Literature DB >> 23726129

Intraoperative detection of sentinel lymph nodes in breast cancer patients using ultrasonography-guided direct indocyanine green dye-marking by real-time virtual sonography constructed with three-dimensional computed tomography-lymphography.

Shigeru Yamamoto1, Noriko Maeda, Kiyoshi Yoshimura, Masaaki Oka.   

Abstract

PURPOSE: This study aims to determine the utility of ultrasonography (US)-guided direct dye-marking of sentinel lymph nodes (SLNs) by real-time virtual sonography (RVS) constructed with three-dimensional (3D) computed tomography (CT)-lymphography (LG). PATIENTS AND METHODS: We identified SLNs in 258 clinically node-negative breast cancer patients using an RVS system to display in real time a virtual multiplanar reconstruction CT image obtained from CT volume data corresponding to the same cross-sectional image from US. CT volume data were obtained using our original 3D CT-LG, which accurately detects SLNs in breast cancer. We then perform US-guided dye-marking close to SLNs using indocyanine green (ICG). Subsequently, indigo carmine blue dye was injected into the subareolar and peritumoral areas around each primary tumor. All patients underwent SLN biopsy and SLN metastases were examined pathologically.
RESULTS: In all 258 patients, we were able to detect the same SLNs visualized on 3D CT-LG, using the RVS system. We detected ICG close to SLNs in 257 of 258 patients (99.6%) during SLN biopsy. In 25 patients (9%), we failed to follow the blue lymphatic route stained by indigo carmine and SLNs were not stained by indigo carmine, but easily detected SLNs by ICG marking.
CONCLUSION: US-guided direct ICG dye-marking of SLNs using this RVS system seems useful for the detection of SLNs, allowing easy detection of SLNs even when the stained lymphatic route is not followed.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer; Computed tomography; Lymphography; Real-time virtual sonography; Sentinel lymph node

Mesh:

Substances:

Year:  2013        PMID: 23726129     DOI: 10.1016/j.breast.2013.05.001

Source DB:  PubMed          Journal:  Breast        ISSN: 0960-9776            Impact factor:   4.380


  6 in total

Review 1.  Detection of Sentinel Lymph Nodes with Near-Infrared Imaging in Malignancies.

Authors:  Huan-Cheng Zeng; Jia-Lin Hu; Jing-Wen Bai; Guo-Jun Zhang
Journal:  Mol Imaging Biol       Date:  2019-04       Impact factor: 3.488

2.  Use of indocyanine green for detecting the sentinel lymph node in breast cancer patients: from preclinical evaluation to clinical validation.

Authors:  Chongwei Chi; Jinzuo Ye; Haolong Ding; De He; Wenhe Huang; Guo-Jun Zhang; Jie Tian
Journal:  PLoS One       Date:  2013-12-16       Impact factor: 3.240

3.  Minimize the extent and morbidity of axillary dissection for node-positive breast cancer patients: implementation of axillary lymph node dissection based on breast lymphatics level.

Authors:  Qianqian Yuan; Jinxuan Hou; Yukun He; Yiqian Liao; Lewei Zheng; Gaosong Wu
Journal:  BMC Cancer       Date:  2021-03-19       Impact factor: 4.430

4.  Identification of sentinel lymph nodes by contrast-enhanced ultrasonography with Sonazoid in patients with breast cancer: a feasibility study in three hospitals.

Authors:  Kenzo Shimazu; Toshikazu Ito; Kumiko Uji; Tomohiro Miyake; Toyokazu Aono; Kazuyoshi Motomura; Yasuto Naoi; Atsushi Shimomura; Masafumi Shimoda; Naofumi Kagara; Seung Jin Kim; Shinzaburo Noguchi
Journal:  Cancer Med       Date:  2017-08-01       Impact factor: 4.452

5.  A novel somatic mutation of SIN3A detected in breast cancer by whole-exome sequencing enhances cell proliferation through ERα expression.

Authors:  Kenji Watanabe; Shigeru Yamamoto; Syuiti Sakaguti; Keishiro Isayama; Masaaki Oka; Hiroaki Nagano; Yoichi Mizukami
Journal:  Sci Rep       Date:  2018-10-30       Impact factor: 4.379

6.  Network meta-analysis of novel and conventional sentinel lymph node biopsy techniques in breast cancer.

Authors:  C W Mok; S-M Tan; Q Zheng; L Shi
Journal:  BJS Open       Date:  2019-03-25
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.