Search

Purpose. The PET radiotracers 4-18F-fluoro-m-hydroxyphenethylguanidine (18F-4F-MHPG) and 3-18F-fluoro-p-hydroxyphenethylguanidine (18F-3F-PHPG) were developed for quantifying regional cardiac sympathetic nerve density using tracer kinetic analysis methods. The aim of this study was to evaluate their performance in cardiomyopathy patients.Methods: Eight cardiomyopathy patients selected for surgical placement of an implantable cardioverter defibrillator (ICD) were scanned with 18F-4F-MHPG and 18F-3F-PHPG on different days. In addition, an 13N-ammonia scan was performed to assess regional resting perfusion. The myocardial kinetics of 18F-4F-MHPG and 18F-3F-PHPG were analyzed using the Patlak graphical method to obtain Patlak slopes Kp (mL/min/g) as quantitative metrics of regional nerve density. Polar maps of the Patlak slopes were generated to map regional nerve density and to estimate the extent of cardiac denervation. For comparison purposes, regional tracer 'retention index' (RI) values (mL blood/min/mL tissue) were also calculated and used to estimate denervation extent metrics. Polar maps of resting perfusion estimates were used to estimate the pattern and extent of hypoperfusion.Results: Patlak analysis of 18F-4F-MHPG and 18F-3F-PHPG kinetics was successful in all subjects, demonstrating the robustness of this approach in cardiomyopathy patients. Substantial regional denervation was observed in all eight subjects, ranging from 25% to 74% of the left ventricle. Denervation zones were equal to or larger than the size of corresponding areas of hypoperfusion.Conclusion: 18F-4F-MHPG and 18F-3F-PHPG provide quantitative metrics of regional sympathetic nerve density and the extent of left ventricular denervation in patients with cardiomyopathy, supporting further clinical development of these agents.Trial registration: Registered at the ClinicalTrials.gov website (NCT02669563).URL: https://clinicaltrials.gov/ct2/show/NCT02669563

PURPOSE The net uptake rate constant (Ki ) derived from dynamic imaging is considered the gold standard quantification index for FDG PET. In this study, we investigated the feasibility and assessed the clinical usefulness of generating Ki images for FDG PET using only two 5-min scans with population-based input function (PBIF). METHODS Using a Siemens Biograph mCT, 10 subjects with solid lung nodules underwent a single-bed dynamic FDG PET scan and 13 subjects (five healthy and eight cancer patients) underwent a whole-body dynamic FDG PET scan in continuous-bed-motion mode. For each subject, a standard Ki image was generated using the complete 0-90 min dynamic data with Patlak analysis (t* = 20 min) and individual patient's input function, while a dual-time-point Ki image was generated from two 5-min scans based on the Patlak equations at early and late scans with the PBIF. Different start times for the early (ranging from 20 to 55 min with an increment of 5 min) and late (ranging from 50 to 85 min with an increment of 5 min) scans were investigated with the interval between scans being at least 30 min (36 protocols in total). The optimal dual-time-point protocols were then identified. Regions of interest (ROI) were drawn on nodules for the lung nodule subjects, and on tumors, cerebellum, and bone marrow for the whole-body-imaging subjects. Quantification accuracy was compared using the mean value of each ROI between standard Ki (gold standard) and dual-time-point Ki , as well as between standard Ki and relative standardized uptake value (SUV) change that is currently used in clinical practice. Correlation coefficients and least squares fits were calculated for each dual-time-point protocol and for each ROI. Then, the predefined criteria for identifying a reliable dual-time-point Ki estimation for each ROI were empirically determined as: (1) the squared correlation coefficient (R2 ) between standard Ki and dual-time-point Ki is larger than 0.9; (2) the absolute difference between the slope of the equality line (1.0) and that of the fitted line when plotting standard Ki versus dual-time-point Ki is smaller than 0.1; (3) the absolute value of the intercept of the fitted line when plotting standard Ki versus dual-time-point Ki normalized by the mean of the standard Ki across all subjects for each ROI is smaller than 10%. Using Williams' one-tailed t test, the correlation coefficient (R) between standard Ki and dual-time-point Ki was further compared with that between standard Ki and relative SUV change, for each dual-time-point protocol and for each ROI. RESULTS Reliable dual-time-point Ki images were obtained for all the subjects using our proposed method. The percentage error introduced by the PBIF on the dual-time-point Ki estimation was smaller than 1% for all 36 protocols. Using the predefined criteria, reliable dual-time-point Ki estimation could be obtained in 25 of 36 protocols for nodules and in 34 of 36 protocols for tumors. A longer time interval between scans provided a more accurate Ki estimation in general. Using the protocol of 20-25 min plus 80-85 or 85-90 min, very high correlations were obtained between standard Ki and dual-time-point Ki (R2 = 0.994, 0.980, 0.971 and 0.925 for nodule, tumor, cerebellum, and bone marrow), with all the slope values with differences ≤0.033 from 1 and all the intercept values with differences ≤0.0006 mL/min/cm3 from 0. The corresponding correlations were much lower between standard Ki and relative SUV change (R2 = 0.673, 0.684, 0.065, 0.246). Dual-time-point Ki showed a significantly higher quantification accuracy with respect to standard Ki than relative SUV change for all the 36 protocols (p

