scholarly journals Dynamic 18F-FDopa PET Imaging for Newly-diagnosed Gliomas: Is a Semi-quantitative Model Sufficient?

2021 ◽  
Author(s):  
Timothée ZARAGORI ◽  
Matthieu Doyen ◽  
Fabien Rech ◽  
Marie Blonski ◽  
Luc Taillandier ◽  
...  
Keyword(s):  
Kinetic Model ◽  
Dynamic Analysis ◽  
Pet Imaging ◽  
Compartmental Model ◽  
Area Under The Curve ◽  
Quantitative Model ◽  
Newly Diagnosed ◽  
Reference Region ◽  
Time Activity ◽  
Idh Mutations

Abstract Purpose: Even though the semi quantitative dynamic analysis of 18F-FDOPA PET effectively and non-invasively predicts isocitrate dehydrogenase (IDH) mutations in newly-diagnosed gliomas, the underlying kinetic model of 18F-FDOPA is complex. Our current study addresses whether a semi quantitative analysis indeed captures all the clinically relevant predictive features of the more sophisticated graphical and compartmental models.Methods: Thirty-seven tumour time-activity curves from 18F-FDOPA PET dynamic acquisitions of newly-diagnosed gliomas were analysed using a semi quantitative model with (Ref SQ) or without reference region (SQ), a graphical Logan model with input function (Logan) or reference region (Ref Logan), and a two-tissue compartmental model validated for 18F-FDOPA PET imaging in gliomas (2TCM). The overall predictive performance of each model for predicting IDH mutations was assessed, by an area under the curve (AUC) comparison of multivariate analyses of all parameters included in the model.Results: SQ model with an AUC of 0.733 showed comparable performances to other models with AUCs of 0.814, 0.693, 0.786, 0.863, respectively corresponding to Ref SQ, Logan, Ref Logan and 2 TCM (p≥0.11 for the pairwise comparisons with other models). SQ time-to-peak parameter had the best diagnostic performance relative to all individual parameters with an accuracy of 75.7%.Conclusions: The SQ model circumvents the complexities of the 18F-FDOPA kinetic model and yields similar performances compared to other models most notably the compartmental model for predicting IDH mutations. This validates the application of the SQ model for the dynamic analysis of 18F-FDOPA PET images in routine clinical practice for newly-diagnosed gliomas.

scholarly journals Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?

2021 ◽  
Vol 11 ◽  
Author(s):  
Timothée Zaragori ◽  
Matthieu Doyen ◽  
Fabien Rech ◽  
Marie Blonski ◽  
Luc Taillandier ◽  
...  
Keyword(s):  
Kinetic Model ◽  
Dynamic Analysis ◽  
Pet Imaging ◽  
Compartmental Model ◽  
Univariate Analysis ◽  
The Other ◽  
Newly Diagnosed ◽  
Reference Region ◽  
Time Activity ◽  
Idh Mutations

PurposeDynamic amino acid positron emission tomography (PET) has become essential in neuro-oncology, most notably for its prognostic value in the noninvasive prediction of isocitrate dehydrogenase (IDH) mutations in newly diagnosed gliomas. The 6-[18F]fluoro-l-DOPA (18F-FDOPA) kinetic model has an underlying complexity, while previous studies have predominantly used a semiquantitative dynamic analysis. Our study addresses whether a semiquantitative analysis can capture all the relevant information contained in time–activity curves for predicting the presence of IDH mutations compared to the more sophisticated graphical and compartmental models.MethodsThirty-seven tumour time–activity curves from 18F-FDOPA PET dynamic acquisitions of newly diagnosed gliomas (median age = 58.3 years, range = 20.3–79.9 years, 16 women, 16 IDH-wild type) were analyzed with a semiquantitative model based on classical parameters, with (SQ) or without (Ref SQ) a reference region, or on parameters of a fit function (SQ Fit), a graphical Logan model with input function (Logan) or reference region (Ref Logan), and a two-tissue compartmental model previously reported for 18F-FDOPA PET imaging of gliomas (2TCM). The overall predictive performance of each model was assessed with an area under the curve (AUC) comparison using multivariate analysis of all the parameters included in the model. Moreover, each extracted parameter was assessed in a univariate analysis by a receiver operating characteristic curve analysis.ResultsThe SQ model with an AUC of 0.733 for predicting IDH mutations showed comparable performance to the other models with AUCs of 0.752, 0.814, 0.693, 0.786, and 0.863, respectively corresponding to SQ Fit, Ref SQ, Logan, Ref Logan, and 2TCM (p ≥ 0.10 for the pairwise comparisons with other models). In the univariate analysis, the SQ time-to-peak parameter had the best diagnostic performance (75.7% accuracy) compared to all other individual parameters considered.ConclusionsThe SQ model circumvents the complexities of the 18F-FDOPA kinetic model and yields similar performance in predicting IDH mutations when compared to the other models, most notably the compartmental model. Our study provides supportive evidence for the routine clinical application of the SQ model for the dynamic analysis of 18F-FDOPA PET images in newly diagnosed gliomas.

