derived input function. In the bevacizumab group, mean tumor blood flow was statistically significantly reduced post-chemotherapy (pre-chemotherapy 0.27 ± 0.14 mL/cm3/min, post-chemotherapy 0.18 ± 0.12 mL/cm3/min). In the no bevacizumab group, there was no significant difference between mean tumor perfusion pre-chemotherapy (0.42 ± 0.42 mL/cm3/min) and post-chemotherapy (0.40 ± 0.27 mL/cm3/min). In the bevacizumab group, there was a positive correlation between the blood flow ratio (tumor blood flow post-chemotherapy/tumor blood flow pre-chemotherapy) and PFS (correlation coefficient 0.94). Mean tumor blood flow decreases after bevacizumab administration and was positively correlated with longer PFS.

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.

Conditional Generative Adversarial Networks Aided Motion Correction of Dynamic 18F-FDG PET Brain Studies.

This work set out to develop a motion-correction approach aided by conditional generative adversarial network (cGAN) methodology that allows reliable, data-driven determination of involuntary subject motion during dynamic 18F-FDG brain studies. Methods: Ten healthy volunteers (5 men/5 women; mean age ± SD, 27 ± 7 y; weight, 70 ± 10 kg) underwent a test-retest 18F-FDG PET/MRI examination of the brain (n = 20). The imaging protocol consisted of a 60-min PET list-mode acquisition contemporaneously acquired with MRI, including MR navigators and a 3-dimensional time-of-flight MR angiography sequence. Arterial blood samples were collected as a reference standard representing the arterial input function (AIF). Training of the cGAN was performed using 70% of the total datasets (n = 16, randomly chosen), which was corrected for motion using MR navigators. The resulting cGAN mappings (between individual frames and the reference frame [55-60 min after injection]) were then applied to the test dataset (remaining 30%, n = 6), producing artificially generated low-noise images from early high-noise PET frames. These low-noise images were then coregistered to the reference frame, yielding 3-dimensional motion vectors. Performance of cGAN-aided motion correction was assessed by comparing the image-derived input function (IDIF) extracted from a cGAN-aided motion-corrected dynamic sequence with the AIF based on the areas under the curves (AUCs). Moreover, clinical relevance was assessed through direct comparison of the average cerebral metabolic rates of glucose (CMRGlc) values in gray matter calculated using the AIF and the IDIF. Results: The absolute percentage difference between AUCs derived using the motion-corrected IDIF and the AIF was (1.2% + 0.9%). The gray matter CMRGlc values determined using these 2 input functions differed by less than 5% (2.4% + 1.7%). Conclusion: A fully automated data-driven motion-compensation approach was established and tested for 18F-FDG PET brain imaging. cGAN-aided motion correction enables the translation of noninvasive clinical absolute quantification from PET/MR to PET/CT by allowing the accurate determination of motion vectors from the PET data itself.

Cerebral oxygen extraction fraction (OEF): Comparison of challenge-free gradient echo QSM+qBOLD (QQ) with 15O PET in healthy adults

We aimed to validate oxygen extraction fraction (OEF) estimations by quantitative susceptibility mapping plus quantitative blood oxygen-level dependence (QSM+qBOLD, or QQ) using 15O-PET. In ten healthy adult brains, PET and MRI were acquired simultaneously on a PET/MR scanner. PET was acquired using C[15O], O[15O], and H2[15O]. Image-derived arterial input functions and standard models of oxygen metabolism provided quantification of PET. MRI included T1-weighted imaging, time-of-flight angiography, and multi-echo gradient-echo imaging that was processed for QQ. Region of interest (ROI) analyses compared PET OEF and QQ OEF. In ROI analyses, the averaged OEF differences between PET and QQ were generally small and statistically insignificant. For whole brains, the average and standard deviation of OEF was 32.8 ± 6.7% for PET; OEF was 34.2 ± 2.6% for QQ. Bland-Altman plots quantified agreement between PET OEF and QQ OEF. The interval between the 95% limits of agreement was 16.9 ± 4.0% for whole brains. Our validation study suggests that respiratory challenge-free QQ-OEF mapping may be useful for non-invasive clinical assessment of regional OEF impairment.

Noninvasive Measurement of [11C]PiB Distribution Volume Using Integrated PET/MRI.