Background The aim of the study was to derive and compare metabolic parameters relating to benign and malignant pulmonary nodules using dynamic 2-deoxy-2-[fluorine-18]fluoro-D-glucose (18F-FDG) PET/CT, and nodule perfusion parameters derived through perfusion computed tomography (CT). Patients and methods Twenty patients with 21 pulmonary nodules incidentally detected on CT underwent a dynamic 18F-FDG PET/CT and a perfusion CT. The maximum standardized uptake value (SUVmax) was measured on conventional 18F-FDG PET/CT images. The influx constant (Ki ) was calculated from the dynamic 18F-FDG PET/CT data using Patlak model. Arterial flow (AF) using the maximum slope model and blood volume (BV) using the Patlak plot method for each nodule were calculated from the perfusion CT data. All nodules were characterized as malignant or benign based on histopathology or 2 year follow up CT. All parameters were statistically compared between the two groups using the nonparametric Mann-Whitney test. Results Twelve malignant and 9 benign lung nodules were analysed (median size 20.1 mm, 9–29 mm) in 21 patients (male/female = 11/9; mean age ± SD: 65.3 ± 7.4; age range: 50–76 years). The average SUVmax values ± SD of the benign and malignant nodules were 2.2 ± 1.7 vs. 7.0 ± 4.5, respectively (p = 0.0148). Average Ki values in benign and malignant nodules were 0.0057 ± 0.0071 and 0.0230 ± 0.0155 min-1, respectively (p = 0.0311). Average BV for the benign and malignant nodules were 11.6857 ± 6.7347 and 28.3400 ± 15.9672 ml/100 ml, respectively (p = 0.0250). Average AF for the benign and malignant nodules were 74.4571 ± 89.0321 and 89.200 ± 49.8883 ml/100g/min, respectively (p = 0.1613). Conclusions Dynamic 18F-FDG PET/CT and perfusion CT derived blood volume had similar capability to differentiate benign from malignant lung nodules.

Purpose Parametric imaging using the Patlak model has been shown to provide improved lesion detectability and specificity. The Patlak model requires both tissue time-activity curves (TACs) after equilibrium and knowledge of the input function from the start of injection. Therefore, the conventional dynamic scanning protocol typically starts from the radiotracer injection all the way to equilibrium. In this paper, we propose the use of hybrid population-based and model-based input function estimation and evaluate its use for whole-body Patlak analysis, in order to reduce the total scan time and simplify clinical Patlak parametric imaging protocols. Possible quantitative errors caused by the simplified scanning protocol were also analyzed both theoretically and with the use of clinical data. Materials and methods Clinical data from 24 patients referred for tumor staging were included in this study. The patients underwent a whole-body dynamic PET study, 20 min after FDG injection (0.13 mCi/kg). The proposed whole-body scanning protocol includes 6 passes with 4-5 bed positions, depending on the size of the patient, with 2 min for each bed position. An input function from the literature was selected as the shape of the population-based input function. The descending aorta from the corresponding CT image was segmented and applied on the reconstructed dynamic PET images to acquire an image-based input function, which was later fitted using an exponential model. Due to the late scan time, only the later portion of the input function was available, which was used to scale the population-based input function. The hybrid input function was used to derive the whole-body Patlak images. Assuming a given error in the population-based input function, its influence on the final Patlak images were also derived theoretically and verified using the clinical data sets. Finally, the image quality of the reconstructed Patlak slope image was evaluated by an experienced radiologist in four different aspects: image artifacts, image noise, lesion sharpness, and lesion detectability. Results It was found that errors in the population-based input function only affect the absolute scale of the Patlak slope image. The induced error is proportional to the percentage area-under-curve (AUC) error in the input function. These findings were also confirmed by numerical analysis. The predicted global scale was in good agreement with results from both image-based Patlak and direct Patlak approach. The fractions of the AUC from the early portion population-based input function were also found to be around 18% of the total AUC of the input function, further limiting the propagation of quantitation error from population-based input function to the final Patlak slope image. The reconstructed Patlak images were also found by the radiologist to provide excellent confidence in lesion detection tasks. Conclusions We have proposed a simplified whole-body scanning protocol that utilizes both population-based input function and model-based input function. The error from the population-based function was found to only affect the global scale and the overall quantitative impact can be predicted using our proposed formulas.

[18F]NaF PET imaging is a useful tool for measuring regional bone metabolism. However, due to tracer in urine, [18F]NaF PET images of the hip reconstructed using filtered back projection (FBP) frequently show streaking artifacts in slices through the bladder leading to noisy time-activity curves unsuitable for quantification. This study compares differences between quantitative outcomes at the hip derived from images reconstructed using the FBP and ordered-subset expectation maximization (OSEM) methods. Dynamic [18F]NaF PET data at the hip for four postmenopausal women were reconstructed using FBP and nine variations of the OSEM algorithm (all combinations of 1, 5, 15 iterations and 10, 15, 21 subsets). Seven volumes of interest were placed in the hip. Bone metabolism was measured using standardized uptake values, Patlak analysis (Ki-PAT) and Hawkins model Ki-4k. Percentage differences between the standardized uptake values and Ki values from FBP and OSEM images were assessed. OSEM images appeared visually smoother and without the streaking artifacts seen with FBP. However, due to loss of counts, they failed to recover the quantitative values in VOIs close to the bladder, including the femoral head and femoral neck. This was consistent for all quantification methods. Volumes of interest farther from the bladder or larger and receiving greater counts showed good convergence with 5 iterations and 21 subsets. For VOIs close to the bladder, including the femoral neck and femoral head, 15 iterations and 10, 15 or 21 subsets were not enough to obtain OSEM images suitable for measuring bone metabolism and showed no improvement compared to FBP.

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.