scholarly journals Modeling of the Renal Kinetics of the AT1 Receptor Specific PET Radioligand [11C]KR31173

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Nedim C. M. Gulaldi ◽  
Jinsong Xia ◽  
Tao Feng ◽  
Kelvin Hong ◽  
William B. Mathews ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Compartmental Model ◽  
Radioligand Binding ◽  
Left Kidney ◽  
Binding Parameters ◽  
Retention Parameter ◽  
Time Activity ◽  
Kinetics Of

Purpose. The radioligand [11C]KR31173 has been introduced for PET imaging of the angiotensin II subtype 1 receptor (AT1R). The purpose of the present project was to employ and validate a compartmental model for quantification of the kinetics of this radioligand in a porcine model of renal ischemia followed by reperfusion (IR).Procedures. Ten domestic pigs were included in the study: five controls and five experimental animals with IR of the left kidney. To achieve IR, acute ischemia was created with a balloon inserted into the left renal artery and inflated for 60 minutes. Reperfusion was achieved by deflation and removal of the balloon. Blood chemistries, urine specific gravity and PH values, and circulating hormones of the renin angiotensin system were measured and PET imaging was performed one week after IR. Cortical time-activity curves obtained from a 90 min [11C]KR31173 dynamic PET study were processed with a compartmental model that included two tissue compartments connected in parallel. Radioligand binding quantified by radioligand retention (80 min value to maximum value ratio) was compared to the binding parameters derived from the compartmental model. A binding ratio was calculated asDVR=DVS/DVNS, whereDVSandDVNSrepresented the distribution volumes of specific binding and nonspecific binding. Receptor binding was also determined by autoradiographyin vitro.Results. Correlations between rate constants and binding parameters derived by the convolution and deconvolution curve fittings were significant(r>0.9). Also significant was the correlation between the retention parameter derived from the tissue activity curve (Yret) and the retention parameter derived from the impulse response function (fret). Furthermore, significant correlations were found between these two retention parameters and DVR. Measurements with PET showed no significant changes in the radioligand binding parameters caused by IR, and thesein vivofindings were confirmed by autoradiography performedin vitro.Conclusions. Correlations between various binding parameters support the concept of the parallel connectivity compartmental model. If an arterial input function cannot be obtained, simple radioligand retention may be adequate for estimation ofin vivoradioligand binding.

scholarly journals Texture-Based Analysis of 18F-Labeled Amyloid PET Brain Images

2021 ◽  
Vol 11 (5) ◽  
pp. 1991
Author(s):  
Alexander P. Seiffert ◽  
Adolfo Gómez-Grande ◽  
Eva Milara ◽  
Sara Llamas-Velasco ◽  
Alberto Villarejo-Galende ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Standardized Uptake Value ◽  
Texture Features ◽  
Roc Curves ◽  
Significant Feature ◽  
Study Cohort ◽  
Amyloid Pet ◽  
Reference Region ◽  
Brain Images ◽  
Positron Emission

Amyloid positron emission tomography (PET) brain imaging with radiotracers like [18F]florbetapir (FBP) or [18F]flutemetamol (FMM) is frequently used for the diagnosis of Alzheimer’s disease. Quantitative analysis is usually performed with standardized uptake value ratios (SUVR), which are calculated by normalizing to a reference region. However, the reference region could present high variability in longitudinal studies. Texture features based on the grey-level co-occurrence matrix, also called Haralick features (HF), are evaluated in this study to discriminate between amyloid-positive and negative cases. A retrospective study cohort of 66 patients with amyloid PET images (30 [18F]FBP and 36 [18F]FMM) was selected and SUVRs and 6 HFs were extracted from 13 cortical volumes of interest. Mann–Whitney U-tests were performed to analyze differences of the features between amyloid positive and negative cases. Receiver operating characteristic (ROC) curves were computed and their area under the curve (AUC) was calculated to study the discriminatory capability of the features. SUVR proved to be the most significant feature among all tests with AUCs between 0.692 and 0.989. All HFs except correlation also showed good performance. AUCs of up to 0.949 were obtained with the HFs. These results suggest the potential use of texture features for the classification of amyloid PET images.

