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

Author:

Lopez-Rueda Antonio1ORCID,Puig Josep2ORCID,Thió-Henestrosa Santiago3,Moreno-Negrete Javier Luis4,Zwanzger Christian5,Pujol Teresa1,Aldecoa Iban6ORCID,Pineda Estela7ORCID,Valduvieco Izaskun8,González José Juan9,Oleaga Laura1ORCID

Affiliation:

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

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

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

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

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

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

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

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

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

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.

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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