We aimed to develop a dynamic imaging technique for a novel PET superoxide tracer, [18F]DHMT, to allow for absolute quantification of myocardial reactive oxygen species (ROS) production in a large animal model. Six beagle dogs underwent a single baseline dynamic [18F]DHMT PET study, whereas one animal underwent three serial dynamic studies over the course of chronic doxorubicin administration (1 mg·kg−1·week−1 for 15 weeks). During the scans, sequential arterial blood samples were obtained for plasma metabolite correction. The optimal compartment model and graphical analysis method were identified for kinetic modeling. Values for the left ventricular (LV) net influx rate, Ki, were reported for all the studies and compared with the LV standard uptake values (SUVs) and the LV-to-blood pool SUV ratios from the 60 to 90 minute static images. Parametric images were also generated. [18F]DHMT followed irreversible kinetics once oxidized within the myocardium in the presence of superoxide, as evidenced by the fitting generated by the irreversible two-tissue (2Ti) compartment model and the linearity of Patlak analysis. Myocardial Ki values showed a weak correlation with LV SUV (R2 = 0.27), but a strong correlation with LV-to-blood pool SUV ratio (R2 = 0.92). Generation of high-quality parametric images showed superior myocardial to blood contrast compared to static images. A dynamic PET imaging technique for [18F]DHMT was developed with full and simplified kinetic modeling for absolute quantification of myocardial superoxide production in a large animal model.

Pulmonary arterial hypertension (PAH) is a recognized complication of systemic lupus erythematosus (SLE-PAH) patients and its lung pathology shares similarity to idiopathic PAH (IPAH) with distinctive inflammatory feature. FDG-PET reports glucose metabolism from both hyperproliferative and inflammatory cellular elements of vascular pathology in PAH. We explored the application of FDG-PET in reporting SLE-PAH pulmonary vascular pathology. Sixty-minute dynamic FDG-PET imaging was applied in 14 SLE-PAH patients, 20 IPAH patients and 10 healthy volunteers. Patlak analysis was used to quantify lung FDG uptake (influx rate Ki). Mean lung FDG uptake in SLE-PAH (Ki 0.00714 ± 0.000602 mL/g/min) was significantly higher than that of the healthy volunteers (Ki 0.000262 ± 0.000168 mL/g/min) (p

Radiographic changes of brain metastases after stereotactic radiosurgery (SRS) can signify tumor recurrence and/or radiation necrosis (RN); however, standard imaging modalities cannot easily distinguish between these two entities. We investigated whether 18F-Fluorocholine uptake in surgical samples of the resected lesions correlates with pathologic evidence of recurrent tumor and PET imaging. About 14 patients previously treated with SRS that developed radiographic changes were included. All patients underwent a preoperative 40-min dynamic PET/CT concurrent with 392 ± 11 MBq bolus injection of 18F-Fluorocholine. 18F-Fluorocholine pharmacokinetics were evaluated by standardized uptake value (SUV), graphical analysis (Patlak plot; KiP) and an irreversible two-compartment model (K1, k2, k3, and Ki). 12 out of 14 patients were administered an additional 72 ± 14 MBq injection of 18F-Fluorocholine 95 ± 26 minutes prior to surgical resection. About 113 resected samples from 12 patients were blindly reviewed by a neuropathologist to assess the viable tumor and necrotic content, microvascular proliferation, reactive gliosis, and mono- and polymorphonuclear inflammatory infiltrates. Correlation between these metrics 18F-Fluorocholine SUV was investigated with a linear mixed model. Comparison of survival distributions of two groups of patients (population median split of PET SUVmax) was performed with the log-rank test. Exactly 10 out of 12 patients for which surgical samples were acquired exhibited pathologic recurrence. Strong correlation was observed between SUVmax as measured from a surgically removed sample with highest uptake and by PET (Pearson’s r = 0.66). Patients with 18F-Fluorocholine PET SUVmax > 6 experienced poor survival. Surgical samples with viable tumor had higher 18F-fluorocholine uptake (SUV) than those without tumor (4.5 ± 3.7 and 2.6 ± 3.0; p = 0.01). 18F-fluorocholine count data from surgical samples is driven not only by the percentage viable tumor but also by the degree of inflammation and reactive gliosis (p ≤ 0.02; multivariate regression). 18F-Fluorocholine accumulation is increased in viable tumor; however, inflammation and gliosis may also lead to elevated uptake. Higher 18F-Fluorocholine PET uptake portends worse prognosis. Kinetic analysis of dynamic 18F-Fluorocholine PET imaging supports the adequacy of the simpler static SUV metric.

Abstract Whole-body Patlak images can be obtained from an acquisition of first 6 min of dynamic imaging over the heart to obtain the arterial input function (IF), followed by multiple whole-body sweeps up to 60 min pi. The use of a population-averaged IF (PIF) could exclude the first dynamic scan and minimize whole-body sweeps to 30–60 min pi. Here, the effects of (incorrect) PIFs on the accuracy of the proposed Patlak method were assessed. In addition, the extent of mitigating these biases through rescaling of the PIF to image-derived IF values at 30–60 min pi was evaluated. Methods Using a representative IF and rate constants from the literature, various tumour time-activity curves (TACs) were simulated. Variations included multiplication of the IF with a positive and negative gradual linear bias over 60 min of 5, 10, 15, 20, and 25% (generating TACs using an IF different from the PIF); use of rate constants (K1, k3, and both K1 and k2) multiplied by 2, 1.5, and 0.75; and addition of noise (μ = 0 and σ = 5, 10 and 15%). Subsequent Patlak analysis using the original IF (representing the PIF) was used to obtain the influx constant (Ki) for the differently simulated TACs. Next, the PIF was scaled towards the (simulated) IF value using the 30–60-min pi time interval, simulating scaling of the PIF to image-derived values. Influence of variabilities in IF and rate constants, and rescaling the PIF on bias in Ki was evaluated. Results Percentage bias in Ki observed using simulated modified IFs varied from − 16 to 16% depending on the simulated amplitude and direction of the IF modifications. Subsequent scaling of the PIF reduced these Ki biases in most cases (287 out of 290) to Conclusions Simulations suggest that scaling of a (possibly incorrect) PIF to IF values seen in whole-body dynamic imaging from 30 to 60 min pi can provide accurate Ki estimates. Consequently, dynamic Patlak imaging protocols may be performed for 30–60 min pi making whole-body Patlak imaging clinically feasible.

