scholarly journals Incidental detection of axillary lymph node metastasis from carcinoma breast during technetium-99m methoxyisobutylisonitrile parathyroid scintigraphy

2012 ◽  
Vol 27 (2) ◽  
pp. 133
Author(s):  
BhagwantRai Mittal ◽  
Ashwani Sood ◽  
Sasikumar Arun ◽  
Anish Bhattacharya
2019 ◽  
Vol 6 (8) ◽  
pp. 2889
Author(s):  
Greeshma K. Masthi ◽  
Rohit Krishnappa ◽  
Rajagopalan S.

Background: The aim of this study is to develop a scoring system wherein axillary lymph node metastasis in carcinoma breast can be predicted preoperatively using simple variables.Methods: A prospective study carried out from December 2017-November 2018 at Rajarajeswari Medical College and Hospital. All clinically node negative cases were included. Data from clinical examination, histopathology report and immunohistochemistry (obtained from trucut biopsy preoperatively) is correlated with presence or absence of lymph node metastasis obtained after modified radical mastectomy. And a scoring system is proposed according to the results obtained. Results: Out of 36 cases studied, 12 cases had score <10, 11 cases had score 11-13, 13 cases had score >14, indicating that more than 50% of cases were over treated with axillary lymph node dissection.Conclusions: Lymph node metastasis in carcinoma breast can be predicted clinically using a scoring system. Further a recommendation for or against axillary node dissection can be made according to the respective scores.


2016 ◽  
Vol 34 (15_suppl) ◽  
pp. e18147-e18147
Author(s):  
Amit Choraria ◽  
Sanjit Agrawal ◽  
Aditi Chandra ◽  
Saugata Sen ◽  
Sanjoy Chatterjee ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 757
Author(s):  
Sanaz Samiei ◽  
Renée W. Y. Granzier ◽  
Abdalla Ibrahim ◽  
Sergey Primakov ◽  
Marc B. I. Lobbes ◽  
...  

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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