Axillary Node Status Research Articles

The ratio of lymphocyte/red blood cells and platelets/lymphocytes are predictive biomarkers for lymph node metastasis in patients with breast cancer.

Axillary lymph node metastasis (LNM) affects the progression of breast cancer. However, it is difficult to preoperatively diagnose axillary lymph node status with high sensitivity. Therefore, we hypothesized that platelets/lymphocytes ratio (PLR) and lymphocytes/ red blood cells ratio (LRR) might help in the prognosis of lymph node metastasis in T1-T2 breast cancer. 166 patients (Chang Ning Maternity & Infant Health Institute) were included in our study, and the associations of PLR and LPR with lymph node metastasis were investigated. Peripheral blood was collected one week before the surgery, and the patients were divided into different categories based on their PLR and LRR. The incidence of LNM was significantly increased in the high PLR group (p= 0.002) compared with the low PLR group; LNM was also significantly increased in the low LRR group (p= 0.036) compared with the high LPR group. Further, our study revealed that high PLR (p< 0.001, OR = 4.397, 95% CI = 2.005-9.645), low LRR (p= 0.017, OR = 0.336, 95%CI = 0.136-0.825) and high clinical T stage (p< 0.001, OR = 3.929, 95%CI = 1.913-8.071) are independent predictors of LNM. PLR and LRR could be identified as predictors of LNM in patients with T1/T2 breast cancer.

Non-invasive prediction model of axillary lymph node status in patients with early-stage breast cancer: a feasibility study based on dynamic contrast-enhanced-MRI radiomics.

Accurate axillary evaluation plays an important role in prognosis and treatment planning for breast cancer. This study aimed to develop and validate a dynamic contrast-enhanced (DCE)-MRI-based radiomics model for preoperative evaluation of axillary lymph node (ALN) status in early-stage breast cancer. A total of 410 patients with pathologically confirmed early-stage invasive breast cancer (training cohort, N = 286; validation cohort, N = 124) from June 2018 to August 2022 were retrospectively recruited. Radiomics features were derived from the second phase of DCE-MRI images for each patient. ALN status-related features were obtained, and a radiomics signature was constructed using SelectKBest and least absolute shrinkage and selection operator regression. Logistic regression was applied to build a combined model and corresponding nomogram incorporating the radiomics score (Rad-score) with clinical predictors. The predictive performance of the nomogram was evaluated using receiver operator characteristic (ROC) curve analysis and calibration curves. Fourteen radiomic features were selected to construct the radiomics signature. The Rad-score, MRI-reported ALN status, BI-RADS category, and tumour size were independent predictors of ALN status and were incorporated into the combined model. The nomogram showed good calibration and favourable performance for discriminating metastatic ALNs (N + (≥1)) from non-metastatic ALNs (N0) and metastatic ALNs with heavy burden (N + (≥3)) from low burden (N + (1-2)), with the area under the ROC curve values of 0.877 and 0.879 in the training cohort and 0.859 and 0.881 in the validation cohort, respectively. The DCE-MRI-based radiomics nomogram could serve as a potential non-invasive technique for accurate preoperative evaluation of ALN burden, thereby assisting physicians in the personalized axillary treatment for early-stage breast cancer patients. This study developed a potential surrogate of preoperative accurate evaluation of ALN status, which is non-invasive and easy-to-use.

Application of parametric survival analysis to women patients with breast cancer at Jimma University Medical Center