A noninvasive image-derived input function (IDIF) method using PET/MRI was applied to quantitative measurements of [11C] Pittsburgh compound-B (PiB) distribution volume (DV) and compared with other metrics. Fifty-three patients suspected of early dementia (71 ± 11 y) underwent 70 min [11C]PiB PET/MRI. Nineteen of them (68 ± 11 y) without head motion during the scan were enrolled in this study and compared with 16 age-matched healthy controls (CTL: 68 ± 11 y). The dynamic frames reconstructed from listmode PET data were used for DV calculation. IDIF with metabolite correction was applied to the Logan plot method, and DV was normalized into DV ratio (DVR) images using the cerebellar reference (DVRL). DVR and standardized uptake value ratio (SUVR) images were also calculated using the reference tissue graphical method (DVRr) and the 50–70 min static data with cerebellar reference, respectively. Cortical values were compared using the 3D-T1WI MRI segmentation. All patients were assigned to the early Alzheimer’s disease (eAD) group because of positive [11C]PiB accumulation. The correlations of regional values were better for DVRL vs. DVRr (r2 = 0.97) than for SUVR vs. DVRr (r2 = 0.88). However, all metrics clearly differentiated eAD from CTL with appropriate thresholds. Noninvasive quantitative [11C]PiB PET/MRI measurement provided equivalent DVRs with the two methods. SUVR images showed acceptable results despite inferior variability and image quality to DVR images.

Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET

BackgroundArterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic 18F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (CP*(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated CP*(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling.MethodsThe Feng 18F-FDG plasma concentration model was applied to estimate AIF parameters (n = 23). AIF normalization used either AUC(0–60 min) or CP*(0), estimated from an exponential fit. CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV). iDV was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15–45, 30–60, 45–75, 60–90 min) (PBIFAUC) and estimated CP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak Ki values.ResultsThe IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and Ki comparison, 30–60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimated Ki (− 6 ± 8 to − 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30–60), and PBIFiDV were 0.91, 0.94, and 0.90, respectively. The bias of Ki was − 9 ± 10%, − 1 ± 8%, and 3 ± 9%, respectively.ConclusionsBoth PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.

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

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. 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 (CMRglc) obtained from standard 2-tissue compartment (2TCM) and Patlak analysis. 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 CMRglc 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. We have demonstrated the feasibility and high reproducibility of conducting longitudinal AIF measurements and consequently accurate kinetic modeling using arterial shunt method.

Quantitative evaluation of hepatic integrin \u03b1v\u03b23 expression by positron emission tomography imaging using 18F-FPP-RGD2 in rats with non-alcoholic steatohepatitis

BackgroundIntegrin αvβ3, which are expressed by activated hepatic stellate cells in non-alcoholic steatohepatitis (NASH), play an important role in the fibrosis. Recently, we reported that an RGD peptide positron emission tomography (PET) probe is useful as a predictor of hepatic fibrosis. Kinetic analysis of the RGD PET probe has been performed in tumours, but not in hepatic fibrosis. Therefore, we aimed to quantify hepatic integrin αvβ3 in a model of NASH by kinetic analysis using 18F-FPP-RGD2, an integrin αvβ3 PET probe.Methods18F-FPP-RGD2 PET/CT scans were performed in control and NASH rats. Tissue kinetic analyses were performed using a one-tissue, two-compartment (1T2C) and a two-tissue, three-compartment (2T3C) model using an image-derived input function (IDIF) for the left ventricle. We then conducted correlation analysis between standard uptake values (SUVs) or volume of distribution (VT), evaluated using compartment kinetic analysis and integrin αv or β3 protein expression.ResultsBiochemical and histological evaluation confirmed the development of NASH rats. Integrin αvβ3 protein expression and hepatic SUV were higher in NASH- than normal rats. The hepatic activity of 18F-FPP-RGD2 peaked rapidly after administration and then gradually decreased, whereas left ventricular activity rapidly disappeared. The 2T3C model was found to be preferable for 18F-FPP-RGD2 kinetic analysis in the liver. The VT (IDIF) for 18F-FPP-RGD2, calculated using the 2T3C model, was significantly higher in NASH- than normal rats and correlated strongly with hepatic integrin αv and β3 protein expression. The strengths of these correlations were similar to those between SUV60–90 min and hepatic integrin αv or β3 protein expression.ConclusionsWe have demonstrated that the VT (IDIF) of 18F-FPP-RGD2, calculated using kinetic modelling, positively correlates with integrin αv and β3 protein in the liver of NASH rats. These findings suggest that hepatic VT (IDIF) provides a quantitative assessment of integrin αvβ3 protein in liver.

