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

Author:

Huang Yao12,Cao Ying12,Hu Xiaofei3,Lan Xiaosong2,Chen Huifang2,Tang Sun2,Li Lan2,Cheng Yue2,Gong Xueqin2,Wang Wei2,Jiang Fujie2,Yin Ting4,Wang Xiaoxia2,Zhang Jiuquan2ORCID

Affiliation:

1. School of Medicine, Chongqing University Chongqing China

2. Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China

3. Department of Radiology Southwest Hospital, Third Military Medical University (Army Medical University) Chongqing China

4. MR Collaborations, Siemens Healthineers Ltd. Chengdu China

Abstract

BackgroundSiamese network (SN) using longitudinal DCE‐MRI for pathologic complete response (pCR) identification lack a unified approach to phases selection.PurposeTo identify pCR in early‐stage NAC, using SN with longitudinal DCE‐MRI and introducing IPS for phases selection.Study TypeMulticenter, longitudinal.PopulationCenter 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/SequenceCenter 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.AssessmentPatients 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 TestsModel 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.ResultsIn 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 ConclusionThe longitudinal multiphase DCE‐MRI based on the SN demonstrates promise for identifying pCR in breast cancer.Evidence Level1Technical EfficacyStage 4

Funder

Fundamental Research Funds for the Central Universities

Natural Science Foundation of Chongqing Municipality

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

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