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Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET

Molecular markers are of increasing importance for classifying, treating, and determining the prognosis for central nervous system tumors. Isocitrate dehydrogenase (IDH) is a critical regulator of glucose and amino acid metabolism. Our objective was to investigate metabolic reprogramming of glioma u...

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Autores principales: Lohmeier, Johannes, Radbruch, Helena, Brenner, Winfried, Hamm, Bernd, Tietze, Anna, Makowski, Marcus R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Nuclear Medicine 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626372/
https://www.ncbi.nlm.nih.gov/pubmed/37652542
http://dx.doi.org/10.2967/jnumed.123.265642
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author Lohmeier, Johannes
Radbruch, Helena
Brenner, Winfried
Hamm, Bernd
Tietze, Anna
Makowski, Marcus R.
author_facet Lohmeier, Johannes
Radbruch, Helena
Brenner, Winfried
Hamm, Bernd
Tietze, Anna
Makowski, Marcus R.
author_sort Lohmeier, Johannes
collection PubMed
description Molecular markers are of increasing importance for classifying, treating, and determining the prognosis for central nervous system tumors. Isocitrate dehydrogenase (IDH) is a critical regulator of glucose and amino acid metabolism. Our objective was to investigate metabolic reprogramming of glioma using compartmental uptake (CU) characteristics in O-(2-(18)F-fluoroethyl)-l-tyrosine (FET) PET and to evaluate its diagnostic potential for IDH genotyping. Methods: Between 2017 and 2022, patients with confirmed glioma were preoperatively investigated using static (18)F-FET PET. Metabolic tumor volume (MTV), MTV for 60%–100% uptake (MTV(60)), and T2-weighted and contrast-enhancing lesion volumes were automatically segmented using U-Net neural architecture and isocontouring. Volume intersections were determined using the Dice coefficient. Uptake characteristics were determined for metabolically defined compartments (central [80%–100%] and peripheral [60%–75%] areas of (18)F-FET uptake). CU ratio was defined as the fraction between the peripheral and central compartments. Mean target-to-background ratio was calculated. Comparisons were performed using parametric and nonparametric tests. Receiver-operating-characteristic curves, regression, and correlation were used for statistical analysis. Results: In total, 52 participants (male, 27, female, 25; mean age ± SD, 51 ± 16 y) were evaluated. MTV(60) was greater and distinct from contrast-enhancing lesion volume (P = 0.046). IDH-mutated tumors presented a greater volumetric CU ratio and SUV CU ratio than IDH wild-type tumors (P < 0.05). Volumetric CU ratio determined IDH genotype with excellent diagnostic performance (area under the curve [AUC], 0.88; P < 0.001) at more than 5.49 (sensitivity, 86%, specificity, 90%), because IDH-mutated tumors presented a greater peripheral metabolic compartment than IDH wild-type tumors (P = 0.045). MTV(60) and MTV were not suitable for IDH classification (P > 0.05). SUV CU ratio (AUC, 0.72; P = 0.005) and target-to-background ratio (AUC, 0.68; P = 0.016) achieved modest diagnostic performance—inferior to the volumetric CU ratio. Furthermore, the classification of loss of heterozygosity of chromosomes 1p and 19q (AUC, 0.75; P = 0.019), MGMT promoter methylation (AUC, 0.70; P = 0.011), and ATRX loss (AUC, 0.73; P = 0.004) by amino acid PET was evaluated. Conclusion: We proposed parametric (18)F-FET PET as a noninvasive metabolic biomarker for the evaluation of CU characteristics, which differentiated IDH genotype with excellent diagnostic performance, establishing a critical association between spatial metabolic heterogeneity, mitochondrial tricarboxylic acid cycle, and genomic features with critical implications for clinical management and the diagnostic workup of patients with central nervous system cancer.
