PURPOSE: To investigate the effect of image-derived input functions (IDIF), input function corrections and volume of interest (VOI) size in quantification of [(18)F]FLT uptake in non-small cell lung cancer (NSCLC) patients. PROCEDURES: Twenty-three NSCLC patients were scanned on a HR+ scanner. IDIFs were defined over the aorta and left ventricle. Activity concentration and metabolite fraction were measured in venous blood samples. Venous blood samples at 30, 40 and 60 min after injection were used to calibrate the IDIF time-activity curves. Adaptive thresholds were used for VOI definition. Full kinetic analysis and simplified measures were performed. RESULTS: Non-linear regression analysis showed better fits for the irreversible model compared to the reversible model in the majority. Calibrated and metabolite corrected plus plasma-to-blood ratio corrected input function resulted in high correlations between SUV and Patlak K i (Pearson correlation coefficients 0.86-0.96, p value < 0.001). No significant differences in correlation between SUV and Patlak K i were observed with variation of IDIF structure or VOI size. CONCLUSIONS: Plasma-to-blood ratio correction, metabolite correction and calibration improved the correlation between SUV and Patlak K i significantly, indicating the need for these corrections when K i is used to validate semi-quantitative measures, such as SUV.
PURPOSE: To investigate the effect of image-derived input functions (IDIF), input function corrections and volume of interest (VOI) size in quantification of [(18)F]FLT uptake in non-small cell lung cancer (NSCLC) patients. PROCEDURES: Twenty-three NSCLCpatients were scanned on a HR+ scanner. IDIFs were defined over the aorta and left ventricle. Activity concentration and metabolite fraction were measured in venous blood samples. Venous blood samples at 30, 40 and 60 min after injection were used to calibrate the IDIF time-activity curves. Adaptive thresholds were used for VOI definition. Full kinetic analysis and simplified measures were performed. RESULTS: Non-linear regression analysis showed better fits for the irreversible model compared to the reversible model in the majority. Calibrated and metabolite corrected plus plasma-to-blood ratio corrected input function resulted in high correlations between SUV and Patlak K i (Pearson correlation coefficients 0.86-0.96, p value < 0.001). No significant differences in correlation between SUV and Patlak K i were observed with variation of IDIF structure or VOI size. CONCLUSIONS: Plasma-to-blood ratio correction, metabolite correction and calibration improved the correlation between SUV and Patlak K i significantly, indicating the need for these corrections when K i is used to validate semi-quantitative measures, such as SUV.
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