scholarly journals Population-based input function for TSPO quantification and kinetic modeling with [11C]-DPA-713

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mercy I. Akerele ◽  
Sara A. Zein ◽  
Sneha Pandya ◽  
Anastasia Nikolopoulou ◽  
Susan A. Gauthier ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Kinetic Analysis ◽  
Kinetic Modeling ◽  
Input Function ◽  
Brain Regions ◽  
Population Based ◽  
Patient Specific ◽  
Systematic Bias ◽  
Altman Analysis ◽  
Bland Altman Analysis

Abstract Introduction Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF. Materials and methods Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected, (b) area under AIF curve (AUC), and (c) Weightsubject×AUC. The variability in the VT measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed. Results Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is −10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ± 38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%). Conclusions PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

scholarly journals Population-Based Input Function for TSPO Quantification and Kinetic Modeling with [11C]-DPA-713

2021 ◽  
Author(s):  
Mercy Iyabode Akerele ◽  
Sara A. Zein ◽  
Sneha Pandya ◽  
Anastasia Nikolopoulou ◽  
Susan A. Gauthier ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Kinetic Analysis ◽  
Kinetic Modeling ◽  
Input Function ◽  
Brain Regions ◽  
Population Based ◽  
Patient Specific ◽  
Systematic Bias ◽  
Altman Analysis ◽  
Bland Altman Analysis

Abstract Introduction: Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF. Materials and Methods: Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 minutes of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient specific AIF (PSAIF, ground-truth standard), and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects, and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected (b) Area Under AIF Curve (AUC), and (c) Weightsubject×AUC. The variability in the total distribution volume (VT) measured with PSAIF, in the test/retest study were determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus and amygdala) using the Bland-Altman analysis, and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed.Results: Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ±70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is -10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ±38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions. Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/ HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (%difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%). Conclusions: PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible, and can be an alternative to PSAIF.

scholarly journals Feasibility of Population-Based Input Function for Kinetic Modeling of [11C]-DPA-713

2020 ◽  
Author(s):  
Mercy Iyabode Akerele ◽  
Sara Zein ◽  
Sneha Pandya ◽  
Anastasia Nikolopoulou ◽  
Susan A. Gauthier ◽  
...  
Keyword(s):  
Kinetic Analysis ◽  
Kinetic Modeling ◽  
Gray Matter ◽  
Input Function ◽  
Brain Regions ◽  
Population Based ◽  
Patient Specific ◽  
Systematic Bias ◽  
Altman Analysis ◽  
Bland Altman Analysis

Abstract Introduction: Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [ 11 C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF. Materials and Methods: Eighteen subjects including six healthy controls (HC) and twelve Parkinson disease (PD) subjects from two [ 11 C]-DPA-713 PET studies were included. Each subject underwent 90 minutes of dynamic PET imaging. Five healthy subjects underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient specific AIF (PSAIF, ground-truth standard), and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects, and after normalizing the PSAIFs by 3 techniques: (a) Weight subject ×Dose Injected (b) Area Under AIF Curve (AUC), and (c) Weight subject ×AUC. The variability in the total distribution volume (V T ) measured with PSAIF, in the test/retest study were determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus and amygdala) using the Bland-Altman analysis, and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed. Results: Bland-Altman analysis showed systematic bias between test and retest studies, which was reduced after normalizing the V T estimate by the corresponding gray matter value. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and 5%; ±70% and ±20% without and with gray matter normalization respectively. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, normalization by Weight subject ×AUC yielded the smallest 95% LOA among the three normalization techniques (±12%, ±13% and ±10% for Weight subject ×Dose Injected , AUC and Weight subject ×AUC respectively). Conclusions: The variability in VT is within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible, and can be an alternative to PSAIF.

scholarly journals Dynamic PET of Human Liver Inflammation: Impact of Kinetic Modeling with Optimization-Derived Dual-Blood Input Function

2018 ◽  
Author(s):  
Guobao Wang ◽  
Michael T. Corwin ◽  
Kristin A. Olson ◽  
Ramsey D. Badawi ◽  
Souvik Sarkar
Keyword(s):  
Kinetic Analysis ◽  
Kinetic Modeling ◽  
Fdg Pet ◽  
Human Liver ◽  
Input Function ◽  
Population Based ◽  
Joint Estimation ◽  
Human Studies ◽  
Liver Inflammation ◽  
Time Activity