Public health systems in both industrialized and undeveloped countries continue to struggle with the worldwide problem of breast cancer. In sub-Saharan African countries, notably Ethiopia, it is the form of cancer that strikes women the most commonly. Despite the extreme difficulties, the causes of mortality in Ethiopia have not yet been identified. In addition, little study has been done in this area. Therefore, the major objective of this analysis was to pinpoint the factors that were most responsible for the decreased life expectancy of breast cancer patients at the University of Jimma Medical Center. 552 women who had been treated for breast cancer at Jimma University Medical Center between October 2018 and December 2022 were included in this study, which used a retrospective cohort study design and five-year follow-up data. The most frequent and widely used test for comparing the probability of survival curves between several categorical independent variables was the log-rank test. Next, semi-parametric methods for multivariable analysis using the Cox proportional hazards model were used. Furthermore, a parametric strategy that includes fully parametric survival models better achieves the goal of the analysis. Among covariate, age of patient (ϕ = 254.06; 95% CI (3.95, 7.13), P-value = 0.000), patient live in urban (ϕ = 0.84; 95% CI (-0.35,-0.00), P-value = 0.047), preexisting comorbidity (ϕ = 2.46; 95% CI (0.39, 1.41), P-value = 0.001), overweight women cancer patient (ϕ = 0.05; 95% CI(-4.41,-1.57), P-value = 0.000, positive Axillary Node status cancer patient (ϕ = 0.04; 95% CI(-4.45,-1.88), P-value = 0.000), both surgery and chemotropic baseline treatment patient (ϕ = 0.53; 95% CI(-1.12,-0.16), P-value = 0.009) significantly affected the survival of women breast cancer. Age of breast cancer patient, patient education level, place of residence, marital status, pre-existing comorbidity, axillary node status, estrogen receptor, tumor size, body mass index at diagnosis, stage of cancer, and baseline treatment were found to have a significant effect on time to survive for women with breast cancer at the University of Jimma Medical Center, Oromia region, Ethiopia. However, the covariate histologic grade, number of positive lymph nodes involved, and type of hormone used were insignificant to the survival of breast cancer patients.

Factors Predictive of Positive Lymph Nodes for Breast Cancer.

Axillary node status is an important prognostic factor in breast cancer. The primary aim was to evaluate tumor size and other characteristics relative to axillary disease. Single institution retrospective chart review of stage I-III breast cancer patients collected demographic and clinical/pathologic data from 1998-2019. Student's t-test, Chi-squared test (or Fisher exact test if applicable), and logistic regression models were used for testing the association of pN+ to predictive variables. Of 728 patients (mean age 59 yrs) with mean follow up of 50 months, 86% were estrogen receptor +, 10% Her2+, 78% ER+HER2-negative, and 10% triple-negative. In total, 351/728 (48.2%) were pN+ and mean tumor size was larger in pN+ cases compared to pN- cases (mean = 27.7 mm versus 15.5 mm) (p < 0.001). By univariate analysis, pN+ was associated with lymphovascular invasion (LVI), higher grade, Her2, and histology (p < 0.005). Tumor-to-nipple distance was shorter in pN+ compared to pN- (45 mm v. 62 mm; p< 0.001). Age < 60, LVI, recurrence, mastectomy, larger tumor size, and shorter tumor-nipple distance were associated with 3+ positive nodes (p < 0.05). Larger tumor size and shorter tumor-nipple distance were associated with higher lymph node positivity. Age less than 60, LVI, recurrence, mastectomy, larger tumor size, and shorter tumor-nipple distance were all associated with 3+ positive lymph nodes.

A prospective audit to assess the feasibility of sentinel lymph node biopsy and/or low axillary sampling in clinicoradiologically node-negative axilla for early breast carcinoma

Background: Sentinel lymph node (SLN) dissection was designed to minimize side effects of lymph node surgery but still offer outcomes of axillary lymph node dissection. Aims and Objectives: Our study is designed to determine whether SLN resection achieves the same therapeutics outcome as complete axillary dissection but with fewer side effects for node-negative axilla in clinicoradiologically operable breast cancer patients. Materials and Methods: Duration-based prospective observational study was carried out at the General Surgery and Surgical Oncology Department at Government Medical College and Hospital, Aurangabad with a duration of 2 ½ years from July 2019 to January 2022. A total of 36 patients of breast cancers with stages T1-T2, N0 with clinically and radiologically negative axilla from July 2019 to January 2022 duration were included in our study. Results: When the histopathological status of axillary lymph nodes was compared to the histopathology of SLNs it was seen that out of 36 patients, the histopathology of sentinel node was positive in 10 patients (10/36) however the rest of the axilla was positive in 6 cases and negative in 4 cases and the histopathology sentinel node was negative in 26 patients out of 36 cases (26/36) however the rest of the axilla was also negative in 24 cases and positive in 2 cases. Conclusion: SLN biopsy using methylene blue dye alone is a highly reliable and predictable technique to stage the axilla in breast cancer patients as this study shown a low false-negative rate (7.69%). This technique may help to avoid complete axillary lymph node dissection in sentinel node-negative patients thereby minimizing the morbidity of axillary lymph node dissection. This study demonstrates that sentinel node localization is possible with methylene blue dye alone.

