Efficacy of Abbreviated Breast MRI Following Neoadjuvant Chemotherapy
Abstract
OBJECTIVE: This study evaluates concordance between abbreviated protocol breast MRIs (abMRI) and standard full-protocol MRI in the post-neoadjuvant chemotherapy (NAC) setting. METHODS: This multi-site single institution retrospective study included breast cancer patients with pre- and post-NAC breast MRI during 2016-2023. The abMRI sequences included localizers, pre-contrast fat sat T1, fat sat first post-contrast phase, reconstructed first post-contrast phase subtraction, and maximum-intensity projection images from the institution's standard protocol. Four breast radiologists interpreted abMRIs and full MRIs after a washout period of at least 1 month. Residual tumor size (RTS) was compared to pathology. Statistical analysis with multivariable logistic regression, Receiver Operating Curve analysis, Kappa analysis, and paired t-tests were performed. RESULTS: Ninety-two of 237 patients (38.8%; mean age, 52.6 years) had pathologic complete response (pCR). There was no significant difference between abMRI and full MRI for predicting pCR for any reader individually (P-value range 0.30-0.91) with overall area under curve (AUC) = 0.70. Intraobserver and interobserver agreement for abMRI and full MRI was moderate to good (κ = 0.52-0.78). There was concordance between abMRI and full MRI for predicting pCR when stratified by menopause status, background parenchymal enhancement, tumor stage, tumor biomarkers, and Ki-67. When compared to pathology, all readers demonstrated no significant difference in RTS with abMRI, and one reader underestimated RTS on full MRI by 7 mm (P = 0.005). CONCLUSION: Our study found no significant difference in diagnostic performance between abMRI and full MRI when compared to pathology for evaluating post-NAC patients for pCR and evaluation of residual disease in the breast. Abbreviated MRI and full MRI show similar effectiveness in predicting complete tumor response and assessing residual disease on post-NAC assessment.
Fields of Study & Subjects
MRI in cancer diagnosis
Breast Cancer Treatment Studies
Radiomics and Machine Learning in Medical Imaging
Publication details
- Journal / source
- Journal of Breast Imaging
- Publisher
- Oxford University Press (OUP)
- Publication date
- 28 May 2026
- Language
- EN