Noninvasive estimation of the aorta input function for measurement of tumor blood flow with

Simulation of a novel, non-invasive radiation detector to measure the arterial input function for dynamic positron emission tomography

BACKGROUND

Dynamic positron emission tomography (dPET) is a nuclear medicine imaging technique providing functional images for organs of interest with applications in oncology, cardiology, and drug discovery. This technique requires the acquisition of the time-course arterial plasma activity concentration, called the arterial input function (AIF), which is conventionally acquired via arterial blood sampling.

PURPOSE

The aim of this study was to (A) optimize the geometry for a novel and cost efficient non-invasive detector called NID designed to measure the AIF for dPET scans through Monte Carlo simulations and (B) develop a clinical data analysis chain to successfully separate the arterial component of a simulated AIF signal from the venous component.

METHODS

The NID was optimized by using an in-house Geant4-based software package. The sensitive volume of the NID consists of a band of 10 cm long and 1 mm in diameter scintillating fibers placed over a wrist phantom. The phantom was simulated as a cylinder, 10 cm long and 6.413 cm in diameter comprised of polyethylene with two holes placed through it to simulate the patient's radial artery and vein. This phantom design was chosen to match the wrist phantom used in our previous proof of concept work. Two geometries were simulated with different arrangements of scintillating fibers. The first design used a single layer of 64 fibers. The second used two layers, an inner layer with 29 fibers and an outer layer with 30 fibers. Four positron emitting radioisotopes were simulated: ¹⁸ F, ¹¹ C, ¹⁵ O, and ⁶⁸ Ga with 100 million simulated decay events per run. The total and intrinsic efficiencies of both designs were calculated as well as the full width half maximum (FWHM) of the signal. In addition, contribution by the annihilation photons versus positrons to the signal was investigated. The results obtained from the two simulated detector models were compared. A clinical data analysis chain using an expectation maximization maximum likelihood algorithm was tested. This analysis chain will be used to separate arterial counts from the total signal.

RESULTS

The second NID design with two layers of scintillating fibers had a higher efficiency for all simulations with a maximum increase of 17% total efficiency for ¹¹ C simulation. All simulations had a significant annihilation photon contribution. The signal for ¹⁸ F and ¹¹ C was almost entirely due to photons. The clinical data analysis chain was within 1% of the true value for 434 out of 440 trials. Further experimental studies to validate these simulations will be required.

CONCLUSIONS

The design of the NID was optimized and its efficiency increased through Monte Carlo simulations. A clinical data analysis chain was successfully developed to separate the arterial component of an AIF signal from the venous component. The simulations show that the NID can be used to accurately measure the AIF non-invasively for dPET scans.

Patient-Adaptive Population-Based Modeling of Arterial Input Functions

Kinetic modeling of dynamic PET data requires knowledge of tracer concentration in blood plasma, described by the arterial input function (AIF). Arterial blood sampling is the gold standard for AIF measurement, but is invasive and labour intensive. A number of methods have been proposed to accurately estimate the AIF directly from blood sampling and/or imaging data. Here we consider fitting a patient-adaptive mixture of historical population time course profiles to estimate individual AIFs. Travel time of a tracer atom from the injection site to the right ventricle of the heart is modeled as a realization from a Gamma distribution, and the time this atom spends in circulation before being sampled is represented by a subject-specific linear mixture of population profiles. These functions are estimated from independent population data. Individual AIFs are obtained by projection onto this basis of population profile components. The model incorporates knowledge of injection duration into the fit, allowing for varying injection protocols. Analyses of arterial sampling data from 18F-FDG, 15O-H2O and 18F-FLT clinical studies show that the proposed model can outperform reference techniques. The statistically significant gain achieved by using population data to train the basis components, instead of fitting these from the single individual sampling data, is measured on the FDG cohort. Kinetic analyses of simulated data demonstrate the reliability and potential benefit of this approach in estimating physiological parameters. These results are further supported by numerical simulations that demonstrate convergence and stability of the proposed technique under varying training population sizes and noise levels.

Population-based input function for TSPO quantification and kinetic modeling with [11C]-DPA-713

INTRODUCTION

Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF.

