Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study.
Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study.
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新辅助化疗后乳腺癌复发的定量 DCE-MRI 预测：初步研究。
DOI：
10.1186/s12880-022-00908-0
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发表时间：
2022-10-20
影响因子：
2.7
通讯作者：
Huang, Wei
中科院分区：
文献类型：
--
作者：
Thawani, Rajat;Gao, Lina;Mohinani, Ajay;Tudorica, Alina;Li, Xin;Mitri, Zahi;Huang, Wei
关键词：
乳腺癌患者接受新辅助化疗（NACT）的复发风险取决于临床病理特征。本初步研究旨在探讨定量动态对比增强（DCE） MRI参数单独或联合临床病理变量预测NACT治疗患者复发的预测性能。47例患者接受了nact前后的MRI检查，包括高时空分辨率DCE-MRI。采用Shutter-Speed模型对DCE-MRI数据进行药代动力学分析，并估计Ktrans、ve、keep和τi参数。单变量逻辑回归用于评估每个MRI指标对复发的预测准确性，而Firth逻辑回归用于评估具有多临床病理变量的模型的预测性能，并与单一MRI指标或所有MRI指标的第一主成分相结合。无论是单独使用还是结合临床病理变量，nact前后的DCE-MRI参数在预测复发方面都优于肿瘤大小测量。合并nact后Ktrans与残余癌负担和年龄的预测效果改善最好，ROC AUC = 0.965。通过整合影像学标志物和临床病理变量，准确预测NACT术前和/或术后复发，可能有助于改善临床决策，调整NACT和/或辅助治疗方案，以降低复发风险，改善生存结果。
Breast cancer patients treated with neoadjuvant chemotherapy (NACT) are at risk of recurrence depending on clinicopathological characteristics. This preliminary study aimed to investigate the predictive performances of quantitative dynamic contrast-enhanced (DCE) MRI parameters, alone and in combination with clinicopathological variables, for prediction of recurrence in patients treated with NACT. Forty-seven patients underwent pre- and post-NACT MRI exams including high spatiotemporal resolution DCE-MRI. The Shutter-Speed model was employed to perform pharmacokinetic analysis of the DCE-MRI data and estimate the Ktrans, ve, kep, and τi parameters. Univariable logistic regression was used to assess predictive accuracy for recurrence for each MRI metric, while Firth logistic regression was used to evaluate predictive performances for models with multi-clinicopathological variables and in combination with a single MRI metric or the first principal components of all MRI metrics. Pre- and post-NACT DCE-MRI parameters performed better than tumor size measurement in prediction of recurrence, whether alone or in combination with clinicopathological variables. Combining post-NACT Ktrans with residual cancer burden and age showed the best improvement in predictive performance with ROC AUC = 0.965. Accurate prediction of recurrence pre- and/or post-NACT through integration of imaging markers and clinicopathological variables may help improve clinical decision making in adjusting NACT and/or adjuvant treatment regimens to reduce the risk of recurrence and improve survival outcome.
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