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Comparison of NIR versus SWIR fluorescence imaging of indocyanine green using SI-derived metrics of image performance

Published

Author(s)

Banghe Zhu, Eva Sevick Muraca, Maritoni Litorja

Abstract

Recently, fluorescence imaging using shortwave-wavelength infrared light (SWIR, 1,000-2,000 nm) has been proposed as having advantage over conventional near-infrared fluorescence (NIRF) imaging due to the reduced tissue scattering, negligible autofluorescence, comparable tissue absorption, and the discovery that indocyanine green (ICG), used clinically as a NIRF contrast agent, also has fluorescence emission in SWIR regime. Images of ICG in small animals acquired by commercial Si-based and InGaAs-based imaging cameras have been qualitatively compared, however the lack of working standards to quantify performance of these imaging systems limits quantitative comparison. Without quantification using a traceable in vitro test, clinical adoption of rapidly evolving advances in both NIRF and SWIR imaging devices will become limited. In this work, we developed an ICG based fluorescent solid working standard calibrated with SI units (mW · sr-1 · cm-2) for quantification of measurement sensitivity of Si, GaAs- intensified Si, and InGaAs based camera systems, their signal-to-noise ratio (SNR), and contrast in non-clinical tests. In addition, we present small animal and large animal imaging with ICG for qualitative comparison of the same SWIR fluorescence and NIRF imaging systems. Results suggest that SWIR fluorescence imaging of ICG may have superior resolution in small animal imaging compared to NIRF imaging, but lack of measurement sensitivity, SNR, contrast, as well as water absorption limits deep penetration in large animals.
Citation
IEEE Transactions on Medical Imaging

Keywords

Molecular and cellular imaging, Optical imaging/OCT/DOT, Evaluation and performance, System design, Validation.

Citation

Zhu, B. , Sevick Muraca, E. and Litorja, M. (2019), Comparison of NIR versus SWIR fluorescence imaging of indocyanine green using SI-derived metrics of image performance, IEEE Transactions on Medical Imaging, [online], https://doi.org/10.1109/TMI.2019.2937760 (Accessed July 14, 2024)

Issues

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Created August 26, 2019, Updated October 12, 2021