Utility of positron emission tomography for determination of axillary metastasis of breast cancer.

The involvement of axillary lymph nodes plays a key role in breast cancer staging. Positron emission tomography is a promising modality for detecting axillary lymph node metastasis. In addition, nomograms are used to predict the status of axillary lymph nodes. In this study, the role of positron emission tomography in determining axillary metastasis and its correlation with the nomogram was evaluated. The axillary maximum standard uptake value (SUVmax) values of the patients in the preoperative period, the features in the perioperative and postoperative specimen and Memorial Sloan Kettering Cancer Center nomogram data were evaluated. As axillary SUVmax detected by Positron emission tomography in the preoperative period increased, so did the likelihood of lymph node involvement. Axillary SUVmax value were compared with Memorial Sloan Kettering Cancer Center nomogram data but no correlation was found. Age, lymph node number, histopathology results, mass diameter, presence or absence of lymphovascular invasion and/or perineural invasion, tumor type, estrogen receptor status, Ki67 and Cerb-B2 statuses were not correlated. However, axillary SUVmax was inversely correlated with grade and progesterone receptor status. Results from positron emission tomography of axillary lymph nodes in breasts cancer patients showed that SUVmax was only inversely related to cancer grade and progesterone receptor status while not correlating with other accepted parameters for tumor assessment. Thus there is insufficient reliability for the use of axillary SUVmax alone for accurate assessment of tumor characteristics at present.

Breast Edema of Early-stage Invasive Ductal Carcinoma: Correlation with Axillary Lymph Node Metastasis and Clinical-pathological Characteristics.

This study aimed to evaluate the association of different patterns of breast edema and clinical-pathological features and axillary lymph node (ALN) status in early invasive ductal carcinoma (IDC) for simple and readily available assessment and to guide surgeons to perform sentinel lymph node biopsy for selected patients. This retrospective analysis involved 207 individuals with clinical T1-T2 stage IDC. The clinical-pathological features of the patients were compared with different breast edema and ALN statuses. Independent risk factors for ALN metastasis were verified using multivariate logistic regression analysis. ALN metastasis was confirmed in 100 of 207 patients (48.3%) with early-stage IDC. Significant differences were found between different ALN states for tumour size, clinical T stage, and breast edema (P <0.05). The clinical T2 stage (odds ratio-1.882, p=0.043) and moderate to severe edema (odds ratio-10.869, p=0.004) were independent risk factors for ALN metastasis. Moreover, better prognostic factors, including smaller tumour size, lower Ki-67 index and histologic grade, luminal A subtype, and lower incidence of lymph node metastasis, were more frequently found in patients with no breast edema (p<0.05). Breast edema can be considered a promising feature to improve the predictive performance of pathological ALN status in patients with early-stage breast cancer and thus may contribute to preoperative treatment planning.

The use of axillary ultrasound (AUS) to assess the nodal status after neoadjuvant chemotherapy (NACT) in primary breast cancer patients

IntroductionAxillary Ultrasound (AUS) is standard for pre-therapeutic axillary staging in early breast cancer patients. 35–75 % of the breast cancer (BC) patients with positive axillary lymph nodes receiving neoadjuvant chemotherapy (NACT) convert to pathological node negative. For those patients, axillary surgery after NACT could be de-escalated, if an accurate prediction of the pathologic nodal status following NACT was possible. This study aims to answer the question, whether AUS can be used as a reliable diagnostic tool for restaging of axillary nodal status after NACT. Patients and methodsWe collected data of 96 patients with nodal positive primary breast cancer who received NACT between 2009 and 2015 at the Breast Cancer Center of the University Hospital Ulm. Patients were classified as node negative or positive by AUS after NACT (ycN + or ycN0) and the results were compared to the pathological result obtained after axillary lymph node dissection (ypN + vs ypN0) in all patients. Results58.3 % of the patients had pathological complete remission of axillary lymph nodes after NACT (ypN0). The sensitivity and specificity of AUS were 57.5 % and 78.6 %, respectively. The FNR was 42.5 %. The Positive and Negative Predictive Values (PPV and NPV) were 65.7 % and 72.1 %, respectively. The accuracy of AUS was 69.8 % and not associated with any of the investigated clinico-pathological parameters. ConclusionAUS alone is not accurate enough to replace surgical restaging of the axilla after NACT in initially node positive breast cancer patients.

