Cancer Axillary Lymph Node Metastasis Research Articles

3D reconstruction based novel methods are more effective than traditional clinical assessment in breast cancer axillary lymph node metastasis prediction

The status of axillary lymph node metastases determines the treatment and overall survival of breast cancer (BC) patients. Three-dimensional (3D) assessment methods have advantages for spatial localization and are more responsive to morphological changes in lymph nodes than two-dimensional (2D) assessment methods, and we speculate that methods developed using 3D reconstruction systems have high diagnostic efficacy. This exploratory study included 43 patients with histologically confirmed BC diagnosed at Second Xiangya Hospital of Central South University between July 2017 and August 2020, all of whom underwent preoperative CT scans. Patients were divided into a training cohort to train the model and a validation cohort to validate the model. A 3D axillary lymph node atlas was constructed on a 3D reconstruction system to create various methods of assessing lymph node metastases for a comparison of diagnostic efficacy. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic values of these methods. A total of 43 patients (mean [SD] age, 47 [10] years) met the eligibility criteria and completed 3D reconstruction. An axillary lymph node atlas was established, and a correlation between lymph node sphericity and lymph node metastasis was revealed. By continuously fitting the size and characteristics of axillary lymph nodes on the 3D reconstruction system, formulas and models were established to determine the presence or absence of lymph node metastasis, and the 3D method had better sensitivity for axillary lymph node assessment than the 2D method, with a statistically significant difference in the correct classification rate. The combined diagnostic method was superior to a single diagnostic method, with a 92.3% correct classification rate for the 3D method combined with ultrasound. In addition, in patients who received neoadjuvant chemotherapy (NAC), the correct classification rate of the 3D method (72.7%) was significantly higher than that of ultrasound (45.5%) and CT (54.5%). By establishing an axillary lymph node atlas, the sphericity formula and model developed with the 3D reconstruction system achieve a high correct classification rate when combined with ultrasound or CT and can also be applied to patients receiving NAC.

Predictive value of intravoxel incoherent motion combined with diffusion kurtosis imaging for breast cancer axillary lymph node metastasis: a retrospective study.

Non-invasive imaging technologies for assessing axillary lymph node (ALN) metastasis of breast cancer are needed in clinical practice. To explore the clinical value of intravoxel incoherent motion (IVIM) and diffusional kurtosis imaging (DKI) for predicting ALN metastasis of breast cancer. A total of 194 patients with pathologically confirmed breast cancer who underwent IVIM and DKI examination were reviewed retrospectively. The IVIM derived parameters of D, D*, and f and DKI-derived parameters of MD and MK were measured. The independent samples t-test was used to compare the parameters between the ALN metastasis and non-ALN metastasis groups. Receiver operating characteristic (ROC) curve analysis was also performed. The D and MD in the ALN metastasis group were significantly lower than those in the non-ALN metastasis group (P < 0.001, P < 0.001). The D*, f, and MK were higher in the ALN metastasis group than in the non-ALN metastasis group (P = 0.015, P = 0.014, and P = 0.001, respectively). The area under the ROC curve (AUC) of D (0.768) was highest. In addition, the diagnostic efficiency of both IVIM and DKI were higher than that of the conventional MRI (P = 0.002, P = 0.048). The diagnostic efficiency of IVIM + DKI were higher than that of the IVIM or DKI alone (P = 0.021, P = 0.004). IVIM and DKI can be used for predicting breast cancer ALN metastasis with D as the most meaningful parameter.

The Value of Shear Wave Elastography in the Diagnosis of Breast Cancer Axillary Lymph Node Metastasis and Its Correlation With Molecular Classification of Breast Masses.

ObjectiveTo explore the diagnostic value of shear wave elastography examination (SWE) on axillary node metastasis (ANM) in breast cancer, this study aimed to evaluate the correlation between the SWE features and different molecular types of breast cancer, and to check the elastic modulus differences among the molecular types.MethodsBreast cancer patients from November 2020 to December 2021 were subjected to both conventional ultrasonic examination (CUE) and SWE before ultrasound-guided percutaneous biopsy or axillary lymph node dissection (ALND). We used the pathological results as the gold standard to draw the receiver operating characteristic (ROC) curve.ResultsSWE outperforms CUE, but their conjunctive use is the best option. No significant correlation was found between the elastic modulus values and the molecular types of breast cancer.ConclusionSWE can be used as an routine auxiliary method of CUE for ANM.

