Intratumoral Heterogeneity of Glioblastoma Infiltration Revealed by Joint Histogram Analysis of Diffusion Tensor Imaging

TY - JOUR

T1 - Intratumoral Heterogeneity of Glioblastoma Infiltration Revealed by Joint Histogram Analysis of Diffusion Tensor Imaging

AU - Li, Chao

AU - Wang, Shuo

AU - Yan, Jiun Lin

AU - Piper, Rory J.

AU - Liu, Hongxiang

AU - Torheim, Turid

AU - Kim, Hyunjin

AU - Zou, Jingjing

AU - Boonzaier, Natalie R.

AU - Sinha, Rohitashwa

AU - Matys, Tomasz

AU - Markowetz, Florian

AU - Price, Stephen J.

N1 - Copyright © 2018 by the Congress of Neurological Surgeons.

PY - 2019/10/1

Y1 - 2019/10/1

N2 - Background: Glioblastoma is a heterogeneous disease characterized by its infiltrative growth, rendering complete resection impossible. Diffusion tensor imaging (DTI) shows potential in detecting tumor infiltration by reflecting microstructure disruption. OBJECTIVE: To explore the heterogeneity of glioblastoma infiltration using joint histogram analysis of DTI, to investigate the incremental prognostic value of infiltrative patterns over clinical factors, and to identify specific subregions for targeted therapy. Methods: A total of 115 primary glioblastoma patients were prospectively recruited for surgery and preoperative magnetic resonance imaging. The joint histograms of decomposed anisotropic and isotropic components of DTI were constructed in both contrast-enhancing and nonenhancing tumor regions. Patient survival was analyzed with joint histogram features and relevant clinical factors. The incremental prognostic values of histogram features were assessed using receiver operating characteristic curve analysis. The correlation between the proportion of diffusion patterns and tumor progression rate was tested using Pearson correlation. Results: We found that joint histogram features were associated with patient survival and improved survival model performance. Specifically, the proportion of nonenhancing tumor subregion with decreased isotropic diffusion and increased anisotropic diffusion was correlated with tumor progression rate (P =. 010, r = 0.35), affected progression-free survival (hazard ratio = 1.08, P <. 001), and overall survival (hazard ratio = 1.36, P <. 001) in multivariate models. Conclusion: Joint histogram features of DTI showed incremental prognostic values over clinical factors for glioblastoma patients. The nonenhancing tumor subregion with decreased isotropic diffusion and increased anisotropic diffusion may indicate a more infiltrative habitat and potential treatment target.

AB - Background: Glioblastoma is a heterogeneous disease characterized by its infiltrative growth, rendering complete resection impossible. Diffusion tensor imaging (DTI) shows potential in detecting tumor infiltration by reflecting microstructure disruption. OBJECTIVE: To explore the heterogeneity of glioblastoma infiltration using joint histogram analysis of DTI, to investigate the incremental prognostic value of infiltrative patterns over clinical factors, and to identify specific subregions for targeted therapy. Methods: A total of 115 primary glioblastoma patients were prospectively recruited for surgery and preoperative magnetic resonance imaging. The joint histograms of decomposed anisotropic and isotropic components of DTI were constructed in both contrast-enhancing and nonenhancing tumor regions. Patient survival was analyzed with joint histogram features and relevant clinical factors. The incremental prognostic values of histogram features were assessed using receiver operating characteristic curve analysis. The correlation between the proportion of diffusion patterns and tumor progression rate was tested using Pearson correlation. Results: We found that joint histogram features were associated with patient survival and improved survival model performance. Specifically, the proportion of nonenhancing tumor subregion with decreased isotropic diffusion and increased anisotropic diffusion was correlated with tumor progression rate (P =. 010, r = 0.35), affected progression-free survival (hazard ratio = 1.08, P <. 001), and overall survival (hazard ratio = 1.36, P <. 001) in multivariate models. Conclusion: Joint histogram features of DTI showed incremental prognostic values over clinical factors for glioblastoma patients. The nonenhancing tumor subregion with decreased isotropic diffusion and increased anisotropic diffusion may indicate a more infiltrative habitat and potential treatment target.

KW - Diffusion tensor imaging

KW - Glioblastoma

KW - Heterogeneity

KW - Magnetic resonance imaging

KW - Survival

KW - Tumor infiltration

UR - https://www.scopus.com/pages/publications/85070344057

U2 - 10.1093/neuros/nyy388

DO - 10.1093/neuros/nyy388

M3 - Article

C2 - 30239840

AN - SCOPUS:85070344057

SN - 0148-396X

VL - 85

SP - 524

EP - 534

JO - Clinical Neurosurgery

JF - Clinical Neurosurgery

IS - 4

ER -