Differentiation of High-Grade Glioma and Intracranial Metastasis Using Volumetric Diffusion Tensor Imaging...

Area of Science:

• Neuroimaging
• Oncology
• Radiology

Background:

• Differentiating high-grade glioma (HGG) from intracranial metastasis (IM) noninvasively is challenging.
• Diffusion tensor imaging (DTI) offers potential for characterizing brain tumor microenvironments.

Purpose of the Study:

• To differentiate between HGG and IM using tumoral and peritumoral DTI characteristics.
• To identify DTI metrics that can reliably distinguish between these two brain tumor types.

Main Methods:

• A semiautomated script generated volumetric regions of interest (ROIs) for tumors and peritumoral areas.
• DTI metrics including fractional anisotropy, mean diffusivity, total fiber tract counts, and tract density were analyzed.
• Receiver operating characteristic (ROC) curve analysis identified optimal differentiating metrics.

Main Results:

• High-grade glioma (HGG) group showed a significantly higher tumor-to-brain volume ratio compared to the intracranial metastasis (IM) group.
• HGG group had higher peritumoral fractional anisotropy and lower mean diffusivity than the IM group.
• Tumoral tract count and peritumoral tract density were the most effective DTI metrics for differentiating HGG from IM, with tumoral tract count showing higher sensitivity in predictive analysis.

Conclusions:

• Significant differences in tract count and tract density exist in tumoral and peritumoral regions between HGG and IM.
• These microstructural differences may reflect distinct microenvironmental interactions specific to each tumor type.
• DTI-derived metrics show promise as a noninvasive tool for distinguishing HGG from IM.