MATERIALS AND METHODS

Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected, (b) area under AIF curve (AUC), and (c) Weightsubject×AUC. The variability in the VT measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed.

RESULTS

Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is -10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ± 38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%).

CONCLUSIONS

PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

Cross-validation of a non-invasive positron detector to measure the arterial input function for pharmacokinetic modelling in dynamic positron emission tomography

Kinetic modeling of positron emission tomography (PET) data can assess index rate of uptake, metabolism and predict disease progression more accurately than conventional static PET. However, it requires knowledge of the time-course of the arterial blood radioactivity concentration, called the arterial input function (AIF). The gold standard to acquire the AIF is by invasive means. The purpose of this study was to validate a previously developed dual readout scintillating fiber-based non-invasive positron detector, hereinafter called non-invasive detector (NID), developed to determine the AIF for dynamic PET measured from the human radial artery. The NID consisted of a 3 m long plastic scintillating fiber with each end coupled to a 5 m long transmission fiber followed by a silicon photomultiplier. The scintillating fiber was enclosed inside the grooves of a plastic cylindrical shell. Two sets of experiments were performed to test the NID against a previously validated microfluidic positron detector. A closed-loop microfluidic system combined with a wrist phantom was used. During the first experiment, the three PET radioisotopes ¹⁸F, ¹¹C and ⁶⁸Ga were tested. After optimizing the detector, a second series of tests were performed using only ¹⁸F and ¹¹C. The maximum pulse amplitude to electronic noise ratio was 52 obtained with ¹¹C. Linear regressions showed a linear relation between the two detectors. These preliminary results show that the NID can accurately detect positrons from a patient's wrist and has the potential to non-invasively measure the AIF during a dynamic PET scan. The accuracy of these measurements needs to be determined.

Evaluation of bias and variance in low-count OSEM list mode reconstruction

Statistical algorithms have been widely used in PET image reconstruction. The maximum likelihood expectation maximization reconstruction has been shown to produce bias in applications where images are reconstructed from a relatively small number of counts. In this study, image bias and variability in low-count OSEM reconstruction are investigated on images reconstructed with MOLAR (motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction) platform. A human brain ([(11)C]AFM) and a NEMA phantom are used in the simulation and real experiments respectively, for the HRRT and Biograph mCT. Image reconstructions were repeated with different combinations of subsets and iterations. Regions of interest were defined on low-activity and high-activity regions to evaluate the bias and noise at matched effective iteration numbers (iterations × subsets). Minimal negative biases and no positive biases were found at moderate count levels and less than 5% negative bias was found using extremely low levels of counts (0.2 M NEC). At any given count level, other factors, such as subset numbers and frame-based scatter correction may introduce small biases (1-5%) in the reconstructed images. The observed bias was substantially lower than that reported in the literature, perhaps due to the use of point spread function and/or other implementation methods in MOLAR.

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

Cerebral blood flow with [15O]water PET studies using an image-derived input function and MR-defined carotid centerlines

Full quantitative analysis of brain PET data requires knowledge of the arterial input function into the brain. Such data are normally acquired by arterial sampling with corrections for delay and dispersion to account for the distant sampling site. Several attempts have been made to extract an image-derived input function (IDIF) directly from the internal carotid arteries that supply the brain and are often visible in brain PET images. We have devised a method of delineating the internal carotids in co-registered magnetic resonance (MR) images using the level-set method and applying the segmentations to PET images using a novel centerline approach. Centerlines of the segmented carotids were modeled as cubic splines and re-registered in PET images summed over the early portion of the scan. Using information from the anatomical center of the vessel should minimize partial volume and spillover effects. Centerline time-activity curves were taken as the mean of the values for points along the centerline interpolated from neighboring voxels. A scale factor correction was derived from calculation of cerebral blood flow (CBF) using gold standard arterial blood measurements. We have applied the method to human subject data from multiple injections of [(15)O]water on the HRRT. The method was assessed by calculating the area under the curve (AUC) of the IDIF and the CBF, and comparing these to values computed using the gold standard arterial input curve. The average ratio of IDIF to arterial AUC (apparent recovery coefficient: aRC) across 9 subjects with multiple (n = 69) injections was 0.49 ± 0.09 at 0-30 s post tracer arrival, 0.45 ± 0.09 at 30-60 s, and 0.46 ± 0.09 at 60-90 s. Gray and white matter CBF values were 61.4 ± 11.0 and 15.6 ± 3.0 mL/min/100 g tissue using sampled blood data. Using IDIF centerlines scaled by the average aRC over each subjects' injections, gray and white matter CBF values were 61.3 ± 13.5 and 15.5 ± 3.4 mL/min/100 g tissue. Using global average aRC values, the means were unchanged, and intersubject variability was noticeably reduced. This MR-based centerline method with local re-registration to [(15)O]water PET yields a consistent IDIF over multiple injections in the same subject, thus permitting the absolute quantification of CBF without arterial input function measurements.

