Automated and rapid detection of cancer in suspicious axillary lymph nodes in patients with breast cancer.
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ABSTRACT:
SUBMITTER: Li J
PROVIDER: S-EPMC8263765 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveAutomated breast ultrasound (ABUS) is a relevant imaging technique for early breast cancer diagnosis and is increasingly being used as a supplementary tool for mammography. This study compared the performance of ABUS and handheld ultrasound (HHUS) in detecting and characterizing the axillary lymph nodes (LNs) in patients with breast cancer.Materials and methodsWe retrospectively reviewed the medical records of women with recently diagnosed early breast cancer (≤ T2) who underwent both ABUS and HHUS examinations for axilla (September 2017-May 2018). ABUS and HHUS findings were compared using pathological outcomes as reference standards. Diagnostic performance in predicting any axillary LN metastasis and heavy nodal-burden metastases (i.e., ≥ 3 LNs) was evaluated. The ABUS-HHUS agreement for visibility and US findings was calculated.ResultsThe study included 377 women (53.1 ± 11.1 years). Among 385 breast cancers in 377 patients, 101 had axillary LN metastases and 30 had heavy nodal burden metastases. ABUS identified benign-looking or suspicious axillary LNs (average, 1.4 ± 0.8) in 246 axillae (63.9%, 246/385). According to the per-breast analysis, the sensitivity, specificity, positive and negative predictive values, and accuracy of ABUS in predicting axillary LN metastases were 43.6% (44/101), 95.1% (270/284), 75.9% (44/58), 82.6% (270/327), and 81.6% (314/385), respectively. The corresponding results for HHUS were 41.6% (42/101), 95.1% (270/284), 75.0% (42/56), 82.1% (270/329), and 81.0% (312/385), respectively, which were not significantly different from those of ABUS (P ≥ 0.53). The performance results for heavy nodal-burden metastases were 70.0% (21/30), 89.6% (318/355), 36.2% (21/58), 97.3% (318/327), and 88.1% (339/385), respectively, for ABUS and 66.7% (20/30), 89.9% (319/355), 35.7% (20/56), 97.0% (319/329), and 88.1% (339/385), respectively, for HHUS, also not showing significant difference (P ≥ 0.57). The ABUS-HHUS agreement was 95.9% (236/246; Cohen's kappa = 0.883).ConclusionAlthough ABUS showed limited sensitivity in diagnosing axillary LN metastasis in early breast cancer, it was still useful as the performance was comparable to that of HHUS.
| S-EPMC10831296 | biostudies-literature
Project description:BACKGROUND: Lymph node status is one of the decisive prognostic factors in breast cancer. Chemotherapy targeting regional lymphatic tissues has emerged as a promising therapy for the treatment of malignancies with a high tendency to disseminate lymphatically. The present study determined the drug concentrations in axillary lymph nodes after lymphatic chemotherapy (LC) in patients with breast cancer and compared the results with those receiving intravenous chemotherapy (VC) to investigate whether LC could improve the accumulation of anticancer drug in regional lymph nodes. METHODS: Sixty patients with breast carcinoma confirmed by preoperative puncture-biopsy were divided into two groups at random. The LC group (n = 30) received a subcutaneous injection of 4 ml of carboplatin-activated carbon suspension, containing 20 mg of carboplatin, adjacent to the primary tumour. The VC group (n = 30) received an intravenous administration of an equal dose of aqueous carboplatin. At 1, 12, 24, 36 and 48 hours after administration, modified radical mammectomies were performed on 12 patients at each time point, with 6 from each group. Axillary lymph nodes were removed for pathological examination. The platinum concentrations in nodes were determined by Zeeman atomic absorption spectrometry. RESULTS: A total of 275 axillary lymph nodes were resected, with 154 in the LC group and 121 in the VC group. Of the 275 lymph nodes, 136 (49.5%) from 23 patients (38.3%) had histopathologically detected metastases. At 1, 12, 24, 36 and 48 hours after injection, the carboplatin concentrations in the LC group were 11.82 +/- 3.50, 23.58 +/- 7.34, 18.22 +/- 4.93, 16.70 +/- 5.15 and 14.62 +/- 4.29 microg/g (means +/- SD), respectively, whereas those in the VC group were 0.06 +/- 0.02, 0.11 +/- 0.05, 0.10 +/- 0.02, 0.05 +/- 0.02 and 0 microg/g, respectively. Significant differences were found in each corresponding comparison (P < 0.001). Lymph node metastasis was uncorrelated with drug concentration (P > 0.05). CONCLUSION: LC can effectively and continuously improve the drug concentrations in axillary lymph nodes in patients with breast cancer, in comparison with VC.
