High-grade gliomas (HGGs) are among the most aggressive primary brain tumors in adults and are characterized by diffuse infiltration into the surrounding brain tissue. This infiltrative behavior represents one of the main limitations to complete surgical removal and contributes to tumor recurrence.
Accurate identification of infiltrated tissue beyond the visible tumor margins remains a major challenge in neuro-oncology. Conventional magnetic resonance imaging (MRI) sequences, including contrast-enhanced T1-weighted imaging and fluid-attenuated inversion recovery (FLAIR), are routinely used to define tumor boundaries. However, non-contrast-enhancing regions often contain a mixture of tumor infiltration and vasogenic edema, which cannot be reliably distinguished using standard imaging alone. Improved imaging techniques capable of characterizing the biological properties of the peri-tumoral microenvironment are therefore needed to support more accurate assessment of tumor extent. Advanced MRI techniques provide complementary information about tissue composition and microstructure. Diffusion tensor imaging (DTI) provides information related to tissue organization and cellular architecture through the measurement of water diffusion properties. Amide proton transfer-weighted (APTw) imaging provides information related to endogenous mobile proteins and peptides, which are typically increased in tumor tissue and reflect metabolic and molecular changes. The combined use of these techniques may improve the identification of tumor-infiltrated tissue within regions that appear non-enhancing on conventional MRI.
This study is designed as a prospective, single-center observational study enrolling adult patients with radiologically suspected high-grade gliomas who are scheduled to undergo biopsy or tumor resection as part of standard clinical care. All enrolled participants will undergo a preoperative MRI examination that includes both standard clinical sequences and advanced imaging sequences, including diffusion tensor imaging (DTI) and amide proton transfer-weighted (APTw) imaging. Following imaging acquisition, patients will undergo neurosurgical procedures according to clinical indications. Tissue samples collected during biopsy or tumor resection will undergo standard histopathological evaluation as part of routine diagnostic care. Histological analyses will include assessment of tumor cellularity using hematoxylin and eosin staining and additional immunohistochemical markers.
Imaging data derived from APTw and DTI will be combined to generate maps describing the likelihood of tumor infiltration within the peri-tumoral region. These imaging-derived maps aim to represent spatial variations in tissue characteristics that reflect differences in tumor cellularity. A central objective of the study is the correlation between imaging-derived features and histopathological findings, to validate the maps. Tissue samples obtained during surgery will be spatially related to corresponding imaging locations, allowing comparison between imaging-derived measures and histological characteristics. This approach is intended to validate imaging-derived estimates of tumor infiltration against histological reference standards.
In addition to baseline imaging and histopathological correlation, patients will undergo routine postoperative follow-up according to clinical practice. Follow-up MRI examinations will be analyzed to evaluate patterns of tumor recurrence and to explore the spatial relationship between imaging-derived features identified at baseline and subsequent sites of tumor progression. Moreover the prognostic significance of the area of tumor infiltration described by the imaging-derived map will be evaluated.
The overall objective of this study is to develop and validate imaging-based biomarkers capable of identifying infiltrated tissue beyond the visible tumor margins through integration of advanced MRI techniques, histopathological correlation, and longitudinal follow-up. Improved identification of infiltrated tissue may contribute to a better understanding of tumor growth patterns and support future advances in surgical planning and treatment strategies in patients with high-grade gliomas.
