Contrast-Enhanced Ultrasound-Guided Fine-Needle Aspiration for Sentinel Lymph Node Biopsy in Early-Stage Breast Cancer

Sentinel Lymph Node Identification in Post Neoadjuvant Chemotherapy Breast Cancer Patients Undergoing Surgical Excision Using Lymphosonography

OBJECTIVES

This study evaluated the efficacy of lymphosonography in the identification of sentinel lymph nodes (SLNs) in post neoadjuvant chemotherapy patients with breast cancer scheduled to undergo surgical excision.

METHODS

Seventy-nine subjects scheduled for breast cancer surgery with SLN excision completed this IRB-approved study, out of which 18 (23%) underwent neoadjuvant chemotherapy before surgery. Subjects underwent percutaneous Sonazoid (GE Healthcare) injections around the tumor area for a total of 1.0 mL. Lymphosonography was performed using CPS on an S3000 HELX scanner (Siemens Healthineers) with a linear probe. Subjects received blue dye and radioactive tracer as part of their standard of care. Excised SLNs were classified as positive or negative for the presence of blue dye, radioactive tracer and Sonazoid. The results were compared between methods and pathology findings.

RESULTS

Seventy-two SLNs were surgically excised from 18 subjects, 29 were positive for blue dye, 63 were positive for radioactive tracer and 57 were positive for Sonazoid. Comparison with blue dye showed that both radioactive tracer and lymphosonography achieved an accuracy of 53% (P > .50). Comparison with radioactive tracer showed that blue dye had an accuracy of 53%, while lymphosonography achieved an accuracy of 67% (P < .01). Of the 72 SLNs, 15 were determined malignant by pathology; the detection rate was 47% for blue dye (7/15), 67% for radioactive tracer (10/15) and 100% for lymphosonography (15/15) (P < .001).

CONCLUSIONS

Lymphosonography achieved similar accuracy as radioactive tracer and higher accuracy than blue dye for identifying SLNs. The 15 SLNs positive for malignancy were all identified by lymphosonography.

Contrast-enhanced ultrasound-guided sentinel lymph node biopsy in early-stage breast cancer: a prospective cohort study

OBJECTIVE

This study evaluated the identification efficiency of contrast-enhanced ultrasound (CEUS) for sentinel lymph nodes (SLN) to accurately represent the axillary node status in early-stage breast cancer.

METHOD

In total, 109 consecutive consenting patients with clinically node-negative and T1-2 breast cancer were included in this study. All patients received CEUS to identify SLN before surgery, and a guidewire was deployed to locate SLN in those who were successfully explored by CEUS. The patients underwent sentinel lymph node biopsy (SLNB), and the blue dye was used to trace SLN during the surgery. The decision to perform axillary lymph node dissection (ALND) depended on the intraoperative pathological identification of SLN by CEUS (CE-SLN). The concordance rate of pathological status between CE-SLN and dyed SLN was calculated.

RESULT

The CEUS detection rate was 96.3%; CE-SLN failed in 4 patients. Among the remaining 105 successful identifications, 18 were CE-SLN positive by intraoperative frozen section, and one with CE-SLN micrometastasis was diagnosed by paraffin section. No additional lymph node metastases were found in CE-SLN-negative patients. The concordance rate of pathological status between CE-SLN and dyed SLN was 100%.

CONCLUSION

CEUS can accurately represent the status of axillary lymph nodes in patients with clinically node-negative and small tumor burden breast cancer.

Classification Prediction of Breast Cancer Based on Machine Learning

Breast cancer is the most common and deadly type of cancer in the world. Based on machine learning algorithms such as XGBoost, random forest, logistic regression, and K-nearest neighbor, this paper establishes different models to classify and predict breast cancer, so as to provide a reference for the early diagnosis of breast cancer. Recall indicates the probability of detecting malignant cancer cells in medical diagnosis, which is of great significance for the classification of breast cancer, so this article takes recall as the primary evaluation index and considers the precision, accuracy, and F1-score evaluation indicators to evaluate and compare the prediction effect of each model. In order to eliminate the influence of different dimensional concepts on the effect of the model, the data are standardized. In order to find the optimal subset and improve the accuracy of the model, 15 features were screened out as input to the model through the Pearson correlation test. The K-nearest neighbor model uses the cross-validation method to select the optimal k value by using recall as an evaluation index. For the problem of positive and negative sample imbalance, the hierarchical sampling method is used to extract the training set and test set proportionally according to different categories. The experimental results show that under different dataset division (8 : 2 and 7 : 3), the prediction effect of the same model will have different changes. Comparative analysis shows that the XGBoost model established in this paper (which divides the training set and test set by 8 : 2) has better effects, and its recall, precision, accuracy, and F1-score are 1.00, 0.960, 0.974, and 0.980, respectively.