Noninvasive parametric blood flow imaging of head and neck tumours using [15O]H2O and PET/CT

PURPOSE

The aim of this study was to develop a simple noninvasive method for measuring blood flow using [15O]H2O PET/CT for the head and neck area applicable in daily clinical practice.

PATIENTS AND METHODS

Fifteen dynamic [15O]H2O PET emission scans with simultaneous online radioactivity measurements of radial arterial blood [Blood-input functions (IFs)] were performed. Two noninvasively obtained population-based input functions were calculated by averaging all Blood-IF curves corrected for patients' body mass and injected dose [standardized uptake value (SUV)-IF] and for body surface area (BSA-IF) and injected dose. Parametric perfusion images were calculated for each set of IFs using a linearized two-compartment model, and values for several tissues were compared using Blood-IF as the gold standard.

RESULTS

On comparing all tissues, the correlation between blood flow obtained with the invasive Blood-IF and both SUV-IF and BSA-IF was significant (R2=0.785 with P<0.001 and R2=0.813 with P<0.001, respectively). In individual tissues, the performance of the two noninvasive methods was most reliable in resting muscle and slightly less reliable in tumour and cerebellar regions. In these two tissues, only BSA-IF showed a significant correlation with Blood-IF (R2=0.307 with P=0.032 in tumours and R2=0.398 with P<0.007 in the cerebellum).

CONCLUSION

The BSA-based noninvasive method enables clinically relevant delineation between areas of low and high blood flow in tumours. The blood flow of low-perfusion tissues can be reliably quantified using either of the evaluated noninvasive methods.

Evaluation of limited blood sampling population input approaches for kinetic quantification of [18F]fluorothymidine PET data

BACKGROUND

Quantification of kinetic parameters of positron emission tomography (PET) imaging agents normally requires collecting arterial blood samples which is inconvenient for patients and difficult to implement in routine clinical practice. The aim of this study was to investigate whether a population-based input function (POP-IF) reliant on only a few individual discrete samples allows accurate estimates of tumour proliferation using [18F]fluorothymidine (FLT).

METHODS

Thirty-six historical FLT-PET data with concurrent arterial sampling were available for this study. A population average of baseline scans blood data was constructed using leave-one-out cross-validation for each scan and used in conjunction with individual blood samples. Three limited sampling protocols were investigated including, respectively, only seven (POP-IF7), five (POP-IF5) and three (POP-IF3) discrete samples of the historical dataset. Additionally, using the three-point protocol, we derived a POP-IF3M, the only input function which was not corrected for the fraction of radiolabelled metabolites present in blood. The kinetic parameter for net FLT retention at steady state, Ki, was derived using the modified Patlak plot and compared with the original full arterial set for validation.

RESULTS

Small percentage differences in the area under the curve between all the POP-IFs and full arterial sampling IF was found over 60 min (4.2%-5.7%), while there were, as expected, larger differences in the peak position and peak height.A high correlation between Ki values calculated using the original arterial input function and all the population-derived IFs was observed (R2 = 0.85-0.98). The population-based input showed good intra-subject reproducibility of Ki values (R2 = 0.81-0.94) and good correlation (R2 = 0.60-0.85) with Ki-67.