Total-Body Quantitative Parametric Imaging of Early Kinetics of 18F-FDG.

Parametric imaging has been shown to provide better quantitation physiologically than SUV imaging in PET. With the increased sensitivity from a recently developed total-body PET scanner, whole-body scans with higher temporal resolution become possible for dynamic analysis and parametric imaging. In this paper, we focus on deriving the parameter k1 using compartmental modeling and on developing a method to acquire whole-body 18F-FDG PET parametric images using only the first 90 s of the postinjection scan data with the total-body PET system. Methods: Dynamic projections were acquired with a time interval of 1 s for the first 30 s and a time interval of 2 s for the following minute. Image-derived input functions were acquired from the reconstructed dynamic sequences in the ascending aorta. A 1-tissue-compartment model with 4 parameters (k1, k2, blood fraction, and delay time) was used. A maximum-likelihood-based estimation method was developed with the 1-tissue-compartment model solution. The accuracy of the acquired parameters was compared with the ones estimated using a 2-tissue-compartment irreversible model with 1-h-long data. Results: All 4 parametric images were successfully calculated using data from 2 volunteers. By comparing the time-activity curves acquired from the volumes of interest, we showed that the parameters estimated using our method were able to predict the time-activity curves of the early dynamics of 18F-FDG in different organs. The delay-time effects for different organs were also clearly visible in the reconstructed delay-time image with delay variations of as large as 40 s. The estimated parameters using both 90-s data and 1-h data agreed well for k1 and blood fraction, whereas a large difference in k2 was found between the 90-s and 1-h data, suggesting k2 cannot be reliably estimated from the 90-s scan. Conclusion: We have shown that with total-body PET and the increased sensitivity, it is possible to estimate parametric images based on the very early dynamics after 18F-FDG injection. The estimated k1 might potentially be used clinically as an indicator for identifying abnormalities.

Quantification of [18F]afatinib using PET/CT in NSCLC patients: a feasibility study

IntroductionOnly a subgroup of non-small cell lung cancer (NSCLC) patients benefit from treatment using epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI) such as afatinib. Tumour uptake of [18F]afatinib using positron emission tomography (PET) may identify those patients that respond to afatinib therapy. Therefore, the aim of this study was to find the optimal tracer kinetic model for quantification of [18F]afatinib uptake in NSCLC tumours.Methods[18F]Afatinib PET scans were performed in 10 NSCLC patients. The first patient was scanned for the purpose of dosimetry. Subsequent patients underwent a 20-min dynamic [15O]H2O PET scan (370 MBq) followed by a dynamic [18F]afatinib PET scan (342 ± 24 MBq) of 60 or 90 min. Using the Akaike information criterion (AIC), three pharmacokinetic plasma input models were evaluated with both metabolite-corrected sampler-based input and image-derived (IDIF) input functions in combination with discrete blood samples. Correlation analysis of arterial on-line sampling versus IDIF was performed. In addition, perfusion dependency and simplified measures were assessed.ResultsTen patients were included. The injected activity of [18F]afatinib was 341 ± 37 MBq. Fifteen tumours could be identified in the field of view of the scanner. Based on AIC, tumour kinetics were best described using an irreversible two-tissue compartment model and a metabolite-corrected sampler-based input function (Akaike 50%). Correlation of plasma-based input functions with metabolite-corrected IDIF was very strong (r2 = 0.93). The preferred simplified uptake parameter was the tumour-to-blood ratio over the 60- to 90-min time interval (TBR60–90). Tumour uptake of [18F]afatinib was independent of perfusion.ConclusionThe preferred pharmacokinetic model for quantifying [18F]afatinib uptake in NSCLC tumours was the 2T3K_vb model. TBR60–90 showed excellent correlation with this model and is the best candidate simplified method.Trial registrationhttps://eudract.ema.europa.eu/ nr 2012-002849-38

