Edge Contrast of the FLAIR Hyperintense Region Predicts Survival in Patients with High-Grade Gliomas following Treatment with Bevacizumab

Abstract

Background and Purpose Treatment with bevacizumab is standard of care for recurrent high grade gliomas (HGGs); However, monitoring response to treatment following bevacizumab remains a challenge. The purpose of this study is to determine whether quantifying the sharpness of the fluid-attenuated inversion recovery (FLAIR) hyperintense border using a measure derived from texture analysis—edge contrast (EC)—improves the evaluation of response to bevacizumab in patients with HGG. Materials and Methods MRIs were evaluated in 33 patients with HGG before and after the initiation of bevacizumab. Volumes of interest (VOIs) within the FLAIR hyperintense region were segmented. EC magnitude for each VOI was extracted using gradients of the 3D FLAIR images. Cox proportional hazard models were generated to determine the relationship between EC and PFS/OS using age and the extent of surgical resection as covariates. Results After bevacizumab, lower EC of the FLAIR hyperintense region was associated with poorer PFS (p=0.009) and OS (p = 0.022) among HGG patients. Kaplan-Meier curves revealed that EC cutoff significantly stratified patients for both PFS (log rank χ2 = 8.3, p = 0.003) and OS (log rank χ2 = 5.5, p = 0.019). Conclusion Texture analysis using EC of the FLAIR hyperintense region may be an important predictive indicator in HGG patients following treatment with bevacizumab. Specifically, low FLAIR EC may partially reflect areas of early tumor infiltration. This study adds to a growing body of literature proposing that quantifying features may be important for determining outcomes in patients with HGG.

Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics

“…A 3D analysis was applied to the FLAIR VOI to enhance the local precision and decrease the partial volume effect [40][41][42][43]. The technique of EC extraction has been described in our previous study [44], where the morphological operations of erosion and dilation were applied to the FLAIR VOL binary mask using a spherical 3D mask. Then, the contour of the FLAIR VOL binary mask was drawn in 3D indexing the surface of the FLAIR VOL lesion.…”

High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management

“…In addition, T2 FLAIR is increasingly involved in the texture analysis for assessment of therapeutic response and survival outcomes. It has been reported that 3D shape features could distinguish pseudoprogression from true progression and lower edge contrast of the FLAIR signal is correlated with poor survival after bevacizumab treatment [33,34].…”

Differentiation of recurrent glioblastoma from radiation necrosis using diffusion radiomics with machine learning model development and external validation

“…A total of 93 radiomic features, including shape, first order features, and second-order features (Supplementary Table 2 ), were extracted from the mask. In addition, edge contrast calculation was performed, that characterizes the tumor border, as previously described (Supplementary Information S1 ) 60 . The final set consisted of 263 radiomic features (14 shape features + 83 first-order and second-order 14 features × 3 sequences) for each patient.…”