Dataset Information

Pharmacokinetic Analysis of Dynamic ¹⁸F-Fluoromisonidazole PET Data in Non-Small Cell Lung Cancer.

ABSTRACT: Hypoxic tumors exhibit increased resistance to radiation, chemical, and immune therapies. ¹⁸F-fluoromisonidazole (¹⁸F-FMISO) PET is a noninvasive, quantitative imaging technique used to evaluate the magnitude and spatial distribution of tumor hypoxia. In this study, pharmacokinetic analysis (PKA) of ¹⁸F-FMISO dynamic PET extended to 3 h after injection is reported for the first time, to our knowledge, in stage III-IV non-small cell lung cancer (NSCLC) patients. Methods: Sixteen patients diagnosed with NSCLC underwent 2 PET/CT scans (1-3 d apart) before radiation therapy: a 3-min static ¹⁸ F-FDG and a dynamic ¹⁸F-FMISO scan lasting 168 ± 15 min. The latter data were acquired in 3 serial PET/CT dynamic imaging sessions, registered with each other and analyzed using pharmacokinetic modeling software. PKA was performed using a 2-tissue, 3-compartment irreversible model, and kinetic parameters were estimated for the volumes of interest determined using coregistered ¹⁸F-FDG images for both the volume of interest-averaged and the voxelwise time-activity curves for each patient's lesions, normal lung, and muscle. Results: We derived average values of ¹⁸F-FMISO kinetic parameters for NSCLC lesions as well as for normal lung and muscle. We also investigated the correlation between the trapping rate (k₃) and delivery rate (K₁), influx rate (K_i ) constants, and tissue-to-blood activity concentration ratios (TBRs) for all tissues. Lesions had trapping rates 1.6 times larger, on average, than those of normal lung and 4.4 times larger than those in muscle. Additionally, for almost all cases, k₃ and K_i had a significant strong correlation for all tissue types. The TBR-k₃ correlation was less straightforward, showing a moderate to strong correlation for only 41% of lesions. Finally, K₁-k₃ voxelwise correlations for tumors were varied, but negative for 76% of lesions, globally exhibiting a weak inverse relationship (average R = -0.23 ± 0.39). However, both normal tissue types exhibited significant positive correlations for more than 60% of patients, with 41% having moderate to strong correlations (R > 0.5). Conclusion: All lesions showed distinct ¹⁸F-FMISO uptake. Variable ¹⁸F-FMISO delivery was observed across lesions, as indicated by the variable values of the kinetic rate constant K₁ Except for 3 cases, some degree of hypoxia was apparent in all lesions based on their nonzero k₃ values.

SUBMITTER: Schwartz J

PROVIDER: S-EPMC5450365 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Pharmacokinetic Analysis of Dynamic 18F-Fluoromisonidazole PET Data in Non-Small Cell Lung Cancer.

Schwartz Jazmin J Grkovski Milan M Rimner Andreas A Schöder Heiko H Zanzonico Pat B PB Carlin Sean D SD Staton Kevin D KD Humm John L JL Nehmeh Sadek A SA

Journal of nuclear medicine : official publication, Society of Nuclear Medicine 20170223 6

Hypoxic tumors exhibit increased resistance to radiation, chemical, and immune therapies. 18F-fluoromisonidazole (18F-FMISO) PET is a noninvasive, quantitative imaging technique used to evaluate the magnitude and spatial distribution of tumor hypoxia. In this study, pharmacokinetic analysis (PKA) of 18F-FMISO dynamic PET extended to 3 h after injection is reported for the first time, to our knowledge, in stage III-IV non-small cell lung cancer (NSCLC) patients. < ...[more]

PMID: 28232611

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Project description:PurposeThe aim of this study was to determine the relative abilities of compartment models to describe time-courses of 18 F-fluoromisonidazole (FMISO) uptake in tumor voxels of patients with non-small cell lung cancer (NSCLC) imaged using dynamic positron emission tomography. Also to use fits of the best-performing model to investigate changes in fitted rate-constants with distance from the tumor edge.MethodsReversible and irreversible two- and three-tissue compartment models were fitted to 24 662 individual voxel time activity curves (TACs) obtained from tumors in nine patients, each imaged twice. Descriptions of the TACs provided by the models were compared using the Akaike and Bayesian information criteria (AIC and BIC). Two different models (two- and three-tissue) were fitted to 30 measured voxel TACs to provide ground-truth TACs for a statistical simulation study. Appropriately scaled noise was added to each of the resulting ground-truth TACs, generating 1000 simulated noisy TACs for each ground-truth TAC. The simulation study was carried out to provide estimates of the accuracy and precision with which parameter values are determined, the estimates being obtained for both assumptions about the ground-truth kinetics. A BIC clustering technique was used to group the fitted rate-constants, taking into consideration the underlying uncertainties on the fitted rate-constants. Voxels were also categorized according to their distance from the tumor edge.ResultsFor uptake time-courses of individual voxels an irreversible two-tissue compartment model was found to be most precise. The simulation study indicated that this model had a one standard deviation precision of 39% for tumor fractional blood volumes and 37% for the FMISO binding rate-constant. Weighted means of fitted FMISO binding rate-constants of voxels in all tumors rose significantly with increasing distance from the tumor edge, whereas fitted fractional blood volumes fell significantly. When grouped using the BIC clustering, many centrally located voxels had high-fitted FMISO binding rate-constants and low rate-constants for tracer flow between the vasculature and tumor, both indicative of hypoxia. Nevertheless, many of these voxels had tumor-to-blood (TBR) values lower than the 1.4 level commonly expected for hypoxic tissues, possibly due to the low rate-constants for tracer flow between the vasculature and tumor cells in these voxels.ConclusionsTime-courses of FMISO uptake in NSCLC tumor voxels are best analyzed using an irreversible two-tissue compartment model, fits of which provide more precise parameter values than those of a three-tissue model. Changes in fitted model parameter values indicate that levels of hypoxia rise with increasing distance from tumor edges. The average FMISO binding rate-constant is higher for voxels in tumor centers than in the next tumor layer out, but the average value of the more simplistic TBR metric is lower in tumor centers. For both metrics, higher values might be considered indicative of hypoxia, and the mismatch in this case is likely to be due to poor perfusion at the tumor center. Kinetics analysis of dynamic PET images may therefore provide more accurate measures of the hypoxic status of such regions than the simpler TBR metric, a hypothesis we are presently exploring in a study of tumor imaging versus histopathology.

