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Simplified [¹⁸F]FDG Image-Derived input function Using the Left Ventricle, Liver, and One Venous Blood Sample

MOLECULAR IMAGING 2010年第2期9卷 76-86页

作者： Tantawy, Mohammed Noor Peterson, Todd E. Vanderbilt Univ Inst Imaging Sci Dept Radiol & Radiol Sci Med Ctr Nashville TN 37232 USA

A relatively simple, almost entirely noninvasive imaging-based method is presented for deriving arterial blood input functions for quantitative [F-18]2-fluoro-2-deoxy-D-glucose (FOG) positron emission tomographic (PET) studies in rodents. It requires only one venous blood sample at the end of the scan. MicroPET images and arterial blood time-activity curves {TACs} were downloaded from the Mouse Quantitation Program database at the University of California, Los Angeles. Three-dimensional regions of interest were drawn around the blood-pool region of the left ventricle and within the liver to derive their respective TACs. To construct the "hybrid" image-derived input function (IDIF), the initial part of the left ventricle TAC, containing the peak concentration of [F-18]FDG in the arterial blood, was corrected for spillout (ie, partial-volume effect yielding a recovery coefficient < 1) and then joined to the liver TAC (normalized to the 60-minute arterial blood sample) immediately after it peaks. To validate our method, the [F-18]FDG influx constant (K-i) was estimated using a two-tissue compartment model and compared to estimates of K-i obtained using measured arterial blood TACs. No significant difference in the K-i estimates was obtained with the arterial blood input function and our hybrid IDIF. We conclude that the normalized hybrid IDIF can be used in practice to obtain reliable K-i estimates.

关键词： input function Compartmental models arterial blood Left Ventricle region of interest Cmax Liver Total Access Communication System venous blood

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Estimating the input function non-invasively for FDG-PET quantification with multiple linear regression analysis: simulation and verification with in vivo data

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EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 2004年第5期31卷 692-702页

作者： Fang, YH Kao, T Liu, RS Wu, LC Taipei Vet Gen Hosp Natl PET Cyclotron Ctr Taipei Taiwan Natl Yang Ming Univ Inst Biomed Engn Taipei 112 Taiwan

A novel statistical method, namely Regression-Estimated input function (REIF), is proposed in this study for the purpose of non-invasive estimation of the input function for fluorine-18 2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) quantitative analysis. We collected 44 patients who had undergone a blood sampling procedure during their FDG-PET scans. First, we generated tissue time-activity curves of the grey matter and the whole brain with a segmentation technique for every subject. Summations of different intervals of these two curves were used as a feature vector, which also included the net injection dose. Multiple linear regression analysis was then applied to find the correlation between the input function and the feature vector. After a simulation study with in vivo data, the data of 29 patients were applied to calculate the regression coefficients, which were then used to estimate the input functions of the other 15 subjects. Comparing the estimated input functions with the corresponding real input functions, the averaged error percentages of the area under the curve and the cerebral metabolic rate of glucose (CMRGlc) were 12.13+/-8.85 and 16.60+/-9.61, respectively. Regression analysis of the CMRGlc values derived from the real and estimated input functions revealed a high correlation (r=0.91). No significant difference was found between the real CMRGlc and that derived from our regression-estimated input function (Student's t test, P>0.05). The proposed REIF method demonstrated good abilities for input function and CMRGlc estimation, and represents a reliable replacement for the blood sampling procedures in FDG-PET quantification.

关键词： FDG quantitative analysis non-invasive input function CMRGlc

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Estimation of input function and kinetic parameters using simulated annealing: Application in a flow model

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2002年第3期49卷 707-713页

作者： Wong, KP Meikle, SR Feng, D Fulham, MJ Royal Prince Alfred Hosp Dept PET & Nucl Med Camperdown NSW 2050 Australia Univ Sydney Sch Informat Technol Biomed & Multimedia Informat Technol Sydney NSW 2006 Australia Hong Kong Polytech Univ Ctr Multimedia Signal Proc Dept Elect & Informat Engn Hong Kong Hong Kong Peoples R China Univ Sydney Fac Med Sydney NSW 2006 Australia