ABSTRACTThe hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. This paper aims to identify the optimal dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen patients with nonalcoholic fatty liver disease were included. Each patient underwent 1-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and new model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation score. Results showed that the optimization-derived DBIF model improved liver time activity curve fitting and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for dynamic liver FDG-PET kinetic analysis in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation.

scholarly journals Kinetic Analysis of the 5-HT2A Ligand [11C]MDL 100,907

2000 ◽  
Vol 20 (6) ◽  
pp. 899-909 ◽  
Author(s):  
Hiroshi Watabe ◽  
Michael A. Channing ◽  
Margaret G. Der ◽  
H. Richard Adams ◽  
Elaine Jagoda ◽  
...  
Keyword(s):  
Kinetic Analysis ◽  
Specific Binding ◽  
Compartment Model ◽  
Input Function ◽  
Brain Regions ◽  
Time Activity ◽  
Tissue Compartment ◽  
Arterial Blood ◽  
Fixed Parameter ◽  
Mdl 100,907

The goal of this study was to develop a suitable kinetic analysis method for quantification of 5-HT2A receptor parameters with [11C]MDL 100,907. Twelve control studies and four preblocking studies (400 nmol/kg unlabeled MDL 100,907) were performed in isoflurane-anesthetized rhesus monkeys. The plasma input function was determined from arterial blood samples with metabolite measurements by extraction in ethyl acetate. The preblocking studies showed that a two-tissue compartment model was necessary to fit the time activity curves of all brain regions including the cerebellum—in other words, the need for two compartments is not proof of specific binding. Therefore, a three-tissue compartment model was used to analyze the control studies, with three parameters fixed based on the preblocking data. Reliable fits of control data could be obtained only if no more than three parameters were allowed to vary. For routine use of [11C]MDL 100,907, several simplified methods were evaluated. A two-tissue (2T‘) compartment with one fixed parameter was the most reliable compartmental approach; a one-compartment model failed to fit the data adequately. The Logan graphical approach was also tested and produced comparable results to the 2T’ model. However, a simulation study showed that Logan analysis produced a larger bias at higher noise levels. Thus, the 2T' model is the best choice for analysis of [11C]MDL 100,907 studies.

scholarly journals Quantifying lumbar vertebral perfusion by a Tofts model on DCE-MRI using segmental versus aortic arterial input function

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yi-Jui Liu ◽  
Hou-Ting Yang ◽  
Melissa Min-Szu Yao ◽  
Shao-Chieh Lin ◽  
Der-Yang Cho ◽  
...  
Keyword(s):  
Arterial Input Function ◽  
Lumbar Vertebrae ◽  
Region Of Interest ◽  
Input Function ◽  
Population Based ◽  
Patient Specific ◽  
Rank Test ◽  
Pharmacokinetic Parameters ◽  
Dce Mri ◽  
Signed Rank Test

AbstractThe purpose of this study was to investigate the influence of arterial input function (AIF) selection on the quantification of vertebral perfusion using axial dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In this study, axial DCE-MRI was performed on 2 vertebrae in each of eight healthy volunteers (mean age, 36.9 years; 5 men) using a 1.5-T scanner. The pharmacokinetic parameters Ktrans, ve, and vp, derived using a Tofts model on axial DCE-MRI of the lumbar vertebrae, were evaluated using various AIFs: the population-based aortic AIF (AIF_PA), a patient-specific aortic AIF (AIF_A) and a patient-specific segmental arterial AIF (AIF_SA). Additionally, peaks and delay times were changed to simulate the effects of various AIFs on the calculation of perfusion parameters. Nonparametric analyses including the Wilcoxon signed rank test and the Kruskal–Wallis test with a Dunn–Bonferroni post hoc analysis were performed. In simulation, Ktrans and ve increased as the peak in the AIF decreased, but vp increased when delay time in the AIF increased. In humans, the estimated Ktrans and ve were significantly smaller using AIF_A compared to AIF_SA no matter the computation style (pixel-wise or region-of-interest based). Both these perfusion parameters were significantly greater using AIF_SA compared to AIF_A.

