Simplified quantification of small animal [18F]FDG PET studies using a standard arterial input function

Meyer, Philipp T.; Circiumaru, Valentina; Cardi, Christopher; Thomas, Daniel H.; Bal, Harshali; Acton, Paul D.

doi:10.1007/s00259-006-0121-7

Cited by 52 publications

(47 citation statements)

References 16 publications

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“…Standardized input function methods assume that input functions across animals and experimental conditions have an identical curve shape that can be used to approximate the individual input function by scaling the standard curve to match the concentration measured in 1 or 2 blood samples (9). In reality, the input function curve shape varies between subjects on the basis of several factors, such as the injection technique and speed, dietary state of the animal, metabolic status, catheterization site, and animal species.…”

mentioning

confidence: 99%

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal ¹⁸F-FDG PET Studies

Fang¹,

Muzic²

2008

J Nucl Med

100

123

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We present and validate a method to obtain an input function from dynamic image data and 0 or 1 blood sample for smallanimal 18 F-FDG PET studies. The method accounts for spillover and partial-volume effects via a physiologic model to yield a model-corrected input function (MCIF). Methods: Imagederived input functions (IDIFs) from heart ventricles and myocardial time-activity curves were obtained from 14 Sprague-Dawley rats and 17 C57BL/6 mice. Each MCIF was expressed as a mathematic equation with 7 parameters, which were estimated simultaneously with the myocardial model parameters by fitting the IDIFs and myocardium curves to a dual-output compartment model. Zero or 1 late blood sample was used in the simultaneous estimation. MCIF was validated by comparison with input measured from blood samples. Validation included computing errors in the areas under the curves (AUCs) and in the 18 F-FDG influx constant Ki in 3 types of tissue. Results: For the rat data, the AUC error was 5.3% 6 19.0% in the 0-sample MCIF and 22.3% 6 14.8% in the 1-sample MCIF. When the MCIF was used to calculate the Ki of the myocardium, brain, and muscle, the overall errors were 26.3% 6 27.0% in the 0-sample method (correlation coefficient r 5 0.967) and 3.1% 6 20.6% in the 1-sample method (r 5 0.970). The t test failed to detect a significant difference (P . 0.05) in the Ki estimates from both the 0-sample and the 1-sample MCIF. For the mouse data, AUC errors were 4.3% 6 25.5% in the 0-sample MCIF and 21.7% 6 20.9% in the 1-sample MCIF. Ki errors averaged 28.0% 6 27.6% for the 0-sample method (r 5 0.955) and 22.8% 6 22.7% for the 1-sample method (r 5 0.971). The t test detected significant differences in the brain and muscle in the Ki for the 0-sample method but no significant differences with the 1-sample method. In both rat and mouse, 0-sample and 1-sample MCIFs both showed at least a 10-fold reduction in AUC and Ki errors compared with uncorrected IDIFs. Conclusion: MCIF provides a reliable, noninvasive estimate of the input function that can be used to accurately quantify the glucose metabolic rate in small-animal 18 F-FDG PET studies.

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mentioning

confidence: 99%

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal ¹⁸F-FDG PET Studies

Fang¹,

Muzic²

2008

J Nucl Med

100

123

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“…However, IDIF extraction from the heart in small animals is limited by the large partial-volume effect and spillover from the myocardium, requiring the application of elaborate statistical methods such as factor analysis (11)(12)(13) to overcome this limitation by deconvolving the blood and myocardium contributions to the heart time-activity curve. Finally, simplified glucose uptake measurements using standard input functions scaled by at least 1 blood sample were developed (14). The limitation of this method lies in the necessity of a rigid and repeatable infusion protocol.…”

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confidence: 99%

Image-Derived Input Function from the Vena Cava for¹⁸F-FDG PET Studies in Rats and Mice

