Better predictive value of axillary lymph node (ALN) status after systemic therapy for operable HER2-overexpressing breast cancer: A single-institution retrospective study

2016 ◽  
Vol 42 (8) ◽  
pp. 1146-1152 ◽  
Author(s):  
Y. Zhang ◽  
M. Mo ◽  
J.-w. Li ◽  
Y. Zhou ◽  
J. Wu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Retrospective Study ◽  
Systemic Therapy ◽  
Predictive Value ◽  
Axillary Lymph Node ◽  
Axillary Lymph ◽  
Single Institution

Developing and validating deep learning-based heterogeneous model to improve diagnostic performance of ultrasound elastography for axillary lymph node metastasis of early breast cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12583-e12583
Author(s):  
Jian Li ◽  
Cai Nian ◽  
Xie Ze-Ming ◽  
Zhou Jingwen ◽  
Huang Kemin
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Lymph Node ◽  
Early Breast Cancer ◽  
Predictive Value ◽  
Axillary Lymph Node ◽  
Diagnostic Performance ◽  
Ultrasound Elastography ◽  
Axillary Lymph ◽  
Heterogeneous Model

e12583 Background: To improve the performance of ultrasound (US) for diagnosing metastatic axillary lymph node (ALN), machine learning was used to reveal the inherently medical hints from ultrasonic images and assist pre-treatment evaluation of ALN for patients with early breast cancer. Methods: A total of 214 eligible patients with 220 breast lesions, from whom 220 target ALNs of ipsilateral axillae underwent ultrasound elastography (UE), were prospectively recruited. Based on feature extraction and fusion of B-mode and shear wave elastography (SWE) images of 140 target ALNs using radiomics and deep learning, with reference to the axillary pathological evaluation from training cohort, a proposed deep learning-based heterogeneous model (DLHM) was established and then validated by a collection of B-mode and SWE images of 80 target ALNs from testing cohort. Performance was compared between UE based on radiological criteria and DLHM in terms of areas under the receiver operating characteristics curve (AUC), sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for diagnosing ALN metastasis. Results: DLHM achieved an excellent performance for both training and validation cohorts. In the prospectively testing cohort, DLHM demonstrated the best diagnostic performance with AUC of 0.911(95% confidence interval [CI]: 0.826, 0.963) in identifying metastatic ALN, which significantly outperformed UE in terms of AUC (0.707, 95% CI: 0.595, 0.804, P<0.001). Conclusions: DLHM provides an effective, accurate and non-invasive preoperative method for assisting the diagnosis of ALN metastasis in patients with early breast cancer.[Table: see text]

A retrospective study on the clinical and biological prediction of axillary lymph node metastasis in breast cancer

Surgery Today ◽  
1993 ◽  
Vol 23 (7) ◽  
pp. 573-579 ◽  
Author(s):  
Masakuni Noguchi ◽  
Nagayoshi Ohta ◽  
Michael Thomas ◽  
Hirohisa Kitagawa ◽  
Mitsuharu Earashi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Retrospective Study ◽  
Lymph Node Metastasis ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph ◽  
Node Metastasis

Treatment and survival of patients with occult breast cancer with axillary lymph node metastasis: A nationwide retrospective study

2014 ◽  
Vol 110 (3) ◽  
pp. 270-274 ◽  
Author(s):  
Guiyun Sohn ◽  
Byung Ho Son ◽  
Soo Jung Lee ◽  
Eun Young Kang ◽  
Sung Hoo Jung ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Retrospective Study ◽  
Lymph Node Metastasis ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph ◽  
Occult Breast Cancer ◽  
Node Metastasis

Prognosis and non-sentinel lymph node status of the breast cancer patients with micrometastatic sentinel lymph nodes.

