Can Near-infrared Spectroscopy Detect and Differentiate Implant-associated Biofilms?
BACKGROUND
Established bacterial diagnostic techniques for orthopaedic-related infections rely on a combination of imperfect tests that often can lead to negative culture results. Spectroscopy is a tool that potentially could aid in rapid detection and differentiation of bacteria in implant-associated infections.


OBJECTIVE
We asked: (1) Can principal component analysis explain variation in spectral curves for biofilm obtained from Staphylococcus aureus, Staphylococcus epidermidis, and Pseudomonas aeruginosa? (2) What is the accuracy of Fourier transformed-near infrared (FT-NIR)/multivariate data analysis in identifying the specific species associated with biofilm?


METHODS
Three clinical isolates, S aureus, S epidermidis, and P aeruginosa were cultured to create biofilm on surgical grade stainless steel. At least 52 samples were analyzed per group using a FT-NIR spectrometer. Multivariate and principal component analyses were performed on the spectral data to allow for modeling and identification of the bacterial species.


RESULTS
Spectral analysis was able to correctly identify 86% (37/43) of S aureus, 89% (16/18) of S epidermidis, and 70% (28/40) of P aeruginosa samples with minimal error. Overall, models developed using spectral data preprocessed using a combination of standard normal variant and first-derivative transformations performed much better than models developed with the raw spectral data in discriminating between the three classes of bacteria because of its low Type 1 error and large intermodel distinction.


CONCLUSIONS
The use of spectroscopic methods to identify and classify bacterial biofilms on orthopaedic implant material is possible and improves with advanced modeling that can be obtained rapidly with little error. The sensitivity for identification was 97% for S aureus (95% CI, 88-99%), 100% for S epidermidis (95% CI, 95-100%), and 77% for P aeruginosa (95% CI, 65-86%). The specificity of the S aureus was 86% (95% CI, 3-93%), S epidermidis was 89% (95% CI, 67-97%), and P aeruginosa was 70% (95% CI, 55-82%).


CONCLUSIONS
This technique of spectral data acquisition and advanced modeling should continue to be explored as a method for bacterial biofilm identification. A spectral databank of bacterial and potentially contaminating tissues should be acquired initially through an in vivo animal model and quickly transition to explanted devices and the clinical arena.
Department of Orthopaedics, West Virginia University, PO Box 9196, Morgantown, WV, 26506-9196, USA.
John E
JE
Tidwell
Division of Forestry and Natural Resources, West Virginia University, Morgantown, WV, USA.
Ben
B
Dawson-Andoh
Department of Horticultural Sciences, North Carolina State University, Raleigh, NC, USA.
Emmanuel O
EO
Adedipe
Division of Resource Management, West Virginia University, Morgantown, WV, USA.
Kofi
K
Nkansah
Department of Orthopaedics, West Virginia University, PO Box 9196, Morgantown, WV, 26506-9196, USA. mdietz@hsc.wvu.edu.
Matthew J
http://orcid.org/0000-0003-2468-9837
MJ
Dietz
D001431:Bacteriological Techniques; D018441:Biofilms / Q000145:classification / Q000254:growth & development; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D019736:Prostheses and Implants / Q000009:adverse effects* / Q000382:microbiology; D011474:Prosthesis Design; D016459:Prosthesis-Related Infections / Q000175:diagnosis* / Q000382:microbiology; D011552:Pseudomonas Infections / Q000175:diagnosis* / Q000382:microbiology; D011550:Pseudomonas aeruginosa / Q000254:growth & development*; D017550:Spectroscopy, Fourier Transform Infrared; D013193:Stainless Steel; D013203:Staphylococcal Infections / Q000175:diagnosis* / Q000382:microbiology; D013211:Staphylococcus aureus / Q000145:classification / Q000254:growth & development / Q000302:isolation & purification*; D013212:Staphylococcus epidermidis / Q000145:classification / Q000254:growth & development / Q000302:isolation & purification*
D013193:Stainless Steel