Kinetic Modeling of Dynamic PET-¹⁸F-FDG Atherosclerosis Without Blood Sampling

Atherosclerosis is a disease affecting the peripheral arteries characterized by a deposit of lipids and immune cells forming a plaque. The plaque can be calcified and be measured with CT, and it can be inflamed and be measured with PET and 18F-FDG. Since artery walls are too small and are dominated by blood activity, the conventional compartmental model becomes inadequate to provide artery metabolism especially when using an image derived input function from an artery. The purpose of this study was to quantitatively evaluate glucose metabolism in arteries with a more appropriate compartmental modeling. Kinetic modeling of arteries was conducted using the classical 18F-FDG compartmental model and a modification of this model without the need of blood sampling. The metabolic rate of glucose (MRG) was computed per artery segment in each image slice with both models. The ratio of calcification area (RCA) and Agatston calcification scores (ACSs) were automatically clustered with the automatic hierarchical $K$ -means algorithm. The rate constants showed significant variation between the two models ( $P ), however, $K_{i}$ was with good agreement in both models ( $P >0.05$ ). Both models found that MRG values in non-medication group were statistically significantly different from those in under-medication group.

Quantification and reliability of [11C]VC - 002 binding to muscarinic acetylcholine receptors in the human lung \u2014 a test-retest PET study in control subjects

BackgroundThe radioligand [11C]VC-002 was introduced in a small initial study long ago for imaging of muscarinic acetylcholine receptors (mAChRs) in human lungs using positron emission tomography (PET). The objectives of the present study in control subjects were to advance the methodology for quantification of [11C]VC-002 binding in lung and to examine the reliability using a test-retest paradigm. This work constituted a self-standing preparatory step in a larger clinical trial aiming at estimating mAChR occupancy in the human lungs following inhalation of mAChR antagonists.MethodsPET measurements using [11C]VC-002 and the GE Discovery 710 PET/CT system were performed in seven control subjects at two separate occasions, 2–19 days apart. One subject discontinued the study after the first measurement.Radioligand binding to mAChRs in lung was quantified using an image-derived arterial input function. The total distribution volume (VT) values were obtained on a regional and voxel-by-voxel basis. Kinetic one-tissue and two-tissue compartment models (1TCM, 2TCM), analysis based on linearization of the compartment models (multilinear Logan) and image analysis by data-driven estimation of parametric images based on compartmental theory (DEPICT) were applied.The test-retest repeatability of VT estimates was evaluated by absolute variability (VAR) and intraclass correlation coefficients (ICCs).ResultsThe 1TCM was the statistically preferred model for description of [11C]VC-002 binding in the lungs. Low VAR (< 10%) across analysis methods indicated good reliability of the PET measurements. The VT estimates were stable after 60 min.ConclusionsThe kinetic behaviour and good repeatability of [11C]VC-002 as well as the novel lung image analysis methodology support its application in applied studies on drug-induced mAChR receptor occupancy and the pathophysiology of pulmonary disorders.Trial registrationClinicalTrials.gov identifier: NCT03097380, registered: 31 March 2017.

Design and Implementation of Automated Clinical Whole Body Parametric PET With Continuous Bed Motion

We described workflows and methodologies for fully automated parametric imaging using clinical positron emission tomography (PET) systems with continuous bed motion (CBM) which aim to enable physicians to practice parametric PET routinely. The key components of our implemented methods include automatic generation of image-derived blood input functions, accurate tracking of slice imaging time during CBM acquisitions, and parametric image formation with advanced algorithms. Locations of the left ventricle and the descending aorta were automatically detected from high resolution anatomical images and registered to dynamic PET images to generate blood input functions. A method to accurately track dynamic scans and calculate time information for whole body CBM parametric PET was implemented based on bed position tags. This approach of calculating time information based on finely sampled bed position tags can be applied to flexible scan modes with various scan speeds over different body regions. We applied the calculated slice time information for whole body parametric imaging using a linear Patlak model. Parametric images were reconstructed with a nested expectation maximization (EM) algorithm. We demonstrated that parametric images generated by our automated workflow can provide quantitative parameters in addition to standardized uptake value images. We presented results for a uni-direction dynamic scan from a Biograph mCT system and a bi-direction dynamic scan from a Biograph Vision system.

A Multi-Ligand Imaging Study Exploring GABAergic Receptor Expression and Inflammation in Multiple Sclerosis.

