Image-derived input function in dynamic human PET/CT: methodology and validation with 11C-acetate and 18F-fluorothioheptadecanoic acid in muscle and 18F-fluorodeoxyglucose in brain

PurposeDespite current advances in PET/CT systems, blood sampling still remains the standard method to obtain the radiotracer input function for tracer kinetic modelling. The purpose of this study was to validate the use of image-derived input functions (IDIF) of the carotid and femoral arteries to measure the arterial input function (AIF) in PET imaging. The data were obtained from two different research studies, one using 18F-FDG for brain imaging and the other using 11C-acetate and 18F-fluoro-6-thioheptadecanoic acid (18F-FTHA) in femoral muscles.MethodsThe method was validated with two phantom systems. First, a static phantom consisting of syringes of different diameters containing radioactivity was used to determine the recovery coefficient (RC) and spill-in factors. Second, a dynamic phantom built to model bolus injection and clearance of tracers was used to establish the correlation between blood sampling, AIF and IDIF. The RC was then applied to the femoral artery data from PET imaging studies with 11C-acetate and 18F-FTHA and to carotid artery data from brain imaging with 18F-FDG. These IDIF data were then compared to actual AIFs from patients.ResultsWith 11C-acetate, the perfusion index in the femoral muscle was 0.34±0.18 min−1 when estimated from the actual time–activity blood curve, 0.29±0.15 min−1 when estimated from the corrected IDIF, and 0.66±0.41 min−1 when the IDIF data were not corrected for RC. A one-way repeated measures (ANOVA) and Tukey’s test showed a statistically significant difference for the IDIF not corrected for RC (p<0.0001). With 18F-FTHA there was a strong correlation between Patlak slopes, the plasma to tissue transfer rate calculated using the true plasma radioactivity content and the corrected IDIF for the femoral muscles (vastus lateralis r=0.86, p=0.027; biceps femoris r=0.90, p=0.017). On the other hand, there was no correlation between the values derived using the AIF and those derived using the uncorrected IDIF. Finally, in the brain imaging study with 18F-FDG, the cerebral metabolic rate of glucose (CMRglc) measured using the uncorrected IDIF was consistently overestimated. The CMRglc obtained using blood sampling was 13.1±3.9 mg/100 g per minute and 14.0±5.7 mg/100 g per minute using the corrected IDIF (r2=0.90).ConclusionCorrectly obtained, carotid and femoral artery IDIFs can be used as a substitute for AIFs to perform tracer kinetic modelling in skeletal femoral muscles and brain analyses.

[1]  M. Partridge,et al.  Performance evaluation of the Philips 'Gemini' PET/CT System , 2004, IEEE Symposium Conference Record Nuclear Science 2004..

[2]  Nelleke Tolboom,et al.  Image-derived input functions for PET brain studies , 2009, European Journal of Nuclear Medicine and Molecular Imaging.

[3]  E. Hoffman,et al.  TOMOGRAPHIC MEASUREMENT OF LOCAL CEREBRAL GLUCOSE METABOLIC RATE IN HUMANS WITH (F‐18)2‐FLUORO-2‐DEOXY-D‐GLUCOSE: VALIDATION OF METHOD , 1980, Annals of neurology.

[4]  R L Phillips,et al.  An improved method to calculate cerebral metabolic rates of glucose using PET. , 1995, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[5]  J. Knuuti,et al.  Fatty acid uptake is preserved in chronically dysfunctional but viable myocardium. , 1997, The American journal of physiology.

[6]  Stina Syvänen,et al.  Predicting brain concentrations of drug using positron emission tomography and venous input: modeling of arterial-venous concentration differences , 2006, European Journal of Clinical Pharmacology.

[7]  Adriaan A. Lammertsma,et al.  Use of arterialised venous instead of arterial blood for measurement of myocardial glucose metabolism during euglycaemic-hyperinsulinaemic clamping , 2002, European Journal of Nuclear Medicine and Molecular Imaging.

[8]  S C Huang,et al.  Anatomy of SUV. Standardized uptake value. , 2000, Nuclear medicine and biology.

[9]  P. Herrero,et al.  Measurement of input functions in rodents: challenges and solutions. , 2005, Nuclear medicine and biology.

[10]  Elisabeth Kjellén,et al.  FDG PET studies during treatment: Prediction of therapy outcome in head and neck squamous cell carcinoma , 2002, Head and Neck.

[11]  Jan Pruim,et al.  Comparison of image-derived and arterial input functions for estimating the rate of glucose metabolism in therapy-monitoring 18F-FDG PET studies. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[12]  M Schwaiger,et al.  Effect of carbon-11-acetate recirculation on estimates of myocardial oxygen consumption by PET. , 1991, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[13]  P. Herrero,et al.  Assessment of myocardial blood flow using 15O-water and 1-11C-acetate in rats with small-animal PET. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[14]  C. D. Arnett,et al.  Glucose Metabolic Rate Kinetic Model Parameter Determination in Humans: The Lumped Constants and Rate Constants for [18F]Fluorodeoxyglucose and [11C]Deoxyglucose , 1985, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[15]  A A Lammertsma,et al.  Image-derived input functions for determination of MRGlu in cardiac (18)F-FDG PET scans. , 2001, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[16]  B. Saltin,et al.  Human femoral artery diameter in relation to knee extensor muscle mass, peak blood flow, and oxygen uptake. , 2000, American journal of physiology. Heart and circulatory physiology.

[17]  A. Kriplani,et al.  Simplifications in analyzing positron emission tomography data: effects on outcome measures. , 2007, Nuclear medicine and biology.

