# The Diagnostic Value of Multimodal Contrast-Enhanced Ultrasound in Sentinel Lymph Nodes After Neoadjuvant Therapy for Breast Cancer

## TL;DR

This study explores new ultrasound techniques to better diagnose lymph node status in breast cancer patients after initial treatment.

## Contribution

A novel classification of percutaneous contrast-enhanced ultrasound patterns for sentinel lymph node assessment after neoadjuvant therapy.

## Key findings

- The new PCEUS classification showed higher diagnostic accuracy compared to existing methods.
- Despite improvements, diagnostic accuracy remains moderate with room for enhancement.
- No statistically significant differences were found between the evaluated methods.

## Abstract

Objective: Accurate diagnosis of sentinel lymph node (SLN) status after neoadjuvant therapy (NAT) for breast cancer is crucial for guiding axillary management. This study aimed to evaluate novel contrast-enhanced ultrasound (CEUS) patterns for assessing SLNs following NAT. Methods: We retrospectively analyzed clinical and imaging data from 279 breast cancer patients who completed NAT and underwent surgery between June 2019 and December 2024. Preoperative SLN evaluations included percutaneous CEUS (PCEUS), intravenous CEUS (IVCEUS), and conventional ultrasound (CUS). Intraoperative SLN biopsy was performed using methylene blue tracer, with pathological results serving as the gold standard. Diagnostic efficacy was compared among CUS, previously used PCEUS patterns, newly proposed PCEUS, IVCEUS, and combined CEUS. Results: The newly proposed PCEUS classified SLNs into six types, while IVCEUS categorized enhancement into three sequences and four patterns. Among the 347 SLNs detected via PCEUS, 292 (84.15%) were benign and 55 (15.85%) were malignant. The newly proposed PCEUS demonstrated higher diagnostic efficacy compared to CUS, prior PCEUS patterns, IVCEUS, and combined CEUS, with sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the curve of 49.1% (27/55), 86.3% (252/292), 40.3% (27/67), 90.0% (252/280), 80.4% (279/347), and 0.677 (95% CI: 0.625–0.726), respectively. However, DeLong tests revealed no statistically significant differences between the methods (all p > 0.05). Conclusions: The novel CEUS classification improved diagnostic accuracy for SLNs after NAT, though accuracy remains relatively low. Future integration of artificial intelligence may further enhance diagnostic efficacy.