What Is a False Negative Sentinel Node Biopsy: Definition, Reasons and Ways to Minimize It?

Real-World Implications of the SOUND Trial

BACKGROUND

The SOUND trial demonstrated that omission of sentinel lymph node biopsy (SLNB) is noninferior to axillary staging in patients with early-stage breast cancer (BC) and negative axillary ultrasound (AxUS). We examined the generalizability of these findings in patients with hormone receptor (HR)+HER2- disease.

METHODS

Patients with cT1N0M0, HR+HER2- BC and negative AxUS undergoing breast conservation with SLNB from 2016 to 2023 were identified from a prospectively maintained database. Clinicopathologic characteristics, disease burden, adjuvant treatment, and oncologic outcomes were examined and compared with the SLNB arm of the SOUND trial. In postmenopausal patients, the impact of nodal status and 21-gene recurrence score on chemotherapy recommendations were also examined.

RESULTS

Of 3972 patients with cT1N0M0 HR+HER2- breast cancer, 544 underwent AxUS; 312 met SOUND eligibility criteria. Median age was 57 (interquartile range [IQR] 48-64) years, and 199 (63.8%) were postmenopausal. Median (IQR) tumor size was 1.3 (0.9-1.7) cm, and 260 (83.3%) tumors were grade 1 or 2. Sentinel lymph node biopsy was positive in 38 (12.2%) patients. Only three (0.4%) had ≥ 4 positive lymph nodes. At a median follow-up of 26.2 (IQR 10.8-38.2) months, there were no axillary recurrences and one (0.3%) distant recurrence. Among postmenopausal women with recurrence score ≤ 25, chemotherapy recommendations were not associated with nodal status.

CONCLUSIONS

Examination of our real-world HR+ HER2- "SOUND-eligible" population suggests that nodal disease burden and oncologic outcomes are similar to the SOUND trial population, supporting careful implementation of trial results into multidisciplinary practice. In postmenopausal patients, omission of SLNB does not appear to impact adjuvant chemotherapy recommendations.

Machine Learning Prediction of Lymph Node Metastasis in Breast Cancer: Performance of a Multi-institutional MRI-based 4D Convolutional Neural Network

Purpose To develop a custom deep convolutional neural network (CNN) for noninvasive prediction of breast cancer nodal metastasis. Materials and Methods This retrospective study included patients with newly diagnosed primary invasive breast cancer with known pathologic (pN) and clinical nodal (cN) status who underwent dynamic contrast-enhanced (DCE) breast MRI at the authors' institution between July 2013 and July 2016. Clinicopathologic data (age, estrogen receptor and human epidermal growth factor 2 status, Ki-67 index, and tumor grade) and cN and pN status were collected. A four-dimensional (4D) CNN model integrating temporal information from dynamic image sets was developed. The convolutional layers learned prognostic image features, which were combined with clinicopathologic measures to predict cN0 versus cN+ and pN0 versus pN+ disease. Performance was assessed with the area under the receiver operating characteristic curve (AUC), with fivefold nested cross-validation. Results Data from 350 female patients (mean age, 51.7 years ± 11.9 [SD]) were analyzed. AUC, sensitivity, and specificity values of the 4D hybrid model were 0.87 (95% CI: 0.83, 0.91), 89% (95% CI: 79%, 93%), and 76% (95% CI: 68%, 88%) for differentiating pN0 versus pN+ and 0.79 (95% CI: 0.76, 0.82), 80% (95% CI: 77%, 84%), and 62% (95% CI: 58%, 67%), respectively, for differentiating cN0 versus cN+. Conclusion The proposed deep learning model using tumor DCE MR images demonstrated high sensitivity in identifying breast cancer lymph node metastasis and shows promise for potential use as a clinical decision support tool. Keywords: MR Imaging, Breast, Breast Cancer, Breast MRI, Machine Learning, Metastasis, Prognostic Prediction Supplemental material is available for this article. Published under a CC BY 4.0 license.