Accurate determination of the input function is essential for absolute quantification of physiological parameters in positron emission tomography and single-photon emission computed tomography imaging, but it requires an invasive and tedious procedure of blood sampling that is impractical in clinical studies. We previously proposed a technique that estimates simultaneously kinetic parameters and the input function from the tissue impulse response functions and requires two blood samples. A nonlinear least squares method estimated all the parameters in the impulse response functions and the input function but failed occasionally due to high noise levels in the data, causing an ill-conditioned cost function. This paper investigates the feasibility of applying a Monte Carlo method called simulated annealing to estimate kinetic parameters in the impulse response functions and the input function. Time-activity curves of teboroxime, which is very sensitive to changes in the input function, were simulated based on published data obtained from a canine model. The equations describing the tracer kinetics in different regions were minimized simultaneously by simulated annealing and nonlinear least squares. We found that the physiological parameters obtained with simulated annealing are accurate, and the estimated input function more closely resembled the simulated curve. We conclude that simulated annealing reduces bias in the estimation of physiological parameters and determination of the input function.

关键词： impulse response function input function kinetic parameter estimation nonlinear least squares simulated annealing single-photon emission computed tomography (SPECT) teboroxime

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Computationally efficient vascular input function models for quantitative kinetic modelling using DCE-MRI

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PHYSICS IN MEDICINE AND BIOLOGY 2008年第5期53卷 1225-1239页

作者： Orton, Matthew R. d'Arcy, James A. Walker-Samuel, Simon Hawkes, David J. Atkinson, David Collins, David J. Leach, Martin O. Inst Canc Res Canc Res UK Clin MR Res Grp Sutton SM2 5PT Surrey England Royal Marsden NHS Fdn Trust Sutton SM2 5PT Surrey England UCL Ctr Med Image Comp London WC1E 6BT England

A description of the vascular input function is needed to obtain tissue kinetic parameter estimates from dynamic contrast enhanced MRI (DCE-MRI) data. This paper describes a general modelling framework for defining compact functional forms to describe vascular input functions. By appropriately specifying the components of this model it is possible to generate models that are realistic, and that ensure that the tissue concentration curves can be analytically calculated. This means that the computations necessary to estimate parameters from measured data are relatively efficient, which is important if such methods are to become of use in clinical practice. Three models defined by four parameters, using exponential, gamma-variate and cosine descriptions of the bolus, are described and their properties investigated using simulations. The results indicate that if there is no plasma fraction, then the proposed models are indistinguishable. When a small plasma fraction is present the exponential model gives parameter estimates that are biassed by up to 50%, while the other twomodels give very little bias;up to 10% but less than 5% in most cases. With a larger plasma fraction the exponential model is again biassed, the gammavariate model has a small bias, but the cosine model has a very little bias and is indistinguishable from the model used to generate the data. The computational speed of the analytic approaches is compared with a fast-Fourier-transformbased numerical convolution approach. The analytic methods are nearly 10 times faster than the numerical methods for the isolated computation of the convolution, and around 4-5 times faster when used in an optimization routine to obtain parameter estimates. These results were obtained from five example data sets, one of which was examined in more detail to compare the estimates obtained using the different models, and with literature values.

关键词： CONTRAST-ENHANCED MRI POSITRON EMISSION TOMOGRAPHY GD-DTPA HEALTHY-VOLUNTEERS VOLUME FRACTION PERMEABILITY TRACER DERIVATION PRECISION PERFUSION exponential model input function Perfusion Healthy Volunteers Volume fraction Gadolinium DTPA derivation Precision Permeability

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Assessment of brain glucose metabolism with input function determined from brain PET images by means of Bayesian ICA and MCMC methods

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COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 2012年第8期36卷 620-626页

作者： Berradja, Khadidja Boughanmi, Nabil Univ Mostaganem Mostaganem Algeria Univ Sci & Technol Oran Algeria

