Axillary Lymph Node Metastasis Research Articles

Construction and validation of a nomogram prediction model for axillary lymph node metastasis of cT1 invasive breast cancer.

Based on the ultrasonic characteristics of the breast mass and axillary lymph nodes as well as the clinicopathological information, a model was developed for predicting axillary lymph node metastasis in cT1 breast cancer, and relevant features associated with axillary lymph node metastasis were identified. Our retrospective study included 808 patients with cT1 invasive breast cancer treated at the Second Affiliated Hospital and the Cancer Hospital Affiliated with Harbin Medical University from February 2012 to August 2021 (250 cases in the positive axillary lymph node group and 558 cases in the negative axillary lymph node group). We allocated 564 cases to the training set and 244 cases to the verification set. R software was used to compare clinicopathological data and ultrasonic features between the two groups. Based on the results of multivariate logistic regression analysis, a nomogram prediction model was developed and verified for axillary lymph node metastasis of cT1 breast cancer. Univariate and multivariate logistic regression analysis indicated that palpable lymph nodes (P = 0.003), tumor location (P = 0.010), marginal contour (P < 0.001), microcalcification (P = 0.010), surrounding tissue invasion (P = 0.046), ultrasonic detection of lymph nodes (P = 0.001), cortical thickness (P < 0.001) and E-cadherin (P < 0.001) are independently associated with axillary lymph node metastasis. Using these features, a nomogram was developed for axillary lymph node metastasis. The training set had an area under the curve of 0.869, while the validation set had an area under the curve of 0.820. Based on the calibration curve, the model predicted axillary lymph node metastases were in good agreement with reality (P > 0.05). Nomogram's net benefit was good based on decision curve analysis. The nomogram developed in this study has a high negative predictive value for axillary lymph node metastasis in invasive cT1 breast c ancer. Patients with no axillary lymph node metastases can be accurately screened using this nomogram, potentially allowing this group of patients to avoid invasive surgery.

Lymphovascular invasion is an independent prognostic factor in breast cancer irrespective of axillary node metastasis and molecular subtypes.

Lymphovascular invasion (LVI) is a well-known poor prognostic factor for early breast cancer. However, the effect of LVI on breast cancer subtype and node status remains unknown. In this study, we aimed to evaluate the clinical significance of LVI on the recurrence and long-term survival of patients with early breast cancer by comparing groups according to the subtype and node status. We retrospectively reviewed the medical records of 4554 patients with breast cancer who underwent breast cancer surgery between January 2010 and December 2017. The primary endpoints were disease-free survival (DFS) and overall survival (OS). Univariate and multivariate analyses were performed to identify prognostic factors related to the DFS and OS according to the nodal status and breast cancer subtype. During a follow-up period of 94 months, the median OS and DFS were 92 and 90 months, respectively. The LVI expression rate was 8.4%. LVI had a negative impact on the DFS and OS, regardless of the lymph node status. LVI was associated with higher recurrence and lower survival in the luminal A, human epidermal growth factor receptor 2-positive, and triple-negative breast cancer subtypes. The Cox proportional hazards model showed that LVI was a significant prognostic factor for both DFS and OS. No correlation has been observed between LVI and the Oncotype Dx results in terms of prognostic value in early breast cancer. LVI is an independent poor prognostic factor in patients with early breast cancer, regardless of the node status and molecular subtype. Therefore, the LVI status should be considered when making treatment decisions for patients with early stage breast cancer; however, further prospective studies are warranted.

Positive predictive value of axillary lymph node cortical thickness and nodal, clinical, and tumor characteristics in newly diagnosed breast cancer patients.