Lymphatic flow mapping using near-infrared fluorescence imaging with indocyanine green helps to predict lymph node metastasis intraoperatively in patients with esophageal or esophagogastric junction cancer not treated with neoadjuvant chemotherapy

BACKGROUND

Lymphatic flow mapping using near-infrared fluorescence (NIR) imaging with indocyanine green (ICG) has been used for the intraoperative prediction of lymph node metastasis in esophageal or esophagogastric junction cancer. However, a consistent method that yields sufficient diagnostic quality is yet to be confirmed. This study explored the diagnostic utility of our newly established lymphatic flow mapping protocol for predicting lymph node metastasis in patients with esophageal or esophagogastric junction cancer.

METHODS

We injected 0.5 mL of ICG (500 μg/mL) into the submucosal layer at four peritumoral points on the day before surgery for 54 patients. We performed lymphatic flow mapping intraoperatively using NIR imaging. After determining the NIR status and presence of metastases, evaluable lymph node stations on in vivo imaging and all resected lymph nodes were divided into four categories: ICG+meta+ (true positive), ICG+meta- (false positive), ICG-meta+ (false negative), and ICG-meta- (true negative).

RESULTS

The distribution of ICG+ and meta+ lymph node stations differed according to the primary tumor site. Sensitivity and specificity for predicting meta+ lymph nodes among ICG+ ones were 50% (95% CI 41-59%) and 75% (73-76%), respectively. Predicting meta+ lymph node stations among ICG+ stations improved these values to 66% (54-77%) and 77% (74-79%), respectively. Undergoing neoadjuvant chemotherapy was an independent risk factor for having meta+ lymph nodes with false-negative diagnoses (odds ratio 4.82; 95% CI 1.28-18.19). The sensitivity of our technique for predicting meta+ lymph nodes and meta+ lymph node stations in patients who did not undergo neoadjuvant chemotherapy was 79% (63-90%) and 83% (61-94%), respectively.

CONCLUSION

Our protocol potentially helps to predict lymph node metastasis intraoperatively in patients with esophageal or esophagogastric junction cancer undergoing esophagectomy who did not undergo neoadjuvant chemotherapy.

Role of Sentinel Lymph Node Biopsy for Skin Cancer Based on Clinical Studies

The sentinel lymph node is the first lymph node from the primary tumor. Sentinel lymph node biopsy (SLNB) is a surgical procedure that can detect occult nodal metastasis with relatively low morbidity. It may also have a therapeutic effect via regional disease control. The Multicenter Selective Lymphadenectomy-I (MSLT-I) trial revealed a prognostic benefit from SLNB in melanoma patients. However, it remains unclear whether there is a prognostic benefit from SLNB in patients with nonmelanoma skin cancer owing to a lack of randomized prospective studies. Nevertheless, SLNB provides important information about nodal status, which is one of the strongest factors to predict prognosis and may guide additional nodal treatment. Currently, SLNB is widely used in the management of not only patients with melanoma but also those with nonmelanoma skin cancer. However, the utilization and outcomes of SLNB differ among skin cancers. In addition, SLNB is not recommended for routine use in all patients with skin cancer. In this review, we provide a summary of the role of SLNB and of the indications for SLNB in each skin cancer based on previously published articles.

Who Needs Level III Lymph Node Dissection in Carcinoma Breast-Study from a Tertiary Care Center

In Indian females, breast cancer is the most common cancer with a late stage of presentation leading to one-third of patients undergoing modified radical mastectomy (MRM). Our study is undertaken to find out predictors of level III axillary lymph node metastasis in breast cancer and who needs complete axillary lymph node dissection (ALND). Retrospective study of 146 patients who undergone MRM or breast-conserving surgery (BCS) with complete ALND at Kidwai Memorial Institute of Oncology was done, and data was analyzed to find out the frequency of level III lymph nodes and the demographic relation and its relation to positive lymph nodes in level I + II. Positive metastatic level III lymph node was found in 6% of patients, with the median age of the patient in our study with level III positivity was 48.5 years with 63% pathological stage II with 88% perinodal spread (PNS)- and lymphovascular invasion (LVI)-positive. Involvement of level III lymph node was associated with gross disease in level I + II lymph node having more than four lymph node-positive and with pT3 stage or more which has higher chances of level III lymph node involvement. Level III lymph node involvement, though rare in early-stage breast cancer, is associated with larger clinical and pathological sizes (T3 or more), more than 4 lymph node-positive in level I + II and with PNS and LVI. Hence, based on these results, we recommend that for inpatient with more than 5-cm tumor size and those with the gross disease in axilla, complete ALND is recommended.

