Beijing Neurosurgical Institute, Capital Medical University, 6 Tiantanxili, Beijing, 100050, China.
Institute of Automation, Chinese Academy of Sciences, Beijing, China.
J Neurooncol. 2017 Nov;135(2):317-324. doi: 10.1007/s11060-017-2576-8. Epub 2017 Sep 12.
To investigate the radiomic features associated with Ki-67 expression in lower grade gliomas and assess the prognostic values of these features. Patients with lower grade gliomas (n = 117) were randomly assigned into the training (n = 78) and validation (n = 39) sets. A total of 431 radiological features were extracted from each patient. Differential radiological features between the low and high Ki-67 expression groups were screened by significance analysis of microarrays. Then, generalized linear analysis was performed to select features that could predict the Ki-67 expression level. Predictive efficiencies were further evaluated in the validation set. Cox regression analysis was performed to investigate the prognostic values of Ki-67 expression level and Ki-67-related radiological features. A group of nine radiological features were screened for prediction of Ki-67 expression status; these achieved accuracies of 83.3% and 88.6% (areas under the curves, 0.91 and 0.93) in the training and validation sets, respectively. Of these features, only spherical disproportion (SD) was found to be a prognostic factor. Patients in the high SD group exhibited worse outcomes in the whole cohort (overall survival, p < 0.0001; progression-free survival, p < 0.0001). Ki-67 expression level and SD were independent prognostic factors in the multivariate Cox regression analysis. This study identified a radiomic signature for prediction of Ki-67 expression level as well as a prognostic radiological feature in patients with lower grade gliomas.
为了探究与低级别胶质瘤 Ki-67 表达相关的放射组学特征,并评估这些特征的预后价值,本研究将 117 例低级别胶质瘤患者随机分配至训练集(n = 78)和验证集(n = 39)。从每位患者中提取了 431 个放射学特征。通过微阵列差异分析筛选出 Ki-67 低表达组和高表达组之间的差异放射学特征。然后,进行广义线性分析,以选择能够预测 Ki-67 表达水平的特征。在验证集中进一步评估了预测效率。进行 Cox 回归分析以探讨 Ki-67 表达水平和与 Ki-67 相关的放射学特征的预后价值。筛选出一组 9 个放射学特征用于预测 Ki-67 表达状态,在训练集和验证集中,其准确度分别为 83.3%和 88.6%(曲线下面积分别为 0.91 和 0.93)。在这些特征中,只有球形不均一性(SD)被发现是一个预后因素。高 SD 组患者在整个队列中的预后更差(总生存期,p < 0.0001;无进展生存期,p < 0.0001)。在多变量 Cox 回归分析中,Ki-67 表达水平和 SD 是独立的预后因素。本研究确定了一个用于预测低级别胶质瘤患者 Ki-67 表达水平的放射组学特征,以及一个预后放射学特征。