Image-derived Arterial Input Function Research Articles

Evaluation of an Image-Derived Input Function for Kinetic Modeling of Nicotinic Acetylcholine Receptor-Binding PET Ligands in Mice.

Positron emission tomography (PET) radioligands that bind with high-affinity to α4β2-type nicotinic receptors (α4β2Rs) allow for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. Here, we investigate the use of an image-derived arterial input function and the cerebellum for kinetic analysis of radioligand binding in mice. Two radioligands were explored: 2-[18F]FA85380 (2-FA), displaying similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, displaying similar pKa and binding affinity to nicotine. Time-activity curves of the left ventricle of the heart displayed similar distribution across wild type mice, mice lacking the β2-subunit for ligand binding, and acute nicotine-treated mice, whereas reference tissue binding displayed high variation between groups. Binding potential estimated from a two-tissue compartment model fit of the data with the image-derived input function were higher than estimates from reference tissue-based estimations. Rate constants of radioligand dissociation were very slow for 2-FA and very fast for Nifene. We conclude that using an image-derived input function for kinetic modeling of nicotinic PET ligands provides suitable results compared to reference tissue-based methods and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.

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.

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7–8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other side, which incorporates a quadratic penalty function. The parametric images were then calculated using voxel-wise weighted least-square fitting of the reconstructed myocardial PET TACs. For the direct method, parametric images were estimated directly from the dynamic PET sinograms using a maximum a posteriori (MAP) parametric reconstruction algorithm which optimizes an objective function comprised of the Poisson log-likelihood term, the kinetic model and a quadratic penalty function. Maximization of the objective function with respect to each set of parameters was achieved using a preconditioned conjugate gradient algorithm with a specifically developed pre-conditioner. The performance of the direct method was evaluated by comparing voxel- and segment-wise estimates of , the tracer transport rate (ml · min−1 · ml−1), to those obtained using the indirect method applied to both OSEM and OSL-MAP dynamic reconstructions. The proposed direct reconstruction method produced maps with visibly lower noise than the indirect method based on OSEM and OSL-MAP reconstructions. At normal count levels, the direct method was shown to outperform the indirect method based on OSL-MAP in the sense that at matched level of bias, reduced regional noise levels were obtained. At lower count levels, the direct method produced estimates with significantly lower standard deviation across noise realizations than the indirect method based on OSL-MAP at matched bias level. In all cases, the direct method yielded lower noise and standard deviation than the indirect method based on OSEM. Overall, the proposed direct reconstruction offered a better bias-variance tradeoff than the indirect method applied to either OSEM and OSL-MAP. Direct parametric reconstruction as applied to in vivo dynamic PET MPI data is therefore a promising method for producing MBF maps with lower variance.

Quantitative hemodynamic PET imaging using image-derived arterial input function and a PET/MR hybrid scanner

Positron emission tomography (PET) with 15O-tracers is commonly used to measure brain hemodynamic parameters such as cerebral blood flow, cerebral blood volume, and cerebral metabolic rate of oxygen. Conventionally, the absolute quantification of these parameters requires an arterial input function that is obtained invasively by sampling blood from an artery. In this work, we developed and validated an image-derived arterial input function technique that avoids the unreliable and burdensome arterial sampling procedure for full quantitative 15O-PET imaging. We then compared hemodynamic PET imaging performed on a PET/MR hybrid scanner against a conventional PET only scanner. We demonstrated the proposed imaging-based technique was able to generate brain hemodynamic parameter measurements in strong agreement with the traditional arterial sampling based approach. We also demonstrated that quantitative 15O-PET imaging can be successfully implemented on a PET/MR hybrid scanner.

