Predicting axillary response to neoadjuvant chemotherapy: the role of diffusion weighted imaging

Author:

Graña-López Lucia12ORCID,Pérez-Ramos Tania1,Maciñeira Fiz Andrés1,Villares Ángeles12,Vázquez-Caruncho Manuel12

Affiliation:

1. Department of Radiology, Hospital Lucus Augusti Lugo. Ulises Romero 1, Lugo, Spain

2. Breast Pathology Group, Hospital Universitario Lucus Augusti-IDIS, Ulises Romero 1, Lugo, Spain

Abstract

Objective: The aim of this study is to investigate whether the primary tumour response to neoadjuvant chemotherapy (NAC), based on the increase in the ADC-values (apparent diffusion coefficient) within the breast lesion, could help to predict axillary complete response. Methods: We retrospectively included 74 patients who were treated with NAC followed by surgery at Lucus Augusti Hospital between January 2015 and September 2020. Simple logistic regression was used to evaluate the factors associated with axillary pathological complete response, including the changes in breast tumour ADC-values due to the treatment. Results: Axillary complete response was correlated with negative oestrogen receptor status, Her2 positivity and response of primary tumour. It was achieved in 31% of the patients. In addition, the increase in the tumour ADC-values with NAC was higher for responders. Among the tumours that demonstrated an increase in ADC-value >0.92 ×10−3 mm2/s, 42.8% (15/35) showed axillary complete response. Eight (20.5%) breast cancers with an increase in ADC below the cut-off value were found to have no metastatic nodes after treatment (p = 0.038). Conclusion: Our results suggest that the performance of models predicting axillary response to NAC can be improved by adding the tumour response determined also using diffusion-weighted imaging. Advances in knowledge: For the fist time, we investigate the relation between tumour response to NAC, assessed using diffusion-weighted imaging, and axillary pathologic complete response.

Publisher

British Institute of Radiology

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

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