Abstract
Lymph node (LN) dissection followed by histological analysis is the current standard for diagnosis of LN metastasis but the method suffers from patient morbidity and low sensitivity of detection. Ultra-pH sensitive (UPS) nanoparticles show remarkable accuracy in the delineation of primary tumor margins for precision cancer surgery. Herein we investigate the effectiveness of UPS nanoparticles to detect cancer-involved LNs. Methods: We synthesized a series of indocyanine green (ICG) conjugated UPS nanoparticles with distinct pK(a) (UPS(5.3), UPS(6.1), and UPS(6.9)). Systemically administered UPS-ICG nanoparticles in the 4T1.2-BALB/cj mouse model were imaged with real-time, near-infrared fluorescence (NIRF) to guide removal of LNs. Ex vivo imaging of gross tissue enabled quantification of fluorescence intensity. Histological analysis was used as the gold standard diagnostic test. Results: Macrophage uptake of UPS nanoparticles elevates the background signal in benign LNs. However, cancer foci within LNs show distinctive clustering of UPS-ICG fluorescence. UPS(5.3) achieves accurate detection of metastatic LNs as shown by a receiver operating characteristic (ROC) area under the curve (AUC) of 0.96 ± 0.03. UPS(6.1) and UPS(6.9) offer decreased discriminatory power at ROC AUC of 0.73 ± 0.1 and 0.88 ± 0.07, respectively. Conclusions: All UPS compositions show cancer-specific discrimination of metastatic LNs over benign LNs with the best outcomes from UPS(5.3). Detection of micro-metastatic LNs (cancer foci < 2 mm) remains a challenge. This study provides information on the detection of LN status for image-guided resection of metastatic LNs.