Sentinel lymph node detection by combining nonradioactive techniques with contrast agents: State of the art and prospects

The status of sentinel lymph nodes (SLNs) has a substantial prognostic value because these nodes are the first place where cancer cells accumulate along their spreading route. Routine SLN biopsy ("gold standard") involves peritumoral injections of radiopharmaceuticals, such as technetium-99m, which has obvious disadvantages. This review examines the methods used as "gold standard" analogs to diagnose SLNs. Nonradioactive preoperative and intraoperative methods of SLN detection are analyzed. Promising photonic tools for SLNs detection are reviewed, including NIR-I/NIR-II fluorescence imaging, photoswitching dyes for SLN detection, in vivo photoacoustic detection, imaging and biopsy of SLNs. Also are discussed methods of SLN detection by magnetic resonance imaging, ultrasonic imaging systems including as combined with photoacoustic imaging, and methods based on the magnetometer-aided detection of superparamagnetic nanoparticles. The advantages and disadvantages of nonradioactive SLN-detection methods are shown. The review concludes with prospects for the use of conservative diagnostic methods in combination with photonic tools.

Feasibility and efficiency of contrast enhanced ultrasound real time guided fine needle aspiration for sentinel lymph node of breast cancer

AIM

To assess the feasibility and efficiency of contrast-enhanced ultrasound (CEUS) real-time guided fine needle aspiration (FNA) for sentinel lymph node (SLN) of breast cancer.

MATERIALS AND METHODS

This retrospective study reviewed 21 breast cancer patients who scheduled for surgical resection performed CEUS real-time guided SLN-FNA and intraoperative SLN biopsy (SLNB). The success rate of CEUS real-time guided SLN-FNA was analyzed. The FNA diagnostic efficiency of SLN metastasis was analyzed compared to SLNB.

RESULTS

Twenty-six SLNs were detected by intradermal CEUS whereas 130 SLNs were detected by SLNB. The median SLNs detected by intradermal CEUS (n = 1) and by SLNB (n = 5) was significantly difference (p < 0.001). All 26 CE-SLNs of 21 patients were successfully performed intradermal CEUS dual image real-time guided SLN-FNA including 5 SLNs of 4 patients which were difficult to distinguish in conventional ultrasound. Compared to SLNB, FNA found 2 of 5 cases of SLN metastasis, the diagnosis sensitivity, specificity, positive predictive value, negative predictive value, false negative rate, false positive rate and Yoden index were 40%, 100%, 100%, 84.2%, 60%, 0%and 40%, respectively.

CONCLUSION

SLN-FNA real-time guided by dual CEUS image mode was technically feasible. Patients with a positive SLN-FNA should be advised to ALND without intraoperative SLNB according to Chinese surgeon and patients' conservatism attitude. But a negative SLN-FNA did not obviate the need of conventional SLNB because of the high false negative rate.

Staging of the Axilla in Breast Cancer and the Evolving Role of Axillary Ultrasound

Axillary lymph nodes have long been recognized as a route for breast cancer to spread systemically. As a result, staging of the axilla has always played a central role in the treatment of breast cancer. Anatomic staging was believed to be important for two reasons: 1) it predicts prognosis and guides medical therapy, and 2) it is a potential therapy for removal of disease in the axilla. This paradigm has now been called into question. Prognostic information is driven increasingly by tumor biology, and trials such as the ACOSOG Z0011 demonstrates removal of axillary disease is not therapeutic. Staging of the axilla has undergone a dramatic de-escalation; however, sentinel lymph node biopsy (SLNB) is still an invasive surgery and represents a large economic burden on the healthcare system. In this review, we outline the changing paradigms of axillary staging in breast cancer from emphasis on anatomic staging to tumor biology, and the evolving role of axillary ultrasound, bringing patients less invasive and more personalized therapy.