Axillary lymph nodes (LNs) with cortical thickness > 3mm have a higher likelihood of malignancy. To examine the positive predictive value (PPV) of axillary LN cortical thickness in newly diagnosed breast cancer patients, and nodal, clinical, and tumor characteristics associated with axillary LN metastasis. Retrospective review of axillary LN fine needle aspirations (FNAs) performed 1/1/2018-12/31/2019 included 135 axillary FNAs in 134 patients who underwent axillary surgery. Patient demographics, clinical characteristics, histopathology, and imaging features were obtained from medical records. Hypothesis testing was performed to identify predictors of axillary LN metastasis. Cytology was positive in 72/135 (53.3%), negative in 61/135 (45.2%), and non-diagnostic in 2/135 (1.5%). At surgery, histopathology was positive in 84 (62.2%) and negative in 51 (37.8%). LN cortices were thicker in metastatic compared to negative nodes (p < 0.0001). PPV of axillary LNs with cortical thickness ≥ 3mm, ≥ 3.5mm, ≥ 4mm and, ≥ 4.25mm was 0.62 [95% CI 0.53, 0.70], 0.63 [0.54, 0.72], 0.67 [0.57, 0.76] , and 0.74 [0.64, 0.83], respectively. At multivariable analysis, abnormal hilum (OR = 3.44, p = 0.016) and diffuse cortical thickening (OR = 2.86, p = 0.038) were associated with nodal metastasis. In newly diagnosed breast cancer patients, increasing axillary LN cortical thickness, abnormal fatty hilum, and diffuse cortical thickening are associated with nodal metastasis. PPV of axillary LN cortical thickness ≥ 3mm and ≥ 3.5mm is similar but increases for cortical thickness ≥ 4mm. FNA of axillary LNs with cortex < 4mm may be unnecessary for some patients undergoing sentinel LN biopsy.

Primary, Nonmidline, Extragonadal, Immature Teratoma of the Palm with Axillary Nodal Metastasis: A Rare Case Report and Review of Literature

AbstractPrimary, nonmidline, extragonadal germ cell tumors are rare. Numerous hypotheses have been proposed regarding their origin. There is lack of consensus regarding their appropriate management. We report a case of an immature teratoma arising of the left palm. A 36-year-old lady presented with a recurrent left palm swelling. Histopathological features with immunohistochemical evaluation were characteristic of an immature teratoma. Alpha-fetoprotein (AFP) and lactate dehydrogenase (LDH) were elevated. She received preoperative chemotherapy with bleomycin, etoposide, cisplatin (BEP) followed by wide excision of the palm lesion and reconstruction with free latissimus dorsi flap. Postoperatively, two more cycles of BEP were given. Eight months later, she presented with large left axillary mass which showed metastatic deposits of immature teratoma on trucut biopsy. AFP and LDH were mildly elevated. On staging fluorodeoxyglucose-positron emission tomography (FDG-PET), there were no distant metastases. She received two cycles of vinblastine, ifosfamide, and cisplatin (VeIP). Postchemotherapy FDG-PET showed good metabolic response; however, the mass remained morphologically stable. Complete resection of the axillary mass was achieved with resection of a segment of axillary vein and end-to-end reanastomosis. At 12 months of follow-up the patient is disease free. This is the first report of axillary metastases in immature teratoma of the upper extremity. Axilla is a possible site of lymph node metastases in extremity teratoma. Primary extragonadal germ cell tumor should be managed with complete surgical resection and chemotherapy.

Machine Learning-Based Breast Tumor Ultrasound Radiomics for Pre-operative Prediction of Axillary Sentinel Lymph Node Metastasis Burden in Early-Stage Invasive Breast Cancer

The aim of the work described here was to assess the application of ultrasound (US) radiomics with machine learning (ML) classifiers to the prediction of axillary sentinel lymph node metastasis (SLNM) burden in early-stage invasive breast cancer (IBC). In this study, 278 early-stage IBC patients with at least one SLNM (195 in the training set and 83 in the test set) were studied at our institution. Pathologic SLNM burden was used as the reference standard. The US radiomics features of breast tumors were extracted by using 3D-Slicer and PyRadiomics software. Four ML classifiers-linear discriminant analysis (LDA), support vector machine (SVM), random forest (RF) and decision tree (DT)-were used to construct radiomics models for the prediction of SLNM burden. The combined clinicopathologic-radiomics models were also assessed with respect to sensitivity, specificity, accuracy and areas under the curve (AUCs). Among the US radiomics models, the SVM classifier achieved better predictive performance with an AUC of 0.920 compared with RF (AUC = 0.874), LDA (AUC = 0.835) and DT (AUC = 0.800) in the test set. The clinicopathologic model had low efficacy, with AUCs of 0.678 and 0.710 in the training and test sets, respectively. The combined clinicopathologic (C) factors and SVM classifier (C + SVM) model improved the predictive ability with an AUC of 0.934, sensitivity of 86.7%, specificity of 89.9% and accuracy of 91.0% in the test set. ML-based US radiomics analysis, as a novel and promising predictive tool, is conducive to a precise clinical treatment strategy.

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.

Preoperative Role of Superb Microvascular Imaging and Shear-Wave Elastography for Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer.

