Qiang Zeng1, Fei Dong2, Feina Shi3, Chenhan Ling1, Biao Jiang2, Jianmin Zhang4. 1. Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang, 310009, China. 2. Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China. 3. Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China. 4. Department of Neurosurgery, Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang, 310009, China. zjm135@vip.sina.com.
Abstract
OBJECTIVE: To assess whether ADC maps obtained from high b value DWI were more valuable in preoperatively evaluating the grade, Ki-67 index and outcome of gliomas. METHODS: Sixty-three patients with gliomas, who underwent preoperative multi b value DWI at 3 T, were enrolled. The ADC1000, ADC2000 and ADC3000 maps were generated. Receiver operating characteristic analyses were conducted to determine the area under the curve (AUC) in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG). Pearson correlation coefficients (R value) were calculated to investigate the correlation between parameters with the Ki-67 proliferation index. Survival analysis was conducted by using Cox regression. RESULTS: The AUC of the mean ADC1000 value (0.820) was lower than that of the mean ADC2000 value (0.847) and mean ADC3000 value (0.875) in differentiating HGG from LGG. The R value of the mean ADC1000 value (-0.499) was less negative than that of the mean ADC2000 value (-0.530) and mean ADC3000 value (-0.567). The mean ADC3000 value was an independent prognosis factor for gliomas (p = 0.008), while the mean ADC1000 and ADC2000 values were not. CONCLUSION: ADC maps obtained from high b value DWI might be a better imaging biomarker in the preoperative evaluation of gliomas. KEY POINTS: • ADC 3000 maps could improve the differentiation between HGG and LGG. • The mean ADC 3000 value had a closer correlation with the Ki-67 index. • The mean ADC 3000 value was an independent prognosis factor for gliomas.
OBJECTIVE: To assess whether ADC maps obtained from high b value DWI were more valuable in preoperatively evaluating the grade, Ki-67 index and outcome of gliomas. METHODS: Sixty-three patients with gliomas, who underwent preoperative multi b value DWI at 3 T, were enrolled. The ADC1000, ADC2000 and ADC3000 maps were generated. Receiver operating characteristic analyses were conducted to determine the area under the curve (AUC) in differentiating high-grade gliomas (HGG) from low-grade gliomas (LGG). Pearson correlation coefficients (R value) were calculated to investigate the correlation between parameters with the Ki-67 proliferation index. Survival analysis was conducted by using Cox regression. RESULTS: The AUC of the mean ADC1000 value (0.820) was lower than that of the mean ADC2000 value (0.847) and mean ADC3000 value (0.875) in differentiating HGG from LGG. The R value of the mean ADC1000 value (-0.499) was less negative than that of the mean ADC2000 value (-0.530) and mean ADC3000 value (-0.567). The mean ADC3000 value was an independent prognosis factor for gliomas (p = 0.008), while the mean ADC1000 and ADC2000 values were not. CONCLUSION: ADC maps obtained from high b value DWI might be a better imaging biomarker in the preoperative evaluation of gliomas. KEY POINTS: • ADC 3000 maps could improve the differentiation between HGG and LGG. • The mean ADC 3000 value had a closer correlation with the Ki-67 index. • The mean ADC 3000 value was an independent prognosis factor for gliomas.
Authors: Olaf Dietrich; José G Raya; Scott B Reeder; Maximilian F Reiser; Stefan O Schoenberg Journal: J Magn Reson Imaging Date: 2007-08 Impact factor: 4.813
Authors: Hee Ho Chu; Seung Hong Choi; Inseon Ryoo; Soo Chin Kim; Jeong A Yeom; Hwaseon Shin; Seung Chai Jung; A Leum Lee; Tae Jin Yoon; Tae Min Kim; Se-Hoon Lee; Chul-Kee Park; Ji-Hoon Kim; Chul-Ho Sohn; Sung-Hye Park; Il Han Kim Journal: Radiology Date: 2013-10-28 Impact factor: 11.105