Positron emission tomography (PET) imaging has the capability to produce regional or parametric images of physiological aspects in a tissue of interest. Apart from the acquired PET data, the concentration of the radiotracer supplied to the tissue through the vascularization has to be known as the input function (IF). IF can be obtained by manual or automatic blood sampling and cross calibrated with PET. These procedures are cumbersome, invasive and generate uncertainties. In the present work, we determine IF from internal artery in fluorodeoxyglucose (18F-FDG)brain images by means of Independent Component Analysis (ICA) based on Bayesian theory and Monte Carlo Markov Chain (MCMC) sampling method (BICA, Bayesian ICA). Dynamic brain images were decomposed with BICA into image sequences of blood and tissue components. A region of interest was drawn around the internal artery in the blood image to determine BICA-IF. BICA-IF was therefore corrected for spillover of radioactivity emission from tissue, then it was normalized with three plasma samples to correct for partial volume and blood to plasma radioactivity ratio. BICA-IF was found comparable to IF determined by blood sampling, and rCMRG values in several brain structures obtained with BICA-IF and sampled IF showed a bias of 6.4% which was attributed to the difference in the time sampling of 4s for sampled IF versus 15s for BICA-MC-IF at early times. In conclusion, BICA is a strong approach in image decomposition to extract blood curves in a noninvasive way. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Positron emission tomography input function Independent Component Analysis (ICA) MCMC sampling Bayesian approach

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Noninvasive estimation of the aorta input function for measurement of tumor blood flow with [¹⁵O]water

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2001年第3期20卷 164-174页

作者： Watabe, H Channing, MA Riddell, C Jousse, F Libutti, SK Carrasquillo, JA Bacharach, SL Carson, RE NIH PET Dept WG Magnuson Clin Ctr Bethesda MD 20892 USA NCI NIH Surg Branch Bethesda MD 20892 USA NIH Ctr Clin Dept Nucl Med Bethesda MD 20892 USA Natl Cardiovasc Ctr Res Inst Dept Investigat Radiol Suita Osaka 5658565 Japan Natl Cardiovasc Ctr Res Inst Dept Invest Radiol Osaka 5658565 Japan

Quantitative measurement of tumor blood flow with [O-15]water can be used to evaluate the effects of tumor treatment over time, Since quantitative flow measurements require an input function, we developed the profile fitting method (PFM) to measure the input function from positron emission tomography images of the aorta. First, a [C-11]CO scan was acquired and the aorta region was analyzed, The aorta diameter was determined by fitting the image data with a model that includes scanner resolution, the measured venous blood radioactivity concentration, and the spillover of counts from the background, The diameter was used in subsequent fitting of [O-15]water dynamic images to estimate the aorta and background radioactivity concentrations. Phantom experiments were performed to test the model. Image quantification biases (up to 15%) were found for small objects, particularly for those in a large elliptical phantom, However, the bias in the PFM concentration estimates was much smaller (2%-6%), A simulation study showed that PFM had less bias and/or variability in flow parameter estimates than an ROI method, PFM was applied to human [C-11]CO and [O-15]water dynamic studies with left ventricle input functions used as the gold standard. PFM parameter estimates had higher variability than found in the simulation but with minimal bias, These studies suggest that PFM is a promising technique for the noninvasive measurement of the aorta [O-15]water input function.

关键词： aorta input function tumor blood flow [O-15]water

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Effects of metabolite correction for arterial input function on quantitative receptor images with ¹¹C-flumazenil in clinical positron emission tomography studies

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JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY 2004年第3期28卷 428-435页

作者： Okazawa, H Yamauchi, H Sugimoto, K Magata, Y Kudo, T Yonekura, Y Univ Fukui Biomed Imaging Res Ctr Fukui 9101193 Japan Shiga Med Ctr Res Inst Positron Emiss Tomog Unit Moriyama Japan Hamamatsu Univ Sch Med Photon Med Res Ctr Hamamatsu Shizuoka Japan