The effect of prolonged neoadjuvant endocrine therapy on the efficacy of treatment with breast cancer.

At present, there is no consensus on the required duration of neoadjuvant endocrine therapy (NET), yet there is no consistent conclusion on the factors influencing the efficacy of treatment with breast cancer after prolonged treatment. To explore the effect of prolonged NET on the efficacy of patients with breast cancer and analyze the factors influencing the efficacy of treatment with breast cancer after the treatment duration is prolonged. The case histories of 51 patients who were diagnosed with breast cancer and received NET in our hospital from September 2017 to December 2021 were retrospectively analyzed. All patients received NET for over 12 months. The clinical efficacy and tumor size changes after treatment for six months and 12 months were compared, and the factors influencing the efficacy of treatment with breast cancer after patients' treatment duration was prolonged were analyzed. (1) Among the 51 patients, the objective remission rate (ORR) of NET, at T = 6 months was 21.6%, and the average tumor size was 15.52 ± 7.30 mm. The ORR of the NET at T = 12 months was 52.9%, and the average tumor size was 13.79 ± 7.43 mm. (2) After the treatment duration was prolonged, the clinical ORRs of patients with estrogen receptor (ER) (+) and progesterone receptor (PR) (+) were significantly higher than that of patients with ER (+) and PR (-) and patients with ER (-) and PR (+), which was (P < 0.05). (3) There was no significant difference between the patients' axillary lymph node status and the Ki67 expression before treatment and the clinical ORR after prolonged treatment, which was (P> 0.05). (1) Prolonging the NET duration for patients with breast cancer can improve their clinical ORR and further reduce the tumor size, but patients' conditions should be closely monitored during the treatment process to prevent the progression of disease due to drug resistance. (2) The expression state of ER or PR may be used as a factor influencing the efficacy of treatment with breast cancer after prolonged treatment. (3) There was no significant effect on the patients' axillary lymph node status and the Ki67 expression before treatment on the clinical efficacy after prolonged treatment.

Conservative Axillary Surgery May Prevent Arm Lymphedema without Increasing Axillary Recurrence in the Surgical Management of Breast Cancer.

Axillary lymph node dissection (ALND) has been associated with postoperative morbidities, including arm lymphedema, shoulder dysfunction, and paresthesia. Sentinel lymph node (SLN) biopsy emerged as a method to assess axillary nodal status and possibly obviate the need for ALND in patients with clinically node-negative (cN0) breast cancer. The majority of breast cancer patients are eligible for SLN biopsy only, so ALND can be avoided. However, there are subsets of patients in whom ALND cannot be eliminated. ALND is still needed in patients with three or more positive SLNs or those with gross extranodal or matted nodal disease. Moreover, ALND has conventionally been performed to establish local control in clinically node-positive (cN+) patients with a heavy axillary tumor burden. The sole method to avoid ALND is through neoadjuvant chemotherapy (NAC). Recently, various forms of conservative axillary surgery have been developed in order to minimize arm lymphedema without increasing axillary recurrence. In the era of effective multimodality therapy, conventional ALND may not be necessary in either cN0 or cN+ patients. Further studies with a longer follow-up period are needed to determine the safety of conservative axillary surgery.