scholarly journals Compressed sensing acceleration of cardiac cine imaging allows reliable and reproducible assessment of volumetric and functional parameters of the left and right atrium

2021 ◽  
Author(s):  
Sebastian Altmann ◽  
Moritz C. Halfmann ◽  
Ibukun Abidoye ◽  
Basel Yacoub ◽  
Michaela Schmidt ◽  
...  
Keyword(s):  
Heart Failure ◽  
Compressed Sensing ◽  
Healthy Volunteers ◽  
Acquisition Time ◽  
Cine Imaging ◽  
Functional Evaluation ◽  
Altman Analysis ◽  
Bland Altman Analysis ◽  
Functional Parameters ◽  
And Function

Abstract Objectives To compare volumetric and functional parameters of the atria derived from highly accelerated compressed sensing (CS)–based cine sequences in comparison to conventional (Conv) cine imaging. Methods CS and Conv cine sequences were acquired in 101 subjects (82 healthy volunteers (HV) and 19 patients with heart failure with reduced ejection fraction (HFrEF)) using a 3T MR scanner in this single-center study. Time-volume analysis of the left (LA) and right atria (RA) were performed in both sequences to evaluate atrial volumes and function (total, passive, and active emptying fraction). Inter-sequence and inter- and intra-reader agreement were analyzed using correlation, intraclass correlation (ICC), and Bland-Altman analysis. Results CS-based cine imaging led to a 69% reduction of acquisition time. There was significant difference in atrial parameters between CS and Conv cine, e.g., LA minimal volume (LAVmin) (Conv 24.0 ml (16.7–32.7), CS 25.7 ml (19.2–35.2), p < 0.0001) or passive emptying fraction (PEF) (Conv 53.9% (46.7–58.4), CS 49.0% (42.0–54.1), p < 0.0001). However, there was high correlation between the techniques, yielding good to excellent ICC (0.76–0.99) and small mean of differences in Bland-Altman analysis (e.g. LAVmin − 2.0 ml, PEF 3.3%). Measurements showed high inter- (ICC > 0.958) and intra-rater (ICC > 0.934) agreement for both techniques. CS-based parameters (PEF AUC = 0.965, LAVmin AUC = 0.864) showed equivalent diagnostic ability compared to Conv cine imaging (PEF AUC = 0.989, LAVmin AUC = 0.859) to differentiate between HV and HFrEF. Conclusion Atrial volumetric and functional evaluation using CS cine imaging is feasible with relevant reduction of acquisition time, therefore strengthening the role of CS in clinical CMR for atrial imaging. Key Points • Reliable assessment of atrial volumes and function based on compressed sensing cine imaging is feasible. • Compressed sensing reduces scan time and has the potential to overcome obstacles of conventional cine imaging. • No significant differences for subjective image quality, inter- and intra-rater agreement, and ability to differentiate healthy volunteers and heart failure patients were detected between conventional and compressed sensing cine imaging.

Feasibility of Population-Based Input Function for Kinetic Analysis of [11C]-DPA-713

2020 ◽  
Author(s):  
Susan A. Gauthier ◽  
Claire Henchcliffe ◽  
Mercy I. Akerele ◽  
Sara A. Zein ◽  
Sneha Pandya ◽  
...  
Keyword(s):  
Kinetic Analysis ◽  
Input Function ◽  
Population Based

Reply: Bland-Altman analysis for pupillometer comparison

2010 ◽  
Vol 36 (10) ◽  
pp. 1803-1804
Author(s):  
Magdalena Scheffel ◽  
Christoph Kuehne ◽  
Thomas Kohnen
Keyword(s):  
Altman Analysis ◽  
Bland Altman Analysis

scholarly journals Evaluation of automated microvascular flow analysis software AVA 4: a validation study

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Christian S. Guay ◽  
Mariam Khebir ◽  
T. Shiva Shahiri ◽  
Ariana Szilagyi ◽  
Erin Elizabeth Cole ◽  
...  
Keyword(s):  
General Anesthesia ◽  
Validation Study ◽  
Validation Studies ◽  
Gold Standard ◽  
Flow Analysis ◽  
Automated Analysis ◽  
Altman Analysis ◽  
Analysis Software ◽  
Bland Altman Analysis ◽  
Microvascular Flow

