alexa Abstract | Accuracy of MRI for Prediction of Response to Neo-Adjuvant Chemotherapy in Triple Negative Breast Cancer Compared to Other Molecular Types
ISSN: 2167-7700

Chemotherapy: Open Access
Open Access

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Research Article Open Access

Abstract

Abstract Purpose: The aim of this study was to compare the accuracy of MRI for prediction of response to Neo-adjuvant chemotherapy in Triple negative (TN) breast cancer, with respect to other molecular types. Materials and methods: There were a total of 1610 breast cancers diagnosed between March 2009 and August 2014, out of which 82 patients underwent MRI before and after neo-adjuvant chemotherapy but just before surgery. Triple negative cancers were analysed with respect to others subtypes. Accuracy of MRI for prediction of pathological complete response was compared between different subtypes, by obtaining ROC curves. SPSS (version 21) was used for all data analysis with p value of 0.05 as statistically significant. Results: Out of 82 patients, 29 were Luminal (HR+/HER2 -), 23 were triple negative (HR-, HER2-), 11 HER2 positive (HR-, HER2+) and 19 were of hybrid subtype (HR+/HER2+). Triple negative cancers presented as masses on the pre-chemotherapy MRI scan, were grade 3 on histopathology and show concentric shrinkage following chemotherapy. Triple negative cancers were more likely to have both imaging and pathological complete response following chemotherapy (p=0.055) in contrast to Luminal cancers, which show residual cancer. ROC curves were constructed for prediction of PCR by post chemotherapy MR. For the triple negative sub-group, MR had sensitivity of 0.745 and specificity of 0.700 (p=0.035), with an area under curve (AUC) of 0.745(95% CI 0.526-0.965), which was significantly better compared to other subtypes. Conclusion: Triple negative breast cancers present as masses and show concentric shrinkage following chemotherapy. MRI is most sensitive and specific in predicting response to chemotherapy in the TN group, compared to others subtypes. MRI underestimates residual disease in Luminal cancers.

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Author(s): Bansal Gaurav Jyoti

Keywords

Breast cancer, Magnetic resonance imaging, Neoadjuvant chemotherapy, Residual tumour size, Breast cancer, Magnetic resonance imaging, Neoadjuvant chemotherapy, Residual tumour size

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