Histogram analysis of apparent diffusion coefficient within enhancing and nonenhancing tumor volumes in recurrent glioblastoma patients treated with bevacizumab

Abstract

While patients with recurrent glioblastoma receiving anti-angiogenic therapy demonstrate significant response rates, the benefit on patient survival is less clear. We assessed whether histogram analysis of diffusion weighted MRI can stratify for progression-free and overall survival. Baseline and 3-6 week post-treatment MRI exams of 91 patients with recurrent glioblastoma treated with bevacizumab were retrospectively evaluated. Histograms of apparent diffusion coefficient (ADC) within the volume of contrast enhancing and nonenhancing T2/FLAIR lesions were analyzed using curve-fit analysis. Overall survival (OS) and progression-free survival (PFS) were assessed using ADC parameters in a Cox proportional hazards model adjusted for clinical variables. Baseline ADC(L)/ADC(M) within nonenhancing T2/FLAIR volume (> or ≤0.64) can stratify OS (HR = 2.24, p = 0.002) and PFS (HR = 1.90, p = 0.005). %ADC(H) within enhancing T1+C volume (> or ≤25 %) can also stratify OS (HR = 0.59, p = 0.034) and PFS (HR = 0.56, p = 0.01). Stratification of patient survival can be improved by merging these two ADC parameters into a single combined ADC factor (HR = 0.17, p < 0.0001). The median OS ratio of patient groups stratified by this combined factor was 2.03, larger than median OS ratio when stratifying by either %ADC(H) within T1+C volume alone (1.3) or ADC(L)/ADC(M) within T2/FLAIR alone (1.86). ADC histogram analysis within both enhancing and nonenhancing components of tumor can be used to stratify for PFS and OS in patients with recurrent glioblastoma.

Progressing Bevacizumab-Induced Diffusion Restriction Is Associated with Coagulative Necrosis Surrounded by Viable Tumor and Decreased Overall Survival in Patients with Recurrent Glioblastoma

“…Pope et al 34 investigated low ADC values through histogram analysis and agreed with the conclusion that low values indicated areas of hypercellularity. Other studies, however, have hypothesized that these regions could not correspond to tumor because not all patients progressed 35,36 . They instead hypothesized that these regions would most likely be chronic hypoxia and necrosis 36 .…”

“…Other studies, however, have hypothesized that these regions could not correspond to tumor because not all patients progressed 35,36 . They instead hypothesized that these regions would most likely be chronic hypoxia and necrosis 36 .…”

MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives

“…Functional diffusion maps (fDMs) [75] and histogram analysis need [86] to be highlighted. These techniques, which apply ADC maps to characterize the heterogeneity of therapy response, have been used to evaluate the efficacy of cytotoxic and antiangiogenic therapies [85, 87, 88]. …”

Defining the biological and clinical basis of radiomics

“…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.…”

“…For example, recent studies have suggested that apparent diffusion coefficient histogram analysis has prognostic value in a subset of the BRAIN cohort [54,55]. Similarly, FDG-PET imaging could predict survival in high-grade gliomas treated with the same combination therapy as in the BRAIN trial [56].…”