Decreased Expression of circ_0000160 in Breast Cancer With Axillary Lymph Node Metastasis.

Background: Circular RNAs (circRNAs) have been shown to play important roles in the development and progression of human cancers. Emerging evidence shows that circRNAs have the potential to be promising biomarkers for cancer diagnosis and prognosis. However, the roles of circRNAs in breast cancer axillary lymph node metastasis (ALNM) remain to be determined. Methods: Transcriptome sequencing was utilized to screen the differentially expressed circRNAs in three breast cancer tissues with ALNM and three without ALNM. Differentially expressed circRNAs were further verified by quantitative real-time PCR. Moreover, receiver operating characteristic (ROC) curve analysis was performed to calculate the value of circRNAs to distinguish breast cancer tissues with ALNM and those without ALNM. To explore the potential mechanism of the circRNAs, a circRNA–miRNA–mRNA network was constructed based on the CircInteractome, circBank, and mirDIP online software. Results: In total, 31 differentially expressed circRNAs were identified by transcriptome sequencing; among them, 21 were upregulated and 10 were downregulated in breast cancer with ALNM compared to those without ALNM. Circ_0000160 was validated to be downregulated in breast cancer tissues with ALNM compared with those without ALNM. The ROC curve showed the ability of circ_0000160 to distinguish breast cancer tissues with ALNM and those without ALNM, with an area under the curve of 0.7435. Furthermore, bioinformatics analysis revealed that the predicted mRNAs for circ_0000160 may be related to lymph node metastasis. The predicted mRNAs for circ_0000160 may be involved in many cancer-related pathways. Conclusion: A decreased expression of circ_0000160 was found in breast cancer with axillary lymph node metastasis. Circ_0000160 may have the potential to distinguish breast cancer with axillary lymph node metastasis from those without axillary lymph node metastasis.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Based on Intratumoral and Peritumoral DCE-MRI Radiomics Nomogram.

Objective To investigate the value of preoperative prediction of breast cancer axillary lymph node metastasis based on intratumoral and peritumoral dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) radiomics nomogram. Material and Methods. In this study, a radiomics model was developed based on a training cohort involving 250 patients with breast cancer (BC) who had undergone axillary lymph node (ALN) dissection between June 2019 and January 2021. The intratumoral and peritumoral radiomics features were extracted from the second postcontrast images of DCE-MRI. Based on filtered radiomics features, the radiomics signature was built by using the least absolute shrinkage and selection operator method. The Support Vector Machines (SVM) learning algorithm was used to construct intratumoral, periatumoral, and intratumoral combined periatumoral models for predicting axillary lymph node metastasis (ALNM) in BC. Nomogram performance was determined by its discrimination, calibration, and clinical value. Multivariable logistic regression was adopted to establish a radiomics nomogram. Results The intratumoral combined peritumoral radiomics signature, which was composed of fifteen ALN status-related features, showed the best predictive performance and was associated with ALNM in both the training and validation cohorts (P < 0.001). The prediction efficiency of the intratumoral combined peritumoral radiomics model was higher than that of the intratumoral radiomics model and the peritumoral radiomics model. The AUCs of the training and verification cohorts were 0.867 and 0.785, respectively. The radiomics nomogram, which incorporated the radiomics signature, MR-reported ALN status, and MR-reported maximum diameter of the lesion, showed good calibration and discrimination in the training (AUC = 0.872) and validation cohorts (AUC = 0.863). Conclusion The intratumoral combined peritumoral radiomics model derived from DCE-MRI showed great predictive value for ALNM and may help to improve clinical decision-making for BC.

MRI Diagnosis and Pathological Examination of Axillary Lymph Node Metastasis in Breast Cancer Patients.