The γ-aminobutyric acid (GABA) is the main inhibitory neurotransmitter and essential for normal brain function. The GABAergic system has been shown to have immunomodulatory effects and respond adaptively to excitatory toxicity. The association of the GABAergic system and inflammation in patients with multiple sclerosis (MS) remains unknown. In this pilot study, the in vivo relationship between GABAA binding and the innate immune response is explored using positron emission tomography (PET) with [11C] flumazenil (FMZ) and [11C]-PK11195 PET (PK-PET), a measure of activated microglia/macrophages. Sixteen MS patients had dynamic FMZ-PET and PK-PET imaging. Ten age-matched healthy controls (HC) had a single FMZ-PET. GABAA receptor binding was calculated using Logan reference model with the pons as reference. Distribution of volume ratio (VTr) for PK-PET was calculated using image-derived input function. A hierarchical linear model was fitted to assess the linear association between PK-PET and FMZ-PET among six cortical regions of interest. GABAA receptor binding was higher throughout the cortex in MS patients (5.72 ± 0.91) as compared with HC (4.70 ± 0.41) (p = 0.002). A significant correlation was found between FMZ binding and PK-PET within the cortex (r = 0.61, p < 0.001) and among the occipital (r = 0.61, p = 0.012), parietal (r = 0.49, p = 0.041), and cingulate (r = 0.32, p = 0.006) regions. A higher GABAA receptor density in MS subjects compared with HC was observed and correlated with innate immune activity. Our observations demonstrate that immune-driven GABAergic abnormalities may be present in MS.

Multimodal analysis using [11C]PiB-PET/MRI for functional evaluation of patients with Alzheimer\u2019s disease

BackgroundMultimodal PET/MRI image data simultaneously obtained from patients with early-stage of Alzheimer’s disease (eAD) were assessed in order to observe pathophysiologic and functional changes, as well as alterations of morphology and connectivity in the brain. Fifty-eight patients with mild cognitive impairment and early dementia (29 males, 69 ± 12 years) underwent [11C]Pittsburgh compound-B (PiB) PET/MRI with 70-min PET and MRI scans. Sixteen age-matched healthy controls (CTL) (9 males, 68 ± 11 years) were also studied with the same scanning protocol. Cerebral blood flow (CBF) was calculated from the early phase PET images using the image-derived input function method. A standardized uptake value ratio (SUVr) was calculated from 50 to 70 min PET data with a reference region of the cerebellar cortex. MR images such as 3D-T1WI, resting-state functional MRI (RS-fMRI), diffusion tensor image (DTI), and perfusion MRI acquired during the dynamic PET scan were also analyzed to evaluate various brain functions on MRI.ResultsTwenty-seven of the 58 patients were determined as eAD based on the results of PiB-PET and clinical findings, and a total of 43 subjects’ data including CTL were analyzed in this study. PiB SUVr values in all cortical regions of eAD were significantly greater than those of CTL. The PiB accumulation intensity was negatively correlated with cognitive scores. The regional PET-CBF values of eAD were significantly lower in the bilateral parietal lobes and right temporal lobe compared with CTL, but not in MRI perfusion; however, SPM showed regional differences on both PET- and MRI-CBF. SPM analysis of RS-fMRI delineated regional differences between the groups in the anterior cingulate cortex and the left precuneus. VBM analysis showed atrophic changes in the AD group in a part of the bilateral hippocampus; however, analysis of fractional anisotropy calculated from DTI data did not show differences between the two groups.ConclusionMultimodal analysis conducted with various image data from PiB-PET/MRI scans showed differences in regional CBF, cortical volume, and neuronal networks in different regions, indicating that pathophysiologic and functional changes in the AD brain can be observed from various aspects of neurophysiologic parameters. Application of multimodal brain images using PET/MRI would be ideal for investigating pathophysiologic changes in patients with dementia and other neurodegenerative diseases.

Fully Integrated PET/MR Imaging for the Assessment of the Relationship Between Functional Connectivity and Glucose Metabolic Rate.

