Diffusion kurtosis imaging combined with molecular markers as a comprehensive approach to predict overall survival in patients with gliomas. Issue 128 (July 2020)

• Record Type: Journal Article
• Authors: Wang, Xuan; Li, Fuyan; Wang, Dawei; Zeng, Qingshi
• Is Part Of: European journal of radiology. Issue 128(2020)
• Publication Date: 2020-07
• Subjects: Glioma -- Mean kurtosis -- Magnetic resonance imaging -- Molecular marker -- Survival -- Risk; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2020.108985
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: DKI (MK, MD, AK, RK) and the molecular markers (IDH-1 and ATRX) influenced on glioma prognosis. The patients with high MK, AK, RK and low MD values gliomas had poor prognosis. The patients with IDH-1 mutation and ATRX loss simultaneously gliomas had better prognosis. MK, RK and ATRX could be used as independent prognostic risk factors for gliomas. High MK had the worst effect on glioma prognosis (P < 0.001, hazard ratio = 65.288). Abstract: Purpose: The purpose of this study was to explore the usefulness of diffusion kurtosis imaging (DKI) and molecular markers in predicting the prognosis of glioma patients. Method: Fifty-one patients with gliomas were examined by conventional MRI and DKI at 3.0 T before operation. The mean kurtosis (MK), mean diffusivity (MD), axial kurtosis (AK), and radial kurtosis (RK) values of tumors were measured and normalized to the contralateral normal-appearing white matter. The molecular markers of gliomas, including isocitrate dehydrogenase-1 (IDH1), α thalassemia/mental retardation syndrome x-linked (ATRX) and O6-methylguanine-DNA methyltransferase (MGMT), were immunohistochemically stained on the resected tumor tissues. Statistical methods, including the chi-square test, independent sample t -test, receiver operating characteristic curve analysis, Kaplan-Meier curve analysis, and Cox regression analysis were performed. Results: The patients with lower MK, AK, RK, and higher MD values showed significantly better prognosis ( P < 0.001). Survival time was better in glioma patients with IDH1 mutation (P < 0.01), ATRX loss of expression (P < 0.05), and MGMT negative expression (P < 0.05). However, among the groups of gliomas with IDH1 wild type, ATRX retention and those with MGMT positive expression, the patients with lower MK showed better outcome ( P < 0.01). Cox multivariate regression analysis demonstrated that MK, RK values and ATRX retention could be used as independent prognostic risk factors, and high MK values had the highest risk for prognosis (HR = 65.288). Conclusions: Molecular markers and DKI parameters, especially MK values, can be used to effectively evaluate the prognosis of glioma patients.