Objective: To evaluate the effect of inputs estimated from different methods for metabolite correction on binding potential (BP) of (11)C-flumazenil (FMZ). Methods: Five healthy volunteers underwent (11)C-FMZ positron emission tomography. Arterial blood was sampled to obtain plasma radioactivity and metabolite fraction, followed by estimation of input functions with several methods. Binding potential images for different input functions and that using the noninvasive graphic method were calculated. Images of standardized uptake value (SUV) with different acquisition times were also compared. Results: Binding potential images calculated from arterial inputs were almost equivalent, and regional values were not significantly different irrespective of methods for metabolite correction as well as the noninvasive graphic plot method. Standardized uptake value images showed less contrast compared with quantitative BP images, and the regional values varied depending on scan time. Statistical parametric mapping analysis showed significant regional differences between BP and SUV images. Conclusion: Binding potential images were equivalent irrespective of calculation methods;however, SUV was not appropriate for quantitative evaluation.

关键词： flumazenil receptor imaging binding potential input function statistical parametric mapping

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Partial volume correction of the microPET blood input function using ensemble learning independent component analysis

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PHYSICS IN MEDICINE AND BIOLOGY 2009年第6期54卷 1823-1846页

作者： Su, Kuan-Hao Lee, Jih-Shian Li, Jia-Hung Yang, Yu-Wen Liu, Ren-Shian Chen, Jyh-Cheng Buddhist Tzu Chi Gen Hosp Dept Nucl Med Taipei Taiwan Taipei Vet Gen Hosp Natl PET Cyclotron Ctr Taipei Taiwan Taipei City Hosp Dept Educ & Res Taipei Taiwan

Medical images usually suffer from a partial volume effect (PVE), which may degrade the accuracy of any quantitative information extracted from the images. Our aim was to recreate accurate radioactivity concentration and time-activity curves (TACs) by microPET R4 quantification using ensemble learning independent component analysis (EL-ICA). We designed a digital cardiac phantom for this simulation and in order to evaluate the ability of EL-ICA to correct the PVE, the simulated images were convoluted using a Gaussian function (FWHM = 1-4 mm). The robustness of the proposed method towards noise was investigated by adding statistical noise (SNR = 2-16). During further evaluation, another set of cardiac phantoms were generated from the reconstructed images, and Poisson noise at different levels was added to the sinogram. In real experiments, four rat microPET images and a number of arterial blood samples were obtained;these were used to estimate the metabolic rate of FDG (MR(FDG)). input functions estimated using the FastICA method were used for comparison. The results showed that EL-ICA could correct PVE in both the simulated and real cases. After correcting for the PVE, the errors for MRFDG, when estimated by the EL-ICA method, were smaller than those when TACs were directly derived from the PET images and when the FastICA approach was used.

关键词： Volume E coli protein a physiological aspects Noise Learning 噪声学习 Physiological aspects Escherichia coli Proteins Noise input function sinogram Poisson noise Learning PET Scan Independent component analysis Total Access Communication System MicroPET

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Reliable quantification of ¹⁸F-GE-180 PET neuroinflammation studies using an individually scaled population-based input function or late tissue-to-blood ratio

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EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 2020年第12期47卷 2887-2900页

作者： Buchert, Ralph Dirks, Meike Schuetze, Christian Wilke, Florian Mamach, Martin Wirries, Ann-Katrin Pflugrad, Henning Hamann, Linda Langer, Laura B. N. Wetzel, Christian Lukacevic, Mario Polyak, Andras Kessler, Mariella Petrusch, Carlotta Bengel, Frank M. Geworski, Lilli Rupprecht, Rainer Weissenborn, Karin Ross, Tobias L. Berding, Georg Univ Med Ctr Hamburg Eppendorf Dept Diagnost & Intervent Radiol & Nucl Med Martinistr 52 D-20246 Hamburg Germany Hannover Med Sch Dept Neurol Hannover Germany Hannover Med Sch Dept Med Phys & Radiat Protect Hannover Germany Hannover Med Sch Dept Nucl Med Hannover Germany Univ Regensburg Dept Psychiat & Psychotherapy Regensburg Germany

