OCT Detects, Assesses Bacterial Buildup on Medical Devices
IRVINE, Calif., Jan. 6, 2016 — Optical coherence tomography (OCT) has been used to detect bacterial buildup on medical devices in an effort to reduce infections in hospitals.
The research was led by Andrew Heidari from the University of California, Irvine, along with researchers from the Beckman Laser Institute and development-stage medical device company N8 Medical Inc. The team used OCT to determine the presence of biofilm — bacterial growth that results from micro-organisms attaching themselves to and multiplying on synthetic surfaces.
Biofilm has been linked to ventilator-associated pneumonia (VAP), a prevalent infection in intensive care units. Using OCT, the team visualized and assessed the extent of airway obstruction from biofilm deposited on intubated endotracheal tubes in vivo.
Scanning electron microscopy (SEM), the current method for biofilm characterization, is a lengthy process that requires extracting a sample, drying it and coating it with a thin gold layer — none of which can be performed in vivo. OCT, on the other hand, is noninvasive and can provide high-resolution cross-sectional images of various biological samples, and can be adapted to provide 3D volumetric information.
Images from endotracheal tubes: (a) 5000× SEM image of 120-hour postintubation endotracheal tube showing the presence of extracellular polymeric substrate; (b) 5000× SEM image of same endotracheal tube in a different location; (c) 15,000× SEM of same endotracheal tube focusing in on a cluster of cells; and (d) corresponding OCT image. Courtesy of A. Heidari, S. Moghaddam, et al.
In the study, extubated patients' endotracheal tubes were imaged using both OCT and SEM. Biofilm was present in both images, and the researchers used OCT to measure a reduction in endotracheal inner lumen area between a one-day intubation sample tube and a five-day sample tube.
The team used OCT to detect the presence of biofilm and to gather further information about the extent of biofilm formation based on thickness.
The research was published in the Journal of Biomedical Optics (doi: 10.1117/1.jbo.20.12.126010).
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