Project description:BACKGROUND:To determine the relative abilities of compartment models to describe time-courses of 18F-fluoromisonidazole (FMISO) tumor uptake in patients with advanced stage non-small cell lung cancer (NSCLC) imaged using dynamic positron emission tomography (dPET), and study correlations between values of the blood flow-related parameter K1 obtained from fits of the models and an independent blood flow measure obtained from perfusion CT (pCT). NSCLC patients had a 45-min dynamic FMISO PET/CT scan followed by two static PET/CT acquisitions at 2 and 4-h post-injection. Perfusion CT scanning was then performed consisting of a 45-s cine CT. Reversible and irreversible two-, three- and four-tissue compartment models were fitted to 30 time-activity-curves (TACs) obtained for 15 whole tumor structures in 9 patients, each imaged twice. Descriptions of the TACs provided by the models were compared using the Akaike and Bayesian information criteria (AIC and BIC) and leave-one-out cross-validation. The precision with which fitted model parameters estimated ground-truth uptake kinetics was determined using statistical simulation techniques. Blood flow from pCT was correlated with K1 from PET kinetic models in addition to FMISO uptake levels. RESULTS:An irreversible three-tissue compartment model provided the best description of whole tumor FMISO uptake time-courses according to AIC, BIC, and cross-validation scores totaled across the TACs. The simulation study indicated that this model also provided more precise estimates of FMISO uptake kinetics than other two- and three-tissue models. The K1 values obtained from fits of the irreversible three-tissue model correlated strongly with independent blood flow measurements obtained from pCT (Pearson r coefficient = 0.81). The correlation from the irreversible three-tissue model (r?=?0.81) was stronger than that from than K1 values obtained from fits of a two-tissue compartment model (r?=?0.68), or FMISO uptake levels in static images taken at time-points from tracer injection through to 4 h later (maximum at 2 min, r?=?0.70). CONCLUSIONS:Time-courses of whole tumor FMISO uptake by advanced stage NSCLC are described best by an irreversible three-tissue compartment model. The K1 values obtained from fits of the irreversible three-tissue model correlated strongly with independent blood flow measurements obtained from perfusion CT (r?=?0.81).

Project description:BackgroundPredictive markers for treatment response and survival outcome have not been identified in patients with advanced non-small-cell lung cancer (NSCLC) receiving chemoimmunotherapy. We aimed to evaluate whether imaging biomarkers of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) and routinely assessed clinico-laboratory values were associated with clinical outcomes in patients with advanced NSCLC receiving pembrolizumab plus platinum-doublet chemotherapy as a first-line treatment.MethodsWe retrospectively enrolled 52 patients with advanced NSCLC who underwent baseline 18F-FDG PET/CT before treatment initiation. PET/CT parameters and clinico-laboratory variables, constituting the prognostic immunotherapy scoring system, were collected. Optimal cut-off values for PET/CT parameters were determined using the maximized log-rank test for progression-free survival (PFS). A multivariate prediction model was developed based on Cox models for PFS, and a scoring system was established based on hazard ratios of the predictive factors.ResultsDuring the median follow-up period of 16.7 months (95% confidence interval: 15.7-17.7 months), 43 (82.7%) and 31 (59.6%) patients experienced disease progression and death, respectively. Objective response was observed in 23 (44.2%) patients. In the multivariate analysis, maximum standardized uptake value, metabolic tumour volume2.5, total lesion glycolysis2.5, and bone marrow-to-liver uptake ratio from the PET/CT variables and neutrophil-to-lymphocyte ratio (NLR) from the clinico-laboratory variables were independently associated with PFS. The scoring system based on these independent predictive variables significantly predicted the treatment response, PFS, and overall survival.ConclusionPET/CT variables and NLR were useful biomarkers for predicting outcomes of patients with NSCLC receiving pembrolizumab and chemotherapy as a first-line treatment, suggesting their potential as effective markers for combined PD-1 blockade and chemotherapy.

