Department of Radiology, MC2026, 5841 S Maryland Ave, Chicago, IL, USA.
Cancer Imaging. 2018 Apr 13;18(1):12. doi: 10.1186/s40644-018-0145-9.
The hypothesis of this study was that MRI-based radiomics has the ability to predict recurrence-free survival "early on" in breast cancer neoadjuvant chemotherapy.
A subset, based on availability, of the ACRIN 6657 dynamic contrast-enhanced MR images was used in which we analyzed images of all women imaged at pre-treatment baseline (141 women: 40 with a recurrence, 101 without) and all those imaged after completion of the first cycle of chemotherapy, i.e., at early treatment (143 women: 37 with a recurrence vs. 105 without). Our method was completely automated apart from manual localization of the approximate tumor center. The most enhancing tumor volume (METV) was automatically calculated for the pre-treatment and early treatment exams. Performance of METV in the task of predicting a recurrence was evaluated using ROC analysis. The association of recurrence-free survival with METV was assessed using a Cox regression model controlling for patient age, race, and hormone receptor status and evaluated by C-statistics. Kaplan-Meier analysis was used to estimate survival functions.
The C-statistics for the association of METV with recurrence-free survival were 0.69 with 95% confidence interval of [0.58; 0.80] at pre-treatment and 0.72 [0.60; 0.84] at early treatment. The hazard ratios calculated from Kaplan-Meier curves were 2.28 [1.08; 4.61], 3.43 [1.83; 6.75], and 4.81 [2.16; 10.72] for the lowest quartile, median quartile, and upper quartile cut-points for METV at early treatment, respectively.
The performance of the automatically-calculated METV rivaled that of a semi-manual model described for the ACRIN 6657 study (published C-statistic 0.72 [0.60; 0.84]), which involved the same dataset but required semi-manual delineation of the functional tumor volume (FTV) and knowledge of the pre-surgical residual cancer burden.
本研究的假设是，基于 MRI 的放射组学能够“早期”预测乳腺癌新辅助化疗的无复发生存。
根据可用性，选择了 ACRIN 6657 动态对比增强磁共振成像的子集，我们分析了所有在治疗前基线（141 名女性：40 名复发，101 名无复发）和所有在第一周期化疗后（143 名女性：37 名复发，105 名无复发）成像的女性的图像。我们的方法除了手动定位大致肿瘤中心外，完全是自动化的。对于治疗前和早期检查，自动计算最大增强肿瘤体积（METV）。使用 ROC 分析评估 METV 在预测复发任务中的性能。使用 Cox 回归模型评估无复发生存与 METV 的关联，该模型控制患者年龄、种族和激素受体状态，并通过 C 统计量进行评估。使用 Kaplan-Meier 分析估计生存函数。
治疗前 METV 与无复发生存的关联的 C 统计量为 0.69，95%置信区间为 [0.58；0.80]，早期治疗时为 0.72 [0.60；0.84]。从 Kaplan-Meier 曲线计算出的风险比分别为 2.28 [1.08；4.61]、3.43 [1.83；6.75]和 4.81 [2.16；10.72]，用于早期治疗时 METV 的最低四分位数、中位数四分位数和上四分位数切点。
自动计算的 METV 的性能可与为 ACRIN 6657 研究（已发表的 C 统计量为 0.72 [0.60；0.84]）描述的半手动模型相媲美，该模型涉及相同的数据，但需要半手动描绘功能肿瘤体积（FTV）和术前残留癌负荷的知识。