scholarly journals PET Imaging of [11C]MPC-6827, a Microtubule-Based Radiotracer in Non-Human Primate Brains

Molecules ◽  
2020 ◽  
Vol 25 (10) ◽  
pp. 2289
Author(s):  
Naresh Damuka ◽  
Paul Czoty ◽  
Ashley Davis ◽  
Michael Nader ◽  
Susan Nader ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Neurological Disorders ◽  
Healthy Male ◽  
Time Activity ◽  
Positron Emission ◽  
Pet Ct ◽  
Scan Data ◽  
The Brain ◽  
Human Primate

Dysregulation of microtubules is commonly associated with several psychiatric and neurological disorders, including addiction and Alzheimer’s disease. Imaging of microtubules in vivo using positron emission tomography (PET) could provide valuable information on their role in the development of disease pathogenesis and aid in improving therapeutic regimens. We developed [11C]MPC-6827, the first brain-penetrating PET radiotracer to image microtubules in vivo in the mouse brain. The aim of the present study was to assess the reproducibility of [11C]MPC-6827 PET imaging in non-human primate brains. Two dynamic 0–120 min PET/CT imaging scans were performed in each of four healthy male cynomolgus monkeys approximately one week apart. Time activity curves (TACs) and standard uptake values (SUVs) were determined for whole brains and specific regions of the brains and compared between the “test” and “retest” data. [11C]MPC-6827 showed excellent brain uptake with good pharmacokinetics in non-human primate brains, with significant correlation between the test and retest scan data (r = 0.77, p = 0.023). These initial evaluations demonstrate the high translational potential of [11C]MPC-6827 to image microtubules in the brain in vivo in monkey models of neurological and psychiatric diseases.

scholarly journals In vitro and In vivo Assessment of Suitable Reference Region and Kinetic Modelling for the mGluR1 Radioligand [11C]ITDM in Mice

2019 ◽  
Vol 22 (4) ◽  
pp. 854-863 ◽  
Author(s):  
Daniele Bertoglio ◽  
Jeroen Verhaeghe ◽  
Špela Korat ◽  
Alan Miranda ◽  
Leonie wyffels ◽  
...  
Keyword(s):  
Mouse Brain ◽  
Pet Imaging ◽  
Metabotropic Glutamate Receptor ◽  
Kinetic Modelling ◽  
Input Function ◽  
Dependent Manner ◽  
Reference Region ◽  
Suitable Reference

Abstract Purpose This study aimed at investigating binding specificity, suitability of reference region-based kinetic modelling, and pharmacokinetics of the metabotropic glutamate receptor 1 (mGluR1) radioligand [11C]ITDM in mice. Procedures We performed in vivo blocking as well as displacement of [11C]ITDM during positron emission tomography (PET) imaging using the specific mGluR1 antagonist YM-202074. Additionally, we assessed in vitro blocking of [3H]ITDM at two different doses of YM-202074. As an alternative to reference region models, we validated the use of a noninvasive image-derived input function (IDIF) compared to an arterial input function measured with an invasive arteriovenous (AV) shunt using a population-based curve for radiometabolite correction and characterized the pharmacokinetic modelling of [11C]ITDM in the mouse brain. Finally, we also assessed semi-quantitative approaches. Results In vivo blocking with YM-202074 resulted in a decreased [11C]ITDM binding, ranging from − 35.8 ± 8.0 % in pons to − 65.8 ± 3.0 % in thalamus. Displacement was also markedly observed in all tested regions. In addition, in vitro [3H]ITDM binding could be blocked in a dose-dependent manner. The volume of distribution (VT) based on the noninvasive IDIF (VT (IDIF)) showed excellent agreement with the VT values based on the metabolite-corrected plasma input function regardless of the metabolite correction (r2 > 0.943, p < 0.0001). Two-tissue compartmental model (2TCM) was found to be the preferred model and showed optimal agreement with Logan plot (r2 > 0.960, p < 0.0001). A minimum scan duration of 80 min was required for proper parameter estimation. SUV was not reliable (r2 = 0.379, p = 0.0011), unlike the SUV ratio to the SUV of the input function, which showed to be a valid approach. Conclusions No suitable reference region could be identified for [11C]ITDM as strongly supported by in vivo and in vitro evidence of specific binding in all brain regions. However, by applying appropriate kinetic models, [11C]ITDM PET imaging represents a promising tool to visualize mGluR1 in the mouse brain.

scholarly journals Volume-of-interest-based supervised cluster analysis for pseudo-reference region selection in [18F]DPA-714 PET imaging of the rat brain

