Determination of blood curve and tissue uptake from left ventricle using FADS in rat FDG-PET studies

Bentourkia, M’hamed; Lapointe, D.; Selivanov, V.; Buvat, Irène; Leconte, R.

doi:10.1109/nssmic.1999.845857

Cited by 13 publications

(5 citation statements)

References 4 publications

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“…In rodents, the extraction of 18 F-FDG image-derived input functions (IDIF) was generally focused on the heart (10), because of the limited spatial resolution of small-animal PET scanners and the related difficulty to delineate blood vessels. 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).…”

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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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confidence: 99%

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

2014

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“…The fraction υ is usually calculated together with the tissue kinetic parameters (rate constants K 1 -k 4 ) during the modeling, and consequently, TBV is evaluated (see Annex). Reciprocally, if TBV is known by means of image decomposition by image analysis [5,39,40], by contrast enhanced magnetic resonance imaging (MRI) [41], or by other means, then IF can be determined from TBV as IF(t)=μTBV(t) with μ91, and in this case, the iterations during the TAC modeling are made on μ instead of on υ. At the end, μ=1/ υ.…”

Section: If Determinationmentioning

confidence: 99%

Determination of the Input Function at the Entry of the Tissue of Interest and Its Impact on PET Kinetic Modeling Parameters

Bentourkia

2015

Mol Imaging Biol

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Quantitative positron emission tomography (PET) imaging is employed with several measurement protocols all relying on the a priori determination of the input function (IF). The standard technique to determine IF is by blood sampling. However, a unique IF determined in a subject for a given PET study, either defined by sampling or in the images, and commonly utilized for all analyzed tissues in that study equally at rest and during interventions, is expected to provoke biases in the rate constants and in tissue blood volume. The determination of a specific IF at the site of the tissue to be analyzed enhances PET accuracy and renders PET imaging less invasive.

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“…Since the tumors were implanted in the axillary area at the level of the heart in the rats, the images allowed us to extract a blood curve from an ROI placed on the heart. This ROI was decomposed with factor analysis [15][16][17][18] to determine the blood component. This procedure allowed us to successfully fit TAC data from the heart obtained with an infusion of 18 FDG during 120 min (Fig.…”

Section: Input Functionmentioning

confidence: 99%

A real-time follow-up of photodynamic therapy during PET imaging

Boubacar¹,

Sarrhini²,

Lier³

et al. 2015

Photodiagnosis and Photodynamic Therapy

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Determination of blood curve and tissue uptake from left ventricle using FADS in rat FDG-PET studies

Cited by 13 publications

References 4 publications

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

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

Determination of the Input Function at the Entry of the Tissue of Interest and Its Impact on PET Kinetic Modeling Parameters

A real-time follow-up of photodynamic therapy during PET imaging

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Determination of blood curve and tissue uptake from left ventricle using FADS in rat FDG-PET studies

Cited by 13 publications

References 4 publications

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

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

Determination of the Input Function at the Entry of the Tissue of Interest and Its Impact on PET Kinetic Modeling Parameters

A real-time follow-up of photodynamic therapy during PET imaging

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Product

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

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