From the Department of Radiology (T.R., V.L., M.J., C.M., H.J.B., A.T.), Department of Diagnostic and Theranostic Medicine-Pathology (J.S., A.V.S.), Department of Surgical Oncology (E.L.), Department of Medical Oncology (E.R.), Stress and Cancer Laboratory (F.M.G.), and INSERM U830 (F.M.G.), Institut Curie, PSL University, 26 rue d'Ulm, 75005 Paris, France; Department of Surgical Oncology and INSERM U900, Statistical Methods for Precision Medicine, Institut Curie, University of Versailles Saint-Quentin-en-Yvelines, Saint-Cloud, France (C.B.); Departments of Diagnostic and Theranostic Medicine-Pathology (E.M.), Medical Oncology (D.B.R., F.C.B., L.C.), and Radiology (A.L.), Institut Curie, PSL University, Saint-Cloud, France; Department of Immunology, PSL University, Paris, France (E.R.); and Circulating Tumor Biomarkers Laboratory, Department of Translational Research, Institut Curie, Paris, France (F.C.B.).
Radiology. 2024 Sep;312(3):e240575. doi: 10.1148/radiol.240575.
Background Neoadjuvant chemoimmunotherapy (NACI) has significantly increased the rate of pathologic complete response (pCR) in patients with early-stage triple-negative breast cancer (TNBC), although predictors of response to this regimen have not been identified. Purpose To investigate pretreatment perfusion MRI-based radiomics as a predictive marker for pCR in patients with TNBC undergoing NACI. Materials and Methods This prospective study enrolled women with early-stage TNBC who underwent NACI at two different centers from August 2021 to July 2023. Pretreatment dynamic contrast-enhanced MRI scans obtained using scanners from multiple vendors were analyzed using the Tofts model to segment tumors and analyze pharmacokinetic parameters. Radiomics features were extracted from the rate constant for contrast agent plasma-to-interstitial transfer (or ), volume fraction of extravascular and extracellular space (), and maximum contrast agent uptake rate (Slope) maps and analyzed using unsupervised correlation and least absolute shrinkage and selector operator, or LASSO, to develop a radiomics score. Score effectiveness was assessed using the area under the receiver operating characteristic curve (AUC), and multivariable logistic regression was used to develop a multimodal nomogram for enhanced prediction. The discrimination, calibration, and clinical utility of the nomogram were evaluated in an external test set. Results The training set included 112 female participants from center 1 (mean age, 52 years ± 11 [SD]), and the external test set included 83 female participants from center 2 (mean age, 47 years ± 11). The radiomics score demonstrated an AUC of 0.80 (95% CI: 0.70, 0.89) for predicting pCR. A nomogram incorporating the radiomics score, grade, and Ki-67 yielded an AUC of 0.86 (95% CI: 0.78, 0.94) in the test set. Associations were found between higher radiomics score (>0.25) and tumor size ( < .001), washout enhancement ( = .01), androgen receptor expression ( = .009), and programmed death ligand 1 expression ( = .01), demonstrating a correlation with tumor immune environment in participants with TNBC. Conclusion A radiomics score derived from pharmacokinetic parameters at pretreatment dynamic contrast-enhanced MRI exhibited good performance for predicting pCR in participants with TNBC undergoing NACI, and could potentially be used to enhance clinical decision making. © RSNA, 2024 See also the editorial by Rauch in this issue.
背景 新辅助化疗免疫治疗（NACI）显著提高了早期三阴性乳腺癌（TNBC）患者的病理完全缓解（pCR）率，尽管尚未确定对此治疗方案的反应预测因子。目的 研究基于预处理灌注 MRI 的放射组学作为接受 NACI 的 TNBC 患者 pCR 的预测标志物。材料与方法 本前瞻性研究纳入了 2021 年 8 月至 2023 年 7 月在两个不同中心接受 NACI 的早期 TNBC 女性患者。使用来自多个供应商的扫描仪获得的预处理动态对比增强 MRI 扫描，使用 Tofts 模型进行分析，以分割肿瘤并分析药代动力学参数。从对比剂血浆到间质转移的速率常数（或 ）、血管外和细胞外空间的体积分数（）和最大对比剂摄取率（Slope）图中提取放射组学特征，并使用无监督相关性和最小绝对值收缩和选择器算子（LASSO）进行分析，以开发放射组学评分。使用受试者工作特征曲线（ROC）下面积（AUC）评估评分的有效性，并使用多变量逻辑回归为增强预测开发多模态列线图。在外部测试集中评估了列线图的判别、校准和临床实用性。结果 训练集包括来自中心 1 的 112 名女性参与者（平均年龄，52 岁±11[标准差]），外部测试集包括来自中心 2 的 83 名女性参与者（平均年龄，47 岁±11）。放射组学评分对预测 pCR 的 AUC 为 0.80（95%CI：0.70，0.89）。在测试集中，包含放射组学评分、分级和 Ki-67 的列线图的 AUC 为 0.86（95%CI：0.78，0.94）。发现较高的放射组学评分（>0.25）与肿瘤大小（<0.001）、洗脱增强（=0.01）、雄激素受体表达（=0.009）和程序性死亡配体 1 表达（=0.01）之间存在关联，表明与接受 NACI 的 TNBC 患者的肿瘤免疫环境相关。结论 来自预处理动态对比增强 MRI 的药代动力学参数的放射组学评分对预测 TNBC 患者的 pCR 具有良好的性能，并且可能有助于增强临床决策。
