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Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer....

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Autores principales: Travaglio Morales, Daniela, Huerga Cabrerizo, Carlos, Losantos García, Itsaso, Coronado Poggio, Mónica, Cordero García, José Manuel, Llobet, Elena López, Monachello Araujo, Domenico, Rizkallal Monzón, Sebastián, Domínguez Gadea, Luis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670627/
https://www.ncbi.nlm.nih.gov/pubmed/37998530
http://dx.doi.org/10.3390/diagnostics13223394
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author Travaglio Morales, Daniela
Huerga Cabrerizo, Carlos
Losantos García, Itsaso
Coronado Poggio, Mónica
Cordero García, José Manuel
Llobet, Elena López
Monachello Araujo, Domenico
Rizkallal Monzón, Sebastián
Domínguez Gadea, Luis
author_facet Travaglio Morales, Daniela
Huerga Cabrerizo, Carlos
Losantos García, Itsaso
Coronado Poggio, Mónica
Cordero García, José Manuel
Llobet, Elena López
Monachello Araujo, Domenico
Rizkallal Monzón, Sebastián
Domínguez Gadea, Luis
author_sort Travaglio Morales, Daniela
collection PubMed
description High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer. The aim of our work was to assess the prognostic value of pretreatment 18F-FDG PET radiomic features in patients with HGSOC. A review of 36 patients diagnosed with advanced HGSOC between 2016 and 2020 in our center was performed. Radiomic features were obtained from pretreatment (18)F-FDGPET. Disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with receiver operating characteristic curve/median values were used. A correlation between radiomic features and DFS/OS was made. The mean DFS was 19.6 months and OS was 37.1 months. Total Lesion Glycolysis (TLG), GLSZM_ Zone Size Non-Uniformity (GLSZM_ZSNU), and GLRLM_Run Length Non-Uniformity (GLRLM_RLNU) were significantly associated with DFS. The survival-curves analysis showed a significant difference of DSF in patients with GLRLM_RLNU > 7388.3 versus patients with lower values (19.7 months vs. 31.7 months, p = 0.035), maintaining signification in the multivariate analysis (p = 0.048). Moreover, Intensity-based Kurtosis was associated with OS (p = 0.027). Pretreatment (18)F-FDG PET radiomic features GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis may have prognostic value in patients with advanced HGSOC.
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spelling pubmed-106706272023-11-07 Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer Travaglio Morales, Daniela Huerga Cabrerizo, Carlos Losantos García, Itsaso Coronado Poggio, Mónica Cordero García, José Manuel Llobet, Elena López Monachello Araujo, Domenico Rizkallal Monzón, Sebastián Domínguez Gadea, Luis Diagnostics (Basel) Article High-grade serous ovarian cancer (HGSOC) is an aggressive disease with different clinical outcomes and poor prognosis. This could be due to tumor heterogeneity. The 18F-FDG PET radiomic parameters permit addressing tumor heterogeneity. Nevertheless, this has been not well studied in ovarian cancer. The aim of our work was to assess the prognostic value of pretreatment 18F-FDG PET radiomic features in patients with HGSOC. A review of 36 patients diagnosed with advanced HGSOC between 2016 and 2020 in our center was performed. Radiomic features were obtained from pretreatment (18)F-FDGPET. Disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with receiver operating characteristic curve/median values were used. A correlation between radiomic features and DFS/OS was made. The mean DFS was 19.6 months and OS was 37.1 months. Total Lesion Glycolysis (TLG), GLSZM_ Zone Size Non-Uniformity (GLSZM_ZSNU), and GLRLM_Run Length Non-Uniformity (GLRLM_RLNU) were significantly associated with DFS. The survival-curves analysis showed a significant difference of DSF in patients with GLRLM_RLNU > 7388.3 versus patients with lower values (19.7 months vs. 31.7 months, p = 0.035), maintaining signification in the multivariate analysis (p = 0.048). Moreover, Intensity-based Kurtosis was associated with OS (p = 0.027). Pretreatment (18)F-FDG PET radiomic features GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis may have prognostic value in patients with advanced HGSOC. MDPI 2023-11-07 /pmc/articles/PMC10670627/ /pubmed/37998530 http://dx.doi.org/10.3390/diagnostics13223394 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Travaglio Morales, Daniela
Huerga Cabrerizo, Carlos
Losantos García, Itsaso
Coronado Poggio, Mónica
Cordero García, José Manuel
Llobet, Elena López
Monachello Araujo, Domenico
Rizkallal Monzón, Sebastián
Domínguez Gadea, Luis
Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
title Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
title_full Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
title_fullStr Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
title_full_unstemmed Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
title_short Prognostic (18)F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer
title_sort prognostic (18)f-fdg radiomic features in advanced high-grade serous ovarian cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670627/
https://www.ncbi.nlm.nih.gov/pubmed/37998530
http://dx.doi.org/10.3390/diagnostics13223394
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