Use of infrared spectroscopy for diagnosis of traumatic arthritis in horses.
Abstract: To evaluate use of infrared spectroscopy for diagnosis of traumatic arthritis in horses. Methods: 48 horses with traumatic arthritis and 5 clinically and radiographically normal horses. Methods: Synovial fluid samples were collected from 77 joints in 48 horses with traumatic arthritis. Paired samples (affected and control joints) from 29 horses and independent samples from an affected (n = 12) or control (7) joint from 19 horses were collected for model calibration. A second set of 20 normal validation samples was collected from 5 clinically and radiographically normal horses. Fourier transform infrared spectra of synovial fluids were acquired and manipulated, and data from affected joints were compared with controls to identify spectroscopic features that differed significantly between groups. A classification model that used linear discriminant analysis was developed. Performance of the model was determined by use of the 2 validation datasets. Results: A classification model based on 3 infrared regions classified spectra from the calibration dataset with overall accuracy of 97% (sensitivity, 93%; specificity, 100%). The model, with cost-adjusted prior probabilities of 0.60:0.40, yielded overall accuracy of 89% (sensitivity, 83%; specificity, 100%) for the first validation sample dataset and 100% correct classification of the second set of independent normal control joints. Conclusions: The infrared spectroscopic patterns of fluid from joints with traumatic arthritis differed significantly from the corresponding patterns for controls. These alterations in absorption patterns may be used via an appropriate classification algorithm to differentiate the spectra of affected joints from those of controls.
Publication Date: 2006-08-03 PubMed ID: 16881838DOI: 10.2460/ajvr.67.8.1286Google Scholar: Lookup
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- Journal Article
- Research Support
- Non-U.S. Gov't
Summary
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The research paper discusses how infrared spectroscopy can be effectively used to diagnose traumatic arthritis in horses. The study reveals 97% accuracy using this method, which could usher in a quicker, more reliable way to detect this condition in equines.
Methodology
- The study included 48 horses diagnosed with traumatic arthritis, and sampled synovial fluid from 77 joints of these horses. As control samples, there were 5 horses that were clinically deemed normal with no traces of arthritis.
- Samples of synovial fluid were taken from both the arthritis-affected and control joints for calibration of the model. Some horses provided paired samples (from the affected and unaffected/control joints), while from others only either the affected or the control joint samples was collected.
- In addition, a second set of 20 normal validation samples were collected from the 5 clinically healthy, non-arthritis horses.
- Through Fourier transform infrared spectroscopy, the researchers acquired the infrared spectral data of synovial fluids from the joints and carried out manipulations for data analysis.
Model Construction and Performance
- The spectral data from arthritis joints and control joints were compared to identify any significantly differing spectroscopic features between the two groups.
- A classification model was then built employing linear discriminant analysis, with specific attention to three infrared regions.
- The performance and accuracy of this model was then tested with two validation sets. The model demonstrated a commendable accuracy rate of 97% on the calibration dataset (with a sensitivity of 93% and specificity of 100%).
- Even when the model was adjusted with prior probabilities (cost-setting at a ratio of 0.60:0.40), it maintained an overall accuracy of 89% and 100% correct classification of the second independent normal control joint samples.
Conclusions
- The study concluded that the infrared spectroscopic patterns of fluid from trauma-induced arthritic joints were noticeably different from the patterns of control joints.
- This discovered difference shows potential in helping to diagnose traumatic arthritis in horses more rigorously. With the utilization of an appropriate classification algorithm, it is possible to differentiate the spectra from affected joints and those from control joints.
Cite This Article
APA
Vijarnsorn M, Riley CB, Shaw RA, McIlwraith CW, Ryan DA, Rose PL, Spangler E.
(2006).
Use of infrared spectroscopy for diagnosis of traumatic arthritis in horses.
Am J Vet Res, 67(8), 1286-1292.
https://doi.org/10.2460/ajvr.67.8.1286 Publication
Researcher Affiliations
- Department of Health Management, University of Prince Edward Island, PE C0A 1T0, Canada.
MeSH Terms
- Animals
- Arthritis / diagnosis
- Arthritis / veterinary
- Female
- Horse Diseases / diagnosis
- Horses
- Male
- Spectrophotometry, Infrared / methods
- Spectrophotometry, Infrared / veterinary
- Synovial Fluid / chemistry
- Wounds and Injuries / diagnosis
- Wounds and Injuries / veterinary
Citations
This article has been cited 4 times.- Malek S, Marini F, Rochat MC, Béraud R, Wright GM, Riley CB. Infrared spectroscopy of synovial fluid as a potential screening approach for the diagnosis of naturally occurring canine osteoarthritis associated with cranial cruciate ligament rupture.. Osteoarthr Cartil Open 2020 Dec;2(4):100120.
- Panizzi L, Vignes M, Dittmer KE, Waterland MR, Rogers CW, Sano H, McIlwraith CW, Pemberton S, Owen M, Riley CB. Infrared spectroscopy of serum fails to identify early biomarker changes in an equine model of traumatic osteoarthritis.. Osteoarthr Cartil Open 2022 Dec;4(4):100297.
- Macotpet A, Pattarapanwichien E, Chio-Srichan S, Daduang J, Boonsiri P. Attenuated total reflection Fourier transform infrared as a primary screening method for cancer in canine serum.. J Vet Sci 2020 Jan;21(1):e16.
- Burns J, Hou S, Riley CB, Shaw RA, Jewett N, McClure JT. Use of Fourier-transform infrared spectroscopy to quantify immunoglobulin G concentrations in alpaca serum.. J Vet Intern Med 2014 Mar-Apr;28(2):639-45.
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