Abstract Background Real-time automated analysis of videos of the microvasculature is an essential step in the development of research protocols and clinical algorithms that incorporate point-of-care microvascular analysis. In response to the call for validation studies of available automated analysis software by the European Society of Intensive Care Medicine, and building on a previous validation study in sheep, we report the first human validation study of AVA 4. Methods Two retrospective perioperative datasets of human microcirculation videos (P1 and P2) and one prospective healthy volunteer dataset (V1) were used in this validation study. Video quality was assessed using the modified Microcirculation Image Quality Selection (MIQS) score. Videos were initially analyzed with (1) AVA software 3.2 by two experienced investigators using the gold standard semi-automated method, followed by an analysis with (2) AVA automated software 4.1. Microvascular variables measured were perfused vessel density (PVD), total vessel density (TVD), and proportion of perfused vessels (PPV). Bland–Altman analysis and intraclass correlation coefficients (ICC) were used to measure agreement between the two methods. Each method’s ability to discriminate between microcirculatory states before and after induction of general anesthesia was assessed using paired t-tests. Results Fifty-two videos from P1, 128 videos from P2 and 26 videos from V1 met inclusion criteria for analysis. Correlational analysis and Bland–Altman analysis revealed poor agreement and no correlation between AVA 4.1 and AVA 3.2. Following the induction of general anesthesia, TVD and PVD measured using AVA 3.2 increased significantly for P1 (p < 0.05) and P2 (p < 0.05). However, these changes could not be replicated with the data generated by AVA 4.1. Conclusions AVA 4.1 is not a suitable tool for research or clinical purposes at this time. Future validation studies of automated microvascular flow analysis software should aim to measure the new software’s agreement with the gold standard, its ability to discriminate between clinical states and the quality thresholds at which its performance becomes unacceptable.

scholarly journals Comparison of IOP Measurement by Goldmann Applanation Tonometer, ICare Rebound Tonometer, and Tono-Pen in Keratoconus Patients after MyoRing Implantation

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Mahmoud Rateb ◽  
Mahmoud Abdel-Radi ◽  
Zeiad Eldaly ◽  
Mohamed Nagy Elmohamady ◽  
Asaad Noor El Din
Keyword(s):  
Central Corneal Thickness ◽  
Pearson Correlation ◽  
Corneal Thickness ◽  
Altman Analysis ◽  
Bland Altman Analysis ◽  
Rebound Tonometer ◽  
Goldmann Applanation Tonometer ◽  
Significant Difference ◽  
Applanation Tonometer ◽  
Icare Rebound Tonometer

Purpose. To evaluate the different IOP readings by Goldmann applanation tonometer (GAT), ICare rebound tonometer, and Tono-Pen in keratoconus patients after MyoRing implantation. To assess the influence of central corneal thickness (CCT) and thinnest corneal location (TCL) on IOP measurements by different tonometers. Setting. Prospective observational study was conducted in two private centers in Egypt from February 2015 to November 2016. Methods. Seventeen eyes of 10 patients suffering from keratoconus and who underwent MyoRing implantation were recruited. All subjects underwent GAT, ICare, and Tono-Pen IOP measurements in random order. Central corneal thickness and thinnest corneal location were assessed by Pentacam. Difference in mean in IOP readings was assessed by T-test. Correlation between each pair of devices was evaluated by Pearson correlation coefficient. The Bland–Altman analysis was used to assess intertonometer agreement. Results. Seventeen eyes (10 patients) were evaluated. The mean IOP reading was 13.9 ± 3.68, 12.41 ± 2.87, and 14.29 ± 1.31 mmHg in GAT, ICare, and Tono-Pen group, respectively. There was a significant difference between IOP readings by GAT/ICare and Tono-Pen/ICare (p value: 0.032 and 0.002, respectively) with no significant difference between GAT/Tono-Pen (p value: 0.554). Mean difference in IOP measurements between GAT/ICare was 1.49 ± 2.61 mmHg, Tono-Pen/ICare was 1.89 ± 2.15 mmHg, and GAT/Tono-Pen was −0.39 ± 2.59 mmHg. There was no significant correlation between the difference in IOP readings among any pair of devices and CCC or TCL. The Bland–Altman analysis showed a reasonable agreement between any pair of tonometers.

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