Clinical Characteristics and Magnetic Resonance Imaging-Based Prediction of the KLF4 K409Q Mutation in Meningioma
Meningioma is the most common primary brain tumor in adults. In recent years, several non-neurofibromin 2 mutations, i.e., AKT1, SMO, TRAF7, and KLF4 mutations, specific for meningioma have been identified. This study aims to analyze the clinical impact and imaging characteristics of the KLF4 mutati...
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Veröffentlicht in: | World neurosurgery 2021-10, Vol.154, p.e665 |
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Zusammenfassung: | Meningioma is the most common primary brain tumor in adults. In recent years, several non-neurofibromin 2 mutations, i.e., AKT1, SMO, TRAF7, and KLF4 mutations, specific for meningioma have been identified. This study aims to analyze the clinical impact and imaging characteristics of the KLF4
mutation in meningioma.
Clinical, neuropathologic, and imaging data of 170 patients who underwent meningioma resection between 2013 and 2018 were retrospectively collected and tumors were analyzed for the presence of the KLF4
mutation. We collected imaging characteristics, performed volumetric analysis of tumor size and peritumoral edema (PTBE), and calculated the edema index (EI, i.e., ratio of PTBE to tumor volume). Receiver operating characteristic curve analysis was performed to identify cut-off EI values to predict the mutational status of KLF4.
Eighteen (10.6%) of the meningiomas carried the KLF4
mutation; these were significantly associated with a secretory subtype (P < 0.001) and sphenoid wing location (P = 0.029). Smaller tumor size (P = 0.007), an increased PTBE (P = 0.012), and an increased EI (P = 0.001) proved to be significantly associated with the KLF4
mutation. In receiver operating characteristic curve analysis, EI predicted the KLF4
mutation with an area under the curve of 0.728 (P = 0.0016).
The KLF4
mutation is associated with a distinct small tumor subtype, prone to substantial PTBE. EI is a reliable parameter to predict the KLF4
mutation in meningioma, thus providing a tool for improvement of pre- and perioperative medical management. |
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ISSN: | 1878-8769 |
DOI: | 10.1016/j.wneu.2021.07.119 |