High precision segmentation of glioma and surroundings - a feasibility study using multiparametric MRI and deep learning.
Authors
Affiliations (5)
Affiliations (5)
- Department of Biomedicine, University of Bergen, Bergen, Norway.
- Mohn Medical Imaging and Visualization (MMIV) Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway.
- IT division, University of Bergen, Bergen, Norway.
- Cancer Clinic, Haukeland University Hospital, Bergen, Norway.
- Department Strategy and Management, NHH Norwegian School of Economics, Bergen, Norway.
Abstract
Glioblastoma (GBM) is an aggressive primary brain cancer in which precise spatial characterisation of tumour sub-compartments and surrounding anatomy may support research into targeted treatment. We designed and assessed a feasibility pipeline for subject-specific localisation of glioma and brain regions from standard multiparametric MRI (T1, T1-Gadolinium, T2, FLAIR), combining deep-learning segmentation with robust anatomical parcellation rather than atlas coregistration. Coregistered images yield three tumour compartments: central non-enhancing/necrotic tumour, enhancing tumour, and surrounding edoema. From this multichannel representation, we derive tumour volumes and regional tumour burden "hit-plots" that show, at the voxel level, which brain regions each compartment intersects. In a cohort of <math xmlns="http://www.w3.org/1998/Math/MathML"><mrow><mi>n</mi><mo>=</mo><mn>50</mn></mrow></math> UCSF-PDGM glioblastoma subjects, deep-learning segmentations agreed closely with the reference masks: median Dice of 0.90 (whole tumour), 0.94 (tumour core), and 0.86 (enhancing tumour), with corresponding HD<sub>95</sub> values of 4.1, 2.2, and 2.0 mm. In one longitudinal LUMIERE subject (Patient-048, six timepoints), the pipeline recovered concordant volumetric trajectories and evolving regional-burden patterns with respect to specific brain structures, in agreement with independent comparator segmentations. This subject-specific regional tumour profile may in the future serve as a descriptive anatomical context for radiotherapy target delineation.