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Updated: Jan 3, 2026
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
Published on: September 13, 2022
Heterogeneity Diffusion Imaging of gliomas: Initial experience and validation
Qing Wang1, Gloria J Guzmán Pérez-Carrillo2, Maria Rosana Ponisio1
1Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, United States of America.
Objectives:
Primary brain tumors are composed of tumor cells, neural/glial tissues, edema, and vasculature tissue. Conventional MRI has a limited ability to evaluate heterogeneous tumor pathologies. We developed a novel diffusion MRI-based method-Heterogeneity Diffusion Imaging (HDI)-to simultaneously detect and characterize multiple tumor pathologies and capillary blood perfusion using a single diffusion MRI scan.
Methods:
Seven adult patients with primary brain tumors underwent standard-of-care MRI protocols and HDI protocol before planned surgical resection and/or stereotactic biopsy. Twelve tumor sampling sites were identified using a neuronavigational system and recorded for imaging data quantification. Metrics from both protocols were compared between World Health Organization (WHO) II and III tumor groups. Cerebral blood volume (CBV) derived from dynamic susceptibility contrast (DSC) perfusion imaging was also compared with the HDI-derived perfusion fraction.
Results:
The conventional apparent diffusion coefficient did not identify differences between WHO II and III tumor groups. HDI-derived slow hindered diffusion fraction was significantly elevated in the WHO III group as compared with the WHO II group. There was a non-significantly increasing trend of HDI-derived tumor cellularity fraction in the WHO III group, and both HDI-derived perfusion fraction and DSC-derived CBV were found to be significantly higher in the WHO III group. Both HDI-derived perfusion fraction and slow hindered diffusion fraction strongly correlated with DSC-derived CBV. Neither HDI-derived cellularity fraction nor HDI-derived fast hindered diffusion fraction correlated with DSC-derived CBV.
Conclusions:
Conventional apparent diffusion coefficient, which measures averaged pathology properties of brain tumors, has compromised accuracy and specificity. HDI holds great promise to accurately separate and quantify the tumor cell fraction, the tumor cell packing density, edema, and capillary blood perfusion, thereby leading to an improved microenvironment characterization of primary brain tumors. Larger studies will further establish HDI's clinical value and use for facilitating biopsy planning, treatment evaluation, and noninvasive tumor grading.
Insights
Heterogeneity Diffusion Imaging (HDI) offers a novel approach to characterize primary brain tumors, outperforming conventional MRI. This diffusion MRI method accurately quantifies tumor components and perfusion, aiding in noninvasive tumor grading and biopsy planning.
Area of Science:
- Neuroimaging
- Oncology
- Medical Physics
Background:
- Primary brain tumors exhibit complex heterogeneity, including tumor cells, neural/glial tissues, edema, and vasculature.
- Conventional MRI techniques struggle to adequately assess these diverse pathological components and capillary blood perfusion.
- Accurate characterization is crucial for diagnosis, grading, and treatment planning of brain tumors.
Purpose of the Study:
- To introduce and evaluate Heterogeneity Diffusion Imaging (HDI), a novel diffusion MRI-based method.
- To assess HDI's capability in simultaneously detecting and characterizing multiple tumor pathologies and capillary blood perfusion.
- To compare HDI metrics with conventional MRI and dynamic susceptibility contrast (DSC) perfusion imaging in primary brain tumors.
Main Methods:
- Seven adult patients with primary brain tumors underwent both standard MRI protocols and the HDI protocol.
- Tumor sampling sites were correlated with imaging data for quantification.
- HDI-derived metrics were compared between World Health Organization (WHO) II and III tumor groups and correlated with DSC-derived cerebral blood volume (CBV).
Main Results:
- Conventional apparent diffusion coefficient did not differentiate between WHO II and III tumor groups.
- HDI revealed significantly elevated slow hindered diffusion fraction in WHO III tumors compared to WHO II.
- HDI-derived perfusion fraction and DSC-derived CBV were significantly higher in WHO III tumors; HDI perfusion fraction correlated strongly with DSC-CBV.
Conclusions:
- HDI offers superior accuracy and specificity over conventional apparent diffusion coefficient for brain tumor characterization.
- HDI can effectively separate and quantify tumor cell fraction, packing density, edema, and capillary blood perfusion.
- HDI shows significant promise for improved microenvironment characterization, noninvasive tumor grading, and biopsy planning.
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