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Scientific reports2017; 7(1); 10586; doi: 10.1038/s41598-017-10973-z

Combination of optical coherence tomography and near infrared spectroscopy enhances determination of articular cartilage composition and structure.

Abstract: Conventional arthroscopic evaluation of articular cartilage is subjective and poorly reproducible. Therefore, implementation of quantitative diagnostic techniques, such as near infrared spectroscopy (NIRS) and optical coherence tomography (OCT), is essential. Locations (n = 44) with various cartilage conditions were selected from mature equine fetlock joints (n = 5). These locations and their surroundings were measured with NIRS and OCT (n = 530). As a reference, cartilage proteoglycan (PG) and collagen contents, and collagen network organization were determined using quantitative microscopy. Additionally, lesion severity visualized in OCT images was graded with an automatic algorithm according to International Cartilage Research Society (ICRS) scoring system. Artificial neural network with variable selection was then employed to predict cartilage composition in the superficial and deep zones from NIRS data, and the performance of two models, generalized (including all samples) and condition-specific models (based on ICRS-grades), was compared. Spectral data correlated significantly (p < 0.002) with PG and collagen contents, and collagen orientation in the superficial and deep zones. The combination of NIRS and OCT provided the most reliable outcome, with condition-specific models having lower prediction errors (9.2%) compared to generalized models (10.4%). Therefore, the results highlight the potential of combining both modalities for comprehensive evaluation of cartilage during arthroscopy.
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Publication Date: 2017-09-06 PubMed ID: 28878384PubMed Central: PMC5587743DOI: 10.1038/s41598-017-10973-zGoogle Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

Summary

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The study investigates the use of near-infrared spectroscopy (NIRS) and optical coherence tomography (OCT) in determining the structure and composition of articular cartilage in horses. The results indicated these techniques, when combined, offered a more reliable and quantitative evaluation compared to traditional methods.

Research Context

  • The research is set against the backdrop of traditional methods for the evaluation of articular cartilage, which are relatively subjective and not easily reproducible.
  • This study aims to provide a more objective and reproducible technique by employing NIRS and OCT technologies.

Methodology

  • The research involved selecting various conditions of cartilage from mature equine fetlock joints. The selected areas and their surroundings were then measured using NIRS and OCT.
  • For reference, the content of proteoglycan (PG) and collagen, along with the organization of the collagen network, were determined using quantitative microscopy.
  • An automatic algorithm was used to grade the severity of lesions visible in the OCT images based on the International Cartilage Research Society (ICRS) scoring system.
  • This was followed by the use of an artificial neural network with variable selection, employed to predict the composition of cartilage in the superficial and deep zones from the NIRS data.

Findings

  • The spectral data gathered showed significant correlation with PG and collagen content, and collagen orientation in both the superficial and deep zones of the cartilage.
  • The combination of NIRS and OCT provided the most accurate results, especially when condition-specific models were used. These models demonstrated lower prediction errors (9.2%) compared to generalized models (10.4%).

Conclusion

  • The study concluded that combining NIRS and OCT could be beneficial for a more comprehensive evaluation of cartilage during arthroscopy. The results illustrate the potential of these combined modalities for the evaluation of cartilage composition and structure, providing both reliable and quantitative data.

Cite This Article

APA
Sarin JK, Rieppo L, Brommer H, Afara IO, Saarakkala S, Töyräs J. (2017). Combination of optical coherence tomography and near infrared spectroscopy enhances determination of articular cartilage composition and structure. Sci Rep, 7(1), 10586. https://doi.org/10.1038/s41598-017-10973-z

Publication

Scientific reports
ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 7
Issue: 1
Pages: 10586
PII: 10586

Researcher Affiliations

Sarin, Jaakko K
  • Department of Applied Physics, University of Eastern Finland, Kuopio, Finland. jaakko.sarin@uef.fi.
  • Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland. jaakko.sarin@uef.fi.
Rieppo, Lassi
  • Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
  • Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
Brommer, Harold
  • Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, Netherlands.
Afara, Isaac O
  • Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Saarakkala, Simo
  • Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Oulu, Finland.
  • Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.
  • Department of Diagnostic Radiology, Oulu University Hospital, Oulu, Finland.
Töyräs, Juha
  • Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
  • Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland.

MeSH Terms

  • Algorithms
  • Animals
  • Cartilage, Articular / chemistry
  • Cartilage, Articular / diagnostic imaging
  • Collagen / chemistry
  • Densitometry
  • Horses
  • Image Processing, Computer-Assisted
  • Microscopy, Polarization
  • Neural Networks, Computer
  • Spectroscopy, Near-Infrared / methods
  • Surface Properties
  • Tomography, Optical Coherence / methods

Conflict of Interest Statement

The authors declare that they have no competing interests.

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