Development and Validation of a Nomogram for Predicting Axillary Lymph Node Metastasis in Breast Cancer

BACKGROUND

Axillary lymph node (ALN) status is a key prognosis indicator for breast cancer patients. To develop an effective tool for predicting axillary lymph node metastasis in breast cancer, a nomogram was established based on mRNA expression data and clinicopathological characteristics.

MATERIALS AND METHODS

A 1062 breast cancer patients with mRNA data and clinical information were obtained from The Cancer Genome Atlas (TCGA). We first analyzed the differentially expression genes (DEGs) between ALN positive and ALN negative patients. Then, logistic regression, least absolute shrinkage and selection operator (Lasso) regression, and backward stepwise regression were performed to select candidate mRNA biomarkers. The mRNA signature was constructed by the mRNA biomarkers and corresponding Lasso coefficients. The key clinical factors were obtained by Wilcoxon-Mann-Whitney U test or Pearson's χ² test. Finally, the nomogram for predicting axillary lymph node metastasis was developed and evaluated by concordance index (C-index), calibration curve, decision curve analysis (DCA), and receptor operating characteristic (ROC) curve. Furthermore, the nomogram was externally validated using Gene Expression Omnibus (GEO) dataset.

RESULTS

The nomogram for predicting ALN metastasis yielded a C-index of 0.728 (95% CI: 0.698-0.758) and an AUC of 0.728 (95% CI: 0.697-0.758) in the TCGA cohort. In the independent validation cohort, the C-index and AUC of the nomogram were up to 0.825 (95% CI: 0.695-0.955) and 0.810 (95% CI: 0.666-0.953), respectively.

CONCLUSION

This nomogram could predict the risk of axillary lymph node metastasis in breast cancer and may provide a reference for clinicians to design individualized axillary lymph node management strategies.

Contrast-enhanced and indirect computed tomography lymphangiography accurately identifies the cervical lymphocenter at risk for metastasis in pet dogs with spontaneously occurring oral neoplasia

For dogs with oral tumors, cervical lymph node (LN) metastasis alters treatment and prognosis. It is therefore prudent to make an accurate determination of the clinical presence (cN+ neck) or absence (cN0 neck) of metastasis prior to treatment. Currently, surgical LN extirpation with histopathology is the gold standard for a diagnosis of metastasis. Yet, recommendations to perform elective neck dissection (END) for staging are rare due to morbidity. Sentinel lymph node (SLN) mapping with indirect computed tomography lymphangiography (ICTL) followed by targeted biopsy (SLNB) is an alternative option to END. In this prospective study, SLN mapping followed by bilateral END of all mandibular LNs (MLNs) and medial retropharyngeal LNs (MRLNs) was performed in 39 dogs with spontaneously occurring oral neoplasia. A SLN was identified by ICTL in 38 (97%) dogs. Lymphatic drainage patterns were variable although most often the SLN was identified as a single ipsilateral MLN. In the 13 dogs (33%) with histopathologically confirmed LN metastasis, ICTL correctly identified the draining lymphocentrum in all (100%). Metastasis was confined to the SLN in 11 dogs (85%); 2 dogs (15%) had metastasis beyond the SLN ipsilaterally. Contrast enhanced CT features had good accuracy in predicting metastasis, with short axis measurements less than 10.5 mm most predictive. ICTL imaging features alone were unable to predict metastasis. Cytologic or histopathologic SLN sampling is recommended prior to treatment to inform clinical decision-making. This is the largest study to show potential clinical utility of minimally invasive ICTL for cervical LN evaluation in canine oral tumors.

Classification of Metastatic Lymph Nodes In Vivo Using Quantitative Ultrasound at Clinical Frequencies

