School of Electronics and Information, Xi'an Polytechnic University, China; Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China; Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China.
Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, China; China National Clinical Research Center for Neurological Diseases, China.
Radiother Oncol. 2019 Dec;141:239-246. doi: 10.1016/j.radonc.2019.10.002. Epub 2019 Oct 25.
We used radiomic analysis to establish a radiomic signature based on anatomical magnetic resonance imaging (MRI) sequences and explore its effectiveness as a novel prognostic biomarker for skull base chordoma (SBC).
In this retrospective study, radiomic analysis was performed using preoperative axial T FLAIR, T-weighted, and enhanced T FLAIR from a single hospital. The primary clinical endpoint was progression-free survival. A total of 1860 3-D radiomic features were extracted from manually segmented region of interest. Pearson correlation coefficient was used for feature dimensional reduction and a ridge regression-based Cox proportional hazards model was used to determine a radiomic signature. Afterwards, radiomic signature and nine other potential prognostic factors, including age, gender, histological subtype, dural invasion, blood supply, adjuvant radiotherapy, extent of resection, preoperative KPS, and postoperative KPS were analyzed to build a radiomic nomogram and a clinical model. Finally, we compared the nomogram with each prognostic factor/model by DeLong's test.
A total of 148 SBC patients were enrolled, including 64 with disease progression. The median follow-up time was 52 months (range 4-122 months). The Harrell's concordance index of the radiomic signature was 0.745 (95% CI, 0.709-0.781) for the validation cohort, and its discrimination accuracy in predicting progression risk at 5 years in the same cohort was 82.4% (95% CI, 72.6-89.7%).
The radiomics is a low-cost, non-invasive method to predict SBC prognosis preoperatively. Radiomic signature is a potential prognostic biomarker that may allow the individualized evaluation of patients with SBC.
我们使用放射组学分析，基于解剖磁共振成像（MRI）序列建立放射组学特征，并探讨其作为一种新的颅底脊索瘤（SBC）预后生物标志物的有效性。
本回顾性研究对单一医院的术前轴位 T FLAIR、T 加权和增强 T FLAIR 进行放射组学分析。主要临床终点是无进展生存期。从手动分割的感兴趣区域中提取了 1860 个 3D 放射组学特征。使用 Pearson 相关系数进行特征降维，并使用基于岭回归的 Cox 比例风险模型确定放射组学特征。然后，对放射组学特征和其他 9 个可能的预后因素（包括年龄、性别、组织学亚型、硬脑膜侵犯、血供、辅助放疗、切除程度、术前 KPS 和术后 KPS）进行分析，构建放射组学列线图和临床模型。最后，通过 DeLong 检验比较列线图与每个预后因素/模型。
共纳入 148 例 SBC 患者，其中 64 例疾病进展。中位随访时间为 52 个月（范围 4-122 个月）。验证队列中放射组学特征的 Harrell 一致性指数为 0.745（95%CI，0.709-0.781），在同一队列中预测 5 年进展风险的区分准确率为 82.4%（95%CI，72.6%-89.7%）。
放射组学是一种预测 SBC 术前预后的低成本、非侵入性方法。放射组学特征是一种有潜力的预后生物标志物，可能使 SBC 患者的个体化评估成为可能。
