Diagnostic Value of Breast MRI and Nomogram After Negative Axillary Ultrasound For Predicting Axillary Lymph Node Metastasis in Patients with Clinically T1-2 N0 Breast Cancer

Author:

Song Sung Eun1,Cho Kyu Ran1ORCID,Cho Yongwon1,Jung Seung Pil1,Park Kyong-Hwa1,Woo Ok Hee2,Seo Bo Kyoung3

Affiliation:

1. Korea University Anam Hospital

2. Korea University Guro Hospital

3. Korea University Ansan Hospital

Abstract

Abstract Purpose: To assess the false negative result (FNR) of axillary ultrasound (AUS), the rate of high nodal burden (HNB) in clinically T1-2 N0 breast cancer patients, and the diagnostic performance of breast MRI and nomogram. Methods: We identified 948 consecutive patients with clinically T1-2 N0 cancers who had negative AUS, subsequent MRI, and breast conserving therapy between 2013 and 2020 from two tertiary medical centers of Korea University, Seoul, Korea. Patients from two centers were assigned to development and validation sets, respectively. Using logistic regression analyses, clinical- imaging factors associated with LN metastasis were analyzed in the development set from which nomogram was created. The performance of MRI and nomogram was assessed. HNB was defined as ≥3 positive LNs. Results: Among 948 patients, 402 (mean age ± standard deviation, 57.61 ± 11.58) were within development cohort and 546 (54.43 ± 10.02) within validation cohort. The FNR of AUS was 20.1% (81 of 402) and 19.2% (105 of 546) and the rates of HNB were 1.2% (5/402) and 2.2% (12/546), respectively. Clinical and imaging features associated with LN metastasis were progesterone receptor positivity, outer tumor location on mammography, BI-RADS category 5 assessment of cancer on ultrasound, and positive axilla on MRI. The negative predictive value (NPV) of MRI and clinical-imaging nomogram was 86.5% and 82.0%. Conclusions: The FNR of AUS was approximately 20% but the rate of HNB was low. MRI had merit in reaffirming negative AUS. Clinical-imaging nomogram might be helpful to find possible candidates for the omission of SLNB.

Publisher

Research Square Platform LLC

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