scholarly journals Association of Histopathological Parameters and Axillary Lymphnode Metastasis in Primary Breast Carcinoma

2021 ◽  
Vol 6 (4) ◽  
pp. 379-382
Author(s):  
Manjula K Purushotham ◽  
Pradeep Mitra Venkatesh
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Tumor Size ◽  
Axillary Lymph Node ◽  
Inflammatory Infiltrate ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph ◽  
Node Metastasis ◽  
T Stage ◽  
Common Malignancy

Introduction: The most common malignancy worldwide among females is breast carcinoma and the second most common malignancy in India, next to cervical cancer. A wide range of potential prognostic features have been studied in breast cancer and are mainly divided into two groups i.e. Histopathological and Molecular. The histological features are cost-effective and provide reliable diagnostic and prognostic information in these tumors. Axillary Lymph node status is one of the most important prognostic factors and greatly affects the morbidity and mortality of the patient. Materials and Methods: All breast cancer specimens received in the Department of Pathology over a period of five years. The following histopathological parameters were carefully studied like Tumor size, Histological type, Grade, Presence of necrosis, Inflammatory cell infiltrate, Lymphatic invasion, Blood vessel invasion, Perineural invasion, and other Stromal changes were studied in detail, and association of these histopathological parameters with axillary lymph node metastasis were analyzed. Results: A total of 100 cases were studied, and most of the patients were over the age of 50. The maximum number of cases was in the T2 stage (55%). Infiltrating ductal carcinoma (88%) was the most common type of tumor encountered in the study. The majority of the cases were Grade I tumors. Skin Invasion was seen in 14% and Lymphovascular Invasion was seen in 17% of cases respectively. There was a statistically significant association between the size of the tumor, T stage, Grade of the tumor, necrosis, and inflammatory infiltrate on further analysis. Conclusion: There was a statistically significant correlation between Tumor size, pathological T stage, Grade of the tumor, Necrosis and inflammatory infiltrate with axillary Lymph node metastasis in the present study. Increased tumor size, T stage, higher grade, presence of necrosis and low inflammatory infiltrate are associated with increased axillary Lymph node metastasis.

Relationship of Ki67 to tumor size and lymph node metastasis in breast cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. e21076-e21076
Author(s):  
Ioana Bonta ◽  
Dacian Bonta ◽  
Michelle Marie Loch ◽  
Ann Eapen ◽  
Rita A. Blanchard
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Tumor Size ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph ◽  
Ki67 Index ◽  
Axillary Lymph Node Metastases ◽  
Node Metastasis

e21076 Background: Ki67, a tumor proliferation marker, has demonstrated usefulness in breast cancer prognosis. Prior work with BrdU labeling for cell proliferation in breast cancer has not settled the question whether cell proliferation labeling is independent of other tumor features like tumor size and presence of axillary metastases, see Rew (1992) vs. Thor et al (1999). Methods: We analyzed retrospectively our database of 379 patients for correlation between the and tumor size, presence of axillary lymph node metastases and the percentage of Ki67 positve cells. We used linear and parabolic regression to correlate tumor size with the Ki67 index and receiver operator characteristics curve to correlate the presence of axillary lymph node metastases with the Ki67 index. Results: A very weak linear relationship was detected between tumor size and Ki67 index. The R-squared coefficient was 0.03, indicating that tumor size explained only 3% of the variability in measured Ki67 indexes. The ROC analysis, looking at the correlation between Ki67 and lymph node metastasis, yielded an area under the curve (Az) of 0.53. This indicates a very weak correlation. No relationship between axillary lymph node metastasis would yield an Az of 0.5 and a perfect correlation would yield an Az of 1. Conclusions: Tumor size and axillary lymph node metastasis explain less than 10% of observed Ki67 index variability. Therefore, in breast cancer, the prognostic value of Ki67 is additive to that of tumor size and lymph node involvement.

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.

IV-DSA is a new diagnostic tool for axillary lymph node metastasis in breast cancer patients

2004 ◽  
Vol 87 (2) ◽  
pp. 75-79 ◽  
Author(s):  
Osamu Watanabe ◽  
Tadao Shimizu ◽  
Hiroshi Imamura ◽  
Jun Kinoshita ◽  
Yoshihito Utada ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Cancer Patients ◽  
Diagnostic Tool ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph ◽  
Breast Cancer Patients ◽  
Node Metastasis
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