Infrared microspectroscopic determination of collagen cross-links in articular cartilage

Collagen forms an organized network in articular cartilage to give tensile stiffness to the tissue. Due to its long half-life, collagen is susceptible to cross-links caused by advanced glycation end-products. The current standard method for determination of cross-link concentrations in tissues is the destructive high-performance liquid chromatography (HPLC). The aim of this study was to analyze the cross-link concentrations nondestructively from standard unstained histological articular cartilage sections by using Fourier transform infrared (FTIR) microspectroscopy. Half of the bovine articular cartilage samples (n = 27) were treated with threose to increase the collagen cross-linking while the other half (n = 27) served as a control group. Partial least squares (PLS) regression with variable selection algorithms was used to predict the cross-link concentrations from the measured average FTIR spectra of the samples, and HPLC was used as the reference method for cross-link concentrations. The correlation coefficients between the PLS regression models and the biochemical reference values were r = 0.84 (p <0.001), r = 0.87 (p <0.001) and r = 0.92 (p <0.001) for hydroxylysyl pyridinoline (HP), lysyl pyridinoline (LP), and pentosidine (Pent) cross-links, respectively. The study demonstrated that FTIR microspectroscopy is a feasible method for investigating cross-link concentrations in articular cartilage. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.Peer reviewe

Triple Contrast CT Method Enables Simultaneous Evaluation of Articular Cartilage Composition and Segmentation

Early degenerative changes of articular cartilage are detected using contrast-enhanced computed tomography (CT) with a cationic contrast agent (CA). However, cationic CA diffusion into degenerated cartilage decreases with proteoglycan depletion and increases with elevated water content, thus hampering tissue evaluation at early diffusion time points. Furthermore, the contrast at synovial fluid-cartilage interface diminishes as a function of diffusion time hindering accurate cartilage segmentation. For the first time, we employ quantitative dual-energy CT (QDECT) imaging utilizing a mixture of three CAs (cationic CA4+ and non-ionic gadoteridol which are sensitive to proteoglycan and water contents, respectively, and bismuth nanoparticles which highlight the cartilage surface) to simultaneously segment the articulating surfaces and determine of the cartilage condition. Intact healthy, proteoglycan-depleted, and mechanically injured bovine cartilage samples (n = 27) were halved and imaged with synchrotron microCT 2-h post immersion in triple CA or in dual CA (CA4+ and gadoteridol). CA4+ and gadoteridol partitions were determined using QDECT, and pairwise evaluation of these partitions was conducted for samples immersed in dual and triple CAs. In conclusion, the triple CA method is sensitive to proteoglycan depletion while maintaining sufficient contrast at the articular surface to enable detection of cartilage lesions caused by mechanical impact

Quantification of porcine myocardial perfusion with modified dual bolus MRI : a prospective study with a PET reference

Abstract Background The reliable quantification of myocardial blood flow (MBF) with MRI, necessitates the correction of errors in arterial input function (AIF) caused by the T1 saturation effect. The aim of this study was to compare MBF determined by a traditional dual bolus method against a modified dual bolus approach and to evaluate both methods against PET in a porcine model of myocardial ischemia. Methods Local myocardial ischemia was induced in five pigs, which were subsequently examined with contrast enhanced MRI (gadoteric acid) and PET (O-15 water). In the determination of MBF, the initial high concentration AIF was corrected using the ratio of low and high contrast AIF areas, normalized according to the corresponding heart rates. MBF was determined from the MRI, during stress and at rest, using the dual bolus and the modified dual bolus methods in 24 segments of the myocardium (total of 240 segments, five pigs in stress and rest). Due to image artifacts and technical problems 53% of the segments had to be rejected from further analyses. These two estimates were later compared against respective rest and stress PET-based MBF measurements. Results Values of MBF were determined for 112/240 regions. Correlations for MBF between the modified dual bolus method and PET was rs = 0.84, and between the traditional dual bolus method and PET rs = 0.79. The intraclass correlation was very good (ICC = 0.85) between the modified dual bolus method and PET, but poor between the traditional dual bolus method and PET (ICC = 0.07). Conclusions The modified dual bolus method showed a better agreement with PET than the traditional dual bolus method. The modified dual bolus method was found to be more reliable than the traditional dual bolus method, especially when there was variation in the heart rate. However, the difference between the MBF values estimated with either of the two MRI-based dual-bolus methods and those estimated with the gold-standard PET method were statistically significant

Quantification of porcine myocardial perfusion with modified dual bolus MRI-A prospective study with a PET reference

