Arthroscopic NIRS was found to be highly suitable for in vivo evaluation of car-tilage and underlying bone properties as the technique is non-destructive and al-lows evaluation of the tissue properties without sample preparation. For success-ful adaptation, substantial amount of training data must be collected to establish well-generalized models. Previousin vivostudies [6, 19, 47–49] utilizing NIRS spec-troscopy have evaluated cartilage properties by simply calculating the ratio of two spectral peaks. This parameter has been correlated with various cartilage quali-ties, such as cartilage biomechanical properties and ICRS score, to evaluate cartilage condition. This simplistic approach is highly limited and does not account for the overlapping spectral features in the NIR absorption spectra, therefore highlighting the necessity and importance of multivariate techniques. In studyIV, arthroscopic NIRS probe was introduced forin vivo arthroscopies to evaluate cartilage and un-derlying bone properties in Shetland ponies undergoing cartilage repair procedure.
The ANN models, optimized by variable selection, accurately predicted cartilage and bone properties fromin vitrospectral measurements; however, relatively weaker correlations were observed with predictions based on in vivo NIR measurements.
The relatively weaker prediction accuracy ofin vivoNIR measurements is arguably due to imperfect contact between NIR probe and cartilage surface. To enhance the
identification of optimal spectra for each measurement location, additional indica-tors or classification algorithms, e.g., support vector machines and decision trees, could be utilized.
8 SUMMARY AND CONCLUSIONS
In this thesis, the feasibility of NIRS technique for arthroscopic evaluation of articu-lar cartilage and subchondral bone properties was investigated. In addition, repro-ducibility of scoring of cartilage lesion severity was studied with several techniques, including conventional arthroscope, ultrasound and OCT imaging, and automatic scoring of OCT images. Also, the combined potential of NIRS and OCT for diag-nostics of cartilage degeneration was investigated.
The main conclusion of this thesis can be summarized as follows:
• Quantitative ultrasound and OCT imaging provided valuable complementary information over conventional arthroscope, e.g., enabling visualization of tis-sues underlying cartilage surface. OCT imaging combined with the auto-mated scoring algorithm provided the most reliable scoring of lesion severity.
However, for human cartilage, utilization of ultrasound to determine cartilage thickness is advised due to the limited penetration depth of OCT.
• NIR absorption spectra (700–1050 nm) enabled reliable prediction of cartilage biomechanical properties and composition using PLS regression and ANN methods, respectively. However, this spectral region may have contributions from the subchondral bone due wavelength-dependence of light penetration into and through articular cartilage. Additionally, adaptation of a wider spec-tral region could have enhanced the predictions.
• Automated scoring of cartilage lesion severity based on OCT images enabled creation of subgroups for ANN modeling. Prediction performance of the ANN models based on these subgroups was superior when compared to a general-ized ANN model and, thus, demonstrates the combined potential of NIRS and OCT.
• A novel steam-sterilizable and robust arthroscopic NIRS probe was developed and introduced for determining properties of articular cartilage and subchon-dral bone in vivo. The NIRS technique and probe were found promising for arthroscopic evaluation when utilizing the spectral region of 400–1900 nm.
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