In order to explore the characteristics and diagnostic value of magnetic resonance imaging (MRI) in axillary lymph node metastasis of breast cancer, a total of 200 breast cancer patients diagnosed and treated from January 2021 to January 2022 are selected as the study subjects, and 200 patients are divided into an axillary lymph node metastasis group and a simple breast cancer group according to pathological results. The pathological results are used as the gold standard to determine the accuracy and diagnostic efficacy of MRI results. A multivariate logistic regression method is used to analyze the influencing factors of MRI image characteristics of breast cancer axillary lymph node metastasis. The experimental results show that MRI has high application values in diagnosing axillary lymph node metastasis of breast cancer, which is worthy of clinical promotion and application.

Artificial Intelligence Algorithm-Based Ultrasound Image Segmentation Technology in the Diagnosis of Breast Cancer Axillary Lymph Node Metastasis.

This paper aimed to investigate the application of ultrasound image segmentation technology based on the back propagation neural network (BPNN) artificial intelligence algorithm in the diagnosis of breast cancer axillary lymph node metastasis, thereby providing a theoretical basis for clinical diagnosis. In this study, 90 breast cancer patients with axillary lymph node metastasis were selected as the research objects and rolled randomly into an experimental group and a control group. Besides, all of them were examined by ultrasound. The BPNN algorithm for the ultrasound image segmentation diagnosis method was applied to the patiens from the experimental group, while the control group was given routine ultrasound diagnosis. Thus, the value of this algorithm in ultrasonic diagnosis was compared and explored. The results showed that when the number of hidden layer nodes based on the BPNN artificial intelligence algorithm was 2, 3, 4, 5, 6, 7, and 8, the corresponding segmentation accuracy was 97.3%, 96.5%, 94.8%, 94.8%, and 94.1% in turn. Among them, the segmentation accuracy was the highest when the number of hidden layer nodes was 2. The correlation of independent variable bubble plot analysis showed that the presence or absence of capsules, the presence of crab feet or burrs in breast cancer lesions was critical influencing factors for the occurrence of axillary lymph node metastasis, and the standardized importance was 99.7% and 70.8%, respectively. Besides, the area under the two-dimensional receiver operating characteristic (ROC) curve of the BPNN artificial intelligence algorithm model classification was always greater than the area under the curve of manual segmentation, and the segmentation accuracy was 90.31%, 94.88%, 95.48%, 95.44%, and 97.65% in sequence. In addition, the segmentation specificity of different running times was higher than that of manual segmentation. In conclusion, the BPNN artificial intelligence algorithm had high accuracy, sensitivity, and specificity for ultrasound image segmentation, with a better segmentation effect. Therefore, it had a better diagnostic effect for breast cancer axillary lymph node metastasis.

The Use of CYFRA 21-1 for the Detection of Breast Cancer Axillary Lymph Node Metastases in Needle Washouts of Fine-Needle Aspiration Biopsies.

In the preoperative setting of breast cancer, fine-needle aspiration biopsy (FNAB) guided by ultrasonography can be used to detect axillary lymph node metastases. The aim of the current study was to determine whether measurement in needle washouts of CYFRA 21-1, a soluble fragment of cytokeratin 19 (CK19), can improve the diagnosis of lymph node tumor deposits. Our prospective study included 329 breast cancer patients eligible for a sentinel node procedure. Eighty-two patients had a ultrasonography-guided FNAB of an abnormal or suspicious axillary node and were included in the current analysis. Samples were processed with smears and cell-block histology; afterwards, needles were washed with saline solution, and the CYFRA 21-1 content in the washouts was measured. The cutoff value for positive samples that expressed CK19, as shown by their immunohistochemistry, was determined by a receiver operating characteristic curve. On the basis of this value, the specificity and the sensitivity, as well as the positive and negative predictive values, were then calculated using cytology results as a reference standard. Of the 82 axillary lymph nodes sampled, 61 were positive on cytology and were metastatic for breast cancer, as confirmed by surgery. The median CYFRA 21-1 concentration of positive samples was 88.94 ng/mL, whereas in the 21 negative nodes, its median concentration was 1.02 ng/mL (P<0.0001). A CYFRA 21-1 cutoff value of 1.98 ng/mL, obtained by the receiver operating characteristic curve, was able to clearly separate negative from positive samples and gave the test a sensitivity of 0.98 and a specificity of 1.00. Positive and negative predictive values were 1.00 and 0.95, respectively. The measurement of CYFRA 21-1 levels in needle washouts after axillary lymph node FNABs represents an accurate, sensitive, and highly predictive procedure in detecting metastatic deposits of breast cancer and is fit to complement cytology and CK19 immunohistochemistry as a diagnostic tool.