Radiomic Nomogram for Predicting Axillary Lymph Node Metastasis in Patients with Breast Cancer

The detection of axillary lymph node metastasis (ALNM) in patients with breast cancer is a crucial determinant in the decision-making process for axillary surgery and potential therapies. The objective of this study was to develop and validate a radiomics nomogram that integrates radiomics features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with clinical factors to predict ALNM in patients with breast cancer. A total of 177 patients with breast cancer were randomly divided into a training set (n=123) and a validation set (n=54) using a 7:3 ratio. From the DCE-MRI images, 2818 radiomics features were extracted from the primary tumor and axillary lymph node (ALN). Subsequently, optimal features were selected through the least absolute shrinkage and selection operator algorithmto construct the Radscore. Clinical factors were identified using univariate logistic regression analysis and included in a multivariate logistic regression analysis. Using the Radscore and clinical factors, a radiomics nomogram was developed using the Support Vector Machinemethod. The predicting efficacy of our model was visually appraised utilizing a receiver operator characteristic (ROC) curve, while its clinical application and predictive accuracy were assessed through decision curve analysis (DCA) and calibration curves, respectively. The results revealed Ki67, multifocality, and MRI-reported ALN status as independent risk factors for ALNM. The radiomics nomogram demonstrated good calibration and discrimination with areas under the ROC curve of 0.92 (95% confidence interval [CI], 0.88-0.97) in the training set and 0.90 (95% CI, 0.72-0.90) in the validation set. DCA revealed the clinical usefulness of the radiomics nomogram. The DCE-MRI-based radiomics nomogram is a reliable tool for assessing ALNM in patients with breast cancer.

Assessment of PD-L 1 expression in a tumor improves the accuracy of predicting the risk of regional breast cancer metastases

Background: Improving the accuracy of axillary lymph node (ALN) status assessment and the search for new markers associated with the risk of breast cancer (BC) metastasis continues to be an urgent problem. Aim: To establish the prognostic significance of the expression of PD-L1 in a tumor for assessing the risk of BC metastasis in ALNs. Materials and methods: A retrospective, case‒control cohort study included 158 patients aged 30 to 85 years with newly diagnosed BC. The material for the study was tumor samples obtained by trephine biopsy. The expression of PD-L1 in the tumor was studied on the invasive component of puncture biopsy specimens by immunohistochemistry using PD-L1 polyclonal antibodies. Statistical analysis was performed using Statistica 12.0 software. Receiver operating characteristic (ROC) curves for PD-L1 and Ki67 were constructed to discriminate cases with and without metastases in the ALNs. Univariate and multivariate analyses were performed to establish independent predictors associated with the risk of BC metastasis. A value of p &lt; 0.05 was considered statistically significant. Results: According to the results, independent predictors of a high risk of BC regional metastasis were T2 (OR = 5.81, 95% CI = 1.75–19.35, p = 0.004) and T3-4 (OR = 43.07, 95% CI = 9.31–199.2, p &lt; 0.0001) stages of BC, absence of an intraductal component (OR = 3.68, 95% CI = 1.32–10.33, p = 0.013), presence of lymphovascular invasion (OR = 3.32, 95% CI = 1.34–8.22, p = 0.009), luminal B HER2-positive (OR = 6.82, 95% CI = 1.13–42.26, p = 0.036) and triple negative (OR = 8.52, 95% CI = 1.12–64.89, p = 0.038) molecular biological subtypes of BC, and PD-L1 expression coefficient greater than 1.65 (OR = 6.39, 95% CI = 2.54–16.09, p = 0.0001). Based on the data obtained, an original noninvasive method for assessing a high risk of BC regional metastasis was developed, the sensitivity of which was 80.9%, the specificity - 82.6%, and the accuracy - 85.7%. The area under the curve (AUC) was 0.876 (95% CI = 0.818–0.924, р &lt; 0.0001). Conclusion: The results of the study indicate that the assessment of PD-L1 expression in a tumor can improve the accuracy of predicting the risk of regional BC metastasis.

