Bernard Lanz1, Carole Poitry-Yamate2, Rolf Gruetter3. 1. Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland bernard.lanz@epfl.ch. 2. Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. 3. Laboratory for Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Department of Radiology, University of Lausanne, Lausanne, Switzerland; and Department of Radiology, University of Geneva, Geneva, Switzerland.
Abstract
UNLABELLED: 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 = 4) and C57BL/6 mice (n = 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 (CMRGlc). In the mice measurements, the IDIF was used to compute the CMRGlc, which was compared with previously reported values, using the Patlak approach. RESULTS: The presented IDIF from the vena cava showed a robust determination of CMRGlc using either the compartmental modeling or the Patlak approach, even without bolus dispersion correction or blood sampling, with an underestimation of CMRGlc 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 CMRGlc, 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.
UNLABELLED: 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 = 4) and C57BL/6 mice (n = 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 (CMRGlc). In the mice measurements, the IDIF was used to compute the CMRGlc, which was compared with previously reported values, using the Patlak approach. RESULTS: The presented IDIF from the vena cava showed a robust determination of CMRGlc using either the compartmental modeling or the Patlak approach, even without bolus dispersion correction or blood sampling, with an underestimation of CMRGlc 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 CMRGlc, 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.
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