CONCLUSIONS

Input functions generated using these simplified protocols over scan duration of 60 min estimate net PET-FLT retention with reasonable accuracy.

Non-invasive estimation of hepatic glucose uptake from [18F]FDG PET images using tissue-derived input functions

PURPOSE

The liver is perfused through the portal vein and hepatic artery. Quantification of hepatic glucose uptake (HGU) using PET requires the use of an input function for both the hepatic artery and portal vein. The former can be generally obtained invasively, but blood withdrawal from the portal vein is not practical in humans. The aim of this study was to develop and validate a new technique to obtain quantitative HGU by estimating the input function from PET images.

METHODS

Normal pigs (n = 12) were studied with [18F]FDG PET, in which arterial and portal blood time-activity curves (TAC) were determined invasively to serve as reference measurements. The present technique consisted of two characteristics, i.e. using a model input function and simultaneously fitting multiple liver tissue TACs from images by minimizing the residual sum of square between the tissue TACs and fitted curves. The input function was obtained from the parameters determined from the fitting. The HGU values were computed by the estimated and measured input functions and compared between the methods.

RESULTS

The estimated input functions were well reproduced. The HGU values, ranging from 0.005 to 0.02 ml/min per ml, were not significantly different between the two methods (r = 0.95, p < 0.001). A Bland-Altman plot demonstrated a small overestimation by the image-derived method with a bias of 0.00052 ml/min per g for HGU.

CONCLUSION

The results presented demonstrate that the input function can be estimated directly from the PET image, supporting the fully non-invasive assessment of liver glucose metabolism in human studies.

A hybrid clustering method for ROI delineation in small-animal dynamic PET images: application to the automatic estimation of FDG input functions

Tracer kinetic modeling with dynamic positron emission tomography (PET) requires a plasma time-activity curve (PTAC) as an input function. Several image-derived input function (IDIF) methods that rely on drawing the region of interest (ROI) in large vascular structures have been proposed to overcome the problems caused by the invasive approach for obtaining the PTAC, especially for small-animal studies. However, the manual placement of ROIs for estimating IDIF is subjective and labor-intensive, making it an undesirable and unreliable process. In this paper, we propose a novel hybrid clustering method (HCM) that objectively delineates ROIs in dynamic PET images for the estimation of IDIFs, and demonstrate its application to the mouse PET studies acquired with [ (18)F]Fluoro-2-deoxy-2-D-glucose (FDG). We begin our HCM using k-means clustering for background removal. We then model the time-activity curves using polynomial regression mixture models in curve clustering for heart structure detection. The hierarchical clustering is finally applied for ROI refinements. The HCM achieved accurate ROI delineation in both computer simulations and experimental mouse studies. In the mouse studies, the predicted IDIF had a high correlation with the gold standard, the PTAC derived from the invasive blood samples. The results indicate that the proposed HCM has a great potential in ROI delineation for automatic estimation of IDIF in dynamic FDG-PET studies.

Non-invasive estimation of hepatic blood perfusion from H2 15O PET images using tissue-derived arterial and portal input functions

PURPOSE

The liver is perfused through the portal vein and the hepatic artery. When its perfusion is assessed using positron emission tomography (PET) and (15)O-labeled water (H(2) (15)O), calculations require a dual blood input function (DIF), i.e., arterial and portal blood activity curves. The former can be generally obtained invasively, but blood withdrawal from the portal vein is not feasible in humans. The aim of the present study was to develop a new technique to estimate quantitative liver perfusion from H(2) (15)O PET images with a completely non-invasive approach.

METHODS

We studied normal pigs (n=14) in which arterial and portal blood tracer concentrations and Doppler ultrasonography flow rates were determined invasively to serve as reference measurements. Our technique consisted of using model DIF to create tissue model function and the latter method to simultaneously fit multiple liver time-activity curves from images. The parameters obtained reproduced the DIF. Simulation studies were performed to examine the magnitude of potential biases in the flow values and to optimize the extraction of multiple tissue curves from the image.

RESULTS

The simulation showed that the error associated with assumed parameters was <10%, and the optimal number of tissue curves was between 10 and 20. The estimated DIFs were well reproduced against the measured ones. In addition, the calculated liver perfusion values were not different between the methods and showed a tight correlation (r=0.90).

