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. 2023 Jun 1;15(11):3026.
doi: 10.3390/cancers15113026.

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

Antonio Lopez-Rueda  1 , Josep Puig  2 , Santiago Thió-Henestrosa  3 , Javier Luis Moreno-Negrete  4 , Christian Zwanzger  5 , Teresa Pujol  1 , Iban Aldecoa  6 , Estela Pineda  7 , Izaskun Valduvieco  8 , José Juan González  9 , Laura Oleaga  1
Affiliations

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

Antonio Lopez-Rueda et al. Cancers (Basel). .

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.

Keywords: biomarkers; diffusion; glioblastoma; magnetic resonance imaging; radiomics; treatment.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Tumor segmentation. (A,B) Contrast-enhancing lesions were segmented from T1-weighted images (green). After segmentation, contrast-enhancing lesion volume was mapped to apparent diffusion coefficient maps. (C) Quantitative imaging texture features were extracted from volumes of interest.
Figure 2
Figure 2
Kaplan–Meier plots for progression-free survival.
Figure 3
Figure 3
Kaplan–Meier plots for overall survival.
Figure 4
Figure 4
Hypothetical biological explanation for the ADC-texture analysis of contrast-enhancing lesions for predicting survival in patients with recurrent glioblastoma after treatment with bevacizumab.
See this image and copyright information in PMC

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