216 research outputs found
T2 relaxation time mapping reveals age- and species-related diversity of collagen network architecture in articular cartilage
SummaryObjectiveThe magnetic resonance imaging (MRI) parameter T2 relaxation time has been shown to be sensitive to the collagen network architecture of articular cartilage. The aim of the study was to investigate the agreement of T2 relaxation time mapping and polarized light microscopy (PLM) for the determination of histological properties (i.e., zone and fibril organization) of articular cartilage.MethodsT2 relaxation time was determined at 9.4T field strength in healthy adult human, juvenile bovine and juvenile porcine patellar cartilage, and related to collagen anisotropy and fibril angle as measured by quantitative PLM.ResultsBoth T2 and PLM revealed a mutually consistent but varying number of collagen-associated laminae (3, 3–5 or 3–7 laminae in human, porcine and bovine cartilage, respectively). Up to 44% of the depth-wise variation in T2 was accounted for by the changing anisotropy of collagen fibrils, confirming that T2 contrast of articular cartilage is strongly affected by the collagen fibril anisotropy. A good correspondence was observed between the thickness of T2-laminae and collagenous zones as determined from PLM anisotropy measurements (r=0.91, r=0.95 and r=0.91 for human, bovine and porcine specimens, respectively).ConclusionsAccording to the present results, T2 mapping is capable of detecting histological differences in cartilage collagen architecture among species, likely to be strongly related to the differences in maturation of the tissue. This diversity in the MRI appearance of healthy articular cartilage should also be recognized when using juvenile animal tissue as a model for mature human cartilage in experimental studies
Repair of osteochondral defects with recombinant human type II collagen gel and autologous chondrocytes in rabbit
SummaryObjectiveRecombinant human type II collagen (rhCII) gels combined with autologous chondrocytes were tested as a scaffold for cartilage repair in rabbits in vivo.MethodAutologous chondrocytes were harvested, expanded and combined with rhCII-gel and further pre-cultivated for 2 weeks prior to transplantation into a 4 mm diameter lesion created into the rabbit's femoral trochlea (n = 8). Rabbits with similar untreated lesions (n = 7) served as a control group.ResultsSix months after the transplantation the repair tissue in both groups filled the lesion site, but in the rhCII-repair the filling was more complete. Both repair groups also had high proteoglycan and type II collagen contents, except in the fibrous superficial layer. However, the integration to the adjacent cartilage was incomplete. The O'Driscoll grading showed no significant differences between the rhCII-repair and spontaneous repair, both representing lower quality than intact cartilage. In the repair tissues the collagen fibers were abnormally organized and oriented. No dramatic changes were detected in the subchondral bone structure. The repair cartilage was mechanically softer than the intact tissue. Spontaneously repaired tissue showed lower values of equilibrium and dynamic modulus than the rhCII-repair. However, the differences in the mechanical properties between all three groups were insignificant.ConclusionWhen rhCII was used to repair cartilage defects, the repair quality was histologically incomplete, but still the rhCII-repairs showed moderate mechanical characteristics and a slight improvement over those in spontaneous repair. Therefore, further studies using rhCII for cartilage repair with emphasis on improving integration and surface protection are required
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
Obstructive sleep apnoea-related respiratory events and desaturation severity are associated with the cardiac response
Obstructive sleep apnoea (OSA) causes, among other things, intermittent blood oxygen desaturations, increasing the sympathetic tone. Yet the effect of desaturations on heart rate variability (HRV), a simple and noninvasive method for assessing sympathovagal balance, has not been comprehensively studied. We aimed to study whether desaturation severity affects the immediate HRV.MethodsWe retrospectively analysed the electrocardiography signals in 5-min segments (n=39 132) recorded during clinical polysomnographies of 642 patients with suspected OSA. HRV parameters were calculated for each segment. The segments were pooled into severity groups based on the desaturation severity (i.e.the integrated area under the blood oxygen saturation curve) and the respiratory event rate within the segment. Covariate-adjusted regression analyses were performed to investigate possible confounding effects.ResultsWith increasing respiratory event rate, the normalised high-frequency band power (HFNU) decreased from 0.517 to 0.364 (p<0.01), the normalised low-frequency band power (LFNU) increased from 0.483 to 0.636 (p<0.01) and the mean RR interval decreased from 915 to 869 ms (p<0.01). Similarly, with increasing desaturation severity, the HFNUdecreased from 0.499 to 0.364 (p<0.01), the LFNUincreased from 0.501 to 0.636 (p<0.01) and the mean RR interval decreased from 952 to 854 ms (p<0.01). Desaturation severity-related findings were confirmed by considering the confounding factors in the regression analyses.ConclusionThe short-term HRV response differs based on the desaturation severity and the respiratory event rate in patients with suspected OSA. Therefore, a more detailed analysis of HRV and desaturation characteristics could enhance OSA severity estimation
Estimation of articular cartilage properties using multivariate analysis of optical coherence tomography signal
SummaryObjectiveThe aim was to investigate the applicability of multivariate analysis of optical coherence tomography (OCT) information for determining structural integrity, composition and mechanical properties of articular cartilage.DesignEquine osteochondral samples (N = 65) were imaged with OCT, and their total attenuation and backscattering coefficients (μt and μb) were measured. Subsequently, the Mankin score, optical density (OD) describing the fixed charge density, light absorbance in amide I region (Aamide), collagen orientation, permeability, fibril network modulus (Ef) and non-fibrillar matrix modulus (Em) of the samples were determined. Partial least squares (PLS) regression model was calculated to predict tissue properties from the OCT signals of the samples.ResultsSignificant correlations between the measured and predicted mean collagen orientation (R2 = 0.75, P < 0.0001), permeability (R2 = 0.74, P < 0.0001), mean OD (R2 = 0.73, P < 0.0001), Mankin scores (R2 = 0.70, P < 0.0001), Em (R2 = 0.50, P < 0.0001), Ef (R2 = 0.42, P < 0.0001), and Aamide (R2 = 0.43, P < 0.0001) were obtained. Significant correlation was also found between μb and Ef (ρ = 0.280, P = 0.03), but not between μt and any of the determined properties of articular cartilage (P > 0.05).ConclusionMultivariate analysis of OCT signal provided good estimates for tissue structure, composition and mechanical properties. This technique may significantly enhance OCT evaluation of articular cartilage integrity, and could be applied, for example, in delineation of degenerated areas around cartilage injuries during arthroscopic repair surgery
Rapid CT-based Estimation of Articular Cartilage Biomechanics in the Knee Joint Without Cartilage Segmentation
Knee osteoarthritis (OA) is a painful joint disease,
causing disabilities in daily activities. However, there is no
known cure for OA, and the best treatment strategy might be
prevention. Finite element (FE) modeling has demonstrated
potential for evaluating personalized risks for the progression
of OA. Current FE modeling approaches use primarily
magnetic resonance imaging (MRI) to construct personalized
knee joint models. However, MRI is expensive and has lower
resolution than computed tomography (CT). In this study,
we extend a previously presented atlas-based FE modeling
framework for automatic model generation and simulation
of knee joint tissue responses using contrast agent-free CT. In
this method, based on certain anatomical dimensions measured from bone surfaces, an optimal template is selected and
scaled to generate a personalized FE model. We compared
the simulated tissue responses of the CT-based models with
those of the MRI-based models. We show that the CT-based
models are capable of producing similar tensile stresses, fibril