Caiqiang Xue1, Bin Zhang1, Juan Deng1, Xianwang Liu1, Shenglin Li1, Junlin Zhou2. 1. Department of Radiology, Lanzhou University Second Hospital, Second Clinical School, Lanzhou University, Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, Gansu, China. 2. Department of Radiology, Lanzhou University Second Hospital, Second Clinical School, Lanzhou University, Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, Gansu, China. Electronic address: lzuzjl601@163.com.
Abstract
BACKGROUND: Differential diagnosis of giant cell glioblastoma (GC) and classic glioblastoma (GBM) using conventional radiological modalities is difficult. This study aimed to use diffusion-weighted imaging (DWI) to distinguish GC from GBM and thereby improve the accuracy of preoperative assessment of patients with GB. METHODS: The clinical, magnetic resonance imaging, and pathologic data of 12 patients with GC and 21 patients with GBM were retrospectively analyzed. Independent sample t tests were used to compare the minimum apparent diffusion coefficient (ADCmin) and the normalized apparent diffusion coefficients (nADC) of the 2 tumor types. Receiver operating curve (ROC) analysis was used to assess the diagnostic efficacy of ADCmin and nADC values. RESULTS: Compared with that of the classic GBM group, the ADCmin (0.98 ± 0.14 vs. 0.80 ± 0.19×10-3 mm2/second, P = 0.007) and nADC (1.42 ± 0.25 vs. 1.17 ± 0.25, P = 0.011) of the GC group were significantly higher. ROC curve analysis showed that the maximum area under the curve of ADCmin and nADC were 0.800 ± 0.080 and 0.778 ± 0.082, respectively. The sensitivity, specificity, and accuracy distinguishing GC and classic GBM was best (83.33%, 76.19%, and 78.79%, respectively) when ADCmin = 0.84×10-3 mm2/second (maximum area under the ROC, 0.800). Its positive and negative predictive values under this condition were 88.89% and 66.67%, respectively. CONCLUSIONS: By distinguishing GC from classic GBM, the ADCmin parameter of DWI can improve the accuracy of the preoperative differential diagnosis of the 2 tumor types.
BACKGROUND: Differential diagnosis of giant cell glioblastoma (GC) and classic glioblastoma (GBM) using conventional radiological modalities is difficult. This study aimed to use diffusion-weighted imaging (DWI) to distinguish GC from GBM and thereby improve the accuracy of preoperative assessment of patients with GB. METHODS: The clinical, magnetic resonance imaging, and pathologic data of 12 patients with GC and 21 patients with GBM were retrospectively analyzed. Independent sample t tests were used to compare the minimum apparent diffusion coefficient (ADCmin) and the normalized apparent diffusion coefficients (nADC) of the 2 tumor types. Receiver operating curve (ROC) analysis was used to assess the diagnostic efficacy of ADCmin and nADC values. RESULTS: Compared with that of the classic GBM group, the ADCmin (0.98 ± 0.14 vs. 0.80 ± 0.19×10-3 mm2/second, P = 0.007) and nADC (1.42 ± 0.25 vs. 1.17 ± 0.25, P = 0.011) of the GC group were significantly higher. ROC curve analysis showed that the maximum area under the curve of ADCmin and nADC were 0.800 ± 0.080 and 0.778 ± 0.082, respectively. The sensitivity, specificity, and accuracy distinguishing GC and classic GBM was best (83.33%, 76.19%, and 78.79%, respectively) when ADCmin = 0.84×10-3 mm2/second (maximum area under the ROC, 0.800). Its positive and negative predictive values under this condition were 88.89% and 66.67%, respectively. CONCLUSIONS: By distinguishing GC from classic GBM, the ADCmin parameter of DWI can improve the accuracy of the preoperative differential diagnosis of the 2 tumor types.