Quantitative ultrasound (QUS) methods characterizing the backscattered echo signal have been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods have been successful in detecting metastases in surgically excised lymph nodes (LNs), but limited evidence exists regarding the efficacy of QUS for evaluating LNs in vivo at clinical frequencies (2-10 MHz). In this study, a clinical scanner and 10-MHz linear probe were used to collect radiofrequency (RF) echo data of LNs in vivo from 19 cancer patients. QUS methods were applied to estimate parameters derived from the backscatter coefficient (BSC) and statistics of the envelope-detected RF signal. QUS parameters were used to train classifiers based on linear discriminant analysis (LDA) and support vector machines (SVMs). Two BSC-based parameters, scatterer diameter and acoustic concentration, were the most effective for accurately detecting metastatic LNs, with both LDA and SVMs achieving areas under the receiver operating characteristic (AUROC) curve ≥0.94. A strategy of classifying LNs based on the echo frame with the highest cancer probability improved performance to 88% specificity at 100% sensitivity (AUROC = 0.99). These results provide encouraging evidence that QUS applied at clinical frequencies may be effective at accurately identifying metastatic LNs in vivo, helping in diagnosis while reducing unnecessary biopsies and surgical treatments.

Guidelines for breast cancer management in Bosnia and Herzegovina

Breast cancer is the most common cancer among women. In Bosnia and Herzegovina, accurate data on the status of breast cancer are lacking due to the absence of a central registry. Multiple international guidelines imply that institutions that monitor breast cancer patients should have optimal therapeutic options for treatment. In addition, there have been several international consensus guidelines written on the management of breast cancer. Application of consensus guidelines has previously been demonstrated to have a positive influence on breast cancer care. The importance of specialty breast centers has previously been reported. As part of the 2021 Bosnian-Herzegovinian American Academy of Arts and Sciences (BHAAAS) conference in Mostar, a round table of multidisciplinary specialists from Bosnia and Herzegovina and the diaspora was held. All were either members of BHAAAS or regularly participate in collaborative projects. The focus of the consortium was to write the first multidisciplinary guidelines for the general management of breast cancer in Bosnia and Herzegovina. Guidelines were developed for each area of breast cancer treatment and management. These guidelines will serve as a resource for practitioners managing breast cancer in the Bosnia and Herzegovina region. This might also be of benefit to the ministry of health and any future investors interested in developing breast cancer care policies in this region of the world.

Magnetic resonance imaging evaluation of single axillary lymph node metastasis in breast cancer: Emphasis on the location of lymph nodes

To evaluate the frequency and location of abnormal lymph nodes (LNs) in breast cancer patients with a single axillary lymph node (ALN) metastasis on breast magnetic resonance imaging (MRI). We retrospectively reviewed the MRI findings of 219 consecutive patients with breast cancer with single ALN metastasis who were surgically confirmed at our institution between January 2018 and December 2018. The morphological features and locations of the abnormal LN on MRI were analyzed. Pathology reports were reviewed to evaluate the size of the metastases and whether they were sentinel LNs (SLNs). Of the 219 patients with a single ALN metastasis, 56 (25.6%) showed abnormal MRI findings. Of these, 54 (96.4%) had either the lowest or second-lowest LN in the level I axilla. In 184 (91.5%) of 201 patients who underwent SLN biopsy, the metastatic LN were SLN. Macrometastases were found more frequently in cases with abnormal LNs than in those with normal-looking LNs (P = .004). The most frequent morphological feature of metastatic ALNs was a diffuse cortical thickening of 3 to 5 mm (37.5%). Although MRI findings of single ALN metastasis in breast cancer patients are none or minimal, abnormalities are observed in the lowest or second-lowest LN in the lower axilla when present, suggesting the location of the SLNs.

Study on intraoperative localization of sentinel lymph nodes using freehand SPECT in breast cancer patients

INTRODUCTION

The diagnostic and therapeutic approach to axillary lymph nodes is considered indispensable in the treatment of breast cancer patients.

AIM

To investigate the effectiveness of 3D freehand SPECT (fhSPECT) in sentinel lymph node (SLN) mapping in breast cancer, compared with the use of a conventional gamma probe.

MATERIAL AND METHODS

We retrospectively compared the fhSPECT lymph node mapping modality, with gamma probe detection in early-stage, clinically node-negative breast cancer patients, with biopsy-confirmed malignancy. The two techniques were compared based on the average number of LNs excised per axilla. The duration of SLN mapping was also compared between the two groups. The performance of the two methods on obese and post-systemic therapy patients was evaluated. FhSPECT was used in 150 cases, while the gamma probe was employed in 50 cases.

