gms | German Medical Science

Objective: In Meningioma, several Non-NF2 driver mutations (KLF4, TRAF7, SMO, AKT1E17K) have been shown to correlate with certain pathological subtypes, tumor locations and clinical features. Specifically, we have recently shown that the KLF4^K409Q mutation may cause enhanced hypoxia signalling and correlates with increased peritumoral edema. While mutation-specific treatment options are still lacking, preoperative identification of the mutational status of meningioma could facilitate selection of pre- and perioperative medical treatment options in the future. The objective of this study was to evaluate the relationship of preoperative MRI features and the KLF4^K409Q mutation in meningioma patients

Methods: Clinical, pathological and preoperative imaging data on 96 patients who previously underwent meningioma resection between 2013 and 2018 were collected and frozen tumor samples sequenced for the KLF4^K409Q mutation. Different imaging characteristics were collected (i.e. tumor surface, arachnoid plane, T2 intensity) and semiautomatic volumetric analysis of tumor size and peritumoral edema (PTE) was performed. In addition, the edema index (EI) (ratio of PTE to tumor volume) was calculated and all factors were correlated with the mutational status of KLF4. Receiver operating characteristic (ROC) curve analysis was performed to identify cut-off EI values to predict the mutational status of KLF4.

Results: 13 (13.5%) of the analysed tumors carried the mutation and the mutation was significantly associated with a secretory subtype (p<0.001) and sphenoid wing location (p<0.005). Increased EI (p<0.005), as well as a large PTE (p<0.05) proved to be significantly associated with the KLF4^K409Q mutation. In receiver operating characteristic (ROC) curve analysis, EI was the most sensitive and specific parameter to predict a KLF4^K409Q mutation with an AUC of 0.767. The optimal cut-off value at >1.7 provided a sensitivity of 69.2% and a specificity of 85.5%.

Conclusion: EI can be used as a specific and sensitive parameter to predict the KLF4^K409Q mutation in meningioma, providing a useful tool for improvement of pre- and perioperative medical management.

Figure 1 [Fig. 1], Figure 2 [Fig. 2]