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Texture analysis of the apparent diffusion coefficient focused on contrast-enhancing Lesions in predicting survival for Bevacizumab-Treated patients with recurrent glioblastoma

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dc.contributor.author López-Rueda, Antonio
dc.contributor.author Puig, Josep
dc.contributor.author Thió-Henestrosa, Santiago
dc.contributor.author Moreno-Negrete, Javier Luis
dc.contributor.author Zwanzger, Christian
dc.contributor.author Pujol, Teresa
dc.contributor.author Aldecoa, Iban
dc.contributor.author Pineda, Estela
dc.contributor.author Valduvieco, Izaskun
dc.contributor.author González, José Juan
dc.contributor.author Oleaga, Laura
dc.date.accessioned 2024-02-28T08:03:06Z
dc.date.available 2024-02-28T08:03:06Z
dc.date.issued 2023
dc.identifier.citation Lopez-Rueda A, Puig J, Thió-Henestrosa S, Moreno-Negrete JL, Zwanzger C, Pujol T, Aldecoa I, Pineda E, Valduvieco I, González JJ, Oleaga L. Texture analysis of the apparent diffusion coefficient focused on contrast-enhancing Lesions in predicting survival for Bevacizumab-Treated patients with recurrent glioblastoma. Cancers (Basel). 2023 Jun 1;15(11):3026. DOI: 10.3390/cancers15113026
dc.identifier.issn 2072-6694
dc.identifier.uri http://hdl.handle.net/10230/59272
dc.description.abstract Purpose: Glioblastoma often recurs after treatment. Bevacizumab increases progression-free survival in some patients with recurrent glioblastoma. Identifying pretreatment predictors of survival can help clinical decision making. Magnetic resonance texture analysis (MRTA) quantifies macroscopic tissue heterogeneity indirectly linked to microscopic tissue properties. We investigated the usefulness of MRTA in predicting survival in patients with recurrent glioblastoma treated with bevacizumab. Methods: We evaluated retrospective longitudinal data from 33 patients (20 men; mean age 56 ± 13 years) who received bevacizumab on the first recurrence of glioblastoma. Volumes of contrast-enhancing lesions segmented on postcontrast T1-weighted sequences were co-registered on apparent diffusion coefficient maps to extract 107 radiomic features. To assess the performance of textural parameters in predicting progression-free survival and overall survival, we used receiver operating characteristic curves, univariate and multivariate regression analysis, and Kaplan-Meier plots. Results: Longer progression-free survival (>6 months) and overall survival (>1 year) were associated with lower values of major axis length (MAL), a lower maximum 2D diameter row (m2Ddr), and higher skewness values. Longer progression-free survival was also associated with higher kurtosis, and longer overall survival with higher elongation values. The model combining MAL, m2Ddr, and skewness best predicted progression-free survival at 6 months (AUC 0.886, 100% sensitivity, 77.8% specificity, 50% PPV, 100% NPV), and the model combining m2Ddr, elongation, and skewness best predicted overall survival (AUC 0.895, 83.3% sensitivity, 85.2% specificity, 55.6% PPV, 95.8% NPV). Conclusions: Our preliminary analyses suggest that in patients with recurrent glioblastoma pretreatment, MRTA helps to predict survival after bevacizumab treatment.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher MDPI
dc.relation.ispartof Cancers (Basel). 2023 Jun 1;15(11):3026
dc.rights © 2023 by the authors. 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/).
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Texture analysis of the apparent diffusion coefficient focused on contrast-enhancing Lesions in predicting survival for Bevacizumab-Treated patients with recurrent glioblastoma
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.3390/cancers15113026
dc.subject.keyword Biomarkers
dc.subject.keyword Diffusion
dc.subject.keyword Glioblastoma
dc.subject.keyword Magnetic resonance imaging
dc.subject.keyword Radiomics
dc.subject.keyword Treatment
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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