RESULTS

FhSPECT detected at least 3 nodes in 83.3% of the patients vs. 72.0% with the γ-probe (p = 0.107). The mean number of SLNs excised per axilla was 3.66 using the γ-probe and 4.18 with fhSPECT (p = 0.03). The average surgical time was 39 ±7 min with the γ-probe and 37.54 ±17 min with fhSPECT (p = 0.228). Sentinel lymph node biopsy (SLNB) mean surgical time evolved from 40.2 ±20.77 min to 32.35 ±10.46 min (p = 0.033). In obese patients, a reduction in surgical times was noted from 45.5 ±3.09 min to 44.04 ±20.9 (p = 0.27), in addition to a significant increase in average LN detection in the fhSPECT group (4.26 ±1.44) compared to the γ-probe group (3.2 ±1.65) (p = 0.043).

CONCLUSIONS

The use of the fhSPECT modality is effective and safe, and, when compared to the γ-probe, has significant advantages in SLN mapping.

iTRAQ proteomics of sentinel lymph nodes for identification of extracellular matrix proteins to flag metastasis in early breast cancer

Patients with early breast cancer are affected by metastasis to axillary lymph nodes. Metastasis to these nodes is crucial for staging and quality of surgery. Sentinel Lymph Node Biopsy that is currently used to assess lymph node metastasis is not effective. This necessitates identification of biomarkers that can flag metastasis. Early stage breast cancer patients were recruited. Surgical resection of breast was followed by identification of sentinel lymph nodes. Fresh frozen section biopsy was used to assign metastatic and non-metastatic sentinel lymph nodes. Discovery phase included iTRAQ proteomics coupled with mass spectrometric analysis to identify differentially expressed proteins. Data is available via ProteomeXchange with identifier PXD027668. Validation was done by bioinformatic analysis and ELISA. There were 2398 unique protein groups and 109 differentially expressed proteins comparing metastatic and non-metastatic lymph nodes. Forty nine proteins were up-regulated, and sixty proteins that were down regulated in metastatic group. Bioinformatic analysis showed ECM-receptor interaction pathways to be implicated in lymph node metastasis. ELISA confirmed up-regulation of ECM proteins in metastatic lymph nodes. ECM proteins have requisite parameters to be developed as a diagnostic tool to assess status of sentinel lymph nodes to guide surgical intervention in early breast cancer.

Axillary ultrasonography combined with pre-operative wire localisation of clipped node in nodal restaging after neoadjuvant chemotherapy in node positive breast cancer patients: a pilot study

OBJECTIVE

To evaluate the role of axillary ultrasonography (axUS) and ultrasound-guided pre-operative wire localisation of pre-treatment positive clipped node (CN) for prediction of nodal response to neoadjuvant chemotherapy (NACT) in node positive breast carcinoma patients.

METHODS AND MATERIALS

A prospective study was conducted between June 2018 and August 2020 after Ethics Committee approval. Breast carcinoma patients (cT1-cT4b) with palpable axillary nodes (cN1-cN3) and suitable for NACT were recruited after written informed consent. Single, most suspicious node was biopsied and clipped. Nodal response to NACT was assessed on axUS. Wire localisation of CN was performed prior to axillary lymph node dissection (ALND). Diagnostic performances of axUS and CN excision were assessed.

RESULTS

Of the 69 patients evaluated, 32 patients (mean age, 43.5 ± 11.8 years; females, 31/32 [97%]; pre-menopausal, 18/32 [56.3%]) with metastatic nodes who received NACT were included. Nodal pathological complete response rate was 34.4% (11/32) overall and 70% (7/10) in patients with ≤2 suspicious nodes on pre-NACT axUS. False-negative rates (FNRs) of axUS and CN excision were 4.8% and 28.6% respectively. Combination of post-NACT axUS and CN excision had an FNR of 4.8% overall and 0% in patients with ≤2 suspicious nodes on pre-NACT axUS.

CONCLUSION

Combination of AxUS and ultrasound-guided wire localisation of pre-treatment positive CN has high diagnostic accuracy for nodal restaging after NACT in node positive breast cancer patients.

ADVANCES IN KNOWLEDGE

Addition of axUS assessment to wire localisation of CN reduces its FNR for detecting residual metastasis after NACT.

