PURPOSE: Despite 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 (18)F-FDG for brain imaging and the other using (11)C-acetate and (18)F-fluoro-6-thioheptadecanoic acid ((18)F-FTHA) in femoral muscles. METHODS: The 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 (11)C-acetate and (18)F-FTHA and to carotid artery data from brain imaging with (18)F-FDG. These IDIF data were then compared to actual AIFs from patients. RESULTS: With (11)C-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 (18)F-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 (18)F-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 (r ( 2 )=0.90). CONCLUSION: Correctly 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.
PURPOSE: Despite 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 (18)F-FDG for brain imaging and the other using (11)C-acetate and (18)F-fluoro-6-thioheptadecanoic acid ((18)F-FTHA) in femoral muscles. METHODS: The 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 (11)C-acetate and (18)F-FTHA and to carotid artery data from brain imaging with (18)F-FDG. These IDIF data were then compared to actual AIFs from patients. RESULTS: With (11)C-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 (18)F-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 (18)F-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 (r ( 2 )=0.90). CONCLUSION: Correctly 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.
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