Abstract
Purpose: According to the revised World Health Organization (WHO) Classification of Tumors of the Central Nervous System (CNS) of 2016, oligodendrogliomas are now defined primarily by a specific molecular signature (presence of IDH mutation and 1p19q codeletion). The purpose of our study was to assess the value of dynamic susceptibility contrast MR imaging (DSC-MRI) and diffusion-weighted imaging (DWI) to characterize oligodendrogliomas and to distinguish them from astrocytomas. Methods: Seventy-one adult patients with untreated WHO grade II and grade III diffuse infiltrating gliomas and known 1p/19q codeletion status were retrospectively identified and analyzed using relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC) maps based on whole-tumor volume histograms. The Mann-Whitney U test and logistic regression were used to assess the ability of rCBV and ADC to differentiate between oligodendrogliomas and astrocytomas both independently, but also related to the WHO grade. Prediction performance was evaluated in leave-one-out cross-validation (LOOCV). Results: Oligodendrogliomas showed significantly higher microvascularity (higher rCBV Mean ≥ 0.80, p = 0.013) and higher vascular heterogeneity (lower rCBV Peak ≤ 0.044, p = 0.015) than astrocytomas. Diffuse gliomas with higher cellular density (lower ADC Mean ≤ 1094 × 10 −6 mm 2 /s, p = 0.009) were more likely to be oligodendrogliomas than astrocytomas. Histogram analysis of rCBV and ADC was able to differentiate between diffuse astrocytomas (WHO grade II) and anaplastic astrocytomas (WHO grade III). Conclusion: Histogram-derived rCBV and ADC parameter may be used as biomarkers for identification of oligodendrogliomas and may help characterize diffuse gliomas based upon their genetic characteristics.
| Original language | English |
|---|---|
| Journal | Neuroradiology |
| Volume | 61 |
| Issue number | 5 |
| Pages (from-to) | 545-555 |
| Number of pages | 11 |
| ISSN | 0028-3940 |
| DOIs | |
| Publication status | Published - 01.05.2019 |
Funding
Funding This work was funded by the Southeastern Norway Regional Health Authority Extended Career Grants 2017073, 2013069 (KEE), the Research Council of Norway Grant ES435705 (KEE), Deutsche Forschungsgemeinschaft/Germany (DFG PA930/9, DFG PA930/12) (JP), the Leibniz Society/Germany (SAW-2015-IPB-2) (JP), HelseSØ/ Norway (2016062) (JP), Norsk forskningsrådet/Norway (247179 NeuroGeM, 251290 FRIMEDIO, 260786 PROP-AD) (JP) and Horizon 2020/European Union (643417 (PROP-AD) (JP).
Research Areas and Centers
- Academic Focus: Center for Infection and Inflammation Research (ZIEL)