Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging
Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging
复制标题
DOI：
10.1007/s11060-014-1614-z
复制
发表时间：
2015-01-01
影响因子：
3.9
通讯作者：
Kim, Il Han
中科院分区：
文献类型：
--
作者：
Lee, Seunghyun;Choi, Seung Hong;Kim, Il Han
本研究的目的是利用表观扩散系数(ADC)直方图和归一化脑血容量(NCBV)图探讨异柠檬酸脱氢酶(IDH)-1/2基因突变阳性和阴性高级别胶质瘤(HGG)的差异。我们登记了52例经组织病理证实为IDH1/2(P)(16例)或IDH1/2(N)(36例)的HGGS患者。用非配对学生t检验和多因素逐步Logistic回归分析ADC图和nCBV图的直方图参数与基因突变之间的关系。IDH1(P)组平均ADC值高于IDH1(N)组(1,282.8比1,159.6 mm(2)/S，P=0.0113)。在累积ADC直方图方面，IDH1(P)的第10和第50百分位值也高于IDH1(N)(分别P=0.0104和0.0183)。在IDH1(N)组，我们观察到更高的第90百分位值(3.121比2.397，P=.0208)和累积nCBV直方图的第10位(C10)和第90位(C90)之间的斜率(0.03386比0.02425/%，P=0.0067)。多变量分析显示，平均ADC值(P=0.0048)、C90值(P=0.0113)和C10与C90之间的斜率(P=0.0049)是区分IDH1(P)和IDH1(N)的重要变量。总之，基于整个肿瘤体积的ADC和nCBV图的直方图分析可以作为区分IDH1(P)和IDH1(N)的有用工具，它预测IDHP肿瘤比IDHN肿瘤具有更不均匀的微环境。
The purpose of our study was to explore the difference between isocitrate dehydrogenase (IDH)-1/2 gene mutation-positive and -negative high-grade gliomas (HGGs) using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. We enrolled 52 patients with histopathologically confirmed HGGs with IDH1/2(P) (n = 16) or IDH1/2(N) (n = 36). Histogram parameters of ADC and nCBV maps were correlated with gene mutations by using the unpaired student's t test and multivariable stepwise logistic regression analysis. The mean ADC value was higher in the IDH1(P) group than IDH1(N) (1,282.8 vs. 1,159.6 mm(2)/s, P = .0113). In terms of the cumulative ADC histograms, the 10th and 50th percentile values were also higher in the IDH1(P) than IDH1(N) (P = .0104 and .0183, respectively). We observed a higher 90th percentile value (3.121 vs. 2.397, P = .0208) and a steeper slope between the 10th (C10) and 90th (C90) of cumulative nCBV histograms (0.03386 vs. 0.02425/%, P = .0067) in the IDH1(N) group. Multivariate analysis showed that the mean ADC mean value (P = .0048), the C90 value (P = .0113), and the slope between C10 and C90 (P = .0049) were the significant variables in the differentiation of IDH1(P) from IDH1(N). In conclusion, histogram analysis of ADC and nCBV maps based on entire tumor volume can be a useful tool for distinguishing IDH1(P) and IDH1(N), and it predicts that IDHP tumors have a more heterogeneous microenvironment than IDHN ones.