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spelling pubmed-106263722023-11-07 Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET Lohmeier, Johannes Radbruch, Helena Brenner, Winfried Hamm, Bernd Tietze, Anna Makowski, Marcus R. J Nucl Med Clinical Investigation Molecular markers are of increasing importance for classifying, treating, and determining the prognosis for central nervous system tumors. Isocitrate dehydrogenase (IDH) is a critical regulator of glucose and amino acid metabolism. Our objective was to investigate metabolic reprogramming of glioma using compartmental uptake (CU) characteristics in O-(2-(18)F-fluoroethyl)-l-tyrosine (FET) PET and to evaluate its diagnostic potential for IDH genotyping. Methods: Between 2017 and 2022, patients with confirmed glioma were preoperatively investigated using static (18)F-FET PET. Metabolic tumor volume (MTV), MTV for 60%–100% uptake (MTV(60)), and T2-weighted and contrast-enhancing lesion volumes were automatically segmented using U-Net neural architecture and isocontouring. Volume intersections were determined using the Dice coefficient. Uptake characteristics were determined for metabolically defined compartments (central [80%–100%] and peripheral [60%–75%] areas of (18)F-FET uptake). CU ratio was defined as the fraction between the peripheral and central compartments. Mean target-to-background ratio was calculated. Comparisons were performed using parametric and nonparametric tests. Receiver-operating-characteristic curves, regression, and correlation were used for statistical analysis. Results: In total, 52 participants (male, 27, female, 25; mean age ± SD, 51 ± 16 y) were evaluated. MTV(60) was greater and distinct from contrast-enhancing lesion volume (P = 0.046). IDH-mutated tumors presented a greater volumetric CU ratio and SUV CU ratio than IDH wild-type tumors (P < 0.05). Volumetric CU ratio determined IDH genotype with excellent diagnostic performance (area under the curve [AUC], 0.88; P < 0.001) at more than 5.49 (sensitivity, 86%, specificity, 90%), because IDH-mutated tumors presented a greater peripheral metabolic compartment than IDH wild-type tumors (P = 0.045). MTV(60) and MTV were not suitable for IDH classification (P > 0.05). SUV CU ratio (AUC, 0.72; P = 0.005) and target-to-background ratio (AUC, 0.68; P = 0.016) achieved modest diagnostic performance—inferior to the volumetric CU ratio. Furthermore, the classification of loss of heterozygosity of chromosomes 1p and 19q (AUC, 0.75; P = 0.019), MGMT promoter methylation (AUC, 0.70; P = 0.011), and ATRX loss (AUC, 0.73; P = 0.004) by amino acid PET was evaluated. Conclusion: We proposed parametric (18)F-FET PET as a noninvasive metabolic biomarker for the evaluation of CU characteristics, which differentiated IDH genotype with excellent diagnostic performance, establishing a critical association between spatial metabolic heterogeneity, mitochondrial tricarboxylic acid cycle, and genomic features with critical implications for clinical management and the diagnostic workup of patients with central nervous system cancer. Society of Nuclear Medicine 2023-11 /pmc/articles/PMC10626372/ /pubmed/37652542 http://dx.doi.org/10.2967/jnumed.123.265642 Text en © 2023 by the Society of Nuclear Medicine and Molecular Imaging. https://creativecommons.org/licenses/by/4.0/Immediate Open Access: Creative Commons Attribution 4.0 International License (CC BY) allows users to share and adapt with attribution, excluding materials credited to previous publications. License: https://creativecommons.org/licenses/by/4.0/. Details: http://jnm.snmjournals.org/site/misc/permission.xhtml.
spellingShingle Clinical Investigation
Lohmeier, Johannes
Radbruch, Helena
Brenner, Winfried
Hamm, Bernd
Tietze, Anna
Makowski, Marcus R.
Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET
title Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET
title_full Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET
title_fullStr Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET
title_full_unstemmed Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET
title_short Predictive IDH Genotyping Based on the Evaluation of Spatial Metabolic Heterogeneity by Compartmental Uptake Characteristics in Preoperative Glioma Using (18)F-FET PET
title_sort predictive idh genotyping based on the evaluation of spatial metabolic heterogeneity by compartmental uptake characteristics in preoperative glioma using (18)f-fet pet
topic Clinical Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626372/
https://www.ncbi.nlm.nih.gov/pubmed/37652542
http://dx.doi.org/10.2967/jnumed.123.265642
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