Sentinel lymph node biopsy in breast cancer—an updated overview

Research gaps in sentinel lymph node biopsy in breast cancer

This commentary focuses on 5 questions that need to be answered when considering sentinel lymph node biopsy in breast cancer, aiming to highlight these issues and provide researchers with ideas to resolve.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

The location of metastatic lymph nodes and the evaluation of lymphadenectomy by near-infrared photoacoustic imaging with iridium complex nanoparticles

Histopathology evaluation and lymphadenectomy of node-positive patients is the usual procedure in clinical therapy. However, it requires days for the histopathology result analysis, which impedes intraoperative decision-making and immediate treatment. Noninvasive real-time imaging of metastatic lymph nodes can overcome these defects and help medical workers evaluate lymph nodes and make the operation decision more efficiently. Herein we developed iridium(III)-cyanine complex/bovine serum albumin (BSA)-based nanoparticles which are conjugated with folic acid (FA) (IrCy-FA NPs). The synthesized IrCy-FA NPs exhibit good biocompatibility, strong near-infrared absorption, and impressive lymph node accumulation and can serve as a photoacoustic (PA) imaging probe for lymph node imaging. Besides, the lymph nodes enriched with IrCy-FA NPs showing green color are easily visible to the naked eye, suggesting their potential as an intraoperative indicator. The real-time PA imaging with excellent contrast and high spatial resolution can promote efficient and reliable quantitative analysis of lymph nodes in vivo. By employing IrCy-FA NPs as the PA agent for lymph node imaging, we achieve effective pre-operative and post-operative evaluations of metastatic lymph nodes in lymphadenectomy. This study may provide helpful information for PA imaging guided colocalization and evaluation of lymph nodes and facilitate this method towards clinical trials.

Phosphorylcholine-conjugated gold-molecular clusters improve signal for Lymph Node NIR-II fluorescence imaging in preclinical cancer models

Sentinel lymph node imaging and biopsy is important to clinical assessment of cancer metastasis, and novel non-radioactive lymphographic tracers have been actively pursued over the years. Here, we develop gold molecular clusters (Au₂₅) functionalized by phosphorylcholine (PC) ligands for NIR-II (1000–3000 nm) fluorescence imaging of draining lymph nodes in 4T1 murine breast cancer and CT26 colon cancer tumor mouse models. The Au-phosphorylcholine (Au-PC) probes exhibit ‘super-stealth’ behavior with little interactions with serum proteins, cells and tissues in vivo, which differs from the indocyanine green (ICG) dye. Subcutaneous injection of Au-PC allows lymph node mapping by NIR-II fluorescence imaging at an optimal time of ~ 0.5 − 1 hour postinjection followed by rapid renal clearance. Preclinical NIR-II fluorescence LN imaging with Au-PC affords high signal to background ratios and high safety and biocompatibility, promising for future clinical translation.

Fluorescent tracers facilitate the identification and subsequent collection of tumour draining lymph node biopsies, enabling important clinical assessment. Here, the authors present a molecular gold nanocluster NIR-II fluorescent imaging probe and demonstrate its utility to visualise draining lymph nodes in breast and colon cancer mouse models.

Candidates of Genomic Tests in HR+/HER2- Breast Cancer Patients With 1-2 Positive Sentinel Lymph Node Without Axillary Lymph Node Dissection: Analysis From Multicentric Cohorts

Background

The genomic tests such as the MammaPrint and Oncotype DX test are being gradually applied for hormone receptor positive/HER-2 negative (HR+/HER2-) breast cancer patients with up to three positive axillary lymph nodes (ALNs). The first results from RxPONDER trial suggested that Oncotype DX could be applied to patients with 1-2 positive sentinel lymph nodes (SLNs) without axillary lymph node dissection (ALND), which constituted 37.4% of the intent-to-treat population. However, there was no distinctive research on how to apply genomic tests precisely to HR+/HER2- patients with 1-2 positive SLNs without ALND. The purpose was to construct a nomogram using the multi-center retrospective data to predict precisely which HR+/HER2- candidates with 1-2 positive SLNs could be subjected to genomic tests (≤ 3 positive lymph nodes).

Methods

We conducted a retrospective analysis of 18,600 patients with stage I-III breast cancer patients treated with sentinel lymph node biopsy (SLNB) in Shandong Cancer Hospital, Fudan University Shanghai Cancer Center, and West China Hospital. The univariate and multivariate logistic regression analysis was conducted to identify the independent predictive factors of having ≤ 3 positive nodes among patients with 1-2 positive SLNs. A nomogram was developed based on variables in the final model with p<0.05. Calibration of the nomogram was carried out by internal validation using the bootstrap resampling approach and was displayed using a calibration curve. The discrimination of the model was evaluated using the ROC curve.

Results

Based on the database of the three institutions, a total of 18,600 breast cancer patients were identified undergoing SLNB between May 2010 and 2020. Among the 1817 HR+/HER2- patients with 1-2 positive SLNs undergoing ALND, 84.2% harbored ≤ 3 totals metastatic ALNs. The multivariate logistic regression analysis identified imaging abnormal nodes (OR=0.197, 95%CI: 0.082-0.472), the number of positive SLNs (OR=0.351, 95%CI: 0.266-0.464), the number of negative SLNs (OR=1.639, 95%CI: 1.465-1.833), pathological tumor stage (OR=0.730, 95%CI: 0.552-0.964), and lympho-vascular invasion (OR=0.287, 95%CI: 0.222-0.398) as independent predictors for the proportion of patients with ≤ 3 total metastatic ALNs (all p<0.05). These five predictors were used to create a predictive nomogram. The AUC value was 0.804 (95%CI: 0.681-0.812, p<0.001). The calibration curve showed a satisfactory fit between the predictive and actual observation based on internal validation with a bootstrap resampling frequency of 1000.

Conclusion

The nomogram based on the multi-centric database showed a good accuracy and could assist the oncologist in determining precisely which HR+/HER2- candidates with 1-2 positive SLNs without ALND could perform genomic tests. In the era of SLNB and precision medicine, the combined application of genomic tests and SLNB could provide patients with a better strategy of dual de-escalation management, including the de-escalation of both surgery and systemic treatment.

Sentinel lymph node biopsy in breast cancer guided by CT lymphography; History, evolution and current applications

Sentinel lymph node biopsy (SLNB) has efficiently replaced axillary lymph node dissection (ALND) in axillary staging in node-negative breast cancer patients. Dual sentinel lymph node (SLN) localization using radioisotopes and blue dye is the standard technique for SLN mapping. Yet, nuclear medicine facilities are not widely available worldwide. In Japan, Computed tomography lymphography (CTLG) is presented as an SLN mapping technique which was first suggested in 2003 by Suga et al. Multiple subsequent studies confirmed the efficacy of CTLG in SLN mapping in breast cancer. Further applications of the technique followed; such as prediction of SLN metastasis using CTLG, the use of CTLG guided SLN biopsy after neoadjuvant therapy, video-assisted CTLG guided SLN biopsy, the use of real-time virtual sonography with 3-D CTLG, and preoperative localization of the CTLG mapped SLN using either real-time virtual sonography (RVS) guided Indocyanine green (ICG) injection or its marking using liquid charcoal and silver wire and the use of SPIO enhanced magnetic resonance imaging (MRI) for prediction of metastasis in SLNs detected by CTLG. This efficacy and variable applications open the door for conducting wide-scale randomized controlled trials to suggest using CTLG as an efficient alternative for the use of radioisotopes in SLN mapping in breast cancer patients, especially in low and middle-income countries.