Dr. Huda Asfour Profile

Dr. Huda Asfour

at George Washington Univ

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Publications (3)

SPIE Journal Paper | 20 October 2020 Open Access

Autofluorescence properties of balloon polymers used in medical applications

Huda Asfour, Jeremy Otridge, Robert Thomasian, Cinnamon Larson, Narine Sarvazyan

JBO, Vol. 25, Issue 10, 106004, (October 2020) https://doi.org/10.1117/12.10.1117/1.JBO.25.10.106004

KEYWORDS: Polymers, Polyurethane, Tissues, Luminescence, Positron emission tomography, Manufacturing, Talc, Tissue optics, Ultraviolet radiation, Hyperspectral imaging

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Significance: For use in medical balloons and related clinical applications, polymers are usually designed for transparency under illumination with white-light sources. However, when illuminated with ultraviolet (UV) or blue light, most of these materials autofluoresce in the visible range, which can be a concern for modalities that rely on tissue autofluorescence for diagnostic or therapeutic purposes. Aim: A search for published information on spectral properties of polymers that can be used for medical balloon manufacturing revealed a scarcity of published information on this subject. The aim of these studies was to address this gap. Approach: The autofluorescence properties of polymers used in medical balloon manufacturing were examined for their suitability for hyperspectral imaging and related applications. Excitation-emission matrices of different balloon materials were acquired within the 320- to 620-nm spectral range. In parallel, autofluorescence profiles from the 420- to 620-nm range were extracted from hyperspectral datasets of the same samples illuminated with UV light. The list of tested polymers included polyurethanes, nylon, polyethylene terephthalate (PET), polyether block amide (PEBAX), vulcanized silicone, thermoplastic elastomers with and without talc, and cyclic olefin copolymers, known by their trade name TOPAS. Results: Each type of polymer exhibited a specific pattern of autofluorescence. Polyurethanes, PET, and thermoplastic elastomers containing talc had the highest autofluorescence values, while sheets made of nylon, PEBAX, and TOPAS exhibited negligible autofluorescence. Hyperspectral imaging was used to illustrate how the choice of specific balloon material can impact the ability of principal component analysis to reveal the ablated cardiac tissue. Conclusions: The data revealed significant differences between autofluorescence profiles of the polymers and pointed to the most promising balloon materials for clinical implementation of approaches that depend on tissue autofluorescence.

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SPIE Journal Paper | 15 December 2018

Application of unsupervised learning to hyperspectral imaging of cardiac ablation lesions

Shuyue Guan, Huda Asfour, Narine Sarvazyan, Murray Loew

JMI, Vol. 5, Issue 04, 046003, (December 2018) https://doi.org/10.1117/12.10.1117/1.JMI.5.4.046003

KEYWORDS: Tissues, Machine learning, Hyperspectral imaging, Atrial fibrillation, Radiofrequency ablation, Visualization, Binary data, Surgery, Photons, Natural surfaces

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Proceedings Article | 12 March 2018 Paper

Lesion detection for cardiac ablation from auto-fluorescence hyperspectral images

Shuyue Guan, Murray Loew, Huda Asfour, Narine Sarvazyan, Narine Muselimyan

Proceedings Volume 10578, 105781O (2018) https://doi.org/10.1117/12.2293652

KEYWORDS: Tissues, Radiofrequency ablation, Visualization, Hyperspectral imaging, Atrial fibrillation, Machine learning, Binary data, Image processing, Cameras, Ultraviolet radiation

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