Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients

Abstract

Background: Sex is recognized as a significant determinant of outcome among glioblastoma patients, but the relative prognostic importance of glioblastoma features has not been thoroughly explored for sex differences.

Methods: Combining multi-modal MR images, biomathematical models, and patient clinical information, this investigation assesses which pretreatment variables have a sex-specific impact on the survival of glioblastoma patients (299 males and 195 females).

Results: Among males, tumor (T1Gd) radius was a predictor of overall survival (HR = 1.027, p = 0.044). Among females, higher tumor cell net invasion rate was a significant detriment to overall survival (HR = 1.011, p < 0.001). Female extreme survivors had significantly smaller tumors (T1Gd) (p = 0.010 t-test), but tumor size was not correlated with female overall survival (p = 0.955 CPH). Both male and female extreme survivors had significantly lower tumor cell net proliferation rates than other patients (M p = 0.004, F p = 0.001, t-test).

Conclusion: Despite similar distributions of the MR imaging parameters between males and females, there was a sex-specific difference in how these parameters related to outcomes.

Keywords: Biomathematical models; Glioblastoma; Neuroimaging; Sex differences.

Fig. 1

Schematic of determination and interpretation of patient-specific tumor kinetic parameters. Left: After tumors are segmented on T1Gd and T2/FLAIR images, the volumes of the imaging abnormalities are used to calculate the spherically-equivalent tumor radii. By assuming the volume seen on T1Gd corresponds to a high cell density and that on T2/FLAIR to a lower cell density, the relative sizes of the abnormalities on these two imaging modalities gives an estimated profile or slope of the tumor cell density. The ratio of our biomathematical model parameters D/ϱ is a way to quantify this profile. Right: A tumor that has relatively more diffuse invasion compared to tumor cell proliferation (high D/ ϱ) is expected to have a more diffuse distribution of cell density. Conversely, a tumor with relatively more cell proliferation than diffuse invasion (low D/ϱ) is expected to have a more nodular distribution of cell density (red = high tumor cell density, blue = low tumor cell density). Adapted from Baldock et al. 2014 [17] with permission from Oxford University Press (right) and Corwin et al. 2013 [19] (left)

Fig. 2

Decision trees binning male and female EXS, Non-EXS, STS, and Non-STS based on patient and tumor characteristics. At each node, color (green for EXS, gray for Non-EXS, black for STS, and blue for Non-STS) and percentages indicate concentration of each group. a Female EXS vs Non-EXS DT (n = 141). b Male EXS vs Non-EXS DT (n = 223). c Female EXS vs STS DT (n = 43). d Male EXS vs STS (n = 58). e Female STS vs Non-STS DT (n = 141). f Male STS vs Non-STS DT (n = 223)

Fig. 3

Sex differences in the impact of image-based parameters on survival [31]. The differences between the connections of the red and blue ribbons represent sex differences in the prognostic significance of image-based tumor and patient characteristics. The bottom portion of the outer ring lists the relevant quantitative variables and the top portion shows the three aspects of survival that are associated with these variables (EXS, STS, and Overall Survival). Red ribbons indicate significant relationships for female patients between the parameter and the survival group and blue ribbons indicate significant relationships for male patients. Variables that were significant in multivariate CPH are connected to the Overall Survival segment and variables that were significant in Student t-tests with Welch’s correction are connected to the relevant EXS or STS segments