Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas

SIMPLE SUMMARY: With the release of the fifth WHO classification for CNS tumors in 2021, biology-based tumor classification is further advanced with the addition of molecular characteristics into diagnosis. This both poses challenges as well as opens up new opportunities for radiological diagnosis, which was long based on the correspondence of imaging features and histological criteria. In this work, using advanced imaging and AI-based image processing on newly-diagnosed adult glioma patients (n = 226) with extensive molecular characterization, significant differences in biological MR imaging metrics among molecularly defined glioma subgroups were demonstrated. In particular, diffuse glioma (IDH wild type) with molecular characteristics of glioblastoma (now recognized as glioblastoma, WHO CNS grade 4) showed higher perfusion as well as increased cell density compared to “classical” glioblastoma (IDH wild type), WHO CNS grade 4, and astrocytoma (IDH mutant, 1p/19q non-codeleted), WHO CNS grade 4. Our results add relevantly to the emerging picture that fine tumor grading is possible in part by visualization of tumor biology with advanced MRI. ABSTRACT: Background: The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated. Materials and Methods: We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4. Results: Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA). Conclusions: This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.