Targeting c-MET for Endoscopic Detection of Dysplastic Lesions within Barrett's Esophagus Using EMI-137 Fluorescence Imaging.

Purpose: Esophageal cancer carries a poor prognosis with a 5-year overall survival of less than 20%. Barrett's esophagus increases the risk of esophageal adenocarcinoma. The aim of this study was to investigate the ability of EMI-137, a mesenchymal-epithelial transition factor (c-MET)-targeting optical imaging tracer, to detect dysplasia in Barrett's esophagus.

Hybrid Raman and Partial Wave Spectroscopy Microscope for the Characterization of Molecular and Structural Alterations in Tissue.

We present a hybrid Raman spectroscopy (RS) and partial wave spectroscopy (PWS) microscope for the characterization of molecular and structural tissue alterations. The PWS performance was assessed with surface roughness standards, while the Raman performance with a silicon crystal standard. We also validated the system on stomach and intestinal mouse tissues, two closely-related tissue types, and demonstrate that the addition of PWS information improves RS data classification for these tissue types from R = 0.

Intravascular ICG-enhanced NIRF-IVUS imaging to assess progressive atherosclerotic lesions in excised human coronary arteries.

Indocyanine green (ICG)-enhanced intravascular near-infrared fluorescence (NIRF) imaging enhances the information obtained with intravascular ultrasound (IVUS) by visualizing pathobiological characteristics of atherosclerotic plaques. To advance our understanding of this hybrid method, we aimed to assess the potential of NIRF-IVUS to identify different stages of atheroma progression by characterizing ICG uptake in human pathological specimens. After excision, 15 human coronary specimens from 13 adult patients were ICG-perfused and imaged with NIRF-IVUS.

Impact of signal-to-noise ratio and contrast definition on the sensitivity assessment and benchmarking of fluorescence molecular imaging systems.

Significance: Standardization of fluorescence molecular imaging (FMI) is critical for ensuring quality control in guiding surgical procedures. To accurately evaluate system performance, two metrics, the signal-to-noise ratio (SNR) and contrast, are widely employed. However, there is currently no consensus on how these metrics can be computed.