Surface-Based Falff: A Potential Novel Biomarker for Prediction of Radiation Encephalopathy in Patients With Nasopharyngeal Carcinoma - Zhang, You-ming; Kang, Ya-fei; Zeng, Jun-jie; Li, Li; Gao, Jian-ming; Liu, Li-zhi; Shi, Liang-rong; Liao, Wei-hua (Frontiers in Neuroscience, 2021)
Radiation encephalopathy (RE) is an important potential complication in patients with nasopharyngeal carcinoma (NPC) who undergo radiotherapy (RT) that can affect quality of life. However, a functional imaging biomarker of pre-symptomatic RE has not yet been established. This study aimed to assess radiation-induced gray matter functional alterations and explore fractional amplitude of low-frequency ﬂuctuation (fALFF) as an imaging biomarker for predicting or diagnosing RE in NPC patients. A total of 60 NPC patients were examined, 21 in the pre-RT cohort and 39 in the post-RT cohort. The post-RT patients were further divided into two subgroups according to occurrence of RE in follow-up: post-RT non-RE (n = 21) and post-RT RE proved in follow-up (n = 18). Surface-based and volume-based fALFF were used to detect radiation-induced functional alterations. Functional derived features were then adopted to construct a predictive model for diagnosis of RE. We observed that surface-based fALFF could sensitively detect radiation-induced functional alterations in intratemporal brain regions (such as the hippocampus and superior temporal gyrus), as well as extratemporal regions (such as the insula and prefrontal lobe); however, no significant intergroup differences were observed using volume-based fALFF. No significant correlation between fALFF and radiation dose to the ipsilateral temporal lobe was observed. Support vector machine analysis revealed that surface-based fALFF in the bilateral superior temporal gyri and left insula exhibited impressive performance (accuracy = 80.49%) in identifying patients likely to develop RE. We conclude that surface-based fALFF may serve as a sensitive imaging biomarker in prediction of RE.