Purpose The purpose of this study is to compare dynamic and static whole-body (WB) [18F]NaF PET/CT scan methods used for analysis of bone plasma clearance in patients with chronic kidney disease-mineral and bone disorder (CKD-MBD). Methods Seventeen patients with CKD-MBD underwent a 60-min dynamic scan followed by a 30-min static WB scan. Tracer kinetics in four thoracic vertebrae were analysed using nonlinear regression and Patlak analysis using image-derived arterial input functions. The static WB scan was analysed using a simplified Patlak method requiring only a single data point in combination with a fixed y-intercept value (V0), both obtained using a semi-population function. The semi-population function was constructed by combining a previously derived population input function in combination with data from venous blood samples. Static WB scan analysis data, obtained from the semi-population input functions, was compared with paired data obtained using dynamic input functions. Results Bone plasma clearance (Ki) from Patlak analyses correlated well with nonlinear regression analysis, but Ki results using Patlak analysis were lower than Ki results using nonlinear regression analysis. However, no significant difference was found between Ki obtained by static WB scans and Ki obtained by dynamic scans using nonlinear regression analysis (p = 0.29). Conclusion Bone plasma clearance measured from static WB scans correlates with clearance data measured by dynamic analysis. Static [18F]NaF PET/CT scans can be applied in future studies to measure Ki in patients with CKD-MBD, but the results should not be compared uncritically with results obtained by dynamic scan analysis.

Objectives68Ga-P15-041 (68Ga-HBED-CC-BP) is a novel bone-seeking PET radiotracer, which can be readily prepared by using a simple kit formulation and an in-house 68Ga/68Ge generator. The aim of this study is to assess the potential human application of 68Ga-P15-041 for clinical PET/CT imaging and to compare its efficacy to detect bone metastases of different cancers with 99mTc-MDP whole-body bone scintigraphy (WBBS).MethodsInitial kinetic study using Patlak analysis and parametric maps were performed in five histopathologically proven cancer patients (three males, two females) using 68Ga-P15-041 PET/CT scan only. Another group of 51 histopathologically proven cancer patients (22 males, 29 females) underwent both 99mTc-MDP WBBS and 68Ga-P15-041 PET/CT scans within a week, sequentially. Using either pathology examination or follow-up CT or MRI scans as the gold standard, the diagnostic efficacy and receiver operating characteristic curve (ROC) of the two methods in identifying bone metastases were compared (p ResultsFifty-one patients were imaged, and 174 bone metastatic sites were identified. 68Ga-P15-041 PET/CT and 99mTc-MDP WBBS detected 162 and 81 metastases, respectively. Sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 68Ga-P15-041 PET/CT and 99mTc-MDP WBBS were 93.1% vs 81.8%, 89.8% vs 90.7%, 77.5% vs 69.2%, 97.2% vs 93.4% and 90.7% vs 88.4%, respectively. Our results showed that the mean of SUVmax was significantly higher in metastases than that in benign lesions, 15.1 ± 6.9 vs. 5.6 ± 1.3 (P Conclusions68Ga-P15-041 PET/CT, offering a rapid bone scan and high contrast images in minutes, is superior to the current method of choice in detecting bone metastases. It is reasonable to suggest that 68Ga-P15-041 PET/CT could become a valuable routine nuclear medicine procedure in providing excellent images for detecting bone metastases in cancer patients. 68Ga-P15-041 could become a valuable addition expanding the collection of 68Ga-based routine nuclear medicine procedures where 18F fluoride is not currently available.

OBJECTIVE: 11C-metomidate (11C-MTO) PET-computed tomography (CT) imaging has shown good sensitivity and specificity for the classification of bilateral or unilateral overexpression of aldosterone. This work seeks to investigate the usefulness of parametric maps via kinetic modeling of 11C-metomidate data into the clinical diagnosis pathway. METHODS: Twenty-five patients were injected with 172 ± 12 MBq of 11C-metomidate and a dynamic PET scan performed of the adrenal glands. A blood time-activity curve was drawn from a volume of interest in the left ventricle and converted to a plasma time-activity curve. Metabolite correction was performed with a population-based correction. We performed regional-based graphical Patlak analysis to calculate the regional uptake rate constant Ki(REG), and also calculated parametric maps of Ki(VOX) using a voxel-based technique. RESULTS: Comparison of Ki(REG), and the maximum lesion voxel from parametric maps Ki(mVOX) demonstrated a high correlation for all subjects (r2 = 0.96). Ki(mVOX) allowed differentiation between cases of active and inactive unilateral adenoma when compared to bilateral hyperplasia (P < 0.017), a feature not observed with standardized uptake ratios (SUVmax) analysis. Ki(mVOX) demonstrated a poor correlation of 0.68 with SUVmax, indicating the differences through the use of static and dynamic imaging. Three false-negative cases based on SUV analysis indicated that Ki(mVOX) was able to successfully differentiate the clinical presentation for these cases. CONCLUSION: Our work demonstrates that parametric Ki(VOX) was able to successfully differentiate between patients with bilateral hyperplasia and patients with unilateral adrenal adenoma in our cohort and that Ki may be considered be an additional useful metric to SUV in 11C-metomidate PET-CT imaging.

