Effects of Carbidopa Premedication on <sup>18</sup>F-FDOPA PET Imaging of Glioma: A Multiparametric Analysis
Purpose: This study aimed to determine the impact of carbidopa premedication on static, dynamic and radiomics parameters of <sup>18</sup>F-FDOPA PET in brain tumors. Methods: The study included 54 patients, 18 of whom received carbidopa, who underwent <sup>18</sup>F-FDOPA PET...
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| Autores principales: | , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/e5ef4850102e4b4e99bb04af7da0c816 |
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| Sumario: | Purpose: This study aimed to determine the impact of carbidopa premedication on static, dynamic and radiomics parameters of <sup>18</sup>F-FDOPA PET in brain tumors. Methods: The study included 54 patients, 18 of whom received carbidopa, who underwent <sup>18</sup>F-FDOPA PET for newly diagnosed gliomas. SUV-derived, 105 radiomics features and TTP dynamic parameters were extracted from volumes of interest in healthy brains and tumors. Simulation of the effects of carbidopa on time-activity curves were generated. Results: All static and TTP dynamic parameters were significantly higher in healthy brain regions of premedicated patients (ΔSUV<sub>mean</sub> = +53%, ΔTTP = +48%, <i>p</i> < 0.001). Furthermore, carbidopa impacted 81% of radiomics features, of which 92% correlated with SUV<sub>mean</sub> (absolute correlation coefficient ≥ 0.4). In tumors, premedication with carbidopa was an independent predictor of SUV<sub>mean</sub> (ΔSUV<sub>mean</sub> = +52%, <i>p</i> < 0.001) and TTP (ΔTTP = +24%, <i>p</i> = 0.025). All parameters were no longer significantly modified by carbidopa premedication when using ratios to healthy brain. Simulated data confirmed that carbidopa leads to higher tumor TTP values, corrected by the ratios. Conclusion: In <sup>18</sup>F-FDOPA PET, carbidopa induces similarly higher SUV and TTP dynamic parameters and similarly impacts SUV-dependent radiomics in healthy brain and tumor regions, which is compensated for by correcting for the tumor-to-healthy-brain ratio. This is a significant advantage for multicentric study harmonization. |
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