Li Qin, Xiao Qin, Li Jianwei, Duan Shaofeng, Wang He, Gu Yajia
Shanghai Institute of Medical Imaging, Shanghai, China.
Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Cancer Manag Res. 2020 Oct 27;12:10603-10613. doi: 10.2147/CMAR.S271876. eCollection 2020.
To identify MRI-based radiomics signature (Rad-score) as a biomarker of risk stratification for disease-free survival (DFS) in patients with HER2-positive invasive breast cancer treated with trastuzumab-based neoadjuvant chemotherapy (NAC) and establish a radiomics-clinicoradiologic-based nomogram that combines Rad-score, MRI findings, and clinicopathological variables for DFS estimation.
A total of 127 patients were divided into a training set and testing set according to the ratio of 7:3. Radiomic features were extracted from multiphase CE-MRI (CE). Rad-score was calculated using the LASSO (least absolute shrinkage and selection operator) regression analysis. The cutoff point of Rad-score to divide the patients into high- and low-risk groups was determined by receiver operating characteristic curve analysis. A Kaplan-Meier survival curves and the Log rank test were used to investigate the association of the Rad-score with DFS. Univariate and multivariate Cox proportional hazards model were used to determine the association of Rad-score, MRI features, and clinicopathological variables with DFS. A radiomics-clinicoradiologic-based nomogram combining the Rad-score, MRI features, and clinicopathological findings was plotted to validate the radiomic signatures for DFS estimation.
The Rad-score stratified patients into high- and low-risk groups for DFS in the training set (<0.0001) and was validated in the testing set (=0.002). The radiomics-clinicoradiologic-based nomogram estimated DFS (training set: C-index=0.974, 95% confidence interval (CI)=0.954-0.994; testing set: C-index=0.917, 95% CI=0.842-0.991) better than the clinicoradiologic-based nomogram (training set: C-index=0.855, 95% CI=0.739-0.971; testing set: C-index=0.831, 95% CI=0.643-0.999).
The Rad-score is an independent biomarker for the estimation of DFS in invasive HER2-positive breast cancer with NAC and the radiomics-clinicoradiologic-based nomogram improved individualized DFS estimation.
确定基于MRI的放射组学特征(Rad评分)作为接受曲妥珠单抗辅助新辅助化疗(NAC)的HER2阳性浸润性乳腺癌患者无病生存期(DFS)风险分层的生物标志物,并建立一种基于放射组学-临床放射学的列线图,该列线图结合Rad评分、MRI表现和临床病理变量来估计DFS。
根据7:3的比例将127例患者分为训练集和测试集。从多期对比增强MRI(CE-MRI)中提取放射组学特征。使用LASSO(最小绝对收缩和选择算子)回归分析计算Rad评分。通过受试者工作特征曲线分析确定将患者分为高风险组和低风险组的Rad评分临界值。采用Kaplan-Meier生存曲线和对数秩检验研究Rad评分与DFS的相关性。使用单因素和多因素Cox比例风险模型确定Rad评分、MRI特征和临床病理变量与DFS的相关性。绘制结合Rad评分、MRI特征和临床病理结果的基于放射组学-临床放射学的列线图,以验证用于DFS估计的放射组学特征。
Rad评分在训练集(<0.0001)中将患者分为DFS的高风险组和低风险组,并在测试集(=0.002)中得到验证。基于放射组学-临床放射学的列线图对DFS的估计(训练集:C指数=0.974,95%置信区间(CI)=0.954-0.994;测试集:C指数=0.917,95%CI=0.842-0.991)优于基于临床放射学的列线图(训练集:C指数=0.855,95%CI=0.739-0.971;测试集:C指数=0.831,95%CI=0.643-0.999)。
Rad评分是评估接受NAC的HER2阳性浸润性乳腺癌DFS的独立生物标志物,基于放射组学-临床放射学的列线图改善了个体化DFS估计。