Automated detection of vascular remodeling in tumor-draining lymph nodes by the deep-learning tool HEV-finder.

Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high-throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep-learning model and created a graphical user interface for visualization of the results. The tool, named the HEV-finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV-finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large-scale, fully automated, and user-independent, image-based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Magnetic-Guided Axillary UltraSound (MagUS) Sentinel Lymph Node Biopsy and Mapping in Patients with Early Breast Cancer. A Phase 2, Single-Arm Prospective Clinical Trial.

Lymph Node Dissection (SLND) is standard of care for diagnosing sentinel lymph node (SLN) status in patients with early breast cancer. Study aim was to determine whether the combination of Superparamagnetic iron oxide nanoparticles (SPIO) MRI-lymphography (MRI-LG) and a Magnetic-guided Axillary UltraSound (MagUS) with biopsy can allow for minimally invasive, axillary evaluation to de-escalate surgery. Patients were injected with 2 mL of SPIO and underwent MRI-LG for SN mapping. Thereafter MagUS and core needle biopsy (CNB) were performed. Patients planned for neoadjuvant treatment, the SLN was clipped and SLND was performed after neoadjuvant with the addition of isotope. During surgery, SLNs were controlled for signs of previous biopsy or clip. The primary endpoint was MagUS SLN detection rate, defined as successful SLN detection of at least one SLN of those retrieved in SLND. In 79 patients, 48 underwent upfront surgery, 12 received neoadjuvant and 19 had recurrent cancer. MagUS traced the SLN in all upfront and neoadjuvant cases, detecting all patients with macrometastases (n = 10). MagUS missed only one micrometastasis, outperforming baseline axillary ultrasound AUS (AUC: 0.950 vs. 0.508, p < 0.001) and showing no discordance to SLND (p = 1.000). MagUS provides the niche for minimally invasive axillary mapping that can reduce diagnostic surgery.