| S-EPMC468670 | biostudies-other
Project description:We have established a highly sensitive and quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) method to detect axillary lymph node metastases of breast cancer. Amplifying cytokeratin 19 (CK19) mRNA transcripts using real-time TaqMan PCR made it possible to quantify axillary metastatic burden. Metastases in 358 axillary lymph nodes obtained from 23 breast cancers of 22 patients were investigated by conventional haematoxylin and eosin (H&E) staining, immunohistochemical staining and quantitative RT-PCR assay. The detection rates of axillary lymph node metastasis using H&E staining, immunohistochemistry and RT-PCR assay were 4.5, 5.9 and 13.1%, respectively. RT-PCR assay was the most sensitive of these three methods for detecting lymph node metastases. Cytokeratin 19 mRNA expression values of both histologically and immunohistochemically positive lymph nodes were significantly higher than the values for lymph nodes judged to be negative by both histological and immunohistochemical methods (P<0.0001), and those of histologically negative, but immunohistochemically positive lymph nodes were significantly higher than the values for lymph nodes judged to be negative by both histological and immunohistochemical methods (P<0.0001). Furthermore, metastatic rates of sentinel nodes were higher than the rates of nonsentinel lymph nodes as measured by all three methods. These results indicate that quantitative RT-PCR assay is a sensitive and reliable method for detecting lymph node metastasis. Furthermore, quantification of metastases in sentinel lymph nodes by quantitative RT-PCR assay may be useful to assess the entire axillary burden of breast cancer patients.
| S-EPMC2394408 | biostudies-other
Project description:PurposeObesity associated fat infiltration of organ systems is accompanied by organ dysfunction and poor cancer outcomes. Obese women demonstrate variable degrees of fat infiltration of axillary lymph nodes (LNs), and they are at increased risk for node-positive breast cancer. However, the relationship between enlarged axillary nodes and axillary metastases has not been investigated. The purpose of this study is to evaluate the association between axillary metastases and fat-enlarged axillary nodes visualized on mammograms and breast MRI in obese women with a diagnosis of invasive breast cancer.MethodsThis retrospective case-control study included 431 patients with histologically confirmed invasive breast cancer. The primary analysis of this study included 306 patients with pre-treatment and pre-operative breast MRI and body mass index (BMI) > 30 (201 node-positive cases and 105 randomly selected node-negative controls) diagnosed with invasive breast cancer between April 1, 2011, and March 1, 2020. The largest visible LN was measured in the axilla contralateral to the known breast cancer on breast MRI. Multivariate logistic regression models were used to assess the association between node-positive status and LN size adjusting for age, BMI, tumor size, tumor grade, tumor subtype, and lymphovascular invasion.ResultsA strong likelihood of node-positive breast cancer was observed among obese women with fat-expanded lymph nodes (adjusted OR for the 4th vs. 1st quartile for contralateral LN size on MRI: 9.70; 95% CI 4.26, 23.50; p < 0.001). The receiver operating characteristic curve for size of fat-enlarged nodes in the contralateral axilla identified on breast MRI had an area under the curve of 0.72 for predicting axillary metastasis, and this increased to 0.77 when combined with patient and tumor characteristics.ConclusionFat expansion of axillary lymph nodes was associated with a high likelihood of axillary metastases in obese women with invasive breast cancer independent of BMI and tumor characteristics.
