Predicting Breast Cancer Pathologic Complete Response after Neoadjuvant Chemotherapy Using Bimodal US and MRI

Purpose To determine whether bimodal US improves prediction of pathologic complete response following neoadjuvant chemotherapy (NAC) compared with MRI, as well as to assess the diagnostic value of a combined imaging model. Materials and Methods In this prospective two-center study, participants with primary breast cancer undergoing NAC between January 2020 and January 2024 were enrolled. Preoperative bimodal US (grayscale and shear wave) and MRI data were collected. Complete response on US (uCR) and MR images (mCR) were defined by radiologists. Diagnostic models based on uCR, mCR, and their combination were evaluated using postsurgical pathology as the reference standard. Pathologic complete response was defined as no residual tumor (ypT0) or no invasive cancer with possible ductal carcinoma in situ (ypT0/Tis). Model performance was evaluated by area under the receiver operating characteristic curve (AUC), with sensitivity, specificity, positive and negative likelihood ratios, and comparisons by the DeLong test. All tests were two-sided (<i>P</i> < .05). Results A total of 224 female participants (median age, 46 years; IQR, 38.75-56) with breast cancer undergoing NAC were included. Overall, 82 of 224 (37%) achieved ypT0/Tis, and 62 of 224 (28%) achieved ypT0. Using ypT0/Tis as the pathologic complete response standard, the uCR model achieved an AUC of 0.76 (95% CI: 0.67, 0.83), while the mCR model achieved an AUC of 0.80 (95% CI: 0.71, 0.87). Using ypT0, the uCR model achieved an AUC of 0.79 (95% CI: 0.70, 0.86), and the mCR model an AUC of 0.75 (95% CI: 0.65, 0.82) in the test set. The combined imaging model (ypT0/Tis, AUC = 0.87; ypT0, AUC = 0.87) outperformed both the uCR (ypT0/Tis, <i>P</i> = .002; ypT0, <i>P</i> = .002) and mCR models (ypT0/Tis, <i>P</i> = .04; ypT0, <i>P</i> = .004). Conclusion Bimodal US effectively predicted pathologic response to NAC in breast cancer with accuracy comparable to MRI. A combined US/MRI model demonstrated higher diagnostic performance than either modality alone. <b>Keywords:</b> Breast, Ultrasound Chinese Clinical Trial Registry (ChiCTR2400085035) <i>Supplemental material is available for this article.</i> © RSNA, 2025 See also commentary by Horvat and Fazzio in this issue.

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Journal
Radiology Imaging Cancer
Published
2025-10-17
DOI
https://doi.org/10.1148/rycan.240493
Citations
1
Primary Topic
MRI in cancer diagnosis
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article
Field-Weighted Citation Impact
1.36
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article

Predicting Breast Cancer Pathologic Complete Response after Neoadjuvant Chemotherapy Using Bimodal US and MRI

Xue-Yan Wang, Huining Huang, Xiao‐Qing Pei, Yan-Fen Xu et al.
1 citations
Radiology Imaging Cancer
MRI in cancer diagnosis
1.36
article

Predicting Breast Cancer Pathologic Complete Response after Neoadjuvant Chemotherapy Using Bimodal US and MRI

Xue-Yan Wang, Huining Huang, Xiao‐Qing Pei, Yan-Fen Xu, Feng-Tao Liu, Jingsi Mei, Jia-Xin Huang, Meiqin Xiao, Ming-Jie Wei, Yu-Ting Zhang, Gui-Ling Huang
article en
1 citations

Abstract

Purpose To determine whether bimodal US improves prediction of pathologic complete response following neoadjuvant chemotherapy (NAC) compared with MRI, as well as to assess the diagnostic value of a combined imaging model. Materials and Methods In this prospective two-center study, participants with primary breast cancer undergoing NAC between January 2020 and January 2024 were enrolled. Preoperative bimodal US (grayscale and shear wave) and MRI data were collected. Complete response on US (uCR) and MR images (mCR) were defined by radiologists. Diagnostic models based on uCR, mCR, and their combination were evaluated using postsurgical pathology as the reference standard. Pathologic complete response was defined as no residual tumor (ypT0) or no invasive cancer with possible ductal carcinoma in situ (ypT0/Tis). Model performance was evaluated by area under the receiver operating characteristic curve (AUC), with sensitivity, specificity, positive and negative likelihood ratios, and comparisons by the DeLong test. All tests were two-sided (<i>P</i> < .05). Results A total of 224 female participants (median age, 46 years; IQR, 38.75-56) with breast cancer undergoing NAC were included. Overall, 82 of 224 (37%) achieved ypT0/Tis, and 62 of 224 (28%) achieved ypT0. Using ypT0/Tis as the pathologic complete response standard, the uCR model achieved an AUC of 0.76 (95% CI: 0.67, 0.83), while the mCR model achieved an AUC of 0.80 (95% CI: 0.71, 0.87). Using ypT0, the uCR model achieved an AUC of 0.79 (95% CI: 0.70, 0.86), and the mCR model an AUC of 0.75 (95% CI: 0.65, 0.82) in the test set. The combined imaging model (ypT0/Tis, AUC = 0.87; ypT0, AUC = 0.87) outperformed both the uCR (ypT0/Tis, <i>P</i> = .002; ypT0, <i>P</i> = .002) and mCR models (ypT0/Tis, <i>P</i> = .04; ypT0, <i>P</i> = .004). Conclusion Bimodal US effectively predicted pathologic response to NAC in breast cancer with accuracy comparable to MRI. A combined US/MRI model demonstrated higher diagnostic performance than either modality alone. <b>Keywords:</b> Breast, Ultrasound Chinese Clinical Trial Registry (ChiCTR2400085035) <i>Supplemental material is available for this article.</i> © RSNA, 2025 See also commentary by Horvat and Fazzio in this issue.

Radiology Imaging CancerVol. 7(6)
Sun Yat-sen University (CN), Sun Yat-sen Memorial Hospital (CN), Sun Yat-sen University Cancer Center (CN), University of Hong Kong (HK)
Openalex Percentile: Top 15%
MRI in cancer diagnosis
1.36
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