Effect of MR contrast agent on quantitative PET during simultaneous PET-MR imaging in cardiology

Background MR sequences used in the determination of PET linear attenuation coefficients (LAC) are a common procedure in simultaneous PET-MRI scanning. However during dynamic PET imaging, the introduction of gadolinium-based contrast agents (MRCA) at high concentrations during a dual injection of MRCA and PET radiotracer may cause attenuation effects of the PET radiotracer, and thus errors in quantification of dynamic images. Method We performed simultaneous PET-MR imaging of a phantom using increasing MRCA concentration from 0 to 65 mM (based on MRCA left ventricular concentration in a clinical study) mixed with water and 25 MBq of [18F]-FDG. LAC of the solution was calculated by a mixture rule and compared to measurements from CT images and automated MR LAC segmentation. The effect of increases in the resulting LAC over 0–65 mM was evaluated on a simulated image-derived arterial input function (IDIF) used in the PET kinetic model. Results From 0 to 46 mM, MR segmentation applied a LAC of 0.1 cm −1 , and at >46 mM the LAC = 0.0854 cm −1 due to T1 shortening effects. Our results show an increase of only 1.3% in the LAC of the solution over the range of 0–65 mM of MRCA, with an effect on the area under an IDIF of

Image-derived arterial input function for quantitative fluorescence imaging of receptor-drug binding in vivo.

Receptor concentration imaging (RCI) with targeted-untargeted optical dye pairs has enabled in vivo immunohistochemistry analysis in preclinical subcutaneous tumors. Successful application of RCI to fluorescence guided resection (FGR), so that quantitative molecular imaging of tumor-specific receptors could be performed in situ, would have a high impact. However, assumptions of pharmacokinetics, permeability and retention, as well as the lack of a suitable reference region limit the potential for RCI in human neurosurgery. In this study, an arterial input graphic analysis (AIGA) method is presented which is enabled by independent component analysis (ICA). The percent difference in arterial concentration between the image-derived arterial input function (AIFICA ) and that obtained by an invasive method (ICACAR ) was 2.0 ± 2.7% during the first hour of circulation of a targeted-untargeted dye pair in mice. Estimates of distribution volume and receptor concentration in tumor bearing mice (n = 5) recovered using the AIGA technique did not differ significantly from values obtained using invasive AIF measurements (p = 0.12). The AIGA method, enabled by the subject-specific AIFICA , was also applied in a rat orthotopic model of U-251 glioblastoma to obtain the first reported receptor concentration and distribution volume maps during open craniotomy.

Quantitative amyloid imaging using image-derived arterial input function.

Amyloid PET imaging is an indispensable tool widely used in the investigation, diagnosis and monitoring of Alzheimer’s disease (AD). Currently, a reference region based approach is used as the mainstream quantification technique for amyloid imaging. This approach assumes the reference region is amyloid free and has the same tracer influx and washout kinetics as the regions of interest. However, this assumption may not always be valid. The goal of this work is to evaluate an amyloid imaging quantification technique that uses arterial region of interest as the reference to avoid potential bias caused by specific binding in the reference region. 21 participants, age 58 and up, underwent Pittsburgh compound B (PiB) PET imaging and MR imaging including a time-of-flight (TOF) MR angiography (MRA) scan and a structural scan. FreeSurfer based regional analysis was performed to quantify PiB PET data. Arterial input function was estimated based on coregistered TOF MRA using a modeling based technique. Regional distribution volume (VT) was calculated using Logan graphical analysis with estimated arterial input function. Kinetic modeling was also performed using the estimated arterial input function as a way to evaluate PiB binding (DVRkinetic) without a reference region. As a comparison, Logan graphical analysis was also performed with cerebellar cortex as reference to obtain DVRREF. Excellent agreement was observed between the two distribution volume ratio measurements (r>0.89, ICC>0.80). The estimated cerebellum VT was in line with literature reported values and the variability of cerebellum VT in the control group was comparable to reported variability using arterial sampling data. This study suggests that image-based arterial input function is a viable approach to quantify amyloid imaging data, without the need of arterial sampling or a reference region. This technique can be a valuable tool for amyloid imaging, particularly in population where reference normalization may not be accurate.

