Impact of deformable registration methods for prediction of recurrence free survival response to neoadjuvant chemotherapy in breast cancer: Results from the ISPY 1/ACRIN 6657 trial.
Impact of deformable registration methods for prediction of recurrence free survival response to neoadjuvant chemotherapy in breast cancer: Results from the ISPY 1/ACRIN 6657 trial.
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DOI：
10.1016/j.tranon.2022.101411
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发表时间：
2022-06
影响因子：
5
通讯作者：
Kontos D
中科院分区：
文献类型：
--
作者：
Thakran S;Cohen E;Jahani N;Weinstein SP;Pantalone L;Hylton N;Newitt D;DeMichele A;Davatzikos C;Kontos D
比较了六种可变形配准算法（ANTs、DRAMMS、ART、niftyregg、SSD-FFD和NMI-FFD）对乳腺纵向DCE-MRI扫描的配准。这些登记方法的效果评估了放射学特征对局部晚期乳腺癌接受NAC的妇女的RFS模型的预测价值。还以专家定义的解剖标志作为金标准评估了不同注册方法的准确性。图像配准在空间对齐多个MRI扫描以更好地纵向评估肿瘤形态特征方面起着至关重要的作用。目的是评估六种已建立的可变形登记方法（ANTs、DRAMMS、ART、niftyregg、SSD-FFD和NMI-FFD）在对局部晚期乳腺癌新辅助化疗（NAC）后妇女无复发生存（RFS）建模时提取的放射学特征的预测价值的登记准确性。在ISPY1/ACRIN-6657队列中，有130名妇女在前两次就诊时进行了DCE-MRI扫描。我们从每种不同的可变形配准方法中计算变换场，并使用它来计算已建立的四个动力学特征的体素参数响应图（PRM）。从每个PRM图谱中计算104个放射学特征，以表征肿瘤内的异质性。我们使用Cox-regression、C-statistic和Kaplan-Meier（KM）图来评估RFS的性能。基线模型（F1：年龄、种族和激素受体状态）的c统计值为0.54，模型F2（基线+早期治疗就诊时功能肿瘤体积（FTV2））的c统计值为0.63。与其他车型相比，F2+ANTs的c统计量最高（0.72），地标性差异最小（5.40±4.40mm）。与模型F1（p=0.31）相比，模型F2的KM曲线给出了高于和低于中位风险的女性之间的间隔p=0.004。除F2+ART模型外，具有放射学特征的A模型也实现了显著的KM曲线分离（p<0.001）。结合图像配准量化NAC期间肿瘤异质性的变化，可以提高对RFS的预测。与其他方法相比，利用ANTs配准方法对DCE-MRI动力学图进行扭曲得到的PRM图的放射学特征进一步提高了对RFS的早期预测。
Six deformable registration algorithms (ANTs, DRAMMS, ART, NiftyReg, SSD-FFD, and NMI-FFD) were compared for the registration of longitudinal breast DCE-MRI scans. The effect of these registration methods was evaluated on the predictive value of radiomic features to model RFS in women undergoing NAC for locally advanced breast cancer. The accuracies of the different registration methods were also evaluated with expert-defined anatomical landmarks as a gold standard. Image registration plays a vital role in spatially aligning multiple MRI scans for better longitudinal assessment of tumor morphological features. The objective was to evaluate the effect of registration accuracy of six established deformable registration methods(ANTs, DRAMMS, ART, NiftyReg, SSD-FFD, and NMI-FFD) on the predictive value of extracted radiomic features when modeling recurrence-free-survival(RFS) for women after neoadjuvant chemotherapy(NAC) for locally advanced breast cancer. 130 women had DCE-MRI scans available from the first two visits in the ISPY1/ACRIN-6657 cohort. We calculated the transformation field from each of the different deformable registration methods, and used it to compute voxel-wise parametric-response-maps(PRM) for established four kinetic features.104-radiomic features were computed from each PRM map to characterize intra-tumor heterogeneity. We evaluated performance for RFS using Cox-regression, C-statistic, and Kaplan-Meier(KM) plots. A baseline model(F1:Age, Race, and Hormone-receptor-status) had a 0.54 C-statistic, and model F2(baseline + functional-tumor-volume at early treatment visit(FTV2)) had 0.63. The F2+ANTs had the highest C-statistic(0.72) with the smallest landmark differences(5.40±4.40mm) as compared to other models. The KM curve for model F2 gave p=0.004 for separation between women above and below the median hazard compared to the model F1(p=0.31). A models augmented with radiomic features, also achieved significant KM curve separation(p<0.001) except the F2+ART model. Incorporating image registration in quantifying changes in tumor heterogeneity during NAC can improve prediction of RFS. Radiomic features of PRM maps derived from warping the DCE-MRI kinetic maps using ANTs registration method further improved the early prediction of RFS as compared to other methods.
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影响因子：
19.7
作者：
Kim, Jae-Hun;Ko, Eun Sook;Nam, Seok Jin
通讯作者：
Nam, Seok Jin
影响因子：
19.7
作者：
Bhooshan, Neha;Giger, Maryellen L.;Newstead, Gillian M.
通讯作者：
Newstead, Gillian M.
影响因子：
4.4
作者：
Clark, Kenneth;Vendt, Bruce;Prior, Fred
通讯作者：
Prior, Fred
影响因子：
3.3
作者：
Mazurowski, Maciej A.;Grimm, Lars J.;Johnson, Karen S.
通讯作者：
Johnson, Karen S.
影响因子：
3.3
作者：
Ou Y;Weinstein SP;Conant EF;Englander S;Da X;Gaonkar B;Hsieh MK;Rosen M;DeMichele A;Davatzikos C;Kontos D
通讯作者：
Kontos D