Preoperative evaluation and influencing factors of sentinel lymph node detection for early breast cancer with contrast-enhanced ultrasonography: What matters

Sentinel lymph node (SLN) is important in the early diagnosis of breast cancer. We aimed to evaluate the role of contrast-enhanced ultrasonography (CEUS) in the preoperative evaluation for SLN and potentially influencing factors, to provide evidence to the management of breast cancer.Patients with breast cancer who treated in our hospital from May 2018 to May 2020 were selected. All patients underwent CEUS examination to find SLN and judged whether the lymph node had cancer metastasis. We evaluated the sensitivity, specificity, and accuracy of CEUS in predicting SLN, and its differences in pathological diagnosis results and related influencing factors were also analyzed.A total of 108 patients with breast cancer were included. And a total of 248 SLNs were detected. The sensitivity of CEUS to the preoperative evaluation of SLN was 84.67%, the specificity was 81.14%, the positive predictive value was 76.08%, and the negative predictive value was 89.27%, the positive likelihood ratio was 4.06, and the negative likelihood ratio was 0.14. The area under the curve of the preoperative evaluation of SLN in CEUS examination was 0.813 (95% confidence interval: 0.765-0.911), and there was significant difference in the size of SLNs between SLN-negative and SLN-positive groups (P = .043).Preoperative CEUS has good predictive value for the SLN detection in patients with breast cancer, and it is worthy of clinical application.

The value of contrast-enhanced ultrasound in determining the location of sentinel lymph nodes in breast cancer

Background

This study aimed to explore the sentinel lymph node (SLN) identification rate in breast cancer by subcutaneous and intradermal injection of ultrasound contrast agent in the mammary areola region, compared to the results achieved with methylene blue (MB).

Methods

A total of 390 breast cancer patients with planned sentinel lymph node biopsy from our breast surgery department from July 2017 to February 2019 were enrolled. All patients were subjected to preoperative contrast-enhanced ultrasound (CEUS), that involved an intracutaneous injection of 1 mL ultrasonic contrast agent (UCA) at 3 and 6 o ‘clock, as well as a subcutaneous injection of 1 mL UCA at 9 and 12 o’clock. The enhanced lymph nodes along the enhanced lymphatic vessels from the mammary areola were traced. The number of enhanced lymph nodes were recorded, and an ultrasound-guided injection of 1:10 diluted carbon nanoparticles were used to mark all first site enhanced lymph nodes (i.e., SLNs). An intraoperative dye method (MB) was used to track the SLNs and the results were compared with the CEUS findings.

Results

Among the 390 cases of breast cancer, enhanced SLNs were observed in 373 patients after an injection of UCA with an identification rate of 95.64 % (373/390), compared to the identification rate of 92.05 % (359/390) using the intraoperative MB. The difference between the two methods was statistically significant (P = 0.016). And among the 390 patients, a total of 808 enhanced lymph nodes were traced by preoperative CEUS, with a median of 2 (1,3). A total of 971 blue-stained lymph nodes were traced using the intraoperative MB, with a median of 2 (2,3), indicating a statistically significant difference (p < 0.001).

Conclusions

Intradermal and subcutaneous injections of UCA in the mammary areola region may have clinical application value for the identification and localization of SLNs in breast cancer patients. The identification rate is higher than that of blue dye method, which can be used as a new tracer of sentinel lymph node biopsy and complement other staining methods to improve the success rate.

Predictive risk factors for sentinel lymph node metastasis using preoperative contrast-enhanced ultrasound in early-stage breast cancer patients

Background

Sentinel lymph node biopsy (SLNB) is the standard procedure for axillary staging in clinically node-negative (cN0) breast cancer patients. The positive rate of SLNs in cN0 stage patients ranges from 20.5% to 25.5%, so identifying appropriate candidates for SLNB is quite challenging. The aims of this study were to assess whether contrast-enhanced ultrasound (CEUS) could be utilized to noninvasively predict SLN metastasis, and to explore the predictive value of the involved factors.

