Differentiation between high-grade gliomas and solitary brain metastases: a comparison of five diffusion weighted MRI models

Motivation: Differentiating high-grade gliomas (HGGs) from solitary brain metastases (SBMs) using conventional MRI remains challenging due to similar imaging features. Goal(s): Evaluating the diagnostic performance of advanced diffusion models, like NODDI and MAP, against traditional techniques like DWI, DTI and DKI in distinguishing HGGs from SBMs. Approach: Using a 12-minute sequence, parameters of NODDI, MAP, DKI, DTI, and DWI were reconstructed using specialized postprocessing tools. Results: NODDI_Viso was the most effective parameter in distinguishing HGGs from SBMs, and combining parameters of DTI_AD, DTI_RD, MAP_MSD and NODDI_Viso further enhanced classification accuracy. Impact: Combined models from DTI, MAP and NODDI shows promise as sensitive imaging biomarkers for neuro-oncology and potentially improves treatment strategies for HGGs and SBMs.