| S-EPMC8302552 | biostudies-literature
Project description:ObjectiveFat-infiltrated axillary lymph nodes (LNs) are unique sites for ectopic fat deposition. Early studies showed a strong correlation between fatty LNs and obesity-related diseases. Confirming this correlation requires large-scale studies, hindered by scarce labeled data. With the long-term goal of developing a rapid and generalizable tool to aid data labeling, we developed an automated deep learning (DL)-based pipeline to classify the status of fatty LNs on screening mammograms.MethodsOur internal data set included 886 mammograms from a tertiary academic medical institution, with a binary status of the fat-infiltrated LNs based on the size and morphology of the largest visible axillary LN. A two-stage DL model training and fine-tuning pipeline was developed to classify the fat-infiltrated LN status using the internal training and development data set. The model was evaluated on a held-out internal test set and a subset of the Digital Database for Screening Mammography.ResultsOur model achieved 0.97 (95% CI: 0.94-0.99) accuracy and 1.00 (95% CI: 1.00-1.00) area under the receiver operator characteristic curve on 264 internal testing mammograms, and 0.82 (95% CI: 0.77-0.86) accuracy and 0.87 (95% CI: 0.82-0.91) area under the receiver operator characteristic curve on 70 external testing mammograms.ConclusionThis study confirmed the feasibility of using a DL model for fat-infiltrated LN classification. The model provides a practical tool to identify fatty LNs on mammograms and to allow for future large-scale studies to evaluate the role of fatty LNs as an imaging biomarker of obesity-associated pathologies.Advances in knowledgeOur study is the first to classify fatty LNs using an automated DL approach.
| S-EPMC10607412 | biostudies-literature
Project description:Prostate Specific Ets factor is a recently identified transcriptional activator that is overexpressed in prostate cancer. To determine whether this gene is overexpressed in breast cancer, we performed a virtual Northern blot using data available online at the Cancer Genome Anatomy Project website. Ninety-five SAGE libraries were probed with a unique sequence tag to the Prostate Specific Ets gene. The results indicate that Prostate Specific Ets is expressed in 14 out of 15 breast cancer libraries (93%), nine out of 10 prostate cancer libraries (90%), three out of 40 libraries from other cancers (7.5%), and four out of 30 normal tissue libraries (13%). To determine the possibility that the Prostate Specific Ets gene is a novel marker for detection of metastatic breast cancer in axillary lymph nodes, quantitative real-time RT-PCR analyses were performed. The mean level of Prostate Specific Ets expression in lymph nodes containing metastatic breast cancer (n=22) was 410-fold higher than in normal lymph node (n=51). A receiver operator characteristic curve analysis indicated that Prostate Specific Ets was overexpressed in 18 out of 22 lymph nodes containing metastatic breast cancer (82%). The receiver operator characteristic curve analysis also indicated that the diagnostic accuracy of the Prostate Specific Ets gene for detection of metastatic breast cancer in axillary lymph nodes was 0.949. These results provide evidence that Prostate Specific Ets is a potentially informative novel marker for detection of metastatic breast cancer in axillary lymph nodes, and should be included in any study that involves molecular profiling of breast cancer.
| S-EPMC2364139 | biostudies-literature
Project description:We have previously reported that a quantitative reverse transcription (QRT)-PCR assay accurately analyzes sentinel lymph nodes (SLNs) from breast cancer patients. The aim of this study was to assess a completely automated, cartridge-based version of the assay for accuracy, predictive value, and reproducibility. The triplex (two markers + control) QRT-PCR assay was incorporated into a single-use cartridge for point-of-care use on the GeneXpert system. Three academic centers participated equally. Twenty-nine positive lymph nodes and 30 negative lymph nodes were analyzed to establish classification rules. SLNs from 120 patients were subsequently analyzed by QRT-PCR and histology (including immunohistochemistry), and the predetermined decision rules were used to classify the SLNs; 112 SLN specimens produced an informative result by both QRT-PCR and histology. By histological analysis, 21 SLNs were positive and 91 SLNs were negative for metastasis. QRT-PCR characterization produced a classification with 100% sensitivity, 97.8% specificity, and 98.2% accuracy compared with histology (91.3% positive predictive value and 100% negative predictive value). Interlaboratory reproducibility analyses demonstrated that a 95% prediction interval for a new measurement (DeltaCt) ranged between 0.403 and 0.956. This fully automated QRT-PCR assay accurately characterizes breast cancer SLNs for the presence of metastasis. Furthermore, the assay is not dependent on subjective interpretation, is reproducible across three clinical environments, and is rapid enough to allow intraoperative decision making.