In the past, determination of absolute values of cerebral metabolic rate of glucose (CMRGlc) in clinical routine was rarely carried out due to the invasive nature of arterial sampling. With the advent of combined PET/MR imaging technology, CMRGlc values can be obtained non-invasively, thereby providing the opportunity to take advantage of fully quantitative data in clinical routine. However, CMRGlc values display high physiological variability, presumably due to fluctuations in the intrinsic activity of the brain at rest. To reduce CMRGlc variability associated with these fluctuations, the objective of this study was to determine whether functional connectivity measures derived from resting-state fMRI (rs-fMRI) could be used to correct for these fluctuations in intrinsic brain activity. Methods: We studied 10 healthy volunteers who underwent a test-retest dynamic [18F]FDG-PET study using a fully integrated PET/MR system (Siemens Biograph mMR). To validate the non-invasive derivation of an image-derived input function based on combined analysis of PET and MR data, arterial blood samples were obtained. Using the arterial input function (AIF), parametric images representing CMRGlc were determined using the Patlak graphical approach. Both directed functional connectivity (dFC) and undirected functional connectivity (uFC) were determined between nodes in six major networks (Default mode network, Salience, L/R Executive, Attention, and Sensory-motor network) using either a bivariate-correlation (R coefficient) or a Multi-Variate AutoRegressive (MVAR) model. In addition, the performance of a regional connectivity measure, the fractional amplitude of low frequency fluctuations (fALFF), was also investigated. Results: The average intrasubject variability for CMRGlc values between test and retest was determined as (14 ±8%) with an average inter-subject variability of 25% at test and 15% at retest. The average CMRGlc value (umol/100 g/min) across all networks was 39 ±10 at test and increased slightly to 43 ±6 at retest. The R, MVAR and fALFF coefficients showed relatively large test-retest variability in comparison to the inter-subjects variability, resulting in poor reliability (intraclass correlation in the range of 0.11–0.65). More importantly, no significant relationship was found between the R coefficients (for uFC), MVAR coefficients (for dFC) or fALFF and corresponding CMRGlc values for any of the six major networks. Discussion: Measurement of functional connectivity within established brain networks did not provide a means to decrease the inter- or intrasubject variability of CMRGlc values. As such, our results indicate that connectivity measured derived from rs-fMRI acquired contemporaneously with PET imaging are not suited for correction of CMRGlc variability associated with intrinsic fluctuations of resting-state brain activity. Thus, given the observed substantial inter- and intrasubject variability of CMRGlc values, the relevance of absolute quantification for clinical routine is presently uncertain.

Longitudinal mouse-PET imaging: a reliable method for estimating binding parameters without a reference region or blood sampling

Longitudinal mouse PET imaging is becoming increasingly popular due to the large number of transgenic and disease models available but faces challenges. These challenges are related to the small size of the mouse brain and the limited spatial resolution of microPET scanners, along with the small blood volume making arterial blood sampling challenging and impossible for longitudinal studies. The ability to extract an input function directly from the image would be useful for quantification in longitudinal small animal studies where there is no true reference region available such as TSPO imaging.MethodsUsing dynamic, whole-body 18F-DPA-714 PET scans (60 min) in a mouse model of hippocampal sclerosis, we applied a factor analysis (FA) approach to extract an image-derived input function (IDIF). This mouse-specific IDIF was then used for 4D-resolution recovery and denoising (4D-RRD) that outputs a dynamic image with better spatial resolution and noise properties, and a map of the total volume of distribution (VT) was obtained using a basis function approach in a total of 9 mice with 4 longitudinal PET scans each. We also calculated percent injected dose (%ID) with and without 4D-RRD. The VT and %ID parameters were compared to quantified ex vivo autoradiography using regional correlations of the specific binding from autoradiography against VT and %ID parameters.ResultsThe peaks of the IDIFs were strongly correlated with the injected dose (Pearson R = 0.79). The regional correlations between the %ID estimates and autoradiography were R = 0.53 without 4D-RRD and 0.72 with 4D-RRD over all mice and scans. The regional correlations between the VT estimates and autoradiography were R = 0.66 without 4D-RRD and 0.79 with application of 4D-RRD over all mice and scans.ConclusionWe present a FA approach for IDIF extraction which is robust, reproducible and can be used in quantification methods for resolution recovery, denoising and parameter estimation. We demonstrated that the proposed quantification method yields parameter estimates closer to ex vivo measurements than semi-quantitative methods such as %ID and is immune to tracer binding in tissue unlike reference tissue methods. This approach allows for accurate quantification in longitudinal PET studies in mice while avoiding repeated blood sampling.