Chinese Journal of Contemporary Neurology and Neurosurgery (May 2022)

Clinical characteristics and MRI features of IDH⁃mutant in insular glioma

  • ZHANG Zi⁃feng,
  • ZHOU Zheng⁃xu ,
  • TANG Wen⁃tian,
  • HONG Xun⁃ning,
  • WANG Xie⁃feng,
  • CHENG Gang ,
  • LIU Ning ,
  • LU Ai⁃lin ,
  • ZHANG Jun⁃xia,
  • YOU Yong⁃ping

DOI
https://doi.org/10.3969/j.issn.1672⁃6731.2022.05.012
Journal volume & issue
Vol. 22, no. 5
pp. 404 – 413

Abstract

Read online

Objective The clinical characteristics and imaging information of insular glioma patients were collected to predict mutation status of isocitrate dehydrogenase 1 (IDH1). Methods A total of 596 patients with gliomas confirmed by postoperative pathology in The First Affiliated Hospital with Nanjing Medical University from January 2011 to June 2021 were enrolled, including 72 insular gliomas, 213 frontal gliomas, 165 temporal gliomas, 76 parietal gliomas, 28 and 29 midline gliomas. All patients were examined by MRI, fifteen glioma⁃related features were selected from the visually accessible rembrandt images (VASARI), including enhancement quality, enhancement proportion, non⁃enhancement proportion, necrosis proportion, edema proportion, cyst, thickness of enhanced margin, definition of the enhanced margin, hemorrhage, diffusion, deep white matter involvement, deep ventricle involvement, midline cross, T2⁃FLAIR mismatch, maximum diameter of tumor. Univariate and multivariate Logistic regression analysis were used to screen the predictive factors related to IDH1⁃mutant in insular glioma. The receiver operating characteristic (ROC) curve was plotted and area under the curve (AUC), sensitivity and specificity were calculated to evaluate the predictive power of MRI features for IDH1⁃mutant glioma. Results IDH1 mutation rate was higher in insular and frontal gliomas (P<0.01, for all). WHO grade Ⅱ had the highest IDH1 mutation rate (P=0.008, 0.000), and grade Ⅳ had the lowest mutation rate (P=0.000). The IDH1 mutation rate in low⁃expression Ki⁃67 gliomas was higher than that in high⁃expression gliomas (P=0.000). Logistic regression analysis showed that weak enhancement (OR=35.671, 95%CI: 2.805-453.600; P=0.006), non⁃enhancement (OR=75.453, 95%CI: 2.881-1872.759; P=0.009), unlimited diffusion (OR=10.573, 95%CI: 1.043-107.175; P=0.046), no deep ventricle involvement (OR=187.601, 95%CI: 2.269-15507.607; P=0.020), T2⁃FLAIR mismatch (OR=47.536, 95%CI: 2.838-796.097; P=0.007) were independent predictive factors for IDH1 mutation in insular glioma. The AUC of enhancement degree, diffusion, deep ventricle involvement and T2⁃FLAIR mismatch for the diagnosis of IDH1⁃mutant glioma were 0.846 (95%CI: 0.748-0.944, P=0.000), 0.730 (95%CI: 0.609-0.850, P=0.001), 0.708 (95%CI: 0.584-0.833, P=0.003) and 0.745 (95%CI: 0.627-0.864, P=0.000). The combination of the 4 groups had the highest diagnostic efficacy, and the AUC was 0.961 (95%CI: 0.923-0.999, P=0.000). Conclusions Low grade insular glioma has a high IDH1 mutation rate. MRI features of weak enhancement and non⁃enhancement, unlimited diffusion, non deep ventricle involvement and T2⁃FLAIR mismatch contribute to noninvasive prediction of IDH1⁃mutant insular glioma.

Keywords