Incidence of Internal Mammary Nodes in Locally Advanced Breast Cancer and Its Prognostic Significance
Journal Title: GCSMC Journal of Medical Sciences - Year 2016, Vol 5, Issue 2
Abstract
Objective: (1) To determine the incidence of internal mammary nodal disease on computed tomography (CT) in patients with locally advanced breast cancer (LABC). (2)To determine the prognostic significance of internal mammary nodal disease in patients with LABC. Materials and Methods: We retrospectively reviewed our st st database of all locally advanced breast cancer patients coming at our centre from 1 January 2015 to 31 December 2015. The inclusion criteria for this study included all patients with clinical staging of locally advanced breast cancer with their baseline CECT of thorax available on our hospital Picture Archiving and Communication System (PACS). All patients whose images were not available on our PACS or those with metastatic disease on baseline imaging were excluded from the study. These patients were followed up for one year at our centre, GCRI. Results: A total of 405 cases of LABC were registered at our centre during this period. Of this, a total of 148 patients had undergone baseline CT at our centre. Of these, 21 patients had metastatic disease on baseline study and hence, these were excluded. A total of 127 patients were hence enrolled in the study. Of the 127 patients, internal mammary nodes were indentified in a total 0f 53 patients. No nodes were seen in remaining 74 patients. In this study, the incidence of internal mammary nodes (IMNs) on LABC was calculated to be 41.73%. Incidence of metastatic disease in LABC patients on follow up were 19.68 %. Incidence of metastatic disease in LABC patients with IMNs on baseline imaging on follow up was 27.3%. Incidence of metastatic disease in LABC patients, without internal mammary nodes on baseline imaging, on follow up was 14.8 %. Conclusion: We conclude that internal mammary nodes are important prognostic factor in LABC and these should be reported in all cases of breast cancer undergoing cross sectional imaging.
Authors and Affiliations
Himanshu C Soni, Tapan V Varlekar, Mehul Pateliya, Rahil Agrawal, Ankit Sukhadeve
Keywords
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