Concurrent finding of Breast cancer and axillary Lymph nodes in Receptor Positive Patients

Background and Objectives: The most frequent site of disease involvement in breast cancer that has progressed from the initial lesion is the axillary lymph nodes (ALN). There are still no reliable ways to anticipate ALN status prior to surgery, despite sentinel node biopsy being a reliable means of managing ALN. Materials and Methods: This was a retrospective study of female patients with invasive breast cancer at Tertiary care hospital between January 2020 and January 2023. The clinical data and tumor character­istics for all invasive breast cancers (425) had been collected in breast cancer database. This study was approved by the institu­tional review board and ethics committee. Breast cancer patients who had undergone surgery were identified. The exclusion criteria were: 1) ductal carcinoma in situ; 2) neoadjuvant therapy; 3) bilateral invasive breast cancer; and 4) patients without breast-conserving surgery with ALND or sentinel lymph node sampling or modified radical mastectomy. SVM was used for analysis. Results: Of these, 242 patients had positive ALNM. The mean tumor size was 24.4 mm (SD=1.5); 38% of the patients had T1 tumors (＜20 mm), followed by 52% with T2 tumors and 10% with T3 tumors. The histology grade was predominantly grade II (57%), with 28% grade III and 15% grade I tumors. Lymph vascular invasion was found in 200 patients (47%). The ER/PR/HER2 profile showed 270 patients (63.5%) had luminal A type tumors, followed by 16.5% with triple-negative tumors, 13.1% with luminal B type tumors, and 6.9% with HER2-positive tumors. A higher AUC value indicated a better diagnostic perfor­mance. The AUC value of this study was 0.754 by SVM. Conclusion: It is possible to forecast ALN status using a model that is just dependent on clinically common pathologic data derived from the source tumor. This could support the surgeon's decision-making for ALN management and breast cancer counseling.

Ultrasound radiomics based on axillary lymph nodes images for predicting lymph node metastasis in breast cancer.

To determine whether ultrasound radiomics can be used to distinguish axillary lymph nodes (ALN) metastases in breast cancer based on ALN imaging. A total of 147 breast cancer patients with 41 non-metastatic lymph nodes and 109 metastatic lymph nodes were divided into a training set (105 ALN) and a validation set (45 ALN). Radiomics features were extracted from ultrasound images and a radiomics signature (RS) was built. The Intraclass correlation coefficients (ICCs), Spearman correlation analysis, and least absolute shrinkage and selection operator (LASSO) methods were used to select the ALN status-related features. All images were assessed by two radiologists with at least 10 years of experience in ALN ultrasound examination. The performance levels of the model and radiologists in the training and validation subgroups were then evaluated and compared. Radiomics signature accurately predicted the ALN status, achieved an area under the receiver operator characteristic curve of 0.929 (95%CI, 0.881-0.978) and area under curve(AUC) of 0.919 (95%CI, 95%CI, 0.841-0.997) in training and validation cohorts respectively. The radiomics model performed better than two experts' prediction of ALN status in both cohorts (P<0.05). Besides, prediction in subgroups based on baseline clinicopathological information also achieved good discrimination performance, with an AUC of 0.937, 0.918, 0.885, 0.930, and 0.913 in HR+/HER2-, HER2+, triple-negative, tumor sized ≤ 3cm and tumor sized>3 cm, respectively. The radiomics model demonstrated a good ability to predict ALN status in patients with breast cancer, which might provide essential information for decision-making.

Simultaneous 18F-FDG PET/MRI Radiomics and Machine Learning Analysis of the Primary Breast Tumor for the Preoperative Prediction of Axillary Lymph Node Status in Breast Cancer.

In this prospective study, 117 female patients (mean age = 53 years) with 127 histologically proven breast cancer lesions (lymph node (LN) positive = 85, LN negative = 42) underwent simultaneous 18F-FDG PET/MRI of the breast. Quantitative parameters were calculated from dynamic contrast-enhanced (DCE) imaging (tumor Mean Transit Time, Volume Distribution, Plasma Flow), diffusion-weighted imaging (DWI) (tumor ADCmean), and PET (tumor SUVmax, mean and minimum, SUVmean of ipsilateral breast parenchyma). Manual whole-lesion segmentation was also performed on DCE, T2-weighted, DWI, and PET images, and radiomic features were extracted. The dataset was divided into a training (70%) and a test set (30%). Multi-step feature selection was performed, and a support vector machine classifier was trained and tested for predicting axillary LN status. 13 radiomic features from DCE, DWI, T2-weighted, and PET images were selected for model building. The classifier obtained an accuracy of 79.8 (AUC = 0.798) in the training set and 78.6% (AUC = 0.839), with sensitivity and specificity of 67.9% and 100%, respectively, in the test set. A machine learning-based radiomics model comprising 18F-FDG PET/MRI radiomic features extracted from the primary breast cancer lesions allows high accuracy in non-invasive identification of axillary LN metastasis.

