Machine learning augmented near-infrared spectroscopy: In vivo follow-up of cartilage defects.

OBJECTIVE: To assess the potential of near-infrared spectroscopy (NIRS) for in vivo arthroscopic monitoring of cartilage defects. METHOD: Sharp and blunt cartilage grooves were induced in the radiocarpal and intercarpal joints of Shetland ponies and monitored at baseline (0 weeks) and at three follow-up timepoints (11, 23, and 39 weeks) by measuring near-infrared spectra in vivo at and around the grooves. The animals were sacrificed after 39 weeks and the joints were harvested. Spectra were reacquired ex vivo to ensure reliability of in vivo measurements and for reference analyses. Additionally, cartilage thickness and instantaneous modulus were determined via computed tomography and mechanical testing, respectively. The relationship between the ex vivo spectra and cartilage reference properties was determined using convolutional neural network. RESULTS: In an independent test set, the trained networks yielded significant correlations for cartilage thickness (ρ = 0.473) and instantaneous modulus (ρ = 0.498). These networks were used to predict the reference properties at baseline and at follow-up time points. In the radiocarpal joint, cartilage thickness increased significantly with both groove types after baseline and remained swollen. Additionally, at 39 weeks, a significant difference was observed in cartilage thickness between controls and sharp grooves. For the instantaneous modulus, a significant decrease was observed with both groove types in the radiocarpal joint from baseline to 23 and 39 weeks. CONCLUSION: NIRS combined with machine learning enabled determination of cartilage properties in vivo, thereby providing longitudinal evaluation of post-intervention injury development. Additionally, radiocarpal joints were found more vulnerable to cartilage degeneration after damage than intercarpal joints.

Near-infrared spectroscopy enables quantitative evaluation of human cartilage biomechanical properties during arthroscopy.

OBJECTIVE: To investigate the feasibility of near-infrared (NIR) spectroscopy (NIRS) for evaluation of human articular cartilage biomechanical properties during arthroscopy. DESIGN: A novel arthroscopic NIRS probe designed in our research group was utilized by an experienced orthopedic surgeon to measure NIR spectra from articular cartilage of human cadaver knee joints (ex vivo, n = 18) at several measurement locations during an arthroscopic surgery. Osteochondral samples (n = 265) were extracted from the measurement sites for reference analysis. NIR spectra were remeasured in a controlled laboratory environment (in vitro), after which the corresponding cartilage thickness and biomechanical properties were determined. Hybrid multivariate regression models based on principal component analysis and linear mixed effects modeling (PCA-LME) were utilized to relate cartilage in vitro spectra and biomechanical properties, as well as to account for the spatial dependency. Additionally, a k-nearest neighbors (kNN) classifier was employed to reject outlying ex vivo NIR spectra resulting from a non-optimal probe-cartilage contact. Model performance was evaluated for both in vitro and ex vivo NIR spectra via Spearman's rank correlation (ρ) and the ratio of performance to interquartile range (RPIQ). RESULTS: Regression models accurately predicted cartilage thickness and biomechanical properties from in vitro NIR spectra (Model: 0.77 ≤ ρ ≤ 0.87, 2.03 ≤ RPIQ ≤ 3.0; Validation: 0.74 ≤ ρ ≤ 0.84, 1.87 ≤ RPIQ ≤ 2.90). When predicting cartilage properties from ex vivo NIR spectra (0.33 ≤ ρ ≤ 0.57 and 1.02 ≤ RPIQ ≤ 2.14), a kNN classifier enhanced the accuracy of predictions (0.52 ≤ ρ ≤ 0.87 and 1.06 ≤ RPIQ ≤ 1.88). CONCLUSION: Arthroscopic NIRS could substantially enhance identification of damaged cartilage by enabling quantitative evaluation of cartilage biomechanical properties. The results demonstrate the capacity of NIRS in clinical applications.

Influence of the marine feeding area on the muscle and egg fatty-acid composition of Atlantic salmon Salmo salar spawners estimated from the scale stable isotopes.

Fatty acids in muscle tissue and eggs of female Atlantic salmon Salmo salar spawners were analysed to evaluate the dietary quality of their final feeding areas in the Baltic Sea. The final likely feeding area was identified by comparing stable carbon and nitrogen isotope composition of the outermost growth region (final annulus) of scales of returned S. salar with that of reference S. salar caught from different feeding areas. Some overlap of stable-isotope reference values among the three areas, in addition to prespawning fasting, decreased the ability of muscle tri-acylglycerols to discriminate the final likely feeding area and the area's dietary quality. Among three long-chained polyunsaturated fatty acids, docosahexaenoic acid (DHA; 22:6n-3), eicosapentaenoic acid (EPA; 20:5n-3) and arachidonic acid (ARA; 20:4n-6), the proportions of ARA in total lipids of spawning S. salar muscle and eggs showed a significant negative correlation with increasing probability of S. salar having returned from the Baltic Sea main basin (i.e. the Baltic Sea proper). The results suggest that ARA in muscle and eggs is the best dietary indicator for dietary characteristics of final marine feeding area dietary characteristics among S. salar in the Baltic Sea.

Terahertz in vivo imaging of human skin: Toward detection of abnormal skin pathologies.

Terahertz (THz) imaging has long held promise for skin cancer detection but has been hampered by the lack of practical technological implementation. In this article, we introduce a technique for discriminating several skin pathologies using a coherent THz confocal system based on a THz quantum cascade laser. High resolution in vivo THz images (with diffraction limited to the order of 100 µm) of several different lesion types were acquired and compared against one another using the amplitude and phase values. Our system successfully separated pathologies using a combination of phase and amplitude information and their respective surface textures. The large scan field (50 × 40 mm) of the system allows macroscopic visualization of several skin lesions in a single frame. Utilizing THz imaging for dermatological assessment of skin lesions offers substantial additional diagnostic value for clinicians. THz images contain information complementary to the information contained in the conventional digital images.

Comparison of water, hydroxyproline, uronic acid and elastin contents of bovine knee ligaments and patellar tendon and their relationships with biomechanical properties.

Mechanical material properties of ligaments originate from their biochemical composition and structural organization. However, it is not yet fully elucidated how biochemical contents vary between knee ligaments and patellar tendon (PT) and how they relate with mechanical properties. The purpose of this study was to compare water, collagen, proteoglycan and elastin contents between bovine knee ligaments and PT and correlate them with tensile material properties. Hydroxyproline (collagen), uronic acid (proteoglycan) and elastin contents per wet and dry weights were measured using colorimetric biochemical methods for bovine knee ligament and PT samples (n = 10 knees). Direct comparison and correlation with multiple linear regression were performed against biomechanical properties measured in our earlier study. Anterior cruciate ligament (ACL) and PT exhibited lower hydroxyproline content per wet weight compared with other ligaments (p < 0.05). Cruciate ligaments had higher uronic acid content per dry weight compared with collateral ligaments (p < 0.05). Posterior cruciate ligament had higher elastin content than ACL (p < 0.05). Higher hydroxyproline content per wet weight implied higher Young's modulus, strength and toughness. Quantitatively, higher elastin content per wet weight predicted higher toe region nonlinearity and Young's modulus whereas higher uronic acid content per dry weight predicted lower Young's modulus, yield stress and toughness. Differences between ligaments in biochemical composition highlight differences in their physiological function and loading regimes. As expected, collagen content showed similar trend with stiffness and strength. The predictive role of proteoglycan and elastin contents on the mechanical properties might indicate their important functional role in ligaments.