Purpose Tracer kinetic modeling of tissue time activity curves and the individual input function based on arterial blood sampling and metabolite correction is the gold standard for quantitative characterization of microglia activation by PET with the translocator protein (TSPO) ligand F-18-GE-180. This study tested simplified methods for quantification of F-18-GE-180 PET. Methods Dynamic F-18-GE-180 PET with arterial blood sampling and metabolite correction was performed in five healthy volunteers and 20 liver-transplanted patients. Population-based input function templates were generated by averaging individual input functions normalized to the total area under the input function using a leave-one-out approach. Individual population-based input functions were obtained by scaling the input function template with the individual parent activity concentration of F-18-GE-180 in arterial plasma in a blood sample drawn at 27.5 min or by the individual administered tracer activity, respectively. The total F-18-GE-180 distribution volume (V-T) was estimated in 12 regions-of-interest (ROIs) by the invasive Logan plot using the measured or the population-based input functions. Late ROI-to-whole-blood and ROI-to-cerebellum ratio were also computed. Results Correlation with the reference V-T (with individually measured input function) was very high for V-T with the population-based input function scaled with the blood sample and for the ROI-to-whole-blood ratio (Pearson correlation coefficient = 0.989 +/- 0.006 and 0.970 +/- 0.005). The correlation was only moderate for V-T with the population-based input function scaled with tracer activity dose and for the ROI-to-cerebellum ratio (0.653 +/- 0.074 and 0.384 +/- 0.177). Reference V-T, population-based V-T with scaling by the blood sample, and ROI-to-whole-blood ratio were sensitive to the TSPO gene polymorphism. Population-based V-T with scaling to the administered tracer activity and the ROI-to-cerebellum ratio failed to detec

关键词： Translocator protein (TSPO) Flutriciclamide GE-180 Kinetic analysis input function Population-based

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Minimally invasive input function for 2-¹⁸F-fluoro-A-85380 brain PET studies

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EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 2012年第4期39卷 651-659页

作者： Zanotti-Fregonara, Paolo Maroy, Renaud Peyronneau, Marie-Anne Trebossen, Regine Bottlaender, Michel NIMH Mol Imaging Branch NIH Bethesda MD 20892 USA Serv Hosp Frederic Joliot CEA DSV I2BM F-91401 Orsay France CEA DSV I2BM F-91191 Gif Sur Yvette France

Quantitative neuroreceptor positron emission tomography (PET) studies often require arterial cannulation to measure input function. While population-based input function (PBIF) would be a less invasive alternative, it has only rarely been used in conjunction with neuroreceptor PET tracers. The aims of this study were (1) to validate the use of PBIF for 2-F-18-fluoro-A-85380, a tracer for nicotinic receptors;(2) to compare the accuracy of measures obtained via PBIF to those obtained via blood-scaled image-derived input function (IDIF) from carotid arteries;and (3) to explore the possibility of using venous instead of arterial samples for both PBIF and IDIF. Ten healthy volunteers underwent a dynamic 2-F-18-fluoro-A-85380 brain PET scan with arterial and, in seven subjects, concurrent venous serial blood sampling. PBIF was obtained by averaging the normalized metabolite-corrected arterial input function and subsequently scaling each curve with individual blood samples. IDIF was obtained from the carotid arteries using a blood-scaling method. Estimated Logan distribution volume (V (T)) values were compared to the reference values obtained from arterial cannulation. For all subjects, PBIF curves scaled with arterial samples were similar in shape and magnitude to the reference arterial input function. The Logan V (T) ratio was 1.00 +/- 0.05;all subjects had an estimation error < 10%. IDIF gave slightly less accurate results (V (T) ratio 1.03 +/- 0.07;eight of ten subjects had an error < 10%). PBIF scaled with venous samples yielded inaccurate results (V (T) ratio 1.13 +/- 0.13;only three of seven subjects had an error < 10%). Due to arteriovenous differences at early time points, IDIF could not be calculated using venous samples. PBIF scaled with arterial samples accurately estimates Logan V (T) for 2-F-18-fluoro-A-85380. Results obtained with PBIF were slightly better than those obtained with IDIF. Due to arteriovenous concentration differences, venous samples cannot be

关键词： input function 2-F-18-Fluoro-A-85380 Brain studies with PET

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