Radiomics nomogram for predicting axillary lymph node metastasis-a potential method to address the limitation of axilla coverage in cone-beam breast CT: a bi-center retrospective study.

Cone-beam breast CT (CBBCT) has an inherent limitation that the axilla cannot be imaged in its entirety. We aimed to develop and validate a nomogram based on clinical factors and contrast-enhanced (CE) CBBCT radiomics features to predict axillary lymph node (ALN) metastasis and complement limited axilla coverage. This retrospective study included 312 patients with breast cancer from two hospitals who underwent CE-CBBCT examination in a clinical trial (NCT01792999) during 2012-2020. Patients from TCIH comprised training set (n = 176) and validation set (n = 43), and patients from SYSUCC comprised external test set (n = 93). 3D ROIs were delineated manually and radiomics features were extracted by 3D Slicer software. RadScore was calculated and radiomics model was constructed after feature selection. Clinical model was built on independent predictors. Nomogram was developed with independent clinical predictors and RadScore. Diagnostic performance was compared among three models by ROC curve, and decision curve analysis (DCA) was used to evaluate the clinical utility of nomogram. A total of 139 patients were ALN positive and 173 patients were negative. Twelve radiomics features remained after feature selection. Location and focality were selected as independent predictors for ALN status. The AUC of nomogram in external test set was higher than that of clinical model (0.80 vs. 0.66, p = 0.012). DCA demonstrated that the nomogram had higher overall net benefit than that of clinical model. The nomogram combined CE-CBBCT-based radiomics features and clinical factors could have potential in distinguishing ALN positive from negative and addressing the limitation of axilla coverage in CBBCT.

Using MammaPrint on core needle biopsy to guide the need for axillary staging during breast surgery

BackgroundAt present, the only opportunity to omit axillary staging is with Choosing Wisely criteria for women ages >70 y with cT1 2N0 estrogen receptor–positive/human epidermal growth factor receptor 2–negative breast cancer. However, many women are diagnosed when pathologic node status–negative, raising the question of additional opportunities to omit sentinel lymph node biopsy. We sought to investigate the association between MammaPrint, a genomic test that estimates estrogen receptor–positive breast cancer recurrence risk, and pathologic node status, with the aim that low-risk MammaPrint could be considered for omission of sentinel lymph node biopsy if associated with pathologic node status–negative. MethodsA single-institution database was queried for all women with cT1 2N0 estrogen receptor–positive/human epidermal growth factor receptor 2–negative invasive breast cancer with breast surgery as their first treatment and MammaPrint performed from 2020 to 2021. Patient and tumor factors, including MammaPrint score, were compared with axillary node status for correlation. ResultsA total of 668 women met inclusion criteria, with a median age of 66 y. MammaPrint was low-risk luminal A in 481 (72%) and high-risk luminal B in 187 (28%). At the time of breast surgery, 588 (88%) had sentinel lymph node biopsy, 27 (4%) had axillary lymph node dissection, and 53 (7.9%) had no axillary staging. Most women in both the pathologic node status–negative and pathologic node status–positive cohorts had low-risk MammaPrint (355 [73.3%] pathologic node status–negative vs 91 [69.5%] pathologic node status–positive), and women with low-risk MammaPrint did not have a significantly lower risk of pathologic node status–positive (P = .377). ConclusionLow-risk MammaPrint does not predict lower risk of pathologic node status–positive breast cancer. Based on our results, genomic testing does not appear to provide additional personalization for the ability to omit sentinel lymph node biopsy for patients outside of the Choosing Wisely guidelines.

