Disturbance of functional connectivity in patients with low grade glioma is associated with worse progression-free survival.

OBJECTIVE

Low grade glioma (LGG) is a disease associated with survival >10 years in most cases. Some patients, however, do not respond well to treatment and exhibit early progression as well as low overall survival. It is a challenge to identify these at-risk patients. Here, we used resting-state functional MRI (rsfMRI) to identify patients with LGG at risk for poor clinical outcome.

METHODS

Twenty-five patients with suspected LGG were prospectively enrolled. All patients underwent rsfMRI before any invasive procedure. Patient data was compared to a reference cohort of 1000 healthy controls to determine abnormality of functional connectivity on an individual level, resulting in a relative numerical measure called the dysconnectivity index (DCI). A median split was performed in order to divide the cohort into 2 groups with low and high DCI, respectively. Progression-free survival (PFS) as a primary outcome measure was calculated in both groups.

RESULTS

Twelve patients were diagnosed with astrocytoma, IDH-mutated, CNS WHO grade 2, and 13 patients were diagnosed with oligodendroglioma, IDH-mutated, 1p/19q-codeleted, CNS WHO grade 2. Eight patients had tumor progression, and 2 patients died during the observation period. 1/12 patients in the low DCI group and 7/13 patients in the high DCI group had tumor progression, resulting in significantly shorter PFS for patients with high DCI (P  = 0.028). No patient in the low DCI group died while 2 patients in the high DCI group died. Malignant transformation occurred in 4 patients with high DCI and in 0 patients with low DCI. There was no statistically significant difference in age, sex, diagnosis, and RANO resect class between the 2 groups.

CONCLUSION

Greater disturbance of functional connectivity at the time of diagnosis as determined by rsfMRI was associated with shorter PFS in our cohort of patients with LGG. This suggests that rsfMRI might be used to identify LGG patients who are at risk of poor clinical outcome.