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Igor Fagner Vieira ◽  
Dieter Ory ◽  
Cindy Casteels ◽  
Fernando R. A. Lima ◽  
Koen Van Laere ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Rat Brain ◽  
Pet Imaging ◽  
Reference Region ◽  
Region Selection ◽  
Volume Of Interest

scholarly journals Test–retest variability and reference region-based quantification of 18F-BCPP-EF for imaging mitochondrial complex I in the human brain

2020 ◽  
pp. 0271678X2092814 ◽  
Author(s):  
Ayla Mansur ◽  
Eugenii A Rabiner ◽  
Hideo Tsukada ◽  
Robert A Comley ◽  
Yvonne Lewis ◽  
...  
Keyword(s):  
Complex I ◽  
Compartment Model ◽  
Mitochondrial Complex I ◽  
Reference Region ◽  
Mitochondrial Complex ◽  
Time Activity ◽  
Non Invasive ◽  
Arterial Blood ◽  
Absolute Test ◽  
Highly Correlated

Mitochondrial complex I (MC-I) is an essential regulator of brain bioenergetics and can be quantified in the brain using PET radioligand 18F-BCPP-EF. Here we evaluate the test–retest reproducibility of 18F-BCPP-EF in humans, and assess the use of a non-invasive quantification method (standardised uptake value ratio – SUVR). Thirty healthy volunteers had a 90-min dynamic 18F-BCPP-EF scan with arterial blood sampling, five of which received a second scan to be included in the test–retest analysis. Time-activity curves (TAC) were analysed using multilinear analysis 1 (MA1) and the two-tissue compartment model (2TC) to estimate volumes of distribution (VT). Regional SUVR-1 values were calculated from the 70 to 90-min TAC data using the centrum semiovale as a pseudo reference region, and compared to kinetic analysis-derived outcome measures. The mean absolute test–retest variability of VT ranged from 12% to 18% across regions. Both DVR-1and SUVR-1 had improved test–retest variability in the range 2%–7%. SUVR-1 was highly correlated with DVR-1 (r2 = 0.97, n = 30). In conclusion, 18F-BCPP-EF has suitable test–retest reproducibility and can be used to quantify MC-I in clinical studies.

Development of an instrument for time–activity curve measurements during PET imaging of rodents

2007 ◽  
Vol 571 (1-2) ◽  
pp. 358-361 ◽  
Author(s):  
Jean-Marc Reymond ◽  
David Guez ◽  
Sophie Kerhoas ◽  
Philippe Mangeot ◽  
Raphaël Boisgard ◽  
...  
Keyword(s):  
Pet Imaging ◽  
Time Activity ◽  
Time Activity Curve ◽  
Activity Curve

scholarly journals Evaluation of the Feasibility of Screening Tau Radiotracers Using an Amyloid Biomathematical Screening Methodology

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Ying-Hwey Nai ◽  
Hiroshi Watabe
Keyword(s):  
Time Window ◽  
Standardized Uptake Value ◽  
Clinical Usefulness ◽  
Reference Region ◽  
Time Activity ◽  
Default Time ◽  
Single Target ◽  
Comparison Results

The purpose of this study is to evaluate the feasibility of extending a previously developed amyloid biomathematical screening methodology to support the screening of tau radiotracers during compound development. 22 tau-related PET radiotracers were investigated. For each radiotracer, in silico MLogP, Vx, and in vitro KD were input into the model to predict the in vivo K1, k2, and BPND under healthy control (HC), mild cognitive impaired (MCI), and Alzheimer’s disease (AD) conditions. These kinetic parameters were used to simulate the time activity curves (TACs) in the target regions of HC, MCI, and AD and a reference region. Standardized uptake value ratios (SUVR) were determined from the integrated area under the TACs of the target region over the reference region within a default time window of 90–110 min. The predicted K1, k2, and BPND values were compared with the clinically observed values. The TACs and SUVR distributions were also simulated with population variations and noise. Finally, the clinical usefulness index (CUI) ranking was compared with clinical comparison results. The TACs and SUVR distributions differed for tau radiotracers with lower tau selectivity. The CUI values ranged from 0.0 to 16.2, with 6 out of 9 clinically applied tau radiotracers having CUI values higher than the recommend CUI value of 3.0. The differences between the clinically observed TACs and SUVR results showed that the evaluation of the clinical usefulness of tau radiotracer based on single target binding could not fully reflect in vivo tau binding. The screening methodology requires further study to improve the accuracy of screening tau radiotracers. However, the higher CUI rankings of clinically applied tau radiotracers with higher signal-to-noise ratio supported the use of the screening methodology in radiotracer development by allowing comparison of candidate radiotracers with clinically applied radiotracers based on SUVR, with respect to binding to a single target.

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