Breast MRI for Evaluation of Response to Neoadjuvant Therapy.

Radiographics

From the Department of Radiology (B.R., A.A.L., L.H., H.K.T., S.L.H., Y.G., L.M.), Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology (L.M.), and Center for Advanced Imaging Innovation and Research (CAI2R) (L.M.), New York University Grossman School of Medicine, 160 E 34th St, New York, NY 10016; and Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Mass (L.D.).

Published: November 2021

Neoadjuvant therapy is increasingly being used to treat early-stage triple-negative and human epidermal growth factor 2-overexpressing breast cancers, as well as locally advanced and inflammatory breast cancers. The rationales for neoadjuvant therapy are to shrink tumor size and potentially decrease the extent of surgery, to serve as an in vivo test of response to therapy, and to reveal prognostic information for the patient. MRI is the most accurate modality to demonstrate response to therapy and to help ensure accurate presurgical planning. Changes in lesion diameter, volume, and enhancement are used to predict complete response, partial response, or nonresponse to therapy. However, residual disease may be overestimated or underestimated at MRI. Fibrosis, necrotic tumors, and residual benign masses may be causes of overestimation of residual disease. Nonmass lesions, invasive lobular carcinoma, hormone receptor-positive tumors, nonconcentric shrinkage patterns, the use of antiangiogenic therapy, and late-enhancing foci may be causes of underestimation of residual disease. In patients with known axillary lymph node metastasis, neoadjuvant therapy may be followed by targeted axillary dissection to avoid the potential morbidity associated with an axillary lymph node dissection. Diffusion-weighted imaging, radiomics, machine learning, and deep learning methods are under investigation to improve MRI accuracy in predicting treatment response.RSNA, 2021.

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http://dx.doi.org/10.1148/rg.2021200134DOI Listing

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