This study aims to evaluate the role of shearwave elastography (SWE) and superb microvascular imaging (SMI) for preoperative prediction of axillary lymph node metastasis (ALNM) in patients with breast cancer. In a cohort of 214 women with breast cancer, B-Mode ultrasonography (US), SMIvascular-index (SMIvi), and SWE (E-mean, E-ratio) values were recorded before tru-cut biopsy. Axillary fine-needle aspiration biopsy (FNAB) and sentinel lymph node sampling results were collected. Imaging findings and histopathological data were statistically compared. Receiver operating characteristic curve analysis was used to evaluate diagnostic performance. Reverse stepwise logistical regression analysis was conducted. Although ALNM was negative in 111 cases, it was positive in 103 patients. Axillary lymph node metastasis (+) group had larger size (P < 0.001), higher vascularization (SMIvi: 8.0 ± 6.0 versus 5.0 ± 4.3, P < 0.001), and higher elasticity value (E-mean: 129 ± 31 kPa versus 117.3 ± 40 kPa, P = 0.014). Axillary lymph node metastasis was observed statistically more frequently in Her-2 positive cases (P = 0.005). There was no significant difference between other B-mode US findings (P > 0.05), SMI Adler (P = 0.878), and E-ratio (P = 0.212). The most appropriate cutoff value for the prediction of ALNM was 23.5 mm for size, 3.8 for SMIvi, and 138.5 kPa for E-mean. The most sensitive (77%) method was the SMIvi measurement, while the most specific (86%) finding was Her-2 positivity. The combined model (being Her-2 positive, >23.5 cm, and >3.8 SMIvi) increased the specificity (78%), PPV (71%), and accuracy (68%). Although the increased size is a previously studied parameter in predicting the risk of ALNM, Her-2 and data obtained by SWE, and SMI can be used to assist conventional US.

Development of a prognostic nomogram for lymph node positive HR+/HER2- breast cancer patients: a study of SEER database and a Chinese cohort.

The hormone receptor+/human epidermal growth factor receptor 2- (HR+/HER2-) breast cancer (BC) patients account for the largest proportion in all patients and are still at high risk of long-range recurrence. This current study aimed to construct a prognostic nomogram to predict 3-year and 5-year BC-specific survival (BCSS) in HR+/HER2- BC patients with axillary lymph node metastasis. A total of 25,338 HR+/HER2- patients with axillary lymph node-positive BC were enrolled from the Surveillance, Epidemiology and End Results (SEER) database and randomly divided into the training (n=17,738) and validation (n=7,600) cohorts using a ratio of 7:3. Univariate and multivariable Cox regression hazards were used to build a prognostic nomogram based on the training cohort. The nomogram was validated with two independent cohorts. Receiver operating characteristic (ROC) curves and calibration plots were used to evaluate the performance of the model, and Kaplan-Meier survival analyses were applied to test the clinical utility of the risk stratification system. Twelve factors including age, race, marital status, grade, T stage, N stage, radiotherapy, chemotherapy, and metastasis to the bone, brain, lung and liver were identified and incorporated to construct the nomogram (P<0.001). The area under the ROC curve (AUC) values at 3- and 5-year in the training and internal validation sets were 0.800, 0.800, 0.831 and 0.819, respectively, while those of the external set were 0.765 and 0.735, indicating a satisfactory discrimination with our nomogram. The calibration curves showed highly consistent results for the actual and predicted survival probabilities. Furthermore, patients were divided into three risk groups according to the total scores of the nomogram. The risk stratification system accurately differentiated between patients with different BCSS rates. We constructed the first nomogram and corresponding risk stratification system to predict the 3-year and 5-year BCSS for HR+/HER2- patients with lymph node-positive BC, indicating a satisfactory accuracy and clinical application.

Study the technical validity and feasibility of serum HER-2/Neu and its correlation with tissue HER-2 status in female breast cancer patients only

