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Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes

OBJECTIVE: Axillary lymph node management is an important part of breast cancer surgery and the accuracy of preoperative imaging evaluation can provide adequate information to guide operation. Different molecular subtypes of breast cancer have distinct imaging characteristics. This article was aimed...

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Autores principales: Zheng, Mingjie, Huang, Yue, Peng, Jinghui, Xia, Yiqin, Cui, Yangyang, Han, Xu, Wang, Shui, Xie, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326026/
https://www.ncbi.nlm.nih.gov/pubmed/35912264
http://dx.doi.org/10.3389/fonc.2022.762906
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author Zheng, Mingjie
Huang, Yue
Peng, Jinghui
Xia, Yiqin
Cui, Yangyang
Han, Xu
Wang, Shui
Xie, Hui
author_facet Zheng, Mingjie
Huang, Yue
Peng, Jinghui
Xia, Yiqin
Cui, Yangyang
Han, Xu
Wang, Shui
Xie, Hui
author_sort Zheng, Mingjie
collection PubMed
description OBJECTIVE: Axillary lymph node management is an important part of breast cancer surgery and the accuracy of preoperative imaging evaluation can provide adequate information to guide operation. Different molecular subtypes of breast cancer have distinct imaging characteristics. This article was aimed to evaluate the predictive ability of imaging methods in accessing the status of axillary lymph node in different molecular subtypes. METHODS: A total of 2,340 patients diagnosed with primary invasive breast cancer after breast surgery from 2013 to 2018 in Jiangsu Breast Disease Center, the First Affiliated Hospital with Nanjing Medical University were included in the study. We collected lymph node assessment results from mammography, ultrasounds, and MRIs, performed receiver operating characteristic (ROC) analysis, and calculated the sensitivity and specificity of each test. The C-statistic among different imaging models were compared in different molecular subtypes to access the predictive abilities of these imaging models in evaluating the lymph node metastasis. RESULTS: In Her-2 + patients, the C-statistic of ultrasound was better than that of MRI (0.6883 vs. 0.5935, p=0.0003). The combination of ultrasound and MRI did not raise the predictability compared to ultrasound alone (p=0.492). In ER/PR+HER2- patients, the C-statistic of ultrasound was similar with that of MRI (0.7489 vs. 0.7650, p=0.5619). Ultrasound+MRI raised the prediction accuracy compared to ultrasound alone (p=0.0001). In ER/PR-HER2- patients, the C-statistics of ultrasound was similar with MRI (0.7432 vs. 0.7194, p=0.5579). Combining ultrasound and MRI showed no improvement in the prediction accuracy compared to ultrasound alone (p=0.0532). CONCLUSION: From a clinical perspective, for Her-2+ patients, ultrasound was the most recommended examination to assess the status of axillary lymph node metastasis. For ER/PR+HER2- patients, we suggested that the lymph node should be evaluated by ultrasound plus MRI. For ER/PR-Her2- patients, ultrasound or MRI were both optional examinations in lymph node assessment. Furthermore, more new technologies should be explored, especially for Her2+ patients, to further raise the prediction accuracy of lymph node assessment.
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spelling pubmed-93260262022-07-28 Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes Zheng, Mingjie Huang, Yue Peng, Jinghui Xia, Yiqin Cui, Yangyang Han, Xu Wang, Shui Xie, Hui Front Oncol Oncology OBJECTIVE: Axillary lymph node management is an important part of breast cancer surgery and the accuracy of preoperative imaging evaluation can provide adequate information to guide operation. Different molecular subtypes of breast cancer have distinct imaging characteristics. This article was aimed to evaluate the predictive ability of imaging methods in accessing the status of axillary lymph node in different molecular subtypes. METHODS: A total of 2,340 patients diagnosed with primary invasive breast cancer after breast surgery from 2013 to 2018 in Jiangsu Breast Disease Center, the First Affiliated Hospital with Nanjing Medical University were included in the study. We collected lymph node assessment results from mammography, ultrasounds, and MRIs, performed receiver operating characteristic (ROC) analysis, and calculated the sensitivity and specificity of each test. The C-statistic among different imaging models were compared in different molecular subtypes to access the predictive abilities of these imaging models in evaluating the lymph node metastasis. RESULTS: In Her-2 + patients, the C-statistic of ultrasound was better than that of MRI (0.6883 vs. 0.5935, p=0.0003). The combination of ultrasound and MRI did not raise the predictability compared to ultrasound alone (p=0.492). In ER/PR+HER2- patients, the C-statistic of ultrasound was similar with that of MRI (0.7489 vs. 0.7650, p=0.5619). Ultrasound+MRI raised the prediction accuracy compared to ultrasound alone (p=0.0001). In ER/PR-HER2- patients, the C-statistics of ultrasound was similar with MRI (0.7432 vs. 0.7194, p=0.5579). Combining ultrasound and MRI showed no improvement in the prediction accuracy compared to ultrasound alone (p=0.0532). CONCLUSION: From a clinical perspective, for Her-2+ patients, ultrasound was the most recommended examination to assess the status of axillary lymph node metastasis. For ER/PR+HER2- patients, we suggested that the lymph node should be evaluated by ultrasound plus MRI. For ER/PR-Her2- patients, ultrasound or MRI were both optional examinations in lymph node assessment. Furthermore, more new technologies should be explored, especially for Her2+ patients, to further raise the prediction accuracy of lymph node assessment. Frontiers Media S.A. 2022-07-13 /pmc/articles/PMC9326026/ /pubmed/35912264 http://dx.doi.org/10.3389/fonc.2022.762906 Text en Copyright © 2022 Zheng, Huang, Peng, Xia, Cui, Han, Wang and Xie https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Zheng, Mingjie
Huang, Yue
Peng, Jinghui
Xia, Yiqin
Cui, Yangyang
Han, Xu
Wang, Shui
Xie, Hui
Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes
title Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes
title_full Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes
title_fullStr Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes
title_full_unstemmed Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes
title_short Optimal Selection of Imaging Examination for Lymph Node Detection of Breast Cancer With Different Molecular Subtypes
title_sort optimal selection of imaging examination for lymph node detection of breast cancer with different molecular subtypes
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326026/
https://www.ncbi.nlm.nih.gov/pubmed/35912264
http://dx.doi.org/10.3389/fonc.2022.762906
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