Journal of Neuro-Oncology最新文献

Purpose: Glioblastoma is an aggressive primary brain tumor that often exhibits perivascular invasion. This behavior may directly interfere with glymphatic flow, hindering perivascular drainage routes. This study aims to assess glymphatic dysfunction in glioblastoma by evaluating the DTI-ALPS index, an MRI-based surrogate of glymphatic activity. We additionally correlate mpMRI-derived tumor features with radio-pathomic maps of hypercellularity.

Methods: We included 368 IDH-wildtype GBM patients from the UCSF-PDGM dataset. Preoperative T1, T1C, FLAIR, ADC, and diffusion tensor imaging (DTI) maps were preprocessed using standard co-registration and intensity normalization protocols. Radio-pathomic maps of tumor cellularity were generated using a previously published model which was trained on spatially aligned autopsy samples. The DTI-ALPS index was computed using DTI maps normalized to the JHU-ICMB-FA template, with ROIs on predefined white matter tracts and categorized by tumor laterality.

Results: The DTI-ALPS index was significantly lower on the ipsilateral side for both the GTR and STR cohorts (p < 0.00001). Furthermore, DTI-ALPS _mean and DTI-ALPS _ipsilateral showed an inverse association with contrast enhancing and FLAIR hyperintensity volumes (both p < 0.00001) and total cellularity within the contrast enhancing and FLAIR hyperintensity regions (both p < 0.00001). Notably, autopsy tissue analysis revealed SOX2 positive tumor cells in the perivascular spaces. DTI-ALPS metrics were not independently associated with overall survival after adjustment for clinical covariates.

Conclusion: Our findings suggest that GBM-associated perivascular invasion disrupts glymphatic function, as evidenced by a significantly lower DTI-ALPS index in the tumor-affected hemisphere. The inverse correlation between the DTI-ALPS index and both volume and cellularity metrics highlights the extent to which GBM alters perivascular fluid dynamics.

Purpose: Brain tumour classification is a rapidly evolving field, with diagnostic evaluation integrating the latest in molecular testing techniques. As data in brain tumour registries and repositories are collected in real time, neuro-oncology researchers face clear challenges when analysing tumour cohorts diagnosed according to differing standards over time. This study aims to evaluate the impact of an evolving tumour classification system on both our institutional registry and widely used multi-institutional repositories in glioma translational research.

Methods: Clinicopathological data, including molecular profiles, were obtained from the Sydney Brain Tumour Bank registry (1993-2025). We sourced available clinicopathological and molecular classification data from the Rembrandt and Gravendeel datasets, the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA). All cases were reclassified according to the WHO Classification of Tumours of the Central Nervous System (5th edition).

Results: Between 37% and 100% of cases diagnosed prior to the 2016 WHO Classification (revised fourth edition) require additional molecular testing for accurate diagnosis and grading. In contrast, the majority of cases in datasets established after the 2016 Classification met the WHO 2021 Classification criteria (61% to 97%). Two cohorts that consistently failed to meet 2021 requirements over time were high-grade gliomas in patients under 55 years and histological grade 2/3 IDH-mutant gliomas.

Conclusion: An evolving tumour classification system necessitates regular review and reclassification of brain tumour datasets to ensure that brain cancer research is accurate and equitable. The reclassified datasets are provided for use by neuro-oncology researchers worldwide.