Dynamic contrast CT with Patlak plot analysis can be used to determine the glomerular filtration rate (GFR). However, several studies have shown different GFR values and they are most likely less than the values by the standard techniques. The purpose of this prospective, experimental, and method comparison study was to evaluate the GFR using a CT technique (CT-GFR) in 12 healthy dogs compared to serum iohexol clearance (SIC-GFR). All dogs were anesthetized and placed in the right lateral recumbency position and the caudal part was lifted inside the CT gantry. A single-slice dynamic CT of the aorta and both kidneys was scanned sequentially every 2 s for 2 min after a bolus injection (3 mL/s) of iohexol (300 mg/kg). Time attenuation curves (TAC) were constructed and the GFR per volume of kidney was calculated using the Patlak plot analysis method based on 30-120 s time intervals, and results were compared to global GFR from SIC that was determined with eight blood samples for up to 240 min. The CT-GFR value (1.85 ± 0.48 mL/min/kg) was significantly less than the SIC-GFR value (3.40 ± 0.80 mL/min/kg; P

Routine clinical use of absolute PET quantification techniques is limited by the need for serial arterial blood sampling for input function and more importantly by the lack of automated pharmacokinetic analysis tools that can be readily implemented in clinic with minimal effort. PET/MRI provides the ability for absolute quantification of PET probes without the need for serial arterial blood sampling using image-derived input functions (IDIFs). Here we introduce caliPER, a modular and scalable software for simplified pharmacokinetic modelling of PET probes with irreversible uptake or binding based on PET/MR IDIFs and Patlak Plot analysis. caliPER generates regional values or parametric maps of net influx rate (Ki) using reconstructed dynamic PET images and anatomical MRI aligned to PET for IDIF vessel delineation. We evaluated the performance of caliPER for blood-free region-based and pixel-wise Patlak analyses of [18F] FDG by comparing caliPER IDIF to serial arterial blood input functions and its application in imaging brain glucose hypometabolism in Frontotemporal dementia. IDIFs corrected for partial volume errors including spill-out and spill-in effects were similar to arterial blood input functions with a general bias of around 6-8%, even for arteries Ki and cerebral metabolic rate of glucose estimated using caliPER IDIF were similar to estimates using arterial blood sampling (HighlightscaliPER is an adaptable image processing software for extracting image-derived input functions and generating parametric maps of irreversible PET tracer uptake.Anatomical (T1-weighted/T2-weighted/time-of-flight angiography) MRI carefully aligned to PET provides a robust approach for delineation of vessels on PET, eliminating the need for serial blood sampling for input functions.Application of caliPER in modelling glucose uptake in patients with Frontotemporal dementia, demonstrates the feasibility of absolute quantification of cerebral metabolic rate of glucose in clinical populations.

This study characterizes the error that results when performing quantitative analysis of abbreviated dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data of the breast with the Standard Kety–Tofts (SKT) model and its Patlak variant. More specifically, we used simulations and patient data to determine the accuracy with which abbreviated time course data could reproduce the pharmacokinetic parameters, Ktrans (volume transfer constant) and ve (extravascular/extracellular volume fraction), when compared to the full time course data. SKT analysis of simulated abbreviated time courses (ATCs) based on the imaging parameters from two available datasets (collected with a 3T MRI scanner) at a temporal resolution of 15 s (N = 15) and 7.23 s (N = 15) found a concordance correlation coefficient (CCC) greater than 0.80 for ATCs of length 3.0 and 2.5 min, respectively, for the Ktrans parameter. Analysis of the experimental data found that at least 90% of patients met this CCC cut-off of 0.80 for the ATCs of the aforementioned lengths. Patlak analysis of experimental data found that 80% of patients from the 15 s resolution dataset and 90% of patients from the 7.27 s resolution dataset met the 0.80 CCC cut-off for ATC lengths of 1.25 and 1.09 min, respectively. This study provides evidence for both the feasibility and potential utility of performing a quantitative analysis of abbreviated breast DCE-MRI in conjunction with acquisition of current standard-of-care high resolution scans without significant loss of information in the community setting.

Background PET (positron emission tomography) biokinetic modelling relies on accurate quantitative data. One of the main corrections required in PET imaging to obtain high quantitative accuracy is tissue attenuation correction (AC). Incorrect non-uniform PET-AC may result in local bias in the emission images, and thus in relative activity distributions and time activity curves for different regions. MRI (magnetic resonance imaging)-based AC is an active area of research in PET/MRI neuroimaging, where several groups developed in the last few years different methods to calculate accurate attenuation (μ-)maps. Some AC methods have been evaluated for different PET radioisotopes and pathologies. However, AC in PET/MRI has scantly been investigated in dynamic PET studies where the aim is to get quantitative kinetic parameters, rather than semi-quantitative parameters from static PET studies. In this work, we investigated the impact of AC accuracy in PET image absolute quantification and, more importantly, in the slope of the Patlak analysis based on the simplified reference tissue model, from a dynamic [18F]-fluorodopa (FDOPA) PET/MRI study. In the study, we considered the two AC methods provided by the vendor and an in-house AC method based on the dual ultrashort time echo MRI sequence, using as reference a multi-atlas-based AC method based on a T1-weighted MRI sequence. Results Non-uniform bias in absolute PET quantification across the brain, from − 20% near the skull to − 10% in the central region, was observed using the two vendor’s μ-maps. The AC method developed in-house showed a − 5% and 1% bias, respectively. Our study resulted in a 5–9% overestimation of the PET kinetic parameters with the vendor-provided μ-maps, while our in-house-developed AC method showed