Background: Breast cancer is one of the leading causes of death in women worldwide. The future burden of breast cancer is predicted to increase over 3 million new cases and 1 million deaths in 2040. In India, it is being increasingly diagnosed at a younger age as compared to the west. Human epidermal growth factor receptor 2 (HER-2) transmembrane protein, with a molecular weight 185 kDa, plays a key role in cell growth and its overexpression favors cell proliferation by inhibiting apoptosis. HER-2 extracellular domain, released into blood before appearing into tissue, can be easily detected by enzyme-linked immunosorbent assay (ELISA) using serum. HER-2 has many roles in assisting diagnosis, targeted therapy, and evaluating prognosis. Aims and Objectives: The study aimed to monitor the serum HER-2 level and its correlation with tissue HER-2 status in breast cancer patients. Materials and Methods: We performed a prospective study on technical validity and feasibility of serum HER-2 level by ELISA in breast cancer patients and its correlation with tissue HER-2 status by immunohistochemistry (IHC) method. Results: We found the serum ELISA level was raised and within the reference range in all breast cancer patients. A higher level of serum HER-2 level was seen in high tumor stage, high Nottingham grade, and with axillary lymph node metastasis. Serum HER-2 level was significantly higher in IHC score 3+ as compared to score 2+and 1+. Conclusion: This study concluded that serum HER-2 ELISA is a valid and feasible test. Association of serum HER-2 level with tumor stage; Nottingham grade; and axillary nodal metastasis was significant. The correlation between serum HER-2 and tissue HER-2 was found significant. Thus, serum HER-2 may be used as an early diagnostic and prognostic biomarker to guide in clinical practice.

Is Immediate Lymphatic Reconstruction on Breast Cancer Patients Oncologically Safe? A Preliminary Study

Background: In breast cancer patients receiving axillary lymph node dissection (ALND), immediate lymphatic reconstruction (ILR) with lymphovenous anastomosis is an emerging technique for reducing the risk of arm lymphedema. However, the oncologic safety of surgically diverting lymphatic ducts directly into venules in a node-positive axilla is still a concern of inadvertently inducing metastasis of remaining cancer cells. This study aimed to assess the oncologic safety of ILR. Methods: From January 2020 to January 2022, 95 breast cancer patients received ALND, and 45 of them also received ILR. Patients with recurrent cancer, with follow-up less than 12 months, and with missed data were excluded. Variables were compared between ILR and non-ILR groups, and the outcome of interest was the rate of distant recurrence after follow-up for at least 1 year. Results: Thirty-four patients in the ILR group and 32 patients in the non-ILR group fulfilled the inclusion criteria for analysis. No statistically significant difference was noted between groups in terms of age, body mass index, type of breast surgery, pathologic cancer staging, histologic type and grade of breast cancer, molecular subtypes, frequency of axillary lymph node metastasis, or adjuvant therapy. For the patients receiving follow-up for at least 1 year, no statistically significant difference was found in terms of distant recurrence rates between ILR and non-ILR groups (P = 0.44). Conclusion: For breast cancer patients receiving ALND, ILR with lymphovenous anastomosis is oncologically safe, within an average follow-up period of 21 months.

Dedifferentiated endometrial carcinoma metastasis to axillary lymph node: a case report

BackgroundWe present an unusual case of a left axillary lymph node metastasis from a primary dedifferentiated endometrial carcinoma. This pattern of metastasis is likely the result of circulating tumor cells reaching the node through its arterial blood supply.Case presentationIn this report, a 68-year-old white woman with a dedifferentiated endometrial carcinoma underwent a hysterectomy. She later developed an enlarged axillary lymph node due to metastatic dedifferentiated endometrial carcinoma, treated with chemotherapy and anti-programmed cell death protein 1 immunotherapy resulting in a complete clinical and radiological response.ConclusionA review of the literature reveals the rarity of blood-borne lymph node metastasis, especially with uterine carcinoma. Immunotherapy has shown promising results in the treatment of some subtypes of metastatic uterine carcinoma.

Concordance between Axillary Ultrasound and Sentinel Biopsy in Clinically Node-Negative Early Breast Cancer

Objective: To determine the sensitivity of axillary ultrasound in detecting axillary nodal metastasis in clinically and radiologically uninvolved axillary nodes in early carcinoma breast by comparing with sentinel node biopsy histopathology on frozen section. Study Design: Comparative cross-sectional study Place and Duration of Study: Breast Clinic, CMH, Rawalpindi Pakistan, from Aug 2020 to May 2021. Methodology: Patients included in the study presented with breast cancer lesions with clinically impalpable axillary lymph nodes aged 18-75. Patients with clinically impalpable nodes underwent an ultrasound of the axilla; if suspicious nodes were found, the patient had subsequent axillary node dissection. Sentinel node biopsy (SLNB) was performed on axillary ultrasound in all patients with no suspicious or benign-looking nodes. Histopathological reporting was taken as standard. Lymph nodal status on axillary ultrasound, SLN biopsy and axillary lymph node clearance were documented and analyzed. Results: Twenty-nine patients were included who had benign-looking lymph nodes on axillary ultrasound and underwent sentinel lymph node biopsy. The mean age of the patients was 54.03 ± 7.94. Out of 29 patients, 24(82.8%) patients had negative Sentinel lymph node biopsy, and 5(17.2%) had positive Sentinel lymph node biopsy, who then underwent axillary lymph node dissection. Conclusion: Sentinel lymph node biopsy is the gold standard to determine axillary lymph nodes involved in early carcinoma breast, which seem benign on pre-operative axillary ultrasound.

