Texture Analysis of the Apparent Diffusion Coefficient Focused on Contrast-Enhancing Lesions in Predicting Survival for Bevacizumab-Treated Patients with Recurrent Glioblastoma.

biomarkers diffusion glioblastoma magnetic resonance imaging radiomics treatment

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
01 Jun 2023
Historique:
received: 23 01 2023
revised: 19 04 2023
accepted: 24 05 2023
medline: 10 6 2023
pubmed: 10 6 2023
entrez: 10 6 2023
Statut: epublish

Résumé

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. 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. 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). Our preliminary analyses suggest that in patients with recurrent glioblastoma pretreatment, MRTA helps to predict survival after bevacizumab treatment.

Identifiants

pubmed: 37296988
pii: cancers15113026
doi: 10.3390/cancers15113026
pmc: PMC10252262
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Antonio Lopez-Rueda (A)

Department of Radiology (CDI), Hospital Clínic de Barcelona, 08036 Barcelona, Spain.

Josep Puig (J)

Department of Radiology (IDI) and IDIBGI Hospital Universitari de Girona Doctor Josep Trueta, 17190 Girona, Spain.

Santiago Thió-Henestrosa (S)

Department of Computer Science Applied Mathmatics and Statistics, University of Girona, 17003 Girona, Spain.

Javier Luis Moreno-Negrete (JL)

Clínica Iribas-IRM Asunción Paraguay, Asuncion 1430, Paraguay.

Christian Zwanzger (C)

Department of Radiology, Hospital Del Mar, 08003 Barcelona, Spain.

Teresa Pujol (T)

Department of Radiology (CDI), Hospital Clínic de Barcelona, 08036 Barcelona, Spain.

Iban Aldecoa (I)

Department of Anatomical Pathology, Hospital Clínic de Barcelona, 08036 Barcelona, Spain.

Estela Pineda (E)

Translational Genomics and Targeted Therapeutics in Solid Tumors Group, Medical Oncology Department, Hospital Clínic de Barcelona, IDIBAPS, University of Barcelona, 08036 Barcelona, Spain.

Izaskun Valduvieco (I)

Radiotherapy Oncology Service, Hospital Clínic de Barcelona, 08036 Barcelona, Spain.

José Juan González (JJ)

Department of Neurosurgery, Laboratory of Experimental Oncological Neurosurgery, Hospital Clínic de Barcelona, 08036 Barcelona, Spain.

Laura Oleaga (L)

Department of Radiology (CDI), Hospital Clínic de Barcelona, 08036 Barcelona, Spain.

Classifications MeSH