Metachronous secondary primary occult breast cancer initially presenting with metastases to the contralateral axillary lymph nodes: report of a case

Breast Cancer ◽  
2009 ◽  
Vol 17 (1) ◽  
pp. 71-74 ◽  
Author(s):  
Satoki Kinoshita ◽  
Akio Hirano ◽  
Susumu Kobayashi ◽  
Kazumasa Komine ◽  
Shigeya Kyoda ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Occult Breast Cancer

Occult breast cancer may originate from ectopic breast tissue present in axillary lymph nodes

2018 ◽  
Vol 172 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Mitsuo Terada ◽  
Yayoi Adachi ◽  
Masataka Sawaki ◽  
Masaya Hattori ◽  
Akiyo Yoshimura ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Breast Tissue ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Occult Breast Cancer ◽  
Ectopic Breast Tissue ◽  
Ectopic Breast

scholarly journals Occult primary breast cancer presenting with brachial plexopathy: A case report

2021 ◽  
Vol 9 ◽  
pp. 2050313X2098564
Author(s):  
Karen L Zhao ◽  
Yusha Liu ◽  
Kathryn P Scherpelz ◽  
Dennis S Kao ◽  
Jeffrey B Friedrich
Keyword(s):  
Breast Cancer ◽  
Case Report ◽  
Lymph Nodes ◽  
Primary Breast Cancer ◽  
Unusual Case ◽  
Distant Metastases ◽  
Axillary Lymph Nodes ◽  
Brachial Plexopathy ◽  
Axillary Lymph ◽  
Occult Breast Cancer

Breast cancer affects about one in eight women over the course of her lifetime. Occult breast cancer, in which primary breast cancer is detected without evidence of disease in the breast itself, comprises up to 1% of new diagnoses; this is typically detected from abnormal axillary lymph nodes, and distant metastases are rare. Here, we present an unusual case of occult breast cancer presenting as upper extremity pain, edema, and weakness, with a metastatic mass to the brachial plexus being the only site of disease.

scholarly journals Intra-mammary lymph nodes, an overlooked breast cancer prognostic tool?

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Tarek Hashem ◽  
Ahmed Abdelmoez ◽  
Ahmed Mohamed Rozeka ◽  
Hazem Abdelazeem
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Ductal Carcinoma ◽  
Percutaneous Biopsy ◽  
Preoperative Imaging ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Pathological Features ◽  
Breast Cancer Patients ◽  
Surgical Data

Abstract Background Due to the high variability of incidence and prevalence of intra-mammary lymph nodes (IMLNs), they might be overlooked during clinical and radiological examinations. Properly characterizing pathological IMLNs and detecting the factors that might influence their prevalence in different stages of breast cancer might aid in proper therapeutic decision-making and could be of possible prognostic value. Methods Medical records were reviewed for all breast cancer patients treated at the National Cancer Institute of Cairo University between 2013 and 2019. Radiological, pathological, and surgical data were studied. Results Intra-mammary lymph nodes were described in the final pathology reports of 100 patients. Five cases had benign breast lesion. Three cases had phyllodes tumors and two cases had ductal carcinoma in situ (DCIS). All ten cases were excluded. The remaining 90 cases all had invasive breast cancer and were divided into two groups: one group for patients with malignant IMLNs (48) and another for patients with benign IMLNs (42). Pathological features of the malignant IMLN group included larger mean tumor size in pathology (4.7 cm), larger mean size of the IMLN in pathology (1.7 cm), higher incidence of lympho-vascular invasion (65.9%), and higher rate of extracapsular extension in axillary lymph nodes (57.4%). In addition, the pathological N stage was significantly higher in the malignant IMLN group. Conclusion Clinicians frequently overlook intra-mammary lymph nodes. More effort should be performed to detect them during preoperative imaging and during pathological processing of specimens. A suspicious IMLN should undergo a percutaneous biopsy. Malignant IMLNs are associated with advanced pathological features and should be removed during surgery.

scholarly journals Dedicated Axillary MRI-Based Radiomics Analysis for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 757
Author(s):  
Sanaz Samiei ◽  
Renée W. Y. Granzier ◽  
Abdalla Ibrahim ◽  
Sergey Primakov ◽  
Marc B. I. Lobbes ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Mr Images ◽  
Node Metastasis

Radiomics features may contribute to increased diagnostic performance of MRI in the prediction of axillary lymph node metastasis. The objective of the study was to predict preoperative axillary lymph node metastasis in breast cancer using clinical models and radiomics models based on T2-weighted (T2W) dedicated axillary MRI features with node-by-node analysis. From August 2012 until October 2014, all women who had undergone dedicated axillary 3.0T T2W MRI, followed by axillary surgery, were retrospectively identified, and available clinical data were collected. All axillary lymph nodes were manually delineated on the T2W MR images, and quantitative radiomics features were extracted from the delineated regions. Data were partitioned patient-wise to train 100 models using different splits for the training and validation cohorts to account for multiple lymph nodes per patient and class imbalance. Features were selected in the training cohorts using recursive feature elimination with repeated 5-fold cross-validation, followed by the development of random forest models. The performance of the models was assessed using the area under the curve (AUC). A total of 75 women (median age, 61 years; interquartile range, 51–68 years) with 511 axillary lymph nodes were included. On final pathology, 36 (7%) of the lymph nodes had metastasis. A total of 105 original radiomics features were extracted from the T2W MR images. Each cohort split resulted in a different number of lymph nodes in the training cohorts and a different set of selected features. Performance of the 100 clinical and radiomics models showed a wide range of AUC values between 0.41–0.74 and 0.48–0.89 in the training cohorts, respectively, and between 0.30–0.98 and 0.37–0.99 in the validation cohorts, respectively. With these results, it was not possible to obtain a final prediction model. Clinical characteristics and dedicated axillary MRI-based radiomics with node-by-node analysis did not contribute to the prediction of axillary lymph node metastasis in breast cancer based on data where variations in acquisition and reconstruction parameters were not addressed.

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