2011 ◽  
Vol 29 (27_suppl) ◽  
pp. 140-140
Author(s):  
M. Takahashi ◽  
H. Jinno ◽  
T. Hayashida ◽  
S. Hirose ◽  
M. Mukai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Cancer Patients ◽  
Systemic Therapy ◽  
Axillary Lymph Node ◽  
Lymph Node Status ◽  
Axillary Lymph ◽  
Breast Cancer Patients ◽  
Significant Difference

140 Background: Sentinel lymph node biopsy (SLNB) is a more sensitive and accurate nodal staging procedure than axillary lymph node dissection (ALND). Because of detailed pathologic evaluation in SLNs, more nodal micrometastases have been identified. However, it remains controversial whether to perform ALND for patients with micrometastases in SLNs and their prognostic significance is also a matter of debate. The purpose of this study is to determine the non-sentinel lymph node (NSLN) status and prognosis of the patients with micrometastatic SLNs. Methods: A prospective database of 1,012 clinically node-negative, T1-T2 breast cancer patients, who underwent SLNB from January 2002 to Dec 2010 at Keio University Hospital was analyzed. SLNs were detected using a combined method of isosulfun blue dye and small-sized technetium-99m-labeled tin colloid. Intraoperative frozen examination was performed with hematoxylin and eosin (HE) staining. SLNs, fixed and embedded in paraffin, were additionally diagnosed with HE staining and immunohistochemical (IHC) analysis. Results: Micrometastases in SLNs were found in 69 (6.8%) of 1,012 patients. Thirty eight (55.1%) of 69 patients with micrometastatic SLNs underwent immediate or delayed ALND and revealed no NSLN metastasis. Among 31 (44.9%) patients with micrometastatic SLNs who omitted ALND and axillary radiation therapy, no axillary lymph node recurrence has been observed after a median follow-up of 50 months, although 29 patients (93.5%) in these 31 patients received adjuvant systemic therapy. There is no significant difference in recurrence free survival between the patients with micrometastatic and negative SLNs (98.0% vs. 95.7%, respectively). Conclusions: These date suggested that it may not be necessary to perform ALND for the patients with micrometastatic SLNs and the presence of micrometastases in SLNs may not worsen prognosis with proper systemic therapy.

Major Reduction in Axillary Lymph Node Dissections After Neoadjuvant Systemic Therapy for Node-Positive Breast Cancer by combining PET/CT and the MARI Procedure

2018 ◽  
Vol 25 (6) ◽  
pp. 1512-1520 ◽  
Author(s):  
M. E. M. van der Noordaa ◽  
F. H. van Duijnhoven ◽  
M. E. Straver ◽  
E. J. Groen ◽  
M. Stokkel ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Systemic Therapy ◽  
Axillary Lymph Node ◽  
Axillary Lymph ◽  
Node Positive ◽  
Neoadjuvant Systemic Therapy ◽  
Pet Ct ◽  
Major Reduction ◽  
Positive Breast Cancer

scholarly journals A Novel High-resolution Dedicated Axillary PET Improve Sensitivity in the Assessment of Regional Nodal Spread of Disease in Early Breast Cancer.

2020 ◽  
Author(s):  
Jingyi Cheng ◽  
Junjie Li ◽  
Guangyu Liu ◽  
Ruohong Shui ◽  
Sheng Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
High Resolution ◽  
Breast Carcinoma ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Axillary Lymph Node ◽  
False Negative ◽  
False Negative Rate ◽  
Axillary Lymph

Abstract Background: The aim of this study was to assess if a novel high-resolution dedicated axillary lymph node Positron Emission Tomography (LymphPET) system could improve sensitivity analysing Lymph Node involvement in early breast carcinoma with clinical N0-N1 stage. Methods: A total of 103 patients with clinical stage of T1-2N0-1M0 breast cancer were evaluated with LymphPET. The maximum single-voxel PET uptake value of Axillary Lymph Node (maxLUV) and the tumor-to-background ratio (TBR) for fat (TBR1) and muscle (TBR2) tissue were calculated. Then, seventy-eight patients with cN0 stage received sentinel lymph node biopsy (SLNB) alone or in combination with ALN dissection (ALND) and 25 patients with cN1 stage underwent fine-needle aspiration (FNA). Results: Ninety-nine invasive breast carcinoma entered this study. The diagnostic sensitivity of LymphPET was 87.80%, specificity was 79.31%, false-negative rate was 12.20%, false-positive rate was 20.69%, positive predictive value was 75.00%, negative predictive value was 90.20%, and accuracy was 82.83%. The maxLUV was superior to TBR1 and TBR2 in the detection of ALN, with 0.27 being the most optimal cutoff value. Conclusion: The 18F-FDG LymphPET could be used to identify and recognize more indolent ALNs of the breast cancer because of more sensitivity and much higher negative predictive value.

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