Cervix uterine Cancer with Axillary and Neck Lymph Node Metastasis: An Unusual Finding

Background: Cervix uterii cancer is the fourth most common female malignancy. It commonly spreads by direct extension or lymphatic dissemination within the pelvis into the regional lymph nodes. Distant lymph node metastasis remains exeptionnal. To our knowledge, synchronous cervical and axillary lymph node metastasis from cervix cancer have never been reported. Here we report a case of cervical and axillary lymph node metastasis from cervix uterii cancer. Case presentation: A 51-year-old woman diagnosed with cervix uterii cancer and treated with cocomitant chemoradiotherapy, presented 8 months after the initial diagnosis multiple round masses located at the left side of her neck. F-18 FDG PET/CT revealed pathological axillary and neck lymph nodes. Histopathology and immunohistochemistry confirmed the metastatic nature of the lymph nodes. the patient underwent lymph node dissection before undergoing chemotherapy, followed by radiotherapy to the affected cervical and axillary lymph nodes. Conclusions: Metastases from the uterine cervix to the neck lymph nodes are extremely uncommon. Lymphatic drainage and the lymph node jump phenomenon can explain the possible mode of cervical cancer tumor cell spread to the neck area. The mechanism of axillary lymph node metastasis from cervix uterii cancer can be explained by the communication between neck lymph nodes and axillary lymph nodes due to the alteration of the centripetal flow causing a retrograd spread. Distant lymph node metastasis in cervix uterii cancer are associated with a poor prognosis.

Axillary Lymph Node Metastasis from Ovarian Carcinoma: A Systematic Review of the Literature.

Axillary lymph node metastasis is a rare stage IV ovarian carcinoma manifestation. This manuscript aims to systematically review the literature regarding axillary lymph node metastasis from ovarian carcinoma. We searched three medical internet databases (PubMed, Scopus, and Web of Science) for relevant articles published until 22 July 2023. Cases describing supraclavicular or intramammary lymph node metastases and concurrent metastasis to the breast were excluded. After applying eligibility/inclusion and exclusion criteria, twenty-one manuscripts describing twenty-five cases were included from the English literature. Data were collected and analyzed regarding demographic, clinical, laboratory, radiological, histopathological, and oncological characteristics. We analyzed the clinical and oncological characteristics of patients with axillary lymph node metastasis from ovarian carcinoma, presented either as an initial diagnosis of the disease or as a recurrent disease. The analysis we performed showed a significant difference only in the serum CA-125 level (p = 0.004) between the two groups. There was no observed difference in womens' survival.

Association of a complete breast cancer pathologic response with axillary lymph node metastasis via neoadjuvant chemotherapy: Results from the CSBrS-012 study.

Association of a complete breast cancer pathologic response with axillary lymph node metastasis via neoadjuvant chemotherapy: Results from the CSBrS-012 study.

Construction of a comprehensive predictive model for axillary lymph node metastasis in breast cancer: a retrospective study

PurposeThe accurate assessment of axillary lymph node metastasis (LNM) in early-stage breast cancer (BC) is of great importance. This study aimed to construct an integrated model based on clinicopathology, ultrasound, PET/CT, and PET radiomics for predicting axillary LNM in early stage of BC.Materials and methods124 BC patients who underwent 18 F-fluorodeoxyglucose (18 F-FDG) PET/CT and whose diagnosis were confirmed by surgical pathology were retrospectively analyzed and included in this study. Ultrasound, PET and clinicopathological features of all patients were analyzed, and PET radiomics features were extracted to establish an ultrasound model (clinicopathology and ultrasound; model 1), a PET model (clinicopathology, ultrasound, and PET; model 2), and a comprehensive model (clinicopathology, ultrasound, PET, and radiomics; model 3), and the diagnostic efficacy of each model was evaluated and compared.ResultsThe T stage, US_BIRADS, US_LNM, and PET_LNM in the positive axillary LNM group was significantly higher than that of in the negative LNM group (P = 0.013, P = 0.049, P < 0.001, P < 0.001, respectively). Radiomics score for predicting LNM (RS_LNM) for the negative LNM and positive LNM were statistically significant difference (-1.090 ± 0.448 vs. -0.693 ± 0.344, t = -4.720, P < 0.001), and the AUC was 0.767 (95% CI: 0.674–0.861). The ROC curves showed that model 3 outperformed model 1 for the sensitivity (model 3 vs. model 1, 82.86% vs. 48.57%), and outperformed model 2 for the specificity (model 3 vs. model 2, 82.02% vs. 68.54%) in the prediction of LNM. The AUC of mode 1, model 2 and model 3 was 0.687, 0.826 and 0.874, and the Delong test showed the AUC of model 3 was significantly higher than that of model 1 and model 2 (P < 0.05). Decision curve analysis showed that model 3 resulted in a higher degree of net benefit for all the patients than model 1 and model 2.ConclusionThe use of a comprehensive model based on clinicopathology, ultrasound, PET/CT, and PET radiomics can effectively improve the diagnostic efficacy of axillary LNM in BC. Trial registration: This study was registered at ClinicalTrials Gov (number NCT05826197) on 7th, May 2023.

