Rong Fu Wang
Peking University Health Science Center, China
Scientific Tracks Abstracts: J Neurol Neurophysiol
18F-FDG uptake rate constant Ki is a most interested and commonly used parameter for absolute quantification of 18F-FDG PET/CT. Ki is usually estimated by fitting a kinetic model with plasma input function (PIF) to the measured dynamic PET data. The need for arterial blood sampling to measure PIF (mPIF) is a main barrier to estimate Ki for clinical 18F-FDG PET. Two existing noninvasive PIF estimation methods, image derived PIF and simultaneous fitting method with kinetic model and parametric PIF, require image data to be acquired continuously and immediately post tracer injection. The objective of the study is to validate and optimize a generalized population-based PIF estimation method for noninvasive quantification of dynamic 18F-FDG PET for sparsely sampled PIF. Eight 60-min 27-frame monkey dynamic 18F-FDG PET studies were collected from a Philips Gemini GXL PET/CT with 3D data acquisition mode. Total 34 arterial blood samples were taken during PET scan as: 22 samples for the first 4 min, and followed by sampling at 5, 6, 8, 10, 12, 15, 20, 25, 30, 40, 50 and 60 min. Time activity curves (TACs) of 7 cerebral regions of interests (ROIs) were generated from each study. A generalized population-based approach to recover full kinetics of the PIF from sparsely sampled blood data is proposed. The estimated PIF (ePIF) from the incomplete PIF sampling data was determined by interpolation and extrapolation using scale-calibrated population mean of normalized PIFs. The optimal blood sampling scheme with given sample size m was determined by maximizing coefficient coefficients of Ki estimates between the Kis from measured PIF (mPIF) and estimated PIF (ePIF). The leave-two-out cross validation was performed. The linear correlations between the Ki estimates from the ePIF (with optimal sampling scheme) and those from the mPIF were: Ki(ePIF; 1 sample at 40 min) = 1.015Ki(mPIF) -0.000, R2 = 0.974; Ki(ePIF; 2 samples at 25 and 50 min) = 1.029Ki(mPIF) - 0.000, R2 = 0.985; Ki(ePIF; 3 samples at 8, 20, and 50 min) = 1.039Ki(mPIF) - 0.001, R2= 0.993; and Ki(ePIF; 4 samples at 8,12, 25, 40, and 55 min) = 1.02Ki(mPIF)-0.000, R2=0.997. The correlations of R2 from leave-2-out validation study were 0.978�±0.007, 0.990�±0.006, and 0.996�±0.003 (mean �±SD) for 1, 2, and 3 samples of optimal sampling scheme, respectively. The generalized population-based PIF estimation method is a reliable method to estimate PIFs from incomplete blood sampling data for quantification of dynamic 18F-FDG PET using the Gjedde-Patlak plot.
Rong Fu Wang has completed his MD at the age of 27 years from Fujian Medical University in 1982, postdoctoral studies from Paris V University School of Medicine in 1993 and his PhD at the age of 40 years from Toulous IIl University in 1995. He is the director of Department of Nuclear Medicine, Peking University Health Science Center. The research interests of Dr. Wang include experimental study and clinical application of molecular and clinical nuclear medicine. He has published more than 400 papers in reputed journals and has been serving as many editorial board member of reputed journals at home and abroad. He has published 3 monographs, and has got 3 patents of invention and 3 provincial and ministerial Awards.
Email: rongfu_wang@163.com
