scholarly journals Reliable quantification of 18F-GE-180 PET neuroinflammation studies using an individually scaled population-based input function or late tissue-to-blood ratio

2020 ◽  
Vol 47 (12) ◽  
pp. 2887-2900 ◽  
Author(s):  
Ralph Buchert ◽  
Meike Dirks ◽  
Christian Schütze ◽  
Florian Wilke ◽  
Martin Mamach ◽  
...  
Keyword(s):  
Blood Sample ◽  
Whole Blood ◽  
Input Function ◽  
Population Based ◽  
Blood Sampling ◽  
Tracer Activity ◽  
Arterial Blood Sampling ◽  
Arterial Blood ◽  
The Individual ◽  
Individual Input

Abstract Purpose Tracer kinetic modeling of tissue time activity curves and the individual input function based on arterial blood sampling and metabolite correction is the gold standard for quantitative characterization of microglia activation by PET with the translocator protein (TSPO) ligand 18F-GE-180. This study tested simplified methods for quantification of 18F-GE-180 PET. Methods Dynamic 18F-GE-180 PET with arterial blood sampling and metabolite correction was performed in five healthy volunteers and 20 liver-transplanted patients. Population-based input function templates were generated by averaging individual input functions normalized to the total area under the input function using a leave-one-out approach. Individual population-based input functions were obtained by scaling the input function template with the individual parent activity concentration of 18F-GE-180 in arterial plasma in a blood sample drawn at 27.5 min or by the individual administered tracer activity, respectively. The total 18F-GE-180 distribution volume (VT) was estimated in 12 regions-of-interest (ROIs) by the invasive Logan plot using the measured or the population-based input functions. Late ROI-to-whole-blood and ROI-to-cerebellum ratio were also computed. Results Correlation with the reference VT (with individually measured input function) was very high for VT with the population-based input function scaled with the blood sample and for the ROI-to-whole-blood ratio (Pearson correlation coefficient = 0.989 ± 0.006 and 0.970 ± 0.005). The correlation was only moderate for VT with the population-based input function scaled with tracer activity dose and for the ROI-to-cerebellum ratio (0.653 ± 0.074 and 0.384 ± 0.177). Reference VT, population-based VT with scaling by the blood sample, and ROI-to-whole-blood ratio were sensitive to the TSPO gene polymorphism. Population-based VT with scaling to the administered tracer activity and the ROI-to-cerebellum ratio failed to detect a polymorphism effect. Conclusion These results support the use of a population-based input function scaled with a single blood sample or the ROI-to-whole-blood ratio at a late time point for simplified quantitative analysis of 18F-GE-180 PET.

scholarly journals Assessment of population-based input functions for Patlak imaging of whole body dynamic 18F-FDG PET

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Mika Naganawa ◽  
Jean-Dominique Gallezot ◽  
Vijay Shah ◽  
Tim Mulnix ◽  
Colin Young ◽  
...  
Keyword(s):  
Plasma Concentration ◽  
Gold Standard ◽  
Fdg Pet ◽  
Time Windows ◽  
Input Function ◽  
Population Based ◽  
Blood Sampling ◽  
Whole Body ◽  
Arterial Blood Sampling ◽  
Arterial Blood

