Advanced Diagnosis of Glioma by Using Emerging Magnetic Resonance Sequences

Abstract

Glioma, the most common primary brain tumor in adults, can be difficult to discern radiologically from other brain lesions, which affects surgical planning and follow-up treatment. Recent advances in MRI demonstrate that preoperative diagnosis of glioma has stepped into molecular and algorithm-assisted levels. Specifically, the histology-based glioma classification is composed of multiple different molecular subtypes with distinct behavior, prognosis, and response to therapy, and now each aspect can be assessed by corresponding emerging MR sequences like amide proton transfer-weighted MRI, inflow-based vascular-space-occupancy MRI, and radiomics algorithm. As a result of this novel progress, the clinical practice of glioma has been updated. Accurate diagnosis of glioma at the molecular level can be achieved ahead of the operation to formulate a thorough plan including surgery radical level, shortened length of stay, flexible follow-up plan, timely therapy response feedback, and eventually benefit patients individually.

Keywords: 7-T magnetic resonance imaging; differential diagnosis; glioma; magnetic resonance image; preoperative grading; radiomics; response assessment in neuro-oncology (RANO).

Figure 1

Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) of a glioma. T1-weighted imaging (T1WI) (A), fluid-attenuated inversion recovery (FLAIR) (B), DWI (C), DWI with b = 0 s/mm² (D), DWI with b = 1,000 s/mm² (E), DTI apparent diffusion coefficient (ADC) mapping (F), DTI fractional anisotropy (FA) mapping (G), DTI directional encoded color FA mapping (H), diffusion tensor tractography (DTT) (I).

Figure 2

Glioma clinical practice flow under standard MR scan and advance MR scan.