Project description:18F-T807 is a PET radiotracer developed for imaging tau protein aggregates, which are implicated in neurologic disorders including Alzheimer disease and traumatic brain injury (TBI). The current study characterizes 18F-T807 pharmacokinetics in human subjects using dynamic PET imaging and metabolite-corrected arterial input functions. Methods: Nine subjects (4 controls, 3 with a history of TBI, 2 with mild cognitive impairment due to suspected Alzheimer disease) underwent dynamic PET imaging for up to 120 min after bolus injection of 18F-T807 with arterial blood sampling. Total volume of distribution (VT) was estimated using compartmental modeling (1- and 2-tissue configurations) and graphical analysis techniques (Logan and multilinear analysis 1 [MA1] regression methods). Reference region-based methods of quantification were explored including Logan distribution volume ratio (DVR) and static SUV ratio (SUVR) using the cerebellum as a reference tissue. Results: The percentage of unmetabolized 18F-T807 in plasma followed a single exponential with a half-life of 17.0 ± 4.2 min. Metabolite-corrected plasma radioactivity concentration fit a biexponential (half-lives, 18.1 ± 5.8 and 2.4 ± 0.5 min). 18F-T807 in gray matter peaked quickly (SUV > 2 at ∼5 min). Compartmental modeling resulted in good fits, and the 2-tissue model with estimated blood volume correction (2Tv) performed best, particularly in regions with elevated binding. VT was greater in mild cognitive impairment subjects than controls in the occipital, parietal, and temporal cortices as well as the posterior cingulate gyrus, precuneus, and mesial temporal cortex. High focal uptake was found in the posterior corpus callosum of a TBI subject. Plots from Logan and MA1 graphical methods became linear by 30 min, yielding regional estimates of VT in excellent agreement with compartmental analysis and providing high-quality parametric maps when applied in voxelwise fashion. Reference region-based approaches including Logan DVR (t* = 55 min) and SUVR (80- to 100-min interval) were highly correlated with DVR estimated using 2Tv (R2 = 0.97, P < 0.0001). Conclusion:18F-T807 showed rapid clearance from plasma and properties suitable for tau quantification with PET. Furthermore, simplified approaches using DVR (t* = 55 min) and static SUVR (80-100 min) with cerebellar reference tissue were found to correlate highly with compartmental modeling outcomes.

Project description:BackgroundGlioma grading with dynamic 18F-FET PET (0-40 min p.i.) is typically performed by analysing the mean time-activity curve of the entire tumour or a suspicious area within a heterogeneous tumour. This work aimed to ensure a reader-independent glioma characterisation and identification of aggressive sub-volumes by performing a voxel-based analysis with diagnostically relevant kinetic and static 18F-FET PET parameters. One hundred sixty-two patients with a newly diagnosed glioma classified according to histologic and molecular genetic properties were evaluated. The biological tumour volume (BTV) was segmented in static 20-40 min p.i. 18F-FET PET images using the established threshold of 1.6?×?background activity. For each enclosed voxel, the time-to-peak (TTP), the late slope (Slope15-40), and the tumour-to-background ratios (TBR5-15, TBR20-40) obtained from 5 to 15 min p.i. and 20 to 40 min p.i. images were determined. The percentage portion of these values within the BTV was evaluated with percentage volume fractions (PVFs) and cumulated percentage volume histograms (PVHs). The ability to differentiate histologic and molecular genetic classes was assessed and compared to volume-of-interest (VOI)-based parameters.ResultsAggressive WHO grades III and IV and IDH-wildtype gliomas were dominated by a high proportion of voxels with an early peak, negative slope, and high TBR, whereby the PVHs with TTP <?20 min p.i., Slope15-40 <?0 SUV/h, and TBR5-15 and TBR20-40 >?2 yielded the most significant differences between glioma grades. We found significant differences of the parameters between WHO grades and IDH mutation status, where the effect size was predominantly higher for voxel-based PVHs compared to the corresponding VOI-based parameters. A low overlap of BTV sub-volumes defined by TTP <?20 min p.i. and negative Slope15-40 with TBR5-15?>?2- and TBR20-40?>?2-defined hotspots was observed.ConclusionsThe presented approach applying voxel-wise analysis of dynamic 18F-FET PET enables an enhanced characterisation of gliomas and might potentially provide a fast identification of aggressive sub-volumes within the BTV. Parametric 3D 18F-FET PET information as investigated in this study has the potential to guide individual therapy instrumentation and may be included in future biopsy studies.

Dataset Information

Pharmacokinetic Analysis of Dynamic ¹⁸F-Fluoromisonidazole PET Data in Non-Small Cell Lung Cancer.

Publications

Pharmacokinetic Analysis of Dynamic <sup>18</sup>F-Fluoromisonidazole PET Data in Non-Small Cell Lung Cancer.

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