ReviewThe Indian journal of radiology & imaging2026
Ability of MRI Breast to Predict Pathologic Complete Response Following Neoadjuvant Systemic Therapy in Patients with Breast Cancer.
Review in The Indian journal of radiology & imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
Neoadjuvant systemic therapy (NST) has revolutionized the management of breast cancer by downstaging the disease and improving survival rates. Pathologic complete response, where surgical histopathological examination shows no invasive cancer in the breast and axilla, is not an uncommon scenario. In such patients, surgery may have added value to cancer control only for documenting the absence of cancer cells in the body in response to NST. In other words, could we have forfeited surgery for such patients if we were able to reliably identify them before surgery? However, the challenge lies in accurately identifying such patients. This narrative literature review explores the predictive ability of MRI scans in assessing pathological complete response (pCR) following NST. MRI demonstrates high sensitivity and specificity in detecting residual tumors post-NST, outperforming conventional imaging modalities. Combining diffusion-weighted MRI and contrast-enhanced MRI enhances diagnostic accuracy, particularly in monitoring response to chemotherapy. However, MRI's limitations include over- or underestimation of lesion size and morphology, necessitating complementary approaches for precise assessment. Vacuum-assisted core biopsy (VACB) emerges as a promising adjunct to MRI, offering high negative predictive value and minimal invasiveness. MRI-guided VACB enables accurate tissue sampling and lesion verification, augmenting diagnostic certainty. This integrated approach could particularly benefit patients with smaller-sized triple-negative or HER2-positive tumors. Further research is warranted to establish the clinical utility of combined MRI and VACB in predicting pCR post-NST and guiding personalized treatment decisions. Such advancements hold promise for a paradigm shift in breast cancer management, sparing patients from avoidable surgeries and optimizing therapeutic outcomes.
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