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Journal of Nuclear Medicine

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Meeting ReportInstrumentation & Data Analysis

A generalized population-based input function estimation approach to minimize blood sampling in radioligand-receptor dynamic PET studies

Yun Zhou, Jennifer Coughlin, Arman Rahmim, Gwenn Smith, Christopher Endres, Dean Wong and Martin Pomper
Journal of Nuclear Medicine May 2012, 53 (supplement 1) 377;
Yun Zhou
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Jennifer Coughlin
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Arman Rahmim
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Gwenn Smith
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Christopher Endres
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Dean Wong
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Martin Pomper
1Radiology, Johns Hopkins University School of Medicine, Baltimore, MD
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Abstract

377

Objectives Evaluate and optimize a new population-based plasma input function (PIF) estimation method for non-invasive quantification of radioligand-receptor binding in dynamic PET studies that lack a reference tissue.

Methods Twenty 90-min dynamic [11C]DPA-713 PET studies with arterial blood sampling were performed for quantitative imaging of translocator protein (TSPO) in human brain. Ten regions of interest (ROIs) were drawn manually on the co-registered MRIs and copied to the dynamic PET images for tissue time activity curves (TACs). 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 sampling data was determined by interpolation and extrapolation using a scale-calibrated population mean of normalized PIFs. For cross-validation, 20 PET studies were divided into groups A (n=12) and B (n=8). A mean of normalized measured PIF in group A was used to estimate PIF in group B using the population-based method. Logan plot (t* = 40 min) was applied to ROI TACs to estimate the distribution volume (VT) with VTs estimated from the measured PIF (mPIF) was used as a gold standard. For a fixed number of total samples, the PIFs were estimated from different blood sampling schemes. The quality of each sampling protocol was then determined by statistical comparison of the VT estimates obtained from ePIF and mPIF.

Results The linear correlations between the VT estimates from the ePIF (with optimal blood sampling scheme) and those from the mPIF were: VT (ePIF; 1 sample at 12 min) = 1.07 VT(mPIF) -0.19, R2 = 0.97; VT(ePIF; 2 samples at 10 and 40 min) = 1.07VT(mPIF) - 0.17, R2 = 0.98; VT(ePIF; 3 samples at 12, 25, and 70 min) = 1.03VT(mPIF) - 0.10, R2= 0.99.

Conclusions The generalized population-based PIF estimation method with optimal blood sampling scheme is a reliable method to estimate PIFs from a small sample size of blood sampling data for quantification of [11C]DPA-713 TSPO binding

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Journal of Nuclear Medicine
Vol. 53, Issue supplement 1
May 2012
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A generalized population-based input function estimation approach to minimize blood sampling in radioligand-receptor dynamic PET studies
Yun Zhou, Jennifer Coughlin, Arman Rahmim, Gwenn Smith, Christopher Endres, Dean Wong, Martin Pomper
Journal of Nuclear Medicine May 2012, 53 (supplement 1) 377;

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A generalized population-based input function estimation approach to minimize blood sampling in radioligand-receptor dynamic PET studies
Yun Zhou, Jennifer Coughlin, Arman Rahmim, Gwenn Smith, Christopher Endres, Dean Wong, Martin Pomper
Journal of Nuclear Medicine May 2012, 53 (supplement 1) 377;
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