Methods

Between May 2016 and May 2018, 217 consenting breast cancer patients undergoing SLNB were enrolled. Before the surgery, CEUS was utilized to identify the SLNs, and predict whether metastasis had occurred according to their enhancement pattern. Blue dye was also used to identify the SLNs during SLNB. The rates of identification and accuracy of both methods were recorded. The predictive outcomes of SLNs identified by CEUS were recorded and compared with the pathological diagnosis.

Results

Of the 217 cases, SLNs in 212 cases were successfully identified, comprising 208 cases identified by CEUS and 206 cases by blue dye, with no significant difference between the two methods (P=0.6470). A total of 78 cases were predicted SLN-positive preoperatively by CEUS, comprising 61 cases of SLN metastasis confirmed by pathology and 17 cases of no SLN metastasis, and 130 cases were predicted SLN-negative by CEUS, comprising 6 cases of SLN metastasis and 124 cases of no SLN metastasis. The sensitivity of CEUS preoperative prediction was 91.0%, the specificity was 87.9%, the positive and negative predictive values were 78.2% and 95.4%, respectively, and the accuracy was 88.9%. The maximum diameter size of positive SLNs predicted by CEUS was greater than that of negative SLNs (mean value 1.67±0.06 vs. 1.40±0.05 cm, P=0.0007). Similarly, the primary tumor size predicted SLN-positive by CEUS was greater than that in patients with negative SLNs (mean value 2.64±0.12 vs. 1.79±0.09 cm, P<0.0001).

Conclusions

CEUS accurately identified SLNs and can be used to noninvasively predict SLN metastasis in early-stage breast cancer patients. However, the primary tumor size and the SLN size should not be overlooked by clinicians when judging the status of SLNs. This novel method may be a recommended strategy for identifying appropriate SLNB candidates.

Contrast-Enhanced Ultrasonography in the Diagnosis and Treatment Modulation of Breast Cancer

The aim of this paper is to highlight the role of contrast-enhanced ultrasound in breast cancer in terms of diagnosis, staging and follow-up of the post-treatment response. Contrast-enhanced ultrasound (CEUS) is successfully used to diagnose multiple pathologies and has also clinical relevance in breast cancer. CEUS has high accuracy in differentiating benign from malignant lesions by analyzing the enhancement characteristics and calculating the time-intensity curve’s quantitative parameters. It also has a significant role in axillary staging, especially when the lymph nodes are not suspicious on clinical examination and have a normal appearance on gray-scale ultrasound. The most significant clinical impact consists of predicting the response to neoadjuvant chemotherapy, which offers the possibility of adjusting the therapy by dynamically evaluating the patient. CEUS is a high-performance, feasible, non-irradiating, accessible, easy-to-implement imaging method and has proven to be a valuable addition to breast ultrasound.

Diagnostic Accuracy of Fine-Needle Aspiration Cytology and Core-Needle Biopsy in the Assessment of the Axillary Lymph Nodes in Breast Cancer-A Meta-Analysis

BACKGROUND

The present study aims to evaluate the diagnostic accuracy between ultrasonography-guided fine-needle aspiration cytology (US-FNAC) and core needle biopsy (CNB) of axillary lymph nodes (ALNs) in patients with breast cancer through a meta-analysis and a diagnostic test accuracy (DTA) review.

METHODS

The present meta-analysis and DTA review included 67 eligible studies. The diagnostic accuracy of various preoperative assessments, including US-FNAC and CNB, was evaluated for ALNs assessments in patients with breast cancer. In addition, a subgroup analysis based on methods of cytologic preparation was performed. In the DTA review, the sensitivity, specificity, diagnostic odds ratio (OR) and area under the curve (AUC) on the summary receiver operating characteristic (SROC) curve were calculated.

RESULTS

The diagnostic accuracy of the preoperative assessments of ALNs was 0.850 (95% confidence interval (CI) 0.833-0.866) for patients with breast cancer. The diagnostic accuracy of CNB was significantly higher than that of US-FNAC (0.896, 95% CI 0.844-0.932 vs. 0.844, 95% CI 0.825-0.862; p = 0.044 in a meta-regression test). In the subgroup analysis based on cytologic preparation, the diagnosis accuracies were 0.860, 0.861 and 0.859 for the methods of conventional smear, liquid-based preparation and cell block, respectively. In the DTA review, CNB showed higher sensitivity than US-FNAC (0.849 vs. 0.760). However, there was no difference in specificity between US-FNAC and CNB (0.997 vs. 1.000). US-FNAC with liquid-based preparation and CNB showed the highest diagnostic OR and AUC on the SROC, respectively.