Abstract Background Arterial blood sampling is the gold standard method to obtain the arterial input function (AIF) for quantification of whole body (WB) dynamic 18F-FDG PET imaging. However, this procedure is invasive and not typically available in clinical environments. As an alternative, we compared AIFs to population-based input functions (PBIFs) using two normalization methods: area under the curve (AUC) and extrapolated initial plasma concentration (CP*(0)). To scale the PBIFs, we tested two methods: (1) the AUC of the image-derived input function (IDIF) and (2) the estimated CP*(0). The aim of this study was to validate IDIF and PBIF for FDG oncological WB PET studies by comparing to the gold standard arterial blood sampling. Methods The Feng 18F-FDG plasma concentration model was applied to estimate AIF parameters (n = 23). AIF normalization used either AUC(0–60 min) or CP*(0), estimated from an exponential fit. CP*(0) is also described as the ratio of the injected dose (ID) to initial distribution volume (iDV). iDV was modeled using the subject height and weight, with coefficients that were estimated in 23 subjects. In 12 oncological patients, we computed IDIF (from the aorta) and PBIFs with scaling by the AUC of the IDIF from 4 time windows (15–45, 30–60, 45–75, 60–90 min) (PBIFAUC) and estimated CP*(0) (PBIFiDV). The IDIF and PBIFs were compared with the gold standard AIF, using AUC values and Patlak Ki values. Results The IDIF underestimated the AIF at early times and overestimated it at later times. Thus, based on the AUC and Ki comparison, 30–60 min was the most accurate time window for PBIFAUC; later time windows for scaling underestimated Ki (− 6 ± 8 to − 13 ± 9%). Correlations of AUC between AIF and IDIF, PBIFAUC(30–60), and PBIFiDV were 0.91, 0.94, and 0.90, respectively. The bias of Ki was − 9 ± 10%, − 1 ± 8%, and 3 ± 9%, respectively. Conclusions Both PBIF scaling methods provided good mean performance with moderate variation. Improved performance can be obtained by refining IDIF methods and by evaluating PBIFs with test-retest data.

scholarly journals Kinetic Analysis of [11C]MP4A Using a High-Radioactivity Brain Region That Represents an Integrated Input Function for Measurement of Cerebral Acetylcholinesterase Activity without Arterial Blood Sampling

2001 ◽  
Vol 21 (11) ◽  
pp. 1354-1366 ◽  
Author(s):  
Shin-Ichiro Nagatsuka ◽  
Kiyoshi Fukushi ◽  
Hitoshi Shinotoh ◽  
Hiroki Namba ◽  
Masaomi Iyo ◽  
...  
Keyword(s):  
Kinetic Analysis ◽  
Least Squares ◽  
Ache Activity ◽  
Input Function ◽  
Blood Sampling ◽  
Linear Least Squares ◽  
Reference Tissue ◽  
Arterial Blood Sampling ◽  
Arterial Blood ◽  
The Brain

N-[11C]methylpiperidin-4-yl acetate ([11C]MP4A) is an acetylcholine analog. It has been used successfully for the quantitative measurement of acetylcholinesterase (AChE) activity in the human brain with positron emission tomography (PET). [11C]MP4A is specifically hydrolyzed by AChE in the brain to a hydrophilic metabolite, which is irreversibly trapped locally in the brain. The authors propose a new method of kinetic analysis of brain AChE activity by PET without arterial blood sampling, that is, reference tissue-based linear least squares (RLS) analysis. In this method, cerebellum or striatum is used as a reference tissue. These regions, because of their high AChE activity, act as a biologic integrator of plasma input function during PET scanning, when regional metabolic rates of [11C]MP4A through AChE (k3; an AChE index) are calculated by using Blomqvist's linear least squares analysis. Computer simulation studies showed that RLS analysis yielded k3 with almost the same accuracy as the standard nonlinear least squares (NLS) analysis in brain regions with low (such as neocortex and hippocampus) and moderately high (thalamus) k3 values. The authors then applied these methods to [11C]MP4A PET data in 12 healthy subjects and 26 patients with Alzheimer disease (AD) using the cerebellum as the reference region. There was a highly significant linear correlation in regional k3 estimates between RLS and NLS analyses (456 cerebral regions, [RLS k3] = 0.98 × [NLS k3], r = 0.92, P < 0.001). Significant reductions were observed in k3 estimates of frontal, temporal, parietal, occipital, and sensorimotor cerebral neocortices ( P < 0.001, single-tailed t-test), and hippocampus ( P = 0.012) in patients with AD as compared with controls when using RLS analysis. Mean reductions (19.6%) Fin these 6 regions by RLS were almost the same as those by NLS analysis (20.5%). The sensitivity of RLS analysis for detecting cortical regions with abnormally low k3 in the 26 patients with AD (138 of 312 regions, 44%) was somewhat less than NLS analysis (52%), but was greater than shape analysis (33%), another method of [11C]MP4A kinetic analysis without blood sampling. The authors conclude that RLS analysis is practical and useful for routine analysis of clinical [11C]MP4A studies.

