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Proceedings Paper

Quantitative assessment of hyperspectral imaging in detection of plasmonic nanoparticles: a modified contrast-detail analysis approach
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Paper Abstract

Hyperspectral reflectance imaging (HRI) is an emerging imaging modality being applied for clinical indications such as tissue oximetry, and cancer detection based on endogenous biological constituents including plasmonic nanoparticles. However, there is currently a lack of standardized test methods for objective, quantitative evaluation of HRI system performance. Contrast-detail analysis (CDA) is a phantom-based test method commonly used to evaluate medical imaging devices (e.g., mammography systems) in terms of their lower detection limit. We investigated a modified CDA (mCDA) method to quantify the detectability of gold nanoparticles by HRI systems. Silicone-based turbid phantoms containing micro-fluidic channels were developed for the mCDA tests. Polydimethylsiloxane (PDMS) phantom materials were doped with chromophores and scatterers to achieve biologically relevant optical properties (OPs). Molds were used to produce cylindrical channels of diameters 0.3 to 1.65 mm and depths of 0.2 mm inside the phantoms. Channels were filled with a mixture of hemoglobin and concentrations of gold nanorods (GNR) and measured with our HRI system. The contrast of GNRs was solved with a spectral unmixing algorithm from the reflectance spectra. The lowest detectable concentration was determined as a function of inclusion size and depth and plotted as modified contrast detail curve (mCDC). mCDCs were used to compare the detectabilities of the HRI system with different data processing algorithms. It is demonstrated that our mCDA test method involving turbid microchannel phantoms can help to elucidate the combined performance of imaging devices and plasmonic nanoparticle contrast agents. This approach may be useful for performing clinical trial standardization and device re-calibration, thus ensuring quality control and clinical performance.

Paper Details

Date Published: 18 March 2016
PDF: 8 pages
Proc. SPIE 9700, Design and Quality for Biomedical Technologies IX, 97000D (18 March 2016); doi: 10.1117/12.2214750
Show Author Affiliations
Jianting Wang, U.S. Food and Drug Administration (United States)
Yu Chen, Univ. of Maryland, College Park (United States)
T. Joshua Pfefer, U.S. Food and Drug Administration (United States)


Published in SPIE Proceedings Vol. 9700:
Design and Quality for Biomedical Technologies IX
Ramesh Raghavachari; Rongguang Liang, Editor(s)

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