2014

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Measurement of arterial input function is a restrictive aspect for quantitative 18 F-FDG PET studies in rodents because of their small total blood volume and the related difficulties in withdrawing blood. Methods: In the present study, we took advantage of the high spatial resolution of a recent dedicated small-animal scanner to extract the input function from the 18 F-FDG PET images in Sprague-Dawley rats (n 5 4) and C57BL/6 mice (n 5 5), using the vena cava. In the rat experiments, the validation of the image-derived input function (IDIF) method was made using an external microvolumetric blood counter as reference for the determination of the arterial input function, the measurement of which was confirmed by additional manually obtained blood samples. Correction for tracer bolus dispersion in blood between the vena cava and the arterial tree was applied. In addition, simulation studies were undertaken to probe the impact of the different IDIF extraction approaches on the determined cerebral metabolic rate of glucose (CMR Glc ). In the mice measurements, the IDIF was used to compute the CMR Glc , which was compared with previously reported values, using the Patlak approach. Results: The presented IDIF from the vena cava showed a robust determination of CMR Glc using either the compartmental modeling or the Patlak approach, even without bolus dispersion correction or blood sampling, with an underestimation of CMR Glc of 7% ± 16% as compared with the reference data. Using this approach in the mice experiments, we measured a cerebral metabolic rate in the cortex of 0.22 ± 0.10 μmol/g/min (mean ± SD), in good agreement with previous 18 F-FDG studies in the mouse brain. In the rat experiments, dispersion correction of the IDIF and additional scaling of the IDIF using a single manual blood sample enabled an optimized determination of CMR Glc , with an underestimation of 6% ± 7%. Conclusion: The vena cava time-activity curve is therefore a minimally invasive alternative for the measurement of the 18 F-FDG input function in rats and mice, without the complications associated with repetitive blood sampling. Gl ucose metabolism can be efficiently measured in vivo using PET and adequate radiotracers, such as the glucose analog 18 F-FDG, opening the way to a large range of metabolic studies in rodents (1). The quantification of the metabolic rate of glucose (MR Glc ) from 18 F-FDG PET experiments requires the knowledge of the arterial input function (AIF), which is typically measured by serial arterial blood sampling (2). However, in small animals, the total amount of blood is limited and continuous blood sampling over the entire experiment duration (on the order of 45 min) is technically challenging and might affect the physiology of the animal.Several methods have been developed in the last decade to overcome this difficulty. New microfluidic blood sampling devices were developed to minimize the amount of blood withdrawn (3). Another method minimizing blood losses is the use of an arteriovenous shunt, coupled with either...

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“…Delays between individual curves were adjusted by shifting the curves until the time to maximum coincided with the mean time to the peak for all curves. To test PBIF within this group of healthy subjects, we used a leave-one-out procedure [16]; PBIF was generated for each of the ten subjects by averaging the measured input functions of the remaining nine subjects. This procedure was chosen to avoid any possible bias due to including the input function needing to be calculated to the average PBIF.…”

Section: Arterial and Venous Blood Sampling And Metabolite Correctionmentioning

confidence: 99%

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

Zanotti‐Fregonara

Maroy

Peyronneau

et al. 2012

Eur J Nucl Med Mol Imaging

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Simplified quantification of small animal [18F]FDG PET studies using a standard arterial input function

Cited by 52 publications

References 16 publications

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal ¹⁸F-FDG PET Studies

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal ¹⁸F-FDG PET Studies

Image-Derived Input Function from the Vena Cava for¹⁸F-FDG PET Studies in Rats and Mice

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

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Simplified quantification of small animal [18F]FDG PET studies using a standard arterial input function

Cited by 52 publications

References 16 publications

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal 18F-FDG PET Studies

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal 18F-FDG PET Studies

Image-Derived Input Function from the Vena Cava for18F-FDG PET Studies in Rats and Mice

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

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Product

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Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal ¹⁸F-FDG PET Studies

Spillover and Partial-Volume Correction for Image-Derived Input Functions for Small-Animal ¹⁸F-FDG PET Studies

Image-Derived Input Function from the Vena Cava for¹⁸F-FDG PET Studies in Rats and Mice