Early Identification of Pathologic Complete Response to Neoadjuvant Chemotherapy Using Multiphase DCE‐MRI by Siamese Network in Breast Cancer: A Longitudinal Multicenter Study

医学 接收机工作特性 乳腺癌 阶段(地层学) 乳房磁振造影 核医学 放射科 癌症 内科学 乳腺摄影术 生物 古生物学
作者
Yao Huang,Ying Cao,Xiaofei Hu,Xiaosong Lan,Huifang Chen,Sun Tang,Lan Li,Yue Cheng,Xueqin Gong,Wei Wang,Fujie Jiang,Ting Yin,Xiaoxia Wang,Jiuquan Zhang
出处
期刊:Journal of Magnetic Resonance Imaging [Wiley]
卷期号:60 (4): 1325-1337 被引量:3
标识
DOI:10.1002/jmri.29188
摘要

Background Siamese network (SN) using longitudinal DCE‐MRI for pathologic complete response (pCR) identification lack a unified approach to phases selection. Purpose To identify pCR in early‐stage NAC, using SN with longitudinal DCE‐MRI and introducing IPS for phases selection. Study Type Multicenter, longitudinal. Population Center A: 162 female patients (50.63 ± 8.41 years) divided 7:3 into training and internal validation cohorts. Center B: 61 female patients (50.08 ± 7.82 years) were used as an external validation cohort. Field Strength/Sequence Center A: single vendor 3.0 T with a compressed‐sensing volume interpolated breath‐hold examination sequence. Center B: single vendor 1.5 T with volume interpolated breath‐hold examination sequence. Assessment Patients underwent DCE‐MRI before and after two NAC cycles, with tumor regions of interest (ROI) manually delineated. Histopathology was the reference for pCR identification. Models developed included a clinical one, four SN models based on IPS‐selected phases, and integrated models combining clinical and SN features. Statistical Tests Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The DeLong test was used to compare AUCs. Net reclassification improvement and integrated discrimination improvement (IDI) tests were employed for performance comparison. P < 0.05 was considered significant. Results In internal and external validation cohorts, the clinical model showed AUCs of 0.760 and 0.718. SN and integrated models, with increasing phases via IPS, achieved AUCs ranging from 0.813 to 0.951 and 0.818 to 0.922. Notably, SN‐3 and integrated‐3 and integrated‐4 outperformed the clinical model. However, input phases beyond 20% did not significantly enhance performance (IDI test: SN‐4 vs. SN‐3, P = 0.314 and 0.630; integrated‐4 vs. integrated‐3, P = 0.785 and 0.709). Data Conclusion The longitudinal multiphase DCE‐MRI based on the SN demonstrates promise for identifying pCR in breast cancer. Evidence Level 1 Technical Efficacy Stage 4
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