CONCLUSION

In conclusion, our results demonstrate that DIF can be estimated directly from tissue curves obtained through H(2) (15)O PET imaging. This suggests the possibility to enable completely non-invasive technique to assess liver perfusion in patho-physiological studies.

Tracer Kinetic Modeling in PET

Molecular imaging using PET provides a unique tool for noninvasively investigating the biochemistry of living organs. The wide range of radiolabeled molecules makes it possible to explore various biochemical, physiologic, and pharmacologic processes in vivo. Because each radiotracer is characterized by its particular kinetic behavior in the human body, the quantification of this behavior is a critical component for the improvement of imaging protocols and for rapid translation from research and development to the clinic. Suitable image reconstruction algorithms combined with tracer kinetic modeling techniques are needed to assess parametric or quantitative biologic images from the available fourdimensional images. An appropriate mathematical model is generally used to fit the time-activity curves of a region or volume of interest, thus allowing the assessment of biologic parameters.

PET kinetic analysis--compartmental model

PET enables not only visualization of the distribution of radiotracer, but also has ability to quantify several biomedical functions. Compartmental model is a basic idea to analyze dynamic PET data. This review describes the principle of the compartmental model and categorizes the techniques and approaches for the compartmental model according to various aspects: model design, experimental design, invasiveness, and mathematical solution. We also discussed advanced applications of the compartmental analysis with PET.

Corrections of arterial input function for dynamic H215O PET to assess perfusion of pelvic tumours: arterial blood sampling versus image extraction

Assessment of perfusion with 15O-labelled water (H215O) requires measurement of the arterial input function (AIF). The arterial time activity curve (TAC) measured using the peripheral sampling scheme requires corrections for delay and dispersion. In this study, parametrizations with and without arterial spillover correction for fitting of the tissue curve are evaluated. Additionally, a completely noninvasive method for generation of the AIF from a dynamic positron emission tomography (PET) acquisition is applied to assess perfusion of pelvic tumours. This method uses a volume of interest (VOI) to extract the TAC from the femoral artery. The VOI TAC is corrected for spillover using a separate tissue TAC and for recovery by determining the recovery coefficient on a coregistered CT data set. The techniques were applied in five patients with pelvic tumours who underwent a total of 11 examinations. Delay and dispersion correction of the blood TAC without arterial spillover correction yielded in seven examinations solutions inconsistent with physiology. Correction of arterial spillover increased the fitting accuracy and yielded consistent results in all patients. Generation of an AIF from PET image data was investigated as an alternative to arterial blood sampling and was shown to have an intrinsic potential to determine the AIF noninvasively and reproducibly. The AIF extracted from a VOI in a dynamic PET scan was similar in shape to the blood AIF but yielded significantly higher tissue perfusion values (mean of 104.0 +/- 52.0%) and lower partition coefficients (-31.6 +/- 24.2%). The perfusion values and partition coefficients determined with the VOI technique have to be corrected in order to compare the results with those of studies using a blood AIF.

The influence of tumor oxygenation on (18)F-FDG (fluorine-18 deoxyglucose) uptake: a mouse study using positron emission tomography (PET)

Background

This study investigated whether changing a tumor's oxygenation would alter tumor metabolism, and thus uptake of ¹⁸F-FDG (fluorine-18 deoxyglucose), a marker for glucose metabolism using positron emission tomography (PET).

Results

Tumor-bearing mice (squamous cell carcinoma) maintained at 37°C were studied while breathing either normal air or carbogen (95% O₂, 5% CO₂), known to significantly oxygenate tumors. Tumor activity was measured within an automatically determined volume of interest (VOI). Activity was corrected for the arterial input function as estimated from image and blood-derived data. Tumor FDG uptake was initially evaluated for tumor-bearing animals breathing only air (2 animals) or only carbogen (2 animals). Subsequently, 5 animals were studied using two sequential ¹⁸F-FDG injections administered to the same tumor-bearing mouse, 60 min apart; the first injection on one gas (air or carbogen) and the second on the other gas. When examining the entire tumor VOI, there was no significant difference of ¹⁸F-FDG uptake between mice breathing either air or carbogen (i.e. air/carbogen ratio near unity). However, when only the highest ¹⁸F-FDG uptake regions of the tumor were considered (small VOIs), there was a modest (21%), but significant increase in the air/carbogen ratio suggesting that in these potentially most hypoxic regions of the tumor, ¹⁸F-FDG uptake and hence glucose metabolism, may be reduced by increasing tumor oxygenation.

