Characterisation of Cartilage Damage via Fusing Mid-Infrared, Near-Infrared, and Raman Spectroscopic Data

Author:

Shaikh Rubina12,Tafintseva Valeria3ORCID,Nippolainen Ervin1,Virtanen Vesa4,Solheim Johanne3,Zimmermann Boris3ORCID,Saarakkala Simo45ORCID,Töyräs Juha167,Kohler Achim3,Afara Isaac O.17

Affiliation:

1. Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland

2. School of Physics, Clinical and Optometric Sciences, Technological University Dublin, D07 XT95 Dublin, Ireland

3. Faculty of Science and Technology, Norwegian University of Life Sciences, 1432 Ås, Norway

4. Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland

5. Research Unit of Health Sciences and Technology, University of Oulu, 90220 Oulu, Finland

6. Science Service Center, Kuopio University Hospital, 70210 Kuopio, Finland

7. School of Information Technology and Electrical Engineering, The University of Queensland, Brisban, QLD 4072, Australia

Abstract

Mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR), and Raman spectroscopy are all well-established analytical techniques in biomedical applications. Since they provide complementary chemical information, we aimed to determine whether combining them amplifies their strengths and mitigates their weaknesses. This study investigates the feasibility of the fusion of MIR, NIR, and Raman spectroscopic data for characterising articular cartilage integrity. Osteochondral specimens from bovine patellae were subjected to mechanical and enzymatic damage, and then MIR, NIR, and Raman data were acquired from the damaged and control specimens. We assessed the capacity of individual spectroscopic methods to classify the samples into damage or control groups using Partial Least Squares Discriminant Analysis (PLS-DA). Multi-block PLS-DA was carried out to assess the potential of data fusion by combining the dataset by applying two-block (MIR and NIR, MIR and Raman, NIR and Raman) and three-block approaches (MIR, NIR, and Raman). The results of the one-block models show a higher classification accuracy for NIR (93%) and MIR (92%) than for Raman (76%) spectroscopy. In contrast, we observed the highest classification efficiency of 94% and 93% for the two-block (MIR and NIR) and three-block models, respectively. The detailed correlative analysis of the spectral features contributing to the discrimination in the three-block models adds considerably more insight into the molecular origin of cartilage damage.

Publisher

MDPI AG

Subject

Medicine (miscellaneous)

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