Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?
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 u...
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| Format: | Article |
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Frontiers Media S.A.
2021-10-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.735257/full |
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| author | Timothée Zaragori Timothée Zaragori Matthieu Doyen Matthieu Doyen Fabien Rech Fabien Rech Marie Blonski Marie Blonski Luc Taillandier Luc Taillandier Laëtitia Imbert Laëtitia Imbert Antoine Verger Antoine Verger |
| author_facet | Timothée Zaragori Timothée Zaragori Matthieu Doyen Matthieu Doyen Fabien Rech Fabien Rech Marie Blonski Marie Blonski Luc Taillandier Luc Taillandier Laëtitia Imbert Laëtitia Imbert Antoine Verger Antoine Verger |
| author_sort | Timothée Zaragori |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T19:17:23Z |
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| id | doaj.art-fdbf2044432a406597e5ecacc6c5ee33 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-17T19:17:23Z |
| publishDate | 2021-10-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj.art-fdbf2044432a406597e5ecacc6c5ee332022-12-21T21:35:43ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-10-011110.3389/fonc.2021.735257735257Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient?Timothée Zaragori0Timothée Zaragori1Matthieu Doyen2Matthieu Doyen3Fabien Rech4Fabien Rech5Marie Blonski6Marie Blonski7Luc Taillandier8Luc Taillandier9Laëtitia Imbert10Laëtitia Imbert11Antoine Verger12Antoine Verger13Department of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU-Nancy, Université de Lorraine, Nancy, FranceIADI UMR 1254, INSERM, Université de Lorraine, Nancy, FranceDepartment of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU-Nancy, Université de Lorraine, Nancy, FranceIADI UMR 1254, INSERM, Université de Lorraine, Nancy, FranceDepartment of Neurosurgery, CHRU-Nancy, Université de Lorraine, Nancy, FranceCentre de Recherche en Automatique de Nancy CRAN UMR 7039, CNRS, Université de Lorraine, Nancy, FranceCentre de Recherche en Automatique de Nancy CRAN UMR 7039, CNRS, Université de Lorraine, Nancy, FranceDepartment of Neuro-Oncology, CHRU-Nancy, Université de Lorraine, Nancy, FranceCentre de Recherche en Automatique de Nancy CRAN UMR 7039, CNRS, Université de Lorraine, Nancy, FranceDepartment of Neuro-Oncology, CHRU-Nancy, Université de Lorraine, Nancy, FranceDepartment of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU-Nancy, Université de Lorraine, Nancy, FranceIADI UMR 1254, INSERM, Université de Lorraine, Nancy, FranceDepartment of Nuclear Medicine and Nancyclotep Imaging Platform, CHRU-Nancy, Université de Lorraine, Nancy, FranceIADI UMR 1254, INSERM, Université de Lorraine, Nancy, FrancePurposeDynamic 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.https://www.frontiersin.org/articles/10.3389/fonc.2021.735257/fullDOPAPETcompartmental modelingdynamic analysisgliomaIDH mutation |
| spellingShingle | Timothée Zaragori Timothée Zaragori Matthieu Doyen Matthieu Doyen Fabien Rech Fabien Rech Marie Blonski Marie Blonski Luc Taillandier Luc Taillandier Laëtitia Imbert Laëtitia Imbert Antoine Verger Antoine Verger Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient? Frontiers in Oncology DOPA PET compartmental modeling dynamic analysis glioma IDH mutation |
| title | Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient? |
| title_full | Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient? |
| title_fullStr | Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient? |
| title_full_unstemmed | Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient? |
| title_short | Dynamic 18F-FDopa PET Imaging for Newly Diagnosed Gliomas: Is a Semiquantitative Model Sufficient? |
| title_sort | dynamic 18f fdopa pet imaging for newly diagnosed gliomas is a semiquantitative model sufficient |
| topic | DOPA PET compartmental modeling dynamic analysis glioma IDH mutation |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2021.735257/full |
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