Conclusion

Tumor ¹⁸F-FDG uptake may be reduced by increases in tumor oxygenation and thus may provide a means to further enhance ¹⁸F-FDG functional imaging.

Measurement of input functions in rodents: challenges and solutions

INTRODUCTION

Tracer kinetic modeling used in conjunction with positron emission tomography (PET) is an excellent tool for the noninvasive quantification of physiological, biological and molecular processes and their alterations due to disease. Currently, complex multi-compartment modeling approaches are being applied in a variety of clinical studies to determine myocardial perfusion, viability and glucose utilization as well as fatty acid metabolism and oxidation in the normal and diseased heart. These kinetic models require two key measurements of tracer activity over time, tracer activity in arterial blood (input function) and its corresponding activity in the organ of interest. The alteration in the time course of tracer activity as it travels from blood to the organ of interest describes the kinetics of the tracer. To be able to implement these approaches in rodent models of disease using small-animal PET (microPET), it is imperative that the input function is measured accurately.

METHODS

The blood input functions in rodent experiments were obtained by (1) direct blood sampling, (2) direct measurement of blood activity by a beta-detecting probe that counts the activity in the blood, (3) an arterial-venous bypass (A/V shunt), (4) factor analysis of dynamic structures from dynamic PET images and (5) measurement from region-of-interest (ROI) analysis of dynamic PET images. Direct blood sampling was used as the reference standard to which the results of the other techniques were compared.

RESULTS

Beta probes are difficult to operate and may not provide accurate blood input functions unless they are used intravenously, which requires complicated microsurgery. A similar limitation applies to the A/V shunt. Factor analysis successfully extracts the blood input function for mice and rats. The ROI-based method is less accurate due to limited image resolution of the PET system, which results in severe partial volume effect and spillover from myocardium.

CONCLUSION

The current reference standard, direct blood sampling, is more invasive and has limited temporal resolution. With current imaging technology, image-based extraction of blood input functions is possible by factor analysis, while forthcoming technological developments are likely to allow extraction of input function directly from the images. These techniques will reduce the level of complexity and invasiveness for animal experiments and are likely to be used more widely in the future.

Parametrically defined cerebral blood vessels as non-invasive blood input functions for brain PET studies

A non-invasive alternative to arterial blood sampling for the generation of a blood input function for brain positron emission tomography (PET) studies is presented. The method aims to extract the dimensions of the blood vessel directly from PET images and to simultaneously correct the radioactivity concentration for partial volume and spillover. This involves simulation of the tomographic imaging process to generate images of different blood vessel and background geometries and selecting the one that best fits, in a least-squares sense, the acquired PET image. A phantom experiment was conducted to validate the method which was then applied to eight subjects injected with 6-[18F]fluoro-L-DOPA and one subject injected with [11C]CO-labelled red blood cells. In the phantom study, the diameter of syringes filled with an 11C solution and inserted into a water-filled cylinder were estimated with an accuracy of half a pixel (1 mm). The radioactivity concentration was recovered to 100 +/- 4% in the 8.7 mm diameter syringe, the one that most closely approximated the superior sagittal sinus. In the human studies, the method systematically overestimated the calibre of the superior sagittal sinus by 2-3 mm compared to measurements made in magnetic resonance venograms on the same subjects. Sources of discrepancies related to the anatomy of the blood vessel were found not to be fundamental limitations to the applicability of the method to human subjects. This method has the potential to provide accurate quantification of blood radioactivity concentration from PET images without the need for blood samples, corrections for delay and dispersion, co-registered anatomical images, or manually defined regions of interest.