BackgroundThe reliable quantification of myocardial blood flow (MBF) with MRI, necessitates the correction of errors in arterial input function (AIF) caused by the T1 saturation effect. The aim of this study was to compare MBF determined by a traditional dual bolus method against a modified dual bolus approach and to evaluate both methods against PET in a porcine model of myocardial ischemia.MethodsLocal myocardial ischemia was induced in five pigs, which were subsequently examined with contrast enhanced MRI (gadoteric acid) and PET (O-15 water). In the determination of MBF, the initial high concentration AIF was corrected using the ratio of low and high contrast AIF areas, normalized according to the corresponding heart rates. MBF was determined from the MRI, during stress and at rest, using the dual bolus and the modified dual bolus methods in 24 segments of the myocardium (total of 240 segments, five pigs in stress and rest). Due to image artifacts and technical problems 53% of the segments had to be rejected from further analyses. These two estimates were later compared against respective rest and stress PET-based MBF measurements.ResultsValues of MBF were determined for 112/240 regions. Correlations for MBF between the modified dual bolus method and PET was rs = 0.84, and between the traditional dual bolus method and PET rs = 0.79. The intraclass correlation was very good (ICC = 0.85) between the modified dual bolus method and PET, but poor between the traditional dual bolus method and PET (ICC = 0.07).ConclusionsThe modified dual bolus method showed a better agreement with PET than the traditional dual bolus method. The modified dual bolus method was found to be more reliable than the traditional dual bolus method, especially when there was variation in the heart rate. However, the difference between the MBF values estimated with either of the two MRI-based dual-bolus methods and those estimated with the gold-standard PET method were statistically significant.</div

Quantification of Myocardial Blood Flow by Machine Learning Analysis of Modified Dual Bolus MRI Examination

Contrast-enhanced magnetic resonance imaging (MRI) is a promising method for estimating myocardial blood flow (MBF). However, it is often affected by noise from imaging artefacts, such as dark rim artefact obscuring relevant features. Machine learning enables extracting important features from such noisy data and is increasingly applied in areas where traditional approaches are limited. In this study, we investigate the capacity of machine learning, particularly support vector machines (SVM) and random forests (RF), for estimating MBF from tissue impulse response signal in an animal model. Domestic pigs (n = 5) were subjected to contrast enhanced first pass MRI (MRI-FP) and the impulse response at different regions of the myocardium (n = 24/pig) were evaluated at rest (n = 120) and stress (n = 96). Reference MBF was then measured using positron emission tomography (PET). Since the impulse response may include artefacts, classification models based on SVM and RF were developed to discriminate noisy signal. In addition, regression models based on SVM, RF and linear regression (for comparison) were developed for estimating MBF from the impulse response at rest and stress. The classification and regression models were trained on data from 4 pigs (n = 168) and tested on 1 pig (n = 48). Models based on SVM and RF outperformed linear regression, with higher correlation (R2SVM  = 0.81, R2RF  = 0.74, R2linear_regression  = 0.60; ρSVM = 0.76, ρRF = 0.76, ρlinear_regression = 0.71) and lower error (RMSESVM = 0.67 mL/g/min, RMSERF = 0.77 mL/g/min, RMSElinear_regression = 0.96 mL/g/min) for predicting MBF from MRI impulse response signal. Classifier based on SVM was optimal for detecting impulse response signals with artefacts (accuracy = 92%). Modified dual bolus MRI signal, combined with machine learning, has potential for accurately estimating MBF at rest and stress states, even from signals with dark rim artefacts. This could provide a protocol for reliable and easy estimation of MBF, although further research is needed to clinically validate the approach.</p

Vibrational spectroscopy of articular cartilage

Abstract Articular cartilage is a connective tissue that is located at the ends of long bones. Type II collagen, proteoglycans, water, and chondrocytes are the main constituents of articular cartilage. Osteoarthritis, the most common joint disease in the world, causes degenerative changes in articular cartilage tissue. Fourier transform infrared (FTIR), Raman, and near infrared (NIR) spectroscopic techniques offer versatile tools to assess biochemical composition and quality of articular cartilage. These vibrational spectroscopic techniques can be used to broaden our understanding about the compositional changes during osteoarthritis, and they also hold promise in disease diagnostics. In this article, the current literature of articular cartilage spectroscopic studies is reviewed