2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) has been widely used for imaging brain metabolism. Tracer injection in anesthetized animals is a prerequisite for performing dynamic positron emission tomography (PET) scanning. Since preconditioning, as well as anesthesia, has been described to potentially influence brain [18F] FDG levels, this study evaluated how these variables globally and regionally affect both [18F] FDG uptake and kinetics in murine brain. Sixty-minute dynamic [18F] FDG PET scans were performed in adult male C57BL/6 mice anesthetized with isoflurane [control (in 100 % O2), in medical air, in 100 % O2 + insulin pre-treatment, and in 100 % O2 after 18 h fasting], ketamine/xylazine, sevoflurane, and chloral hydrate. An additional group was scanned after awake uptake. Blood glucose levels were determined, and data was analyzed by comparing percent injected dose per cc tissue (%ID/cc) and glucose influx rate and metabolic rate (MRGlu) calculated by Patlak plot. Ketamine/xylazine and chloral hydrate anesthesia induced a lower whole-brain uptake of [18F] FDG (2.86 ± 0.67 %ID/cc, p

Objectives To assess the feasibility of a novel functional perfusion model based on enhanced computed tomography (CT) for the evaluation of split renal function and orientation of segmental renal artery clamping during laparoscopic partial nephrectomy (LPN). Materials and Methods From December 2016 to November 2017, functional perfusion model was applied in 91 patients with T1a renal tumors who had undergone LPN with segmental renal artery clamping. Split computed tomographic-glomerular filtration rate (CT-GFR) was calculated using the 2-point Patlak plot technique. Parenchymal perfusion areas of segmental renal arteries were marked, and target segmental arteries were determined by the perfusion areas wherein tumors were confined. LPN with precise segmental renal artery clamping was performed based on the novel model. Correlations between CT-GFR and estimated GFR and radioisotope GFR were analyzed using Pearson's method. Intraoperative ischemic status and surgical outcomes were assessed. Results Mean tumor size was 2.9cm. Large tumors were accompanied by more feeding lobar arteries than segmental arteries. CT-GFR was strongly correlated with estimated GFR (r = 0.70) and radioisotope GFR (r = 0.88). All LPNs were successful without converting to main renal artery clamping. Mean operation time was 81.8 minutes; median estimated blood loss was 120mL. The actual parenchymal ischemic region observed during the operation was consistent with the prediction of the perfusion model in all patients. No arterial bleeding or other uncontrollable defect bleeding occurred during tumor resection. Conclusion This model is a reliable method for the determination of split renal function and orientation of segmental artery clamping during LPN.

BackgroundBlood–brain barrier (BBB) disruption has been noted in animal models of Parkinson’s disease (PD) and forms the basis of the vascular hypothesis of neurodegeneration, yet clinical studies are lacking.ObjectiveTo determine alterations in BBB integrity in PD, with comparison to cerebrovascular disease.MethodsDynamic contrast enhanced magnetic resonance images were collected from 49 PD patients, 15 control subjects with cerebrovascular disease [control positive (CP)] and 31 healthy control subjects [control negative (CN)], with all groups matched for age. Quantitative maps of the contrast agent transfer coefficient across the BBB (Ktrans) and plasma volume (vp) were produced using Patlak analysis. Differences in Ktrans and vp were assessed with voxel-based analysis as well as in regions associated with PD pathophysiology. In addition, the volume of white matter lesions (WMLs) was obtained from T2-weighted fluid attenuation inversion recovery (FLAIR) images.ResultsHigher Ktrans, reflecting higher BBB leakage, was found in the PD group than in the CN group using voxel-based analysis; differences were most prominent in the posterior white matter regions. Region of interest analysis confirmed Ktrans to be significantly higher in PD than in CN, predominantly driven by differences in the substantia nigra, normal-appearing white matter, WML and the posterior cortex. WML volume was significantly higher in PD compared to CN. Ktrans values and WML volume were similar in PD and CP, suggesting a similar burden of cerebrovascular disease despite lower cardiovascular risk factors.ConclusionThese results show BBB disruption in PD.

BackgroundArterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic18F-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 estimatedCP*(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 Feng18F-FDG plasma concentration model was applied to estimate AIF parameters (n= 23). AIF normalization used either AUC(0–60 min) orCP*(0), estimated from an exponential fit.CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV).iDVwas 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 estimatedCP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and PatlakKivalues.ResultsThe IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC andKicomparison, 30–60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimatedKi(− 6 ± 8 to − 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30–60), and PBIFiDVwere 0.91, 0.94, and 0.90, respectively. The bias ofKiwas − 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.

Background Arterial 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. Methods The 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. Results The 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. Conclusions Both 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.