scholarly journals Comparison of Eight Methods for the Estimation of the Image-Derived Input Function in Dynamic [18F]-FDG PET Human Brain Studies

2009 ◽  
Vol 29 (11) ◽  
pp. 1825-1835 ◽  
Author(s):  
Paolo Zanotti-Fregonara ◽  
El Mostafa Fadaili ◽  
Renaud Maroy ◽  
Claude Comtat ◽  
Antoine Souloumiac ◽  
...  
Keyword(s):  
Blood Sample ◽  
Rate Constants ◽  
Fdg Pet ◽  
Input Function ◽  
Blood Samples ◽  
Arterial Blood ◽  
Positron Emission ◽  
Phantom Studies ◽  
The Individual ◽  
Individual Rate

The aim of this study was to compare eight methods for the estimation of the image-derived input function (IDIF) in [18F]-FDG positron emission tomography (PET) dynamic brain studies. The methods were tested on two digital phantoms and on four healthy volunteers. Image-derived input functions obtained with each method were compared with the reference input functions, that is, the activity in the carotid labels of the phantoms and arterial blood samples for the volunteers, in terms of visual inspection, areas under the curve, cerebral metabolic rates of glucose (CMRglc), and individual rate constants. Blood-sample-free methods provided less reliable results as compared with those obtained using the methods that require the use of blood samples. For some of the blood-sample-free methods, CMRglc estimations considerably improved when the IDIF was calibrated with a single blood sample. Only one of the methods tested in this study, and only in phantom studies, allowed a reliable calculation of the individual rate constants. For the estimation of CMRglc values using an IDIF in [18F]-FDG PET brain studies, a reliable absolute blood-sample-free procedure is not available yet.

scholarly journals Cerebral blood flow measurements with 15O-water PET using a non-invasive machine-learning-derived arterial input function

2021 ◽  
pp. 0271678X2199139
Author(s):  
Samuel Kuttner ◽  
Kristoffer Knutsen Wickstrøm ◽  
Mark Lubberink ◽  
Andreas Tolf ◽  
Joachim Burman ◽  
...  
Keyword(s):  
Machine Learning ◽  
Blood Flow ◽  
Cerebral Blood Flow ◽  
Arterial Input Function ◽  
Kinetic Modelling ◽  
Input Function ◽  
Blood Sampling ◽  
Arterial Blood Sampling ◽  
Non Invasive ◽  
Arterial Blood

Cerebral blood flow (CBF) can be measured with dynamic positron emission tomography (PET) of 15O-labeled water by using tracer kinetic modelling. However, for quantification of regional CBF, an arterial input function (AIF), obtained from arterial blood sampling, is required. In this work we evaluated a novel, non-invasive approach for input function prediction based on machine learning (MLIF), against AIF for CBF PET measurements in human subjects. Twenty-five subjects underwent two 10 min dynamic 15O-water brain PET scans with continuous arterial blood sampling, before (baseline) and following acetazolamide medication. Three different image-derived time-activity curves were automatically segmented from the carotid arteries and used as input into a Gaussian process-based AIF prediction model, considering both baseline and acetazolamide scans as training data. The MLIF approach was evaluated by comparing AIF and MLIF curves, as well as whole-brain grey matter CBF values estimated by kinetic modelling derived with either AIF or MLIF. The results showed that AIF and MLIF curves were similar and that corresponding CBF values were highly correlated and successfully differentiated before and after acetazolamide medication. In conclusion, our non-invasive MLIF method shows potential to replace the AIF obtained from blood sampling for CBF measurements using 15O-water PET and kinetic modelling.