Acoustic properties of articular cartilage under mechanical stress

Mechano-acoustic and elastographic techniques may provide quantitative means for the in vivo diagnostics of articular cartilage. These techniques assume that sound speed does not change during tissue loading. As articular cartilage shows volumetric changes during compression, acoustic properties of cartilage may change affecting the validity of mechano-acoustic measurements. In this study, we examined the ultrasound propagation through human, bovine and porcine articular cartilage during stress-relaxation in unconfined compression. The time of flight (TOF) technique with known cartilage thickness (true sound speed) as well as in situ calibration method [Suh, Youn, Fu, J. Biomech. 34 (2001), 1347-1353] were used for the determination of sound speed. Ultrasound speed and attenuation decreased in articular cartilage during ramp compression, but returned towards the level of original values during relaxation. Variations in ultrasound speed induced an error in strain and compressive moduli provided that constant ultrasound speed and time-of-flight data was used to determine the tissue thickness. Highest errors in strain (-11.8 ± 12.0%) and dynamic modulus (15.4 ± 17.9%) were recorded in bovine cartilage. TOF and in situ calibration methods yielded different results for changes in sound speed during compression. We speculate that the variations in acoustic properties in loaded cartilage are related to rearrangement of the interstitial matrix, especially to that of collagen fibers. In human cartilage the changes, are, however relatively small and, according to the numerical simulations, mechano-acoustic techniques that assume constant acoustic properties for the cartilage will not be significantly impaired by this phenomenon

Quantitative Information From Ultrasound Evaluation of Articular Cartilage Should Be Interpreted With Care

Department of Health Technology and Informatic

Strain-Dependent Modulation of Ultrasound Speed in Articular Cartilage Under Dynamic Compression

Mechanical properties of articular cartilage may be determined by means of mechano-acoustic indentation, a clinically feasible technique for cartilage diagnostics. Unfortunately, ultrasound speed varies in articular cartilage during mechanical compression. This can cause significant errors to the measured mechanical parameters. In this study, the strain-dependent variation in ultrasound speed was investigated during dynamic compression. In addition, we estimated errors that were induced by the variation in ultrasound speed on the mechano-acoustically measured elastic properties of the tissue. Further, we validated a computational method to correct these errors. Bovine patellar cartilage samples (n = 7) were tested under unconfined compression. Strain-dependence of ultrasound speed was determined under different compressive strains using an identical strain-rate. In addition, the modulation of ultrasound speed was simulated using the transient compositional and structural changes derived from fibril-reinforced poroviscoelastic (FRPVE) model. Experimentally, instantaneous compressive strain modulated the ultrasound speed (p < 0.05) significantly. The decrease of ultrasound speed was found to change nonlinearly as a function of strain. Immediately after the ramp loading ultrasound speed was found to be changed -0.94%, -1.49%, -1.84%, -1.87%, -1.89% and -2.15% at the strains of 2.4%, 4.9%, 7.3%, 9.7%, 12.1% and 14.4%, respectively. The numerical simulation revealed that the compression-related decrease in ultrasound speed induces significant errors in the mechano-acoustically determined strain (39.7%) and dynamic modulus (72.1%) at small strains, e.g., at 2.4%. However, at higher strains, e.g., at 14.4%, the errors were smaller, i.e., 12.6% for strain and 14.5% for modulus. After the proposed computational correction, errors related to ultrasound speed were decreased. By using the correction, with e.g., 2.4% strain, errors in strain and modulus were decreased from 39.7% to 7.2% and from 72.1% to 35.3%, respectively. The FRPVE model, addressing the changes in fibril orientation and void ratio during compression, showed discrepancy of less than 1% between the predicted and measured ultrasound speed during the ramp compression. (E-mail: [email protected])

Effects of freeze-thaw cycle with and without proteolysis inhibitors and cryopreservant on the biochemical and biomechanical properties of articular cartilage

Objective: We investigated the effects of freeze-thawing on the properties of articular cartilage. Design: The reproducibility of repeated biomechanical assay of the same osteochondral sample was first verified with 11 patellar plugs from 3 animals. Then, 4 osteochondral samples from 15 bovine patellae were divided into 4 groups. The reference samples were immersed in phosphate-buffered saline (PBS) containing proteolysis inhibitors and biomechanically tested before storage for further analyses. Samples of group 1 were biomechanically tested before and after freeze-thawing in PBS in the absence and those of group 2 in the presence of inhibitors. Samples of the group 3 were biomechanically tested in PBS-containing inhibitors, but frozen in 30% dimethyl sulfoxide/PBS and subsequently tested in PBS supplemented with the inhibitors. Glycosaminoglycan contents of the samples and immersion solutions were analyzed, and proteoglycan structures examined with SDS-agarose gel electrophoresis. Results: Freeze-thawing decreased slightly dynamic moduli in all 3 groups. The glycosaminoglycan contents and proteoglycan structures of the cartilage were similar in all experimental groups. Occasionally, the diffused proteoglycans were partly degraded in group 1. Digital densitometry revealed similar staining intensities for the glycosaminoglycans in all groups. Use of cryopreservant had no marked effect on the glycosaminoglycan loss during freeze-thawing. Conclusion: The freeze-thawed cartilage samples appear suitable for the biochemical and biomechanical studies