Sentinel lymph node mapping in breast cancer patients following neoadjuvant chemotherapy: systematic review and meta-analysis about head to head comparison of cN0 and cN + patients

PURPOSE

The effectiveness of sentinel lymph node (SLN) mapping and biopsy following neoadjuvant chemotherapy (NAC) in axillary lymph node staging of breast cancer (BCa) patients with initial clinical node positive status (cN +) compared to clinical node negative status (cN0) is not yet known. The aim of this meta-analysis was to compare the accuracy of SLN mapping following NAC in cN + and cN0 BCa patients.

METHODS

PubMed and Scopus were comprehensively reviewed to retrieve all the studies that performed SLN mapping/biopsy and standard axillary lymph node dissection on cN0 and cN + BCa patients following NAC. Pooled detection and false negative rates for N0 and N + patients including 95% confidence interval values (95% CI) were evaluated. Odds ratio (OR) and risk difference (RD) of SLN detection failure and false negative results were compared between two groups.

RESULTS

A total of 27 articles were included for SLN detection rate evaluation and 17 for false negative assessment. The OR and RD of detection failure in N + group compared with N0 group following NAC were 2.22 (p = 0.00, 95% CI 1.4-3.4) and 4% (p = 0.00, 95% CI 2-6%), respectively. The OR and RD of false negative rate were 1.6 (p = 0.01, 95% CI 1-2.6) and 8% (p = 0.02, 95% CI 1-14%), respectively.

CONCLUSION

SLN mapping in BCa patients following NAC shows high risk of detection failure and high false negative rate of SLN biopsy in cN + patients. In comparison with cN0 BCa patients, SLN mapping and biopsy after NAC was associated with almost two times higher odds of detection failure and false negative results in cN + patients; therefore, this method should not be recommended in this group of patients.

Non-invasive prediction of lymph node status for patients with early-stage invasive breast cancer based on a morphological feature from ultrasound images

Background

This study aimed to estimate the value of a morphological feature on ultrasound (US) for preoperative diagnosis of axillary lymph node (ALN) status in patients with early-stage invasive breast cancer (ESIBC).

Methods

In this retrospective work, a total of 239 ESIBC patients, were recruited, and their preoperative US images and postoperative pathology results were collected. The relationship between US images based on morphological features and ALN metastasis was investigated. The tumor circularity and US-reported ALN status were developed as a nomogram to predict the ALN status.

Results

Among the 239 participants, 82 (34.31%) had ALN metastasis, and 157 (65.69%) did not. There was a statistically significant difference in tumors between participants diagnosed with and without ALN metastasis. The median value was 0.47 vs. 0.62 (P<0.001) in the training group, respectively, and the value was 0.50 vs. 0.60 (P<0.001) in the validation group, respectively. The clinical model nomogram was shown to have high efficiency in predicting ALN status among our research population. The area under the curve (AUC) was 0.89 in the training group and 0.90 in the validation group and the accuracy was 85.79% and 81.63%, respectively.

Conclusions

The clinical model nomogram based on tumor circularity and US-reported ALN status is a non-invasive approach for ALN metastasis prediction in ESIBC patients with high efficacy.

Fundamental Statistical Concepts in Clinical Trials and Diagnostic Testing

This article explores basic statistical concepts of clinical trial design and diagnostic testing, or how one starts with a question, formulates it into a hypothesis on which a clinical trial is then built, and integrates it with statistics and probability, such as determining the probability of rejecting the null hypothesis when it is actually true (type I error) and the probability of failing to reject the null hypothesis when it is false (type II error). There are a variety of tests for different types of data, and the appropriate test must be chosen for which the sample data meet the assumptions. Correcting type I error in the presence of multiple testing is needed to control the error's inflation. Within diagnostic testing, identifying false-positive and false-negative results is critical to understanding the performance of a test. These are used to determine the sensitivity and specificity of a test along with the test's negative predictive value and positive predictive value. These quantities, specifically sensitivity and specificity, are used to determine the accuracy of a diagnostic test using receiver-operating-characteristic curves. These concepts are briefly introduced to provide a basic understanding of clinical trial design and analysis, with references to allow the reader to explore various concepts at a more detailed level if desired.

New classifications of axillary lymph nodes and their anatomical-clinical correlations in breast surgery

Background

In the last decade, two research groups, the French group by Clough et al. (Br J Surg. 97:1659–65, 2010) and the Chinese one by Li et al. (ISRN Oncol 2013:279013, 2013), proposed two types of classification of axillary lymph nodes in breast cancer, identifying novel anatomic landmarks for dividing the axillary space in lymph node dissection.

