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Updated: May 1, 2026
Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria
Published on: May 8, 2013
Optical coherence tomography for label-free detection and characterization of methicillin-resistant S. aureus
Natalia Demidova1,2, Jason R Gunn1, Ida Leah Gitajn1,3
1Dartmouth Health, Department of Orthopaedics, Lebanon, New Hampshire, United States.
Significance:
Orthopedic implant-associated infections cause serious complications primarily attributed to bacterial biofilm formation and are often characterized by increased antibiotic resistance and diminished treatment response. Yet, no methods currently exist to identify biofilms intraoperatively-surgeons rely solely on their eyes and hands and cannot detect or differentiate infected tissue to determine the location and extent of contamination.
Aim:
As the first step in addressing this unmet clinical need, here, we develop an optical coherence tomography (OCT)-based imaging method capable of detection in situ and quantification of one of the most dangerous orthopedic biofilms formed by methicillin-resistant Staphylococcus aureus (MRSA).
Approach:
Growing biofilms on orthopedic hardware, we identify MRSA distinct optical signature through histogram-based multi-parametric texture analysis of OCT images and support the findings with bioluminescence imaging and scanning electron microscopy. Under identical experimental conditions, we identify an optical signature of Escherichia coli (E. coli) biofilms and use it to distinguish and quantify both species within MRSA-E. coli biofilms.
Results:
The developed OCT-based methodology was successfully tested for (1) MRSA colonies delineation, (2) detection of metal hardware (an important feature for clinical translation where the metal surface of most orthopedic hardware is not flat), (3) automated quantification of biofilm thickness and roughness, and (4) identification of pores and, therefore, ability to evaluate the role of porosity-one of the critical biological metrics in relation to biofilm maturity and response to treatment. For the first time, we demonstrated complex pore structures of thick ( ) MRSA biofilms in situ with an unprecedented level of detail.
Conclusions:
The proposed rapid noninvasive detection/quantification of MRSA biofilms on metal surfaces and delineation of their complex network of pores opens new venues for label-free MRSA detection in preclinical models of trauma surgery, expansion to other bacterial strains, and further clinical translation.
Insights
A new optical coherence tomography (OCT) method detects methicillin-resistant Staphylococcus aureus (MRSA) biofilms on orthopedic implants. This noninvasive technique quantifies biofilm thickness, roughness, and pore structure, aiding surgical infection detection.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Infectious Diseases
Background:
- Orthopedic implant-associated infections are serious complications driven by antibiotic-resistant bacterial biofilms.
- Current intraoperative methods lack the ability to detect or differentiate infected tissue, leading to challenges in treatment.
- There is a critical unmet need for real-time biofilm detection during surgery.
Purpose of the Study:
- To develop an optical coherence tomography (OCT)-based imaging method for in situ detection and quantification of methicillin-resistant Staphylococcus aureus (MRSA) biofilms.
- To address the clinical need for intraoperative identification of bacterial contamination on orthopedic implants.
- To establish a label-free method for visualizing and quantifying orthopedic biofilms.
Main Methods:
- Utilized histogram-based multi-parametric texture analysis of OCT images to identify distinct optical signatures of MRSA biofilms.
- Supported OCT findings with bioluminescence imaging and scanning electron microscopy for validation.
- Developed and tested an OCT methodology for MRSA colony delineation, metal hardware detection, and biofilm quantification.
Main Results:
- Successfully identified a unique optical signature for MRSA biofilms using OCT texture analysis.
- Demonstrated the ability to detect and quantify MRSA and Escherichia coli biofilms, including mixed species.
- Quantified biofilm thickness, roughness, and complex pore structures in situ with high detail.
- Validated the detection of metal hardware, crucial for clinical translation.
Conclusions:
- The developed OCT method provides rapid, noninvasive detection and quantification of MRSA biofilms on metal surfaces.
- This technique enables the delineation of complex biofilm pore networks, offering insights into biofilm maturity and treatment response.
- Opens new avenues for label-free MRSA detection in preclinical models and facilitates clinical translation for trauma surgery.
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