# Evaluation of [11C]-Methionine Positron Emission Tomography and Cerebral Blood Volume Imaging in the Diagnosis of Non-Contrast-Enhanced Gliomas

## TL;DR

This study compares [11C]-Methionine PET and cerebral blood volume imaging for diagnosing non-contrast-enhanced brain tumors called gliomas.

## Contribution

The study evaluates how cerebral blood volume imaging performs compared to PET in diagnosing different glioma subtypes.

## Key findings

- Relative cerebral blood volume and MET imaging were significantly correlated in glioma assessment.
- Cerebral blood volume showed comparable diagnostic accuracy to MET for differentiating glioma subtypes.
- Cerebral blood volume was more reliable for identifying MET-positive regions in some glioma subtypes than others.

## Abstract

Background/Objectives: Methionine (MET) positron emission tomography (PET) and cerebral blood volume (CBV) imaging provide complementary glioma assessment. This study compared MET and CBV across glioma subtypes defined by the 2021 World Health Organization Classification. Methods: This retrospective study enrolled 106 patients (mean age 41.9 ± 12.4 years; 57 males) with MRI non-contrast-enhanced gliomas: 21 glioblastoma, isocitrate dehydrogenase (IDH)-wildtype (G); 50 astrocytoma, IDH-mutant (A); and 35 oligodendrogliomas, IDH-mutant, and 1p/19q-codeleted (O). Relative CBVs (rCBVs) were measured in VOI-T2 and VOI-MET, and the MET tumor-to-normal (T/N) ratio was calculated. Results: MET and rCBV were significantly correlated (r = 0.5, p < 0.001); rCBV was higher in MET-positive tumors and predicted MET accumulation (area under the curve [AUC] = 0.72, cutoff = 2.99). In VOI-T2, rCBV and MET T/N ratio were the highest in G and lowest in A (p < 0.001). Receiver operating characteristic analyses showed no overall significant difference between MET and rCBV for differentiating G/A/O, but rCBV trended toward higher AUC values in key distinctions, such as G (0.736 vs. 0.612) or grade 4 (0.718 vs. 0.617). The increase in rCBV within the MET-positive region (VOI-MET/VOI-T2 rCBV ratio) was significantly higher in A (119.8%, p = 0.002) than in the other groups (p = 0.01). Conclusions: rCBV differentiated glioma subtype with accuracy comparable to MET and could predict MET accumulation. However, its reliability for identifying MET-positive regions varied by subtype, being useful in A but limited in O. Recognizing these subtype-specific differences, rCBV can serve as a practical tool for evaluating non-contrast-enhanced gliomas.