| S-EPMC2765757 | biostudies-literature
Project description:ObjectivesTo determine whether ultrasound radiomics can be used to distinguish axillary lymph nodes (ALN) metastases in breast cancer based on ALN imaging.MethodsA 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.ResultRadiomics 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.ConclusionThe radiomics model demonstrated a good ability to predict ALN status in patients with breast cancer, which might provide essential information for decision-making.
| S-EPMC10641324 | biostudies-literature
Project description:BackgroundBreast cancer patients with positive axillary lymph nodes usually require axillary lymph node dissection (ALND), with many postoperative complications, such as lymphedema. For these patients, whether sentinel lymph node biopsy (SLNB) can replace ALND has been a research hotspot in the field of breast cancer. This study developed two risk stratification models for predicting the clinical outcomes of breast cancer patients with positive axillary lymph nodes receiving SLNB alone or ALND to determine which patients could potentially avoid ALND.MethodsA total of 21,942 breast cancer patients, including a training set (n=15,362) and a testing set (n=6,580), were enrolled in this study from Surveillance, Epidemiology, and End Results (SEER) between 2000 and 2017. The risk factors associated with breast cancer-specific survival (BCSS) and overall survival (OS) were evaluated using multivariate Cox regression analysis and then integrated into nomograms and risk stratification models examined by receiver operating characteristic (ROC) curves and calibration curves. The survival discrepancies were compared between the SLNB and ALND subgroups with different risk scores with Kaplan-Meier plots.ResultsIn multivariate Cox regression analyses, grade, marital status, T stage, radiotherapy and lymph node metastasis (GMTRL) were independent risk factors in breast cancer patients with both OS and BCSS status in the ALND cohort from the training set. Nomograms have been developed based on these factors to predict 3- and 5-year OS and BCSS in patients with ALND. Calibration curves and ROC curves in both the training and testing sets confirmed the excellent overall predictive performance of the nomograms. Furthermore, we developed two risk stratification models based on OS and BCSS status, revealing that patients with low GMTRL scores might avoid ALND in both OS and BCSS status [OS: hazard ratio (HR) =0.929, 95% confidence interval (CI): 0.841-1.027, P=0.150; BCSS: HR =0.953, 95% CI: 0.831-1.094, P=0.495], but patients with moderate (OS: HR =0.756, 95% CI: 0.666-0.859, P<0.001; BCSS: HR =0.643, 95% CI: 0.537-0.768, P<0.001) and high GMTRL scores could not (OS: HR =0.719, 95% CI: 0.549-0.940, P=0.014; BCSS: HR =0.731, 95% CI: 0.549-0.974, P=0.031).ConclusionsBreast cancer patients with positive nodes could be treated with SLNB alone rather than ALND without affecting prognosis based on GMTRL scores. Patients with high or moderate GMTRL scores benefited greatly from ALND, but not for patients with low GMTRL scores. This study may assist clinicians in tailoring treatments.
| S-EPMC10928607 | biostudies-literature
Project description:Metastatic breast cancers are still incurable. Characterizing the evolutionary landscape of these cancers, including the role of metastatic axillary lymph nodes (ALNs) in seeding distant organ metastasis, can provide a rational basis for effective treatments. Here, we have described the genomic analyses of the primary tumors and metastatic lesions from 99 samples obtained from 20 patients with breast cancer. Our evolutionary analyses revealed diverse spreading and seeding patterns that govern tumor progression. Although linear evolution to successive metastatic sites was common, parallel evolution from the primary tumor to multiple distant sites was also evident. Metastatic spreading was frequently coupled with polyclonal seeding, in which multiple metastatic subclones originated from the primary tumor and/or other distant metastases. Synchronous ALN metastasis, a well-established prognosticator of breast cancer, was not involved in seeding the distant metastasis, suggesting a hematogenous route for cancer dissemination. Clonal evolution coincided frequently with emerging driver alterations and evolving mutational processes, notably an increase in apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like-associated (APOBEC-associated) mutagenesis. Our data provide genomic evidence for a role of ALN metastasis in seeding distant organ metastasis and elucidate the evolving mutational landscape during cancer progression.
| S-EPMC5873882 | biostudies-other