Investig Magn Reson Imaging.  2022 Jun;26(2):135-149. 10.13104/imri.2022.26.2.135.

MRI Features for Prediction Malignant Intra-Mammary Lymph Nodes: Correlations with Mammography and Ultrasound

Affiliations
  • 1Department of Radiology, Uijeongbu St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Uijeongbu, Korea
  • 2Department of Radiology, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul, Korea

Abstract

Purpose
To assess clinically significant imaging findings of malignant intramammary lymph nodes (IMLNs) in breast cancer patients and to evaluate their diagnostic performance in predicting malignant IMLN.
Materials and Methods
A total of 110 cases with IMLN of BI-RADS category 3 or more, not typical benign IMLN, in MR of breast cancer patients between January 2016 and January 2021 were retrospectively reviewed. After excluding 33 cases, 77 cases were finally included. Among them, 58 and 19 were confirmed as benign and malignant, respectively. Qualitative and quantitative MR imaging features of the IMLN were retrospectively analyzed. Sizes and final assessment categories of IMLN on MRI, mammography, and ultrasound were reviewed. Diagnostic performances of imaging features on MRI, mammography, and ultrasound were then evaluated.
Results
For qualitative MR features, shape, margin, and preserved central hilum were significantly different between benign and malignant groups (P < 0.05). For quantitative MR features, long diameter over 6 mm, short diameter over 4 mm, and cortical thickening over 3 mm showed high sensitivities in predicting malignant IMLNs (89.5%, 94.7%, and 100%, respectively). Size exceeding 1 cm showed high specificity and accuracy in predicting malignant IMLN on MR, mammography, and ultrasound (91.4% and 80.5%; 96.6% and 79.25; 98.3% and 80.5%, respectively).
Conclusion
Various MR imaging features and size can be helpful for predicting malignant IMLN in breast cancer patients.

Keyword

Breast cancer; Lymph nodes; Lymphatic metastasis; Magnetic resonance imaging
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