Paper
20 February 2014 Monitoring biofilm attachment on medical devices surfaces using hyperspectral imaging
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Abstract
Microbial biofilm is a colony of single bacteria cells (planktonic) that attached to surfaces, attract other microorganisms to attach and grow, and together they build an extracellular matrix composed of polysaccharides, protein, and DNA. Eventually, some cells will detach and spread to other surface. Biofilm on medical devices can cause severe infection to all age ranges from infant to adult. Therefore, it is important to detect biofilm in a fast and efficient manner. Hyperspectral imaging was utilized for distinguishing wide area of biofilm coverage on various materials and on different textures of stainless steeltest coupons. Not only is the coverage of biofilm important, but also the shear stress of biofilm on the attached surfaces is significant. This study investigates the effects of shear stress on the adhesion of biofilms on common medical device surfaces such as glass, polycarbonate, polytetrafluoroethylene, and stainless steel with different textures. Biofilm was grown using Ps. aeruginosa and growth was monitored after 24 and 48 hours at 37° C. The coupons covered with biofilm were tilted at 45 degrees and 90 degrees for 30 seconds to induce shear stress and Hyperspectral images were taken. We hypothesize that stronger attachment on rough surface would be able to withstand greater shear stress compared to smooth surface.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hanh N. D. Le, Victoria M Hitchins, Ilko K. Ilev, and Do-Hyun Kim "Monitoring biofilm attachment on medical devices surfaces using hyperspectral imaging", Proc. SPIE 8938, Optical Fibers and Sensors for Medical Diagnostics and Treatment Applications XIV, 893809 (20 February 2014); https://doi.org/10.1117/12.2047867
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Cited by 2 scholarly publications.
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KEYWORDS
Glasses

Hyperspectral imaging

Luminescence

Medical devices

Reflectivity

Bacteria

Signal detection

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