Combining MRI with PET for partial volume correction improves image-derived input functions in mice.

Kinetic modelling in PET requires the arterial input function (AIF), defined as the time-activity curve (TAC) in plasma. This measure is challenging to obtain in mice due to low blood volumes, resulting in a reliance on image-based methods for AIF derivation. We present a comparison of PET- and MR-based region-of-interest (ROI) analysis to obtain image-derived AIFs from the left ventricle (LV) of a mouse model. ROI-based partial volume correction (PVC) was performed to improve quantification. MRI and dynamic PET images were obtained from a recent study investigating treatment effects in 12 mice following myocardial infarction [1], where half the mice received a new treatment and half did not. Prospectively gated MRI (4.7T Bruker BioSpec, FLASH TR/TE 400/3ms, spatial resolution 140μm in 1mm slices) were acquired prior to PET acquisition (approx. 25MBq 18F-FDG bolus, 45 minute emission listmode acquisition reconstructed with 3DRP in four cardiac frames) on a split-magnet PET camera [2]. Images were co-registered using SPMMouse [3] (see Figure ​Figure11). Figure 1 Mouse heart MR (left) and fused with 18F-FDG static PET (right). Arrow indicates infarcted region. AIF extraction AIFs were obtained by taking mean time courses from LV Lumen ROIs, shown in Figure ​Figure2.2. The regional geometric transfer matrix (GTM) method was applied for PVC [4], using ROIs drawn on either the co-registered MR images or directly onto the last dynamic frame PET images. ROIs covered LV lumen, myocardium, lungs/body and background. Patlak [5] analysis was performed to evaluate glucose metabolism. Figure 2 AIFs and TACs derived for single subject using (A) MR ROIs, (B) PET ROIs with PVC and (C) MR ROIs with PVC. Insets detail first 500s Uncorrected AIFs and myocardial TACs produced by manual ROI delineation displayed contamination with myocardial signal. AIFs and myocardial curves became distinguishable if GTM PVC was applied. Only MR-based PVC produced significant differences (p<0.05) in Ki values between the treated and untreated groups (see Table ​Table11). Table 1 GTM-based PVC gives best results in mice when ROIs are based on MRI data, due to its high-resolution and excellent soft-tissue contrast.

Combined measurement of tumor perfusion and glucose metabolism for improved tumor characterization in advanced cervical carcinoma

The aim of this pilot study was (1) to evaluate the combination of [(18)F]fluorodeoxyglucose (FDG) and [(15)O]water for detection of flow-metabolism mismatch in advanced cervical carcinomas, i.e., increased glycolysis at low blood flow, as a possible parameter for prediction of response to treatment, and (2) to propose a method for automated quantification of its spatial extent. The study retrospectively included 10women with advanced cervical carcinoma in whom PET with both FDG and [(15)O]water had been performed prior to therapy. The metabolically active tumor volume was delineated automatically in the FDG images. For computation of the regional blood flow in the tumor, a recovery corrected image-derived arterial input function was used. A tumor voxel was classified as mismatched when the voxel SUV of FDG was larger than the median tumor SUV and the voxel perfusion (K1) was smaller than the median perfusion. The absolute mismatch volume (aMMV) was defined as the volume of all mismatched voxels in ml, and the relative mismatch volume (rMMV) as the ratio of the aMMV to the metabolic tumor volume in percent. The tumors were quite heterogeneous with respect to both FDG uptake and perfusion. The aMMV clustered into 2 groups: "large aMMV" ≥ 10ml in 40 % of patients and "small aMMV" ≤ 5ml in 60 % of patients. The rMMV ranged from 12.7-24.9 %. There was no correlation between rMMV and metabolic tumor volume. There was a tendency (p = 0.126) for an association between rMMV and histological grading, rMMV being about 20 % higher in G3 than in G2 tumors. rMMV did not correlate with SUV or perfusion. These results suggest that combined PET with FDG and [(15)O]water allows detection and quantitative characterization of flow-metabolism mismatch in advanced cervical carcinomas.

Image-derived arterial input function for PiB quantification

Image-derived arterial input function for PiB quantification

Noninvasive Estimation of the Arterial Input Function in Positron Emission Tomography Imaging of Cerebral Blood Flow

Positron emission tomography (PET) with (15)O-labeled water can provide reliable measurement of cerebral blood flow (CBF). Quantification of CBF requires knowledge of the arterial input function (AIF), which is usually provided by arterial blood sampling. However, arterial sampling is invasive. Moreover, the blood generally is sampled at the wrist, which does not perfectly represent the AIF of the brain, because of the effects of delay and dispersion. We developed and validated a new noninvasive method to obtain the AIF directly by PET imaging of the internal carotid artery in a region of interest (ROI) defined by coregistered high-resolution magnetic resonance angiography. An ROI centered at the petrous portion of the internal carotid artery was defined, and the AIF was estimated simultaneously with whole brain blood flow. The image-derived AIF (IDAIF) method was validated against conventional arterial sampling. The IDAIF generated highly reproducible CBF estimations, generally in good agreement with the conventional technique.

Dynamic PET-CT studies for characterizing nasopharyngeal carcinoma metabolism

To investigate the optimal PET protocol and analytical method to characterize the glucose metabolism in nasopharyngeal carcinoma (NPC). Newly diagnosed NPC patients were recruited and a dynamic PET-CT scan was performed. The optimized threshold to derive the arterial input function (AIF) was studied. Two-tissue compartmental kinetic modeling using three, four, and five parameters, Patlak graphical analysis, and time sensitivity (S-factor) analysis were performed. The best compartmental model was determined in terms of goodness of fit, and correlated with Ki from Patlak graphical analysis and the S-factor. The methods with R>0.9 and P<0.05 were considered acceptable. The protocols using two static scans with its retention index (RI=(SUV(2)/SUV(1)-1)×100%, where SUV is the standardized uptake value) were also studied and compared with S-factor analysis. The best threshold of 0.6 was determined and used to derive AIF. The kinetic model with five parameters yields the best statistical results, but the model with k4=0 was used as the gold standard. All Ki values and some S-factors from data between various intervals (10-30, 10-45, 15-30, 15-45, 20-30, and 20-45 min) fulfilled the criteria. The RIs calculated from the S-factor were highly correlated to RI derived from simple two-point static scans at 10 and 30 min (R=0.9, P<0.0001). The Patlak graphical analyses and even a 20-min-interval S-factor analysis or simple two-point static scans were shown to be sufficient to characterize NPC metabolism, confirming the clinical feasibility of applying a short dynamic with image-derived AIF or simple two-point static PET scans for studying NPC.

Correction for non-uniform k-space data weighting effects in first-pass cardiac perfusion imaging with TurboFLASH readout

Summary To correct for non-uniform k-space data weighing on image intensity in T1-weighted first-pass cardiac perfusion MR imaging with TurboFLASH readout by using numerical simulations. Background To obtain first-pass cardiac perfusion images, a saturation-recovery (SR) preparation can be used with TurboFLASH readout. However, non-uniform k-space weighting during the SR recovery may lead to distortion of the image point spread function; this may lead to systematic overestimation or underestimation of the imagederived arterial input function (AIF) and myocardium signals, with resulting bias in the perfusion calculations. In this work, we used numerical simulations to correct for non-uniform k-space data weighting effects on the AIF and myocardial wall signals. Methods

Selection of weighting factors for quantification of PET radioligand binding using simplified reference tissue models with noisy input functions

Input function noise contributes to model-predicted values and should be accounted for during parameter estimation. This problem has been examined in the context of PET data analysis using a noisy image-derived arterial input function. Huesman and Mazoyer (1987 Phys. Med. Biol 32 1569–79) incorporated the effect of error in the measured input function into the objective function and observed a subsequent improvement in the accuracy of parameters estimated from a kinetic model of cardiac blood flow. Such a treatment has not been applied to the reference region models commonly used to analyze dynamic positron emission tomography data with receptor–ligand tracers. Here, we propose a strategy for selection of weighting factors that accounts for noise in the reference region input function and test the method on two common formulations of the simplified reference tissue model (SRTM). We present a simulation study which demonstrates that the proposed weighting approach improves the accuracy of estimated binding potential at high noise levels and when the reference tissue and target regions of interest are of comparable size. In the second simulation experiment, we show that using a small, homogeneous reference tissue with our weighting technique may have advantages over input functions derived from a larger (and thus less noisy), heterogeneous region with conventional weighting. A comparative analysis of clinical [11C]flumazenil data found a small but significant increase in estimated binding potential when using the proposed weighting method, consistent with the finding of reduced negative bias in our simulation study. The weighting strategy described here accounts for noise in the reference region input function and may improve the performance of the SRTM in applications where data are noisy and the reference region is relatively small. This technique may offer similar benefits to other models using reference region inputs, particularly those derived from the SRTM.

Image-Derived Arterial Input Function in Dynamic Positron Emission Tomography–Computed Tomography

This study aimed to study the feasibility of measuring the arterial input function (AIF) in dynamic positron emission tomography (PET) studies using both PET and computed tomographic (CT) images. Eighteen newly diagnosed patients with head and neck cancer were recruited, and dynamic PET-CT scan was performed with contrast-enhanced CT. Phantom study with PET-CT scan was also performed for partial volume effect (PVE) correction. The PET-CT AIF was measured from both PET-CT images and corrected for PVE, together with the PET AIF, which was calculated from PET images. Both AIFs were used for calculating the net flux of [18F]fluoro-2-deoxy-D-glucose, Ki, and the correlation between these 2 sets of Ki was studied by Spearman correlation. The PET-CT AIF was much larger than the PET AIF, whereas the Ki's by PET-CT AIF were much lower than the Ki's by PET AIF. However, the 2 sets of Ki were highly correlated (r = 0.969, P < 0.001). It is feasible to measure AIF in PET-CT images without blood sampling. The PET-CT AIF is very different from the PET AIF calculated by PET images only without PVE correction. The PET-CT AIF may be a better choice because the Ki by PET AIF can be overestimated.

Validation of new image-derived arterial input functions at the aorta using 18F-fluoride positron emission tomography

(i) To validate two new image-based methods for finding the plasma arterial input function (AIF) and evaluate the performance of these and two similar techniques against arterial sampling. (ii) To evaluate the performance of all four image-derived AIF (IDAIF) methods against arterial sampling for measuring the F plasma clearance (Ki) to the lumbar spine. Eight healthy postmenopausal women had a F-fluoride positron emission tomography scan of the lumbar spine. Venous blood samples were used to estimate the IDAIFs from: (i) a fixed population-based partial volume correction (PVC) factor method, (ii) a variable PVC factor method, (iii) the Chen method, and (iv) the Cook-Lodge method. Continuous arterial sampling and the respective Ki values were used as the gold standard against which the performance of the IDAIF methods was compared. The IDAIFs were compared with direct arterial sampling in terms of the area under the curve values. The percentage root mean square error in area under the curves compared with arterial sampling were: (i) fixed PVC: 12.7%, (ii) variable PVC: 12.0%, (iii) Chen: 39.0%, and (iv) Cook-Lodge: 17.3%. There were small but significant differences in the Ki values found by all four methods compared with arterial sampling. Bland-Altman plots of Ki values showed the best agreement for the variable and fixed PVC methods with a standard deviation of 0.0026 and 0.0030 ml/min/ml, respectively. The differences in the Ki values obtained at the lumbar spine using direct arterial sampling and any of the IDAIF methods at the aorta were clinically nonsignificant. The variable PVC and fixed PVC methods performed better than the Cook-Lodge and Chen methods.