Assessment of breast cytoarchitecture and its associated axillary lymph node status under normal and pathological conditions in Egyptian women

ObjectiveHerein, we compare the features of neoplastic cancer cells in invasive ductal carcinoma (IDC) grade II and III patients to their corresponding normal cells both in breast and axillary lymph node (ALN) tissues. MethodsA retrospective cohort of 70 female breast cancer patients enrolled between 2018 and 2020 at Medical Research Institute, Alexandria University, Egypt, was analyzed for clinicopathological features presentation. Fresh tiny pieces of breast tissue and its associated ALN tissues were then processed to investigate the morphological appearance by scanning electron microscopy. Moreover, the histological architecture of tissue sections stained with hematoxylin and eosin was studied by light microscope, while the characterization of the ultrastructure features of breast and ALN tissues was analyzed by transmission electron microscopy. ResultsClinicopathological presentation of patients revealed that the Egyptian female breast cancer population adhered to the global trends of breast cancer disease with elevated incidence rate among postmenopausal women (61.3%), high frequency of IDC (95.7%), and increased ALN metastasis (65.7%). The percentage of estrogen receptor alpha (ERα) and human epidermal growth factor receptor 2 (HER2) expression, as key indicators for carcinogenesis and disease progression was 87.1% and 55.8%, respectively. The present study points to the observed discrepancies among the investigated variables in the diagnostic separation between IDC grade II and grade III. Ductal epithelial cells organization, nuclei size and irregularity, chromatin amount and uniformity, mitochondrial abundance and dysfunction were differentially manifested in IDC grades. Moreover, aberrations in the cellular organelles like lysosomes, endoplasmic reticulum, and lipid droplets vary according to the grade of IDC and the aggressiveness of the invasive breast cancer. ConclusionsTo sum up, this study emphasizes the importance of accurate specimen evaluation for treatment choice and decision.

A Study on Prognostic Factors in Management of Breast Carcinoma in A Tertiary Care Hospital

Breast cancer is the most common malignant tumor and leading cause of death in women worldwide. It accounts for 15% of all cancer deaths According to World Health Organisation (WHO), approximately 70% of breast malignancies occur in women with unknown risk factorsThe prognostic factor can be defined as a measurable variable which correlates with natural history of the disease. The most significant factor which influences prognosis in breast cancer is axillary lymph node involvement, which is usually assessed at time of surgery using sentinel lymph node biopsy or axillary lymph node dissection. The number of lymph nodal involvement is also significant. Involvement of 1-3 lymph nodes carry better prognosis than 4-9 and more than 9 lymph nodes involvement. Size of the tumour has long been recognized as a prognostic factor and as predictor of axillary node status, with larger tumours being associated with a bad prognosis and an increased incidence of nodal metastasis. This study is conducted in Department of General Surgery, SVRRGGH, Sri Venkateswara Medical College, Tirupati for a period of more than one and half year after getting approval from Institutional Ethical Committee on March 2021. A prospective study of 50 patients who fulfilled Inclusion Criteria is taken into consideration to know how prognostic factors like tumor size &amp; grade, axillary lymphnode involvement are influencing the prognosis and management of breast carcinoma. Patients who took part in the study were from 28-68 years of age. Majority of people were in the age group of 46-55 years (38%). Increasing age, involvement of axillary lymph nodes, tumors with larger size and higher grade, and lymphovascular invasions are all associated with worse prognosis Keywords: Estrogen Receptor, Progesterone Receptor, Locally Advanced Breast Carcinoma

A Nomogram to Predict Pathological Axillary Status in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

This study aimed to identify factors influencing axillary pathological complete response (pCR) and to develop a predictive nomogram to evaluate axillary pCR rate in breast cancer patients treated with neoadjuvant chemotherapy (NAC). A total of 2368 patients who received NAC and mastectomy between 2000 and 2014 from 12 grade A tertiary hospitals in China were analyzed retrospectively. The patients treated in three cancer hospitals (training set, n = 1629) were used to construct the nomogram based on multivariate logistic regression analyses. The nomograph was validated by the area under the receiver operating characteristic curve (AUC) and calibration curve in patients from 9 other general hospitals (validation set, n = 739). The nomogram incorporated seven predicting factors including NACT cycles, response to NACT, clinical T stage, clinical N stage, grade, LVI, and molecular subtype. The AUC for the training set and validation set were 0.762 and 0.802, respectively. In addition, the calibration curve also showed good agreement between the nomogram-based predictions and the actual observations. A nomogram was established to predict the status of axillary lymph nodes in breast cancer patients after NAC. The predictive model performed well both in the training set and external validation set.