Main body

Knowledge of the exact location of the sentinel node helps to focus the surgical dissection and to reduce the morbidity of sentinel lymph node biopsy procedures, in particular the risk of arm lymphedema, without compromising sensitivity.

Conclusion

In this article, we aimed at focusing on the clinical impact that the most recent classifications of axillary lymph nodes have obtained in literature, highlighting the importance of defining new demarcations to preserve the axillary lymph nodes as much as possible in breast surgery.

Sentinel lymph node biopsy in oral cavity cancer using indocyanine green: A systematic review and meta-analysis

This meta-analysis was conducted to evaluate the value of indocyanine green (ICG) in guiding sentinel lymph node biopsy (SLNB) for patients with oral cavity cancer. An electronic database search (PubMed, MEDLINE, Cochrane Library, Embase, and Web of Science) was performed from their inception to June 2020 to retrieve clinical studies of ICG applied to SLNB for oral cavity cancer. Data were extracted from 14 relevant articles (226 patients), and 9 studies (134 patients) were finally included in the meta-analysis according to the inclusion and exclusion criteria. The pooled sentinel lymph node (SLN) sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 88.0% (95% confidence interval [CI], 74.0-96.0), 64.0% (95% CI, 61.0-66.0), 2.45 (95% CI, 1.31-4.60), 0.40 (95% CI, 0.17-0.90), and 7.30 (95% CI, 1.74-30.68), respectively. The area under the summary receiver operating characteristic curve was 0.8805. In conclusion, ICG applied to SLNB can effectively predict the status of regional lymph nodes in oral cavity cancer.

Proteomics of Sentinel Lymph Nodes in Early Breast Cancer for Identification of Thymidylate Synthase as a Potential Biomarker to Flag Metastasis: A Preliminary Study

Introduction

Breast cancer is the second most common cancer in women across the world. Some of the patients who present in the early stage of disease are affected by metastasis to the axillary group of lymph nodes. The first among this group that is affected is called as sentinel lymph node, and its diagnosis is crucial for the staging of cancer thereby dictating the type of surgical therapy. Therefore, the sentinel lymph node status provides the most relevant information to the surgeon and patient prognosis. The expanded utilization of breast conservation surgery has declined the morbidity associated with mastectomy and axillary lymph node surgery. Recent interest is, therefore, centered on techniques that allow accurate assessment of the sentinel lymph node metastasis. A current procedure such as sentinel lymph node biopsy (SLNB) that is used to assess axillary lymph node metastasis is neither specific nor sensitive, and besides, it is time-consuming.

Objective

To compare the protein profiles between metastatic and non-metastatic lymph nodes to identify a biomarker that can flag lymph node metastasis.

Materials and Methods

Women with early breast cancer were screened using mammography imaging and recruited to the study. Surgical resection was done to remove the breast tissue, and sentinel lymph node was identified using fluorescein and methylene blue tracer. Lymph node was sliced, and one set was sent for histopathology, which was considered the gold standard to assess the metastatic status of the lymph node. One set of slices was taken for proteomic experiments. Proteins were labelled with fluorescent cyanine tags and were subjected to difference gel electrophoresis experiment. Differentially expressed spots that had at least a twofold relative ratio and consistent pattern across three sets of biological replicate experiments were marked. Gel spots were trypsin digested and identified on mass spectrometry machine. Validation study was done by Western blot experiment on the same set of samples.

Results

Thymidylate synthase has a twofold higher expression in the metastatic sentinel lymph nodes as compared to non-metastatic lymph nodes in early breast cancer patients.

Conclusion

Differential in gel expression proteomics is an ideal platform for the identification of potential protein biomarker candidates that can differentiate metastatic from non-metastatic lymph nodes in early breast cancer. The identification of thymidylate synthase offers a scope to develop an on-table diagnostic kit to assess the status of sentinel lymph nodes during mastectomy procedure to guide surgical management of axillary lymph nodes in early breast cancer.

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Predictive performance of ultrasonography-based radiomics for axillary lymph node metastasis in the preoperative evaluation of breast cancer

PURPOSE

The purpose of this study was to evaluate the predictive performance of ultrasonography (US)-based radiomics for axillary lymph node metastasis and to compare it with that of a clinicopathologic model.

