An Early Progression Biomarker in Glioblastoma: Microcirculatory Heterogeneity on Ultrasound Localization Microscopy

Microcirculatory heterogeneity plays an essential role in the initiation and progression of glioblastoma (GBM). This study employs super-resolution ultrasound imaging to visualize the microcirculatory heterogeneity in GBM, with the objective of illustrating its predictive value in histological assessments.

This in vivo study explored the microvasculature in GBM models using 15 Sprague-Dawley rats, divided into three groups based on tumor growth stages (12, 18 and 24 d post-implantation). Ultrasound localization microscopy (ULM) was employed to assess microvascular morphology, hemodynamics and heterogeneity. Structural, functional and heterogeneity parameters at different tumor growth stages were quantified using Kruskal-Wallis H tests, or analysis of variance, followed by Bonferroni correction to characterize tumor progression. Linear correlations between these quantitative parameters and pathological indicators, including histological vascular density (VD-H), proliferation index and histological vascular maturity index (VMI-H), were evaluated. A stepwise linear regression model was constructed to assess the predictive performance in relation to histological parameters.

Compared to histology, ULM enabled the earlier detection of tumor progression. The quantitative parameters derived from ULM provided a more comprehensive assessment than conventional metrics such as tumor size and immunohistochemistry. Multivariate analysis exhibited significant correlations among curvature, blood flow orientation variance (OV) and VD-H. Additionally, curvature, blood flow and OV demonstrated significant correlations with the proliferation index, while blood flow and fractal dimension showed significant associations with VMI-H. Heterogeneity parameters exhibited superior predictive power for certain histological features compared to microvascular morphology and functional perfusion.

ULM provides a basis for early, non-invasive in vivo imaging and quantification of microvascular structures in rat GBM and demonstrates super-resolution predictive capability for histological parameters.