Sensitivity, Specificity and Accuracy of Ultrasound in Diagnosis of Breast Cancer Metastasis to the Axillary Lymph Nodes in Chinese Patients

The use of ultrasound in the diagnosis of axillary lymph node metastases from breast cancer in a Chinese population was investigated. Data for 1,049 with breast cancer were retrospectively collected. All patients had undergone pre-operative axillary ultrasound and then axillary lymph node dissection. The sensitivity, specificity and accuracy of axillary ultrasound in this cohort were 69.4%, 81.8% and 77.0%, respectively. The overall false-negative rate of ultrasound images was 30.6% (123/402). False-negative ultrasound rates for pathologic N1, N2 and N3 patients were 46.2%, 21.8% and 9.3%, respectively. In patients with stage T1 disease and fewer than three metastatic lymph nodes, the false-negative ultrasound rate was 52.2% (47/90). Moreover, breast cancer patients with a false-negative axillary ultrasound were more likely to have a large tumor (p < 0.001) and high tumor grade (p = 0.009). However, there were no statistically significant differences between accuracy of axillary ultrasound and age of patients or experiences of ultrasound practitioners. In conclusion, the sensitivity, specificity and accuracy of ultrasound in the diagnosis of breast cancer metastasis to the axillary lymph nodes in Chinese patients were assessed. These data could help us to carefully use axillary ultrasound to diagnose and predict breast cancer axillary lymph node metastasis.

Correlation of Breast Cancer Axillary Lymph Node Metastases With Stem Cell Mutations

Mutations in oncogenes AKT1, HRAS, and PIK3CA in breast cancers result in abnormal PI3K/Akt signaling and tumor proliferation. They occur in ductal carcinoma in situ, in breast cancers, and in breast cancer stem and progenitor cells (BCSCs). To determine if variability in clinical presentation at diagnosis correlates with PI3K/Akt mutations in BCSCs and provides an early prognostic indicator of increased progression and metastatic potential. Malignant (BCSCs) and benign stem cells were collected from fresh surgical specimens via cell sorting and tested for oncogene mutations in a university hospital surgical oncology research laboratory from 30 invasive ductal breast cancers (stages IA through IIIB). Presence of AKT1, HRAS, and PIK3CA mutations in BCSCs and their correlation with tumor mutations, pathologic tumor stage, tumor histologic grade, tumor hormone receptor status, lymph node metastases, and patient age and condition at the last follow-up contact. Ten tumors had mutations in their BCSCs. In total, 9 tumors with BCSC mutations and 4 tumors with BCSCs without mutations had associated tumor present in the lymph nodes (P = .001). Tumors in which BCSCs have defects in PI3K/Akt signaling are significantly more likely to manifest nodal metastases. These oncogenic defects may be missed by gross molecular testing of the tumor and are markers of more aggressive breast cancer. Molecular profiling of BCSCs may identify patients who would likely benefit from PI3K/Akt inhibitors, which are being tested in clinical trials.

