Axillary Lymph Node Tattooing and Targeted Axillary Dissection in Breast Cancer Patients Who Presented as cN+ Before Neoadjuvant Chemotherapy and Became cN0 After Treatment

2019 ◽  
Vol 19 (3) ◽  
pp. 208-215 ◽  
Author(s):  
Ioannis Natsiopoulos ◽  
Stavros Intzes ◽  
Triantafyllos Liappis ◽  
Konstantinos Zarampoukas ◽  
Thomas Zarampoukas ◽  
...  
2020 ◽  
Author(s):  
Yizhen Zhou ◽  
Lei Zhang ◽  
Zining Jin ◽  
Hailan Yu ◽  
Siyu Ren ◽  
...  

Abstract Background:Axillary ultrasound (AUS) is one of the important bases for evaluating the axillary status of breast cancer patients. And it would be helpful for the reassessment of axillary lymph node status in these patients after neoadjuvant chemotherapy(NAC) and guide the selection of their axillary surgical options.The purpose of this study was to evaluate the diagnostic performance of ultrasound,and to find out the factors related to the outcome of ultrasound.Methods:In this retrospective analysis, 172 patients (one bilateral breast cancer) with breast cancer and clinical positive axillary nodes, were enrolled. After NAC, all patients received mastectomy and axillary lymph node dissection (ALND). AUS was used before and after NAC to assess the axilla status. Results:Of the 173 axillae, 137 (79.19%) had pathological metastasis after NAC. The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of axillary ultrasound in this cohort were 68.21%, 69.34%, 63.89%, 87.96% and 35.38% respectively. Univariate analysis showed that primary axillary lymph node(ALN) short axis, progesterone receptors, hormone receptors, the tumor status after NAC, tumor reduction rate, ALN short axis after NAC, physical examination of axilla after NAC and pN impacted the results of AUS(P = 0.000 ~ 0.040). Multivariate analysis of the above indicators showed that ALN short axis after NAC and pN associated with AUS results independently. Conclusion:AUS can accurately assess axilla status after NAC in most breast cancer patients. If the short axis of ALN≥10mm and AUS negative, SLNB could be chosen. However, AUS cannot detect residual lymph node disease after NAC in a short axis of the ALN <10mm.


2014 ◽  
Vol 29 (4) ◽  
pp. 372-379 ◽  
Author(s):  
Masahiro Sugimoto ◽  
Masahiro Takada ◽  
Masakazu Toi

Nomograms are a standard computational tool to predict the likelihood of an outcome using multiple available patient features. We have developed a more powerful data mining methodology, to predict axillary lymph node (AxLN) metastasis and response to neoadjuvant chemotherapy (NAC) in primary breast cancer patients. We developed websites to use these tools. The tools calculate the probability of AxLN metastasis (AxLN model) and pathological complete response to NAC (NAC model). As a calculation algorithm, we employed a decision tree–based prediction model known as the alternative decision tree (ADTree), which is an analog development of if-then type decision trees. An ensemble technique was used to combine multiple ADTree predictions, resulting in higher generalization abilities and robustness against missing values. The AxLN model was developed with training datasets (n=148) and test datasets (n=143), and validated using an independent cohort (n=174), yielding an area under the receiver operating characteristic curve (AUC) of 0.768. The NAC model was developed and validated with n=150 and n=173 datasets from a randomized controlled trial, yielding an AUC of 0.787. AxLN and NAC models require users to input up to 17 and 16 variables, respectively. These include pathological features, including human epidermal growth factor receptor 2 (HER2) status and imaging findings. Each input variable has an option of “unknown,” to facilitate prediction for cases with missing values. The websites developed facilitate the use of these tools, and serve as a database for accumulating new datasets.


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