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Updated: Dec 23, 2025

Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery

Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery

Published on: September 19, 2014

Performance test methods for near-infrared fluorescence imaging.

Udayakumar Kanniyappan^1,2, Bohan Wang¹, Charles Yang¹

¹Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA.

Medical Physics

|April 19, 2020

Summary

This summary is machine-generated.

This study developed standardized phantom-based methods for evaluating near-infrared fluorescence (NIRF) imaging systems. These techniques enable quantitative assessment of image quality, crucial for advancing diagnostic and research applications.

Keywords:

fluorescence imaging indocyanine green near-infrared standards test methods tissue phantoms

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Area of Science:

Medical Imaging
Biophotonics
Optical Diagnostics

Background:

Near-infrared fluorescence (NIRF) imaging is vital for visualizing vasculature and detecting cancer using targeted or untargeted agents.
Standardization of NIRF imaging technologies is needed for objective, quantitative testing of image quality characteristics.
Developing rigorous test methods applicable to diverse devices is essential for reliable performance evaluation.

Purpose of the Study:

To establish best practices for objective, quantitative testing of key image quality characteristics in NIRF imaging.
To develop a comprehensive battery of test methods for evaluating wide-field fluorescence imagers.
To facilitate the development of international standards for fluorescence image quality assessment.

Main Methods:

Evaluated methods for phantom design, measurement, and calculation of performance metrics for NIRF imaging systems.
Utilized a NIRF system (780 nm excitation, >830 nm detection) with indocyanine green.
Employed multiwell plate, high turbidity planar, and 3D-printed multichannel phantoms, alongside a USAF 1951 resolution target.

Main Results:

Developed and demonstrated a cohesive battery of test methods for assessing fluorescence image quality in wide-field imagers.
Explored techniques to evaluate uniformity, field of view, spectral crosstalk, spatial resolution, depth of field, sensitivity, linearity, and penetration depth.
Proposed key metrics for direct, quantitative comparison of device performance.

Conclusions:

The developed methods provide a framework for uniform evaluation and inter-comparison of clinical and preclinical NIRF imaging systems.
These techniques address the need for standardization in NIRF imaging technologies.
The long-term goal is to establish international standards for fluorescence image quality assessment.