Dynamics of FLAIR Volume Changes in Glioblastoma and Prediction of Survival

Abstract

OS correlated with the immediate postoperative T1Gd-EOTR measured by enhanced T1 MRI, but not by FLAIR volume. Diminished abnormal FLAIR volume at 3 months post-surgery was associated with OS benefit when FLAIR-RTV was <19.3 cm or <46 % of baseline. These threshold values provide a new radiological variable that can be used for prediction of OS in patients with glioblastoma immediately after completion of standard chemoradiation.

Advanced Magnetic Resonance Imaging in Glioblastoma: A Review

“…41 These issues led to the development of the hyperintensity on post-treatment FLAIR imaging, relative to baseline, are correlated with improved survival. 35 Furthermore, some glioblastomas demonstrate imaging changes consistent with progression under the Macdonald criteria, but upon repeat surgical intervention, viable tumor cannot be identified in the resection specimen, suggesting that the adjuvant treatment may actually be having a positive effect that eludes detection on conventional imaging. This finding, termed "pseudoprogression," Axial post-contrast T1 (T1CE) images at 8 months.…”

Defining the biological and clinical basis of radiomics

“…Aerts et al found significant prognostic value of a radiomic CT signature developed for overall survival that validated across multiple independent cohorts of patients with lung and head & neck cancer [49]. Prognostic value across several cancer types has been also observed in a radiomic PET signature [58,59], In colorectal cancer, a seminar study by Huang et al described a radiomics nomogram to predict lymph node metastases [60].…”

“…Hereby, the goal is to quantify the imaging phenotype of a tumor to inform treatment decisions [49]. As genomics refers to the collectivity of all genes within a cell, radiomics refers to the collectivity of all quantitative radiographic features of a subject of interest.…”

“…Multiple studies have documented prognostic and predictive value of radiomics for several clinical endpoints [49,[52][53][54][55][56][57]. Aerts et al found significant prognostic value of a radiomic CT signature developed for overall survival that validated across multiple independent cohorts of patients with lung and head & neck cancer [49].…”

“…In this way, texture features can be a proxy to quantifying intra-tumoral heterogeneity. In fact, texture features seem to be amongst the most promising features in terms of prognosis [49,55,74,75]. First-order statistics and texture features are often also extracted after filtering methods, such as wavelets or Laplace of Gaussian, have been applied to the original image.…”