METHODS

A total of 496 patients (mean age, 52.5±10.9 years) who underwent breast cancer surgery between January 2014 and December 2014 were included in this study. Among them, 306 patients who underwent surgery between January 2014 and August 2014 were enrolled as a training cohort, and 190 patients who underwent surgery between September 2014 and December 2014 were enrolled as a validation cohort. To predict axillary lymph node metastasis in breast cancer, we developed a preoperative clinicopathologic model using multivariable logistic regression and constructed a radiomics model using 23 radiomic features selected via least absolute shrinkage and selection operator regression.

RESULTS

In the training cohort, the areas under the curve (AUC) were 0.760, 0.812, and 0.858 for the clinicopathologic, radiomics, and combined models, respectively. In the validation cohort, the AUCs were 0.708, 0.831, and 0.810, respectively. The combined model showed significantly better diagnostic performance than the clinicopathologic model.

CONCLUSION

A radiomics model based on the US features of primary breast cancers showed additional value when combined with a clinicopathologic model to predict axillary lymph node metastasis.

Preliminary study of contrast-enhanced ultrasound in combination with blue dye vs. indocyanine green fluorescence, in combination with blue dye for sentinel lymph node biopsy in breast cancer

Background

This preliminary study aimed to examine the feasibility of sentinel lymph node biopsy (SLNB) using contrast-enhanced ultrasound (CEUS) vs. indocyanine green fluorescence (ICG), combined with blue dye in patients with breast cancer.

Methods

This was a retrospective study of consecutive female patients with invasive stage I-III (based on pre-operative physical examination and imaging) primary breast cancer at the Peking Union Medical College Hospital between 01/2013 and 01/2015 who underwent preoperative SLNB by ICG + blue dye or CEUS + blue dye. The numbers of detected SLNs, detection rates, and recurrence-free survival (RFS) rates were compared between the two groups.

Results

A total of 443 patients were included. The detection rates of SLNs in the CEUS + blue dye and ICG + blue dye groups were 98.4 and 98.1%, respectively (P = 0.814). The average numbers of SLNs detected per patient showed no significant difference between the two groups (3.06 ± 1.33 and 3.12 ± 1.31 in the CEUS + blue dye and ICG + blue dye groups, respectively; P = 0.659). After a median follow-up of 46 months, five patients in the CEUS + blue dye group and 15 in the ICG + blue dye group had recurrence. RFS rates showed no significant difference (P = 0.55).

Conclusion

This preliminary study suggests that CEUS + blue dye and ICG + blue dye are both feasible for SLN detection in breast cancer.

Ultrasound-based radiomics nomogram: A potential biomarker to predict axillary lymph node metastasis in early-stage invasive breast cancer

PURPOSE

To establish a radiomics nomogram integrating clinical factors and radiomics features from ultrasound for the preoperative diagnosis axillary lymph node (ALN) status in patients with early-stage invasive breast cancer (EIBC).

MATERIALS AND METHODS

Between September 2016 and December 2018, four hundred twenty-six ultrasound manually segmented images of patients with EIBC were enrolled in our retrospective study, which were divided into a primary cohort (n = 300) and a validation cohort (n = 126). A radiomics signature was built with the least absolute shrinkage and selection operator (LASSO) algorithm in the primary cohort. Multivariable logistic regression analysis was used to establish a radiomics nomogram model based on radiomics signature and clinical variables. The performance of nomogram was quantified with respect to discrimination and calibration. The radiomics model was further evaluated in the internal validation cohort.

RESULTS

The radiomics signature, consisted of fourteen selected ALN-status-related features, achieved moderate prediction efficacy with an area under the curve (AUC) of 0.78 and 0.71 in the primary and validation cohorts respectively. The radiomics nomogram, comprising tumor size, US-reported LN status and radiomics signature, showed good calibration and favorite performance for ALN detection (AUC 0.84 and 0.81 in the primary and validation cohort). The decision curve which was demonstrated the radiomics nomogram displayed good clinical utility.

CONCLUSION

The radiomics nomogram could hold promise as a non-invasive and reliable tool in predicting ALN metastasis and may facilitate to develop more effective preoperative decision-making.