Near-infrared fluorescence image quality test methods for standardized performance evaluation

Udayakumar Kanniyappan; Bohan Wang; Charles Yang; Pejhman Ghassemi; Quanzeng Wang; Yu Chen; Joshua Pfefer

doi:10.1117/12.2255867

21 March 2017 Near-infrared fluorescence image quality test methods for standardized performance evaluation

Udayakumar Kanniyappan, Bohan Wang, Charles Yang, Pejhman Ghassemi, Quanzeng Wang, Yu Chen, Joshua Pfefer

Proceedings Volume 10056, Design and Quality for Biomedical Technologies X; 100560J (2017) https://doi.org/10.1117/12.2255867
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Near-infrared fluorescence (NIRF) imaging has gained much attention as a clinical method for enhancing visualization of cancers, perfusion and biological structures in surgical applications where a fluorescent dye is monitored by an imaging system. In order to address the emerging need for standardization of this innovative technology, it is necessary to develop and validate test methods suitable for objective, quantitative assessment of device performance. Towards this goal, we develop target-based test methods and investigate best practices for key NIRF imaging system performance characteristics including spatial resolution, depth of field and sensitivity. Characterization of fluorescence properties was performed by generating excitation-emission matrix properties of indocyanine green and quantum dots in biological solutions and matrix materials. A turbid, fluorophore-doped target was used, along with a resolution target for assessing image sharpness. Multi-well plates filled with either liquid or solid targets were generated to explore best practices for evaluating detection sensitivity. Overall, our results demonstrate the utility of objective, quantitative, target-based testing approaches as well as the need to consider a wide range of factors in establishing standardized approaches for NIRF imaging system performance.

Conference Presentation

Citation Download Citation

Udayakumar Kanniyappan, Bohan Wang, Charles Yang, Pejhman Ghassemi, Quanzeng Wang, Yu Chen, and Joshua Pfefer "Near-infrared fluorescence image quality test methods for standardized performance evaluation", Proc. SPIE 10056, Design and Quality for Biomedical Technologies X, 100560J (21 March 2017); https://doi.org/10.1117/12.2255867

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