[18]  I. Buvat,et al.  Partial-Volume Effect in PET Tumor Imaging* , 2007, Journal of Nuclear Medicine.

[19]  A. Fox,et al.  Carotid Stenosis Index Revisited With Direct CT Angiography Measurement of Carotid Arteries to Quantify Carotid Stenosis , 2007, Stroke.

[20]  M. Reivich,et al.  THE [14C]DEOXYGLUCOSE METHOD FOR THE MEASUREMENT OF LOCAL CEREBRAL GLUCOSE UTILIZATION: THEORY, PROCEDURE, AND NORMAL VALUES IN THE CONSCIOUS AND ANESTHETIZED ALBINO RAT 1 , 1977, Journal of neurochemistry.

[21]  Jyh-Cheng Chen,et al.  Quantification method in [18F]fluorodeoxyglucose brain positron emission tomography using independent component analysis , 2005, Nuclear medicine communications.

[22]  M A Williams,et al.  Predicting the normal dimensions of the internal and external carotid arteries from the diameter of the common carotid. , 1987, European journal of vascular surgery.

[23]  Claude Comtat,et al.  Comparison of 3 Methods of Automated Internal Carotid Segmentation in Human Brain PET Studies: Application to the Estimation of Arterial Input Function , 2009, Journal of Nuclear Medicine.

[24]  M. Sacchetti,et al.  Whole body and leg acetate kinetics at rest, during exercise and recovery in humans , 2002, The Journal of physiology.

[25]  P. Price,et al.  Glucose metabolism in brain tumours can be estimated using [18F]2-fluorodeoxyglucose positron emission tomography and a population-derived input function scaled using a single arterialised venous blood sample. , 2005, International journal of oncology.

[26]  J. Karp,et al.  Performance of Philips Gemini TF PET/CT scanner with special consideration for its time-of-flight imaging capabilities. , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[27]  Roger Lecomte,et al.  Cardiac Studies in Rats With C-Acetate and PET: A Comparison With N-Ammonia , 2002 .

[28]  M. Phelps,et al.  Simple noninvasive quantification method for measuring myocardial glucose utilization in humans employing positron emission tomography and fluorine-18 deoxyglucose. , 1989, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[29]  R. Kessler,et al.  Analysis of emission tomographic scan data: limitations imposed by resolution and background. , 1984, Journal of computer assisted tomography.

[30]  R Todd Ogden,et al.  Estimation of kinetic parameters in graphical analysis of PET imaging data , 2003, Statistics in medicine.

[31]  J van den Hoff,et al.  [1-(11)C]Acetate as a quantitative perfusion tracer in myocardial PET. , 2001, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[32]  E. Croteau,et al.  Cardiac studies in rats with /sup 11/C-acetate and PET: a comparison with /sup 13/N-ammonia , 2002 .

[33]  Philipp T. Meyer,et al.  Simplified quantification of small animal [18F]FDG PET studies using a standard arterial input function , 2006, European Journal of Nuclear Medicine and Molecular Imaging.

[34]  J. Logan Graphical analysis of PET data applied to reversible and irreversible tracers. , 1999, Nuclear medicine and biology.

[35]  M. Partridge,et al.  Performance Evaluation of the Philips “Gemini” PET/CT System , 2006, IEEE Transactions on Nuclear Science.

[36]  D. Feng,et al.  Noninvasive Quantification of the Cerebral Metabolic Rate for Glucose Using Positron Emission Tomography, 18F-Fluoro-2-Deoxyglucose, the Patlak Method, and an Image-Derived Input Function , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[37]  G. Blomqvist,et al.  Improved receptor analysis in PET using a priori information from in vitro binding assays. , 1997, Physics in medicine and biology.

[38]  M E Phelps,et al.  Factor analysis for extraction of blood time-activity curves in dynamic FDG-PET studies. , 1995, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[39]  M. Phelps,et al.  Simultaneous measurement of myocardial oxygen consumption and blood flow using [1-carbon-11]acetate. , 1998, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[40]  T Länne,et al.  The diameter of the common femoral artery in healthy human: influence of sex, age, and body size. , 1999, Journal of vascular surgery.

[41]  M. Bland,et al.  Observer variability in volumetric blood flow measurements in leg arteries using duplex ultrasound. , 1996, Ultrasound in medicine & biology.

[42]  E. Hoffman,et al.  Tomographic measurement of local cerebral glucose metabolic rate in humans with (F‐18)2‐fluoro‐2‐deoxy‐D‐glucose: Validation of method , 1979, Annals of neurology.

[43]  Katharine H Fraser,et al.  A method to estimate wall shear rate with a clinical ultrasound scanner. , 2008, Ultrasound in medicine & biology.

[44]  V. Oikonen,et al.  Free fatty acid uptake in the myocardium and skeletal muscle using fluorine-18-fluoro-6-thia-heptadecanoic acid. , 1998, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[45]  Sung-Cheng Huang,et al.  Anatomy of SUV , 2000 .

[46]  G. Alexander,et al.  Characterization of the image-derived carotid artery input function using independent component analysis for the quantitation of [18F] fluorodeoxyglucose positron emission tomography images , 2007, Physics in medicine and biology.

[47]  M. Graham,et al.  Comparison of simplified quantitative analyses of FDG uptake. , 2000, Nuclear medicine and biology.

[48]  Floris H. P. van Velden,et al.  Image derived input functions for dynamic High Resolution Research Tomograph PET brain studies , 2008, NeuroImage.

[49]  M. Olufsen,et al.  Numerical Simulation and Experimental Validation of Blood Flow in Arteries with Structured-Tree Outflow Conditions , 2000, Annals of Biomedical Engineering.