Trends in the pre-operative diagnosis and surgical management of axillary lymph node metastases in women with screen-detected breast cancer

AimThe aim of the current study was to investigate time-trends in pre-operative diagnosis and surgical treatment of axillary lymph node metastases in breast cancers detected at screening mammography. MethodsWe included all women who underwent screening mammography in the South of the Netherlands between 2005 and 2020. During a follow-up period of at least two years, data on clinical radiological examinations, biopsy procedures and surgical interventions were obtained. The 15 years of inclusion were divided into five cohorts of three years each. ResultsOf the 4049 women with invasive breast cancer, 22.1 % (896/4049) had axillary lymph node metastasis at pathology (ALN+). Percutaneous axillary biopsy was performed in 39.6 % (355/896) of these women, with the proportions of fine needle aspiration biopsy (FNAB) decreasing from 97.6 % (40/41) in 2005–2007 to 41.6 % (37/89) in 2017–2019 and core needle biopsy (CNB) rising from 2.4 % (1/41) in 2005–2007 to 58.4 % (52/89) in 2017–2019 (P < 0.001). Sensitivity of FNAB and CNB was comparable (77.4 % (188/243, 95%CI = 71%–82 %) versus 82.4 % (103/125), 95%CI = 74%–88 %) (P = 0.26). Pre-operative confirmation of ALN + by percutaneous biopsy ranged from 27.3 % (56/205) in 2011–2013 to 39.0 % (80/205) in 2017–2019, with no significant trend changes over time (P = 0.103). The proportion of ALN + women who underwent axillary lymph node dissection (ALND) decreased from 96.0 % (97/101) in 2005–2007 to 16.6 % (34/205) in 2017–2019 (P < 0.001). ConclusionPre-operative confirmation of axillary lymph node metastasis by ultrasound-guided biopsy did not rise despite the increased use of CNB at the expense of less invasive FNAB. A significant reduction in ALND was observed through the years.

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.

Molybdenum target mammography-based prediction model for metastasis of axillary sentinel lymph node in early-stage breast cancer.

Sentinel lymph node (SLN) status is closely related to axillary lymph node metastasis in breast cancer. However, SLN biopsy has certain limitations due to invasiveness and diagnostic efficiency. This study aimed to develop a model to predict the risk of axillary SLN metastasis in early-stage breast cancer based on mammography, a noninvasive, cost-effective, and potential complementary way. Herein, 649 patients with early-stage breast cancer (cT1-T2) who received SLN biopsy were assigned to the training cohort (n = 487) and the validation cohort (n = 162). A prediction model based on specific characteristics of tumor mass in mammography was developed and validated with R software. The performance of model was evaluated by receiver operating characteristic curve, calibration plot, and decision curve analysis. Tumor margins, spicular structures, calcification, and tumor size were independent predictors of SLN metastasis (all P < .05). A nomogram showed a satisfactory performance with an AUC of 0.829 (95% CI = 0.792-0.865) in the training cohort and an AUC of 0.825 (95% CI = 0.763-0.888) in validation cohort. The consistency between model-predicted results and actual observations showed great Hosmer-Lemeshow goodness-of-fit (P = .104). Patients could benefit from clinical decisions guided by the present model within the threshold probabilities of 6% to 84%. The prediction model for axillary SLN metastasis showed satisfactory discrimination, calibration abilities, and wide clinical practicability. These findings suggest that our prediction model based on mammography characteristics is a reliable tool for predicting SLN metastasis in patients with early-stage breast cancer.