scholarly journals Noninvasive Quantification of Cerebral Metabolic Rate for Glucose in Rats Using 18F-FDG PET and Standard Input Function

2015 ◽  
Vol 35 (10) ◽  
pp. 1664-1670 ◽  
Author(s):  
Yuki Hori ◽  
Naoki Ihara ◽  
Noboru Teramoto ◽  
Masako Kunimi ◽  
Manabu Honda ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Repeated Measures ◽  
Arterial Input Function ◽  
Area Under The Curve ◽  
Input Function ◽  
Blood Sampling ◽  
Cerebral Metabolic Rate ◽  
Positron Emission ◽  
The Individual ◽  
Individual Input

Measurement of arterial input function (AIF) for quantitative positron emission tomography (PET) studies is technically challenging. The present study aimed to develop a method based on a standard arterial input function (SIF) to estimate input function without blood sampling. We performed 18F-fluolodeoxyglucose studies accompanied by continuous blood sampling for measurement of AIF in 11 rats. Standard arterial input function was calculated by averaging AIFs from eight anesthetized rats, after normalization with body mass (BM) and injected dose (ID). Then, the individual input function was estimated using two types of SIF: (1) SIF calibrated by the individual's BM and ID (estimated individual input function, EIFNS) and (2) SIF calibrated by a single blood sampling as proposed previously (EIF1S). No significant differences in area under the curve (AUC) or cerebral metabolic rate for glucose (CMRGlc) were found across the AIF-, EIFNS-, and EIF1S-based methods using repeated measures analysis of variance. In the correlation analysis, AUC or CMRGlc derived from EIFNS was highly correlated with those derived from AIF and EIF1S. Preliminary comparison between AIF and EIFNS in three awake rats supported an idea that the method might be applicable to behaving animals. The present study suggests that EIFNS method might serve as a noninvasive substitute for individual AIF measurement.

scholarly journals CALIPER: A software for blood-free parametric Patlak mapping using PET/MRI input function.

2021 ◽  
Author(s):  
Praveen Dassanayake ◽  
Lumeng Cui ◽  
Elizabeth Finger ◽  
Matthew Kewin ◽  
Jennifer Hadaway ◽  
...  
Keyword(s):  
Input Function ◽  
Absolute Quantification ◽  
Blood Sampling ◽  
Pharmacokinetic Analysis ◽  
Influx Rate ◽  
Arterial Blood Sampling ◽  
Arterial Blood ◽  
Pet Tracer ◽  
Free Region ◽  
Pet Probes

Routine clinical use of absolute PET quantification techniques is limited by the need for serial arterial blood sampling for input function and more importantly by the lack of automated pharmacokinetic analysis tools that can be readily implemented in clinic with minimal effort. PET/MRI provides the ability for absolute quantification of PET probes without the need for serial arterial blood sampling using image-derived input functions (IDIFs). Here we introduce CALIPER, a tool for simplified pharmacokinetic modelling of PET probes with irreversible uptake or binding based on and PET/MR IDIFs and Patlak Plot analysis. CALIPER generates regional values or parametric maps of net influx rate (Ki) for tracers using reconstructed dynamic PET images and anatomical MRI for IDIF vessel delineation. We evaluated the performance of CALIPER for blood-free region-based and pixel-wise Patlak analyses of [18F]FDG. IDIFs corrected for partial volume errors including spill-out and spill-in effects were similar to AIF with a general bias of around 6-8%, even for arteries <5 mm. The Ki and cerebral metabolic rate of glucose estimated using IDIF were similar to estimates using blood sampling (<2%) and within limits of whole brain values reported in literature. Overall, CALIPER is a promising tool for irreversible PET tracer quantification and can simplify the ability to perform parametric analysis in clinical settings without the need for blood sampling.

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