1406 Purpose: FDG uptake rate constant Ki is a main physiology parameter measured by dynamic PET study. A model-independent graphical analysis using Patlak plot with plasma input function is a standard approach used to estimate Ki. The plasma input function is the FDG time activity curve in plasma obtained by arterial blood sampling. The purpose of the study is to evaluate aPatlak plot-based optimization approach for noninvasive quantification of dynamic FDG PET. Methods: Eight 60-min monkey dynamic FDG PET studies with arterial blood samples were collected. The measured plasma input function (mPIF) was determined by arterial blood samples. Time activity curves of seven cerebral regions of interest were generated from each study. With a given number of blood samples, the estimated PIF (ePIF) was determined by either interpolation or extrapolation method using scale calibrated population mean of normalized PIF. The optimal time points for those blood samples to estimate PIF (ePIF) was determined by maximizing the correlations between the Ki estimated ePIF and ones estimated mPIF. A leave-two-out cross-validation method was used for evaluation. Results: The linear correlations between the Ki estimates from ePIF with optimal sampling schemes and those from measured PIF were: Ki (ePIF 1 sample) = 1.09 Ki (mPIF) - 0.00, R2 =0.95±0.08; Ki (ePIF 2 samples) = 1.09 Ki (mPIF) - 0.00, R2 =0.95±0.07; Ki (ePIF 3 samples) = 1.04 Ki (mPIF) - 0.00, R2 =0.96±0.05; and Ki (ePIF 4 samples) = 1.02 Ki (mPIF)-0.00, R2 =0.97±0.04. As sample size became greater or equal 4, the Ki estimates from ePIF with optimal protocol were almost identical to those from mPIF. Conclusions: The Patlak plot-based optimization approach is a robust method to estimate plasma input function for noninvasive quantification of non-human primate dynamic FDG PET. KEYWORDSFDG PET; Patlak plot; plasma input function; quantification

Purpose This study aimed to prospectively assess the effects of changes in analytic variables and contrast material (CM) osmolality when measuring glomerular filtration rate using computed tomography (CT-GFR). Methods One hundred healthy participants were included in this analysis. Glomerular filtration rate was measured by technetium-99m diethylene-triamine-penta-acetic acid (Tc-DTPA), and each participant underwent CT-GFR with iodinated CM (iohexol 240 or iobitridol 400) following a crossover study design. Dynamic renal CT scanning was performed. Patlak plot analysis was used to calculate GFR, selecting either the renal cortex or the whole kidney as the region of interest. The renal cortex was analyzed just before time of the second cortical attenuation peak. The whole kidney was analyzed 60, 80, 100, and 120 seconds after the appearance of CM. Automated GFR calculations were performed using perfusion software at 2 noise reduction levels (medium and strong). The CT-GFRs were compared with GFR measured by Tc-DTPA. Results There was no significant difference in CT-GFR with iohexol 240 versus iobitridol 400. The CT-GFR at the renal cortex, for the whole kidney 60 seconds after appearance of CM and calculated by perfusion software with medium noise reduction, did not differ significantly from GFR measured by Tc-DTPA. Whole-kidney CT-GFR at ≥80 seconds after CM appearance and CT-GFR calculated using perfusion CT software with strong noise reduction were lower when compared with GFR measured by Tc-DTPA. Conclusion Results from CT-GFR were most accurate when the kidney cortex was selected as the region of interest or when using 60-second time point for whole-kidney assessment, regardless of CM osmolarity.

Monoacylglycerol lipase (MAGL) is a main regulator of the endocannabinoid system within the central nervous system (CNS). Recently, [11C]SAR127303 was developed as a promising radioligand for MAGL imaging. In this study, we aimed to quantify regional MAGL concentrations in the rat brain using positron emission tomography (PET) with [11C]SAR127303. An irreversible two-tissue compartment model (2-TCMi, k4 = 0) analysis was conducted to estimate quantitative parameters (k3, Ki2-TCMi, and λk3). These parameters were successfully obtained with high identifiability ( striatum > hippocampus > thalamus > cerebellum > hypothalamus ≈ pons. In vitro autoradiographs using [11C]SAR127303 showed a heterogeneous distribution of radioactivity, as seen in the PET images. The Ki2-TCMi and λk3 values correlated relatively highly with in vitro binding (r > 0.4, P

Purpose: An important issue in rodent imaging is the question whether a mixed population of male and female animals can be used rather than animals of a single sex. For this reason, the present study examined the test-retest stability of positron emission tomography (PET) with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) in male rats and female rats at different phases of the estrous cycle. Procedures: Long–Evans rats (age 1 year) were divided into three groups: (1) males (n = 6), (2) females in metestrous (low estrogen levels, n = 9), and (3) females in proestrous (high estrogen levels, n = 7). Two standard [18F]FDG scans with rapid arterial blood sampling were made at an interval of 10 days in subjects anesthetized with isoflurane and oxygen. Body temperature, heart rate, and blood oxygenation were continuously monitored. Regional cerebral metabolic rates of glucose were calculated using a Patlak plot with plasma radioactivity as input function. Results: Regional metabolic rate of glucose (rCMRglucose) in male and female rats, or [18F]FDG uptake in females at proestrous and metestrous, was not significantly different, but females showed significantly higher standardized uptake values (SUVs) and Patlak flux than males, particularly in the initial scan. The relative difference between the scans and the test-retest variability (TRV) were greater in females than in males. Intra-class correlation coefficients (ICCs) of rCMRglucose, SUV, normalized SUV, and glucose flux were good to excellent in males but poor to moderate in females. Conclusions: Based on these data for [18F]FDG, the mixing of sexes in imaging studies of the rodent brain will result in an impaired test-retest stability of PET data and a need for larger group sizes to maintain statistical power in group comparisons. The observed differences between males and females do not indicate any specific gender difference in cerebral metabolism but are related to different levels of non-radioactive glucose in blood plasma during isoflurane anesthesia.