CONCLUSION

Both US-FNAC and CNB are useful in preoperative assessments of ALNs in patients with breast cancer. Although the most sensitive test was found to be CNB in this study, there was no difference in specificity between various preoperative evaluations and the application of US-FNAC or CNB may be impacted by various factors.

A review on methods for diagnosis of breast cancer cells and tissues

Breast cancer has seriously been threatening physical and mental health of women in the world, and its morbidity and mortality also show clearly upward trend in China over time. Through inquiry, we find that survival rate of patients with early‐stage breast cancer is significantly higher than those with middle‐ and late‐stage breast cancer, hence, it is essential to conduct research to quickly diagnose breast cancer. Until now, many methods for diagnosing breast cancer have been developed, mainly based on imaging and molecular biotechnology examination. These methods have great contributions in screening and confirmation of breast cancer. In this review article, we introduce and elaborate the advances of these methods, and then conclude some gold standard diagnostic methods for certain breast cancer patients. We lastly discuss how to choose the most suitable diagnostic methods for breast cancer patients. In general, this article not only summarizes application and development of these diagnostic methods, but also provides the guidance for researchers who work on diagnosis of breast cancer.

Accuracy of CEUS-guided sentinel lymph node biopsy in early-stage breast cancer: a study review and meta-analysis

Objective

To investigate whether preoperative localization of sentinel lymph node (SLN) by contrast-enhanced ultrasound (CEUS) can further improve the accuracy of sentinel lymph node biopsy (SLNB).

Method

Collect published literatures or conference reports by searching electronic databases. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) evaluation method is used to evaluate the quality of the screened literatures. The pooled risk ratio of cancer metastasis of SLN identified by CEUS (CE-SLN) compared with SLN not identified by CEUS (nonCE-SLN) is calculated, and the pooled diagnostic accuracy of CE-SLN for pathological status of all SLNs is also evaluated.

Result

Through search and screening, a total of 16 studies were included, of which five and seven studies, respectively, entered the meta-analysis of metastatic risk ratio and diagnostic accuracy. The localization rate of preoperative CEUS for sentinel lymph nodes was 70 to 100%. The meta-analysis shows that the risk of metastasis of SLN identified by CEUS is significantly higher than that not identified by CEUS, 26.0% vs 4.6%, and risk ratio (RR) is 6.08 (95% CI 4.17–8.85). In early-stage breast cancer, the pathological status of CE-SLN is a good representative of all SLNs, with a pooled sensitivity of 98% (95% CI 0.94–1.00), pooled specificity of 100% (95% CI 0.99–1.00), diagnostic odds ratio (DOR) of 2153.18 (95% CI 476.53–9729.06), and area under the subject receiver operating characteristic (SROC) curve of 0.9968.

Conclusion

In early-stage breast cancer, preoperative localization of SLN by CEUS is expected to further improve the accuracy of sentinel lymph node biopsy (SLNB).

Probability analysis of axillary lymph node metastasis in breast cancer patients using particle space-time distribution model

The possibility of axillary lymph node metastasis differs in different breast cancer patients and is the strongest prognostic indicator in breast cancer. The existing studies mainly explored the relationship of axillary ultrasound imaging and axillary lymph node metastasis, without exploring whether ultrasound imaging of breast tumour can affect and perform axillary lymph node prediction. Therefore, this Letter proposes a novel particle space-time distribution model to find the correlation between contrast-enhanced ultrasonography of breast tumour and axillary lymphatic metastasis. Starting from the imaging principle of dynamic contrast-enhanced ultrasonography, the particle space-time distribution model not only comprises space-time features of contrast-enhanced ultrasonography with an encoder-decoder network, but also the flow field information of microbubble particles is integrated into the space-time features that better serves the metastasis prediction by enhancing the particle distribution information. Extensive experiments on real patients have demonstrated that dynamic contrast-enhanced ultrasonography of breast tumour can be used to predict the probability of lymphatic metastasis. This conclusion can be interpretable from the clinical and pathological perspectives.