Department of Medical Education, Taipei Veterans General Hospital, Taipei, Taiwan.
School of Medicine, National Yang-Ming University, Taipei, Taiwan.
J Neurooncol. 2020 Feb;146(3):439-449. doi: 10.1007/s11060-019-03343-4. Epub 2020 Feb 4.
Gamma Knife radiosurgery (GKRS) is a non-invasive procedure for the treatment of brain metastases. This study sought to determine whether radiomic features of brain metastases derived from pre-GKRS magnetic resonance imaging (MRI) could be used in conjunction with clinical variables to predict the effectiveness of GKRS in achieving local tumor control.
We retrospectively analyzed 161 patients with non-small cell lung cancer (576 brain metastases) who underwent GKRS for brain metastases. The database included clinical data and pre-GKRS MRI. Brain metastases were demarcated by experienced neurosurgeons, and radiomic features of each brain metastasis were extracted. Consensus clustering was used for feature selection. Cox proportional hazards models and cause-specific proportional hazards models were used to correlate clinical variables and radiomic features with local control of brain metastases after GKRS.
Multivariate Cox proportional hazards model revealed that higher zone percentage (hazard ratio, HR 0.712; P = .022) was independently associated with superior local tumor control. Similarly, multivariate cause-specific proportional hazards model revealed that higher zone percentage (HR 0.699; P = .014) was independently associated with superior local tumor control.
The zone percentage of brain metastases, a radiomic feature derived from pre-GKRS contrast-enhanced T1-weighted MRIs, was found to be an independent prognostic factor of local tumor control following GKRS in patients with non-small cell lung cancer and brain metastases. Radiomic features indicate the biological basis and characteristics of tumors and could potentially be used as surrogate biomarkers for predicting tumor prognosis following GKRS.
伽玛刀放射外科(GKRS)是一种治疗脑转移瘤的非侵入性方法。本研究旨在确定源自 GKRS 前磁共振成像(MRI)的脑转移瘤的放射组学特征是否可与临床变量结合使用,以预测 GKRS 在实现局部肿瘤控制方面的效果。
我们回顾性分析了 161 例接受 GKRS 治疗脑转移瘤的非小细胞肺癌患者(576 个脑转移瘤)。该数据库包括临床数据和 GKRS 前 MRI。由有经验的神经外科医生勾画脑转移瘤,并提取每个脑转移瘤的放射组学特征。采用共识聚类进行特征选择。采用 Cox 比例风险模型和特定原因比例风险模型将临床变量和放射组学特征与 GKRS 后脑转移瘤的局部控制相关联。
多变量 Cox 比例风险模型显示,较高的区域百分比(风险比,HR 0.712;P=.022)与更好的局部肿瘤控制独立相关。同样,多变量特定原因比例风险模型显示,较高的区域百分比(HR 0.699;P=.014)与更好的局部肿瘤控制独立相关。
脑转移瘤的区域百分比是源自 GKRS 前对比增强 T1 加权 MRI 的放射组学特征,是预测非小细胞肺癌和脑转移瘤患者 GKRS 后局部肿瘤控制的独立预后因素。放射组学特征表明了肿瘤的生物学基础和特征,可能可作为预测 GKRS 后肿瘤预后的替代生物标志物。