Breast Cancer Axillary Lymph Node Metastasis Detection by a High-Resolution Dedicated Breast Camera: A Comparative Study with SPECT and Pinhole SPECT

We evaluated the usefulness of (99m)Tc-tetrofosmin planar scintigraphy acquired with a high-resolution (HR) dedicated breast camera in comparison with conventional single-photon emission computed tomography (SPECT) and pinhole-SPECT (P-SPECT) in breast cancer (BC) axillary lymph node metastasis detection in a consecutive series of 76 BC patients, 28 of whom had axillary lymph node metastases, including 9 positive at clinical examination. HR planar scintigraphy was true positive in only 7 patients with >3 palpable metastases (sensitivity: 25%), while SPECT was true positive in 23 of 28 cases (sensitivity: 82.1%) and P-SPECT in 25 of 28 (sensitivity: 89.3%). SPECT was false negative in 5 patients with nonpalpable <or= 3 nodes, including 2 with one micrometastatic node, while P-SPECT was false negative in the latter 2 cases, and in another of the cases, false negative at SPECT with one macrometastatic node. Neither planar nor SPECT had false-positive findings (specificity: 100%), while P-SPECT had two (specificity: 95.8%). P-SPECT presented the best resolution in showing the metastatic nodes and was the only procedure able to define the number of involved nodes, thus delivering important prognostic information. HR planar scintigraphy appears an ineffective diagnostic tool in BC axillary lymph node metastasis detection, only succeeding in identifying palpable and >3 metastatic nodes. SPECT should be preferred, significantly improving the sensitivity of planar scintigraphy, especially when using a pinhole collimator.

Characterization of a Novel Breast Carcinoma Xenograft and Cell Line Derived from a BRCA1 Germ-Line Mutation Carrier

A human tumor xenograft (L56Br-X1) was established from a breast cancer axillary lymph node metastasis of a 53-year-old woman with a BRCA1 germ-line nonsense mutation (1806C>T; Q563X), and a cell line (L56Br-C1) was subsequently derived from the xenograft. The xenograft carries only the mutant BRCA1 allele and expresses mutant BRCA1 mRNA but no BRCA1 protein as determined by immunoprecipitation or Western blotting. The primary tumor, lymph node metastasis, and xenograft were hypodiploid by DNA flow cytometry, whereas the cell line displayed an aneuploidy apparently developed via polyploidization. Cytogenetic analysis, spectral karyotyping, and comparative genomic hybridization of the cell line revealed a highly complex karyotype with numerous unbalanced translocations. The xenograft and cell line had retained a somatic TP53 missense mutation (S215I) originating from the primary tumors, as well as a lack of immunohistochemically detectable expression of steroid hormone receptors, epidermal growth factor receptor, human epidermal growth factor receptor 2 (HER-2), and keratin 8. Global gene expression analysis by cDNA microarrays supported a correlation between the expression profiles of the primary tumor, lymph node metastasis, xenograft, and cell line. We conclude that L56Br-X1 and L56Br-C1 are useful model systems for studies of the pathogenesis and new therapeutic modalities of BRCA1-induced human breast cancer.

Intra-patient variation between breast cancer axillary lymph node metastases using quantifiable features.

The intra-patient variations of some clinically relevant quantifiable features, between axillary lymph node metastases were evaluated in 44 breast cancer patients. In all lymph node metastases detected (range 2-33 per patient), the mitotic figures were counted, the volume percentage epithelium was assessed and the mean nuclear area was measured. The intra-patient variation for each quantifiable feature was expressed by the coefficient of variation (CV). Since the measurement techniques used introduce a certain, well known variation themselves because of sampling and measurement errors, the CVs found had to be greater than methodological tolerance limits (established in previous studies) to be interpreted as indicating biological variation. The CVs exceeded the methodological tolerance limits in 86% of the cases for the mitotic count, in 48% of the cases for the volume percentage epithelium, and in 47% of the cases for the mean nuclear area. This indicated that in these cases, the variation found in the quantifiable features could not be explained by sampling or measurement errors and should be regarded as real biological variation. Furthermore, the variation in the quantifiable features studied showed a significant positive correlation with the number of lymph node metastases. Thus, there may be considerable intra-patient variation in quantifiable features between axillary lymph node metastases in breast cancer. This may indicate that these lymph node metastases originate independently from different clones within the primary tumour, that they are independently formed in different stages of tumour development, or that they, as an expression of intrinsic tumour heterogeneity, may develop in different directions from the start.