PURPOSE: To quantitatively evaluate the minimally required scanning time of 3′-deoxy-3′-[(18)F]fluorothymidine ([(18)F]FLT) positron emission tomography (PET) dynamic acquisition for accurate kinetic assessment of the proliferation in breast cancer tumors. PROCEDURES: Within a therapeutic intervention trial, 26 breast tumors of 8 breast cancer patients were analyzed from 30-min dynamic [(18)F]FLT-PET acquisitions. PET/CT was acquired on a Gemini TF 64 system (Philips Healthcare) and reconstructed into 26 frames (8 × 15 s, 6 × 30 s, 5 × 1 min, 5 × 2 min, and 2 × 5 min). Maximum activity concentrations (Bq/ml) of volume of interests over tumors and plasma in descending aorta were obtained over time frames. Kinetic parameters were estimated using in-house developed software with the two-tissue three-compartment irreversible model (2TCM) (K(1), k(2), k(3), and K(i); k(4) = 0) and Patlak model (K(i)) based on different acquisition durations (T(d)) (10, 12, 14, 16, 20, 25, and 30 min, separately). Different linear regression onset time (T(0)) points (1, 2, 3, 4, and 5 min) were applied in Patlak analysis. K(i) of the 30-min data set was taken as the gold standard for comparison. Pearson product-moment correlation coefficient (R) of 0.9 was chosen as a limit for the correlation. RESULTS: The correlation of kinetic parameters between the gold standard and the abbreviated dynamic data series increased with longer T(d) from 10 to 30 min. k(2) and k(3) using 2TCM and K(i) using Patlak model revealed poor correlations for dynamic PET with T(d) ≤ 14 min (k(2): R = 0.84, 0.85, 0.86; k(3): R = 0.67, 0.67, 0.67; K(i): R = 0.72, 0.78, 0.87 at T(d) = 10, 12, and 14 min, respectively). Excellent correlations were shown for all kinetic parameters when T(d) ≥ 16 min regardless of the kinetic model and T(0) value (R > 0.9). CONCLUSIONS: This study indicates that a 16-min dynamic PET acquisition appears to be sufficient to provide accurate [(18)F]FLT kinetics to quantitatively assess the proliferation in breast cancer lesions.

Background A method was developed to assess the kidney parameters glomerular filtration rate (GFR) and effective renal plasma flow (ERPF) from 2-deoxy-2-[18F]fluoro-d-glucose (FDG) concentration behavior in kidneys, measured with positron emission tomography (PET) scans. Twenty-four healthy adult subjects prospectively underwent dynamic simultaneous PET/magnetic resonance imaging (MRI) examination. Time activity curves (TACs) were obtained from the dynamic PET series, with the guidance of MR information. Patlak analysis was performed to determine the GFR, and based on integrals, ERPF was calculated. Results were compared to intra-individually obtained reference values determined from venous blood samples. Results Total kidney GFR and ERPF as estimated by dynamic PET/MRI were highly correlated to their reference values (r = 0.88/p

The aim of this study was to investigate the value of pharmacokinetic modeling for quantifying (11)C-choline uptake in patients with recurrent prostate cancer. Methods: In total, 194 patients with clinically suspected recurrence of prostate cancer underwent (11)C-choline dynamic PET over the pelvic region (0–8 min), followed by a 6-min static acquisition at about 25 min after injection. Regions of interest were drawn over sites of disease identified by a radiologist with experience in nuclear medicine. (11)C-choline uptake and pharmacokinetics were evaluated by SUV, graphical analysis (Patlak plot; K(i)(P)), and 1- and 2-compartment pharmacokinetic models (K(1), K(1)/k(2), k(3), k(4), and the macro parameter K(i)(C)). Twenty-four local recurrences, 65 metastatic lymph nodes, 19 osseous metastases, and 60 inflammatory lymph nodes were included in the analysis, which was subsequently repeated for regions of interest placed over the gluteus maximus muscle and adipose tissue as a control. Results: SUV(mean) and K(i)(P) were 3.60 ± 2.16 and 0.28 ± 0.22 min(−1) in lesions, compared with 2.11 ± 1.33 and 0.15 ± 0.10 min(−1) in muscle and 0.26 ± 0.07 and 0.02 ± 0.01 min(−1) in adipose tissue. According to the Akaike information criterion, the 2-compartment irreversible model was most appropriate in 85% of lesions and resulted in a K(1) of 0.79 ± 0.98 min(−1) (range, 0.11–7.17 min(−1)), a K(1)/k(2) of 2.92 ± 3.52 (range, 0.31–20.00), a k(3) of 0.36 ± 0.30 min(−1) (range, 0.00–1.00 min(−1)) and a K(i)(C) of 0.28 ± 0.22 min(−1) (range, 0.00–1.33 min(−1)). The Spearman ρ between SUV and K(i)(P), between SUV and K(i)(C), and between K(i)(P) and K(i)(C) was 0.94, 0.91, and 0.97, respectively, and that between SUV and K(1), between SUV and K(1)/k(2), and between SUV and k(3) was 0.70, 0.44, and 0.33, respectively. Malignant lymph nodes exhibited a higher SUV, K(i)(P), and K(i)(C) than benign lymph nodes. Conclusion: Although (11)C-choline pharmacokinetic modeling has potential to uncouple the contributions of different processes leading to intracellular entrapment of (11)C-choline, the high correlation between SUV and both K(i)(P) and K(i)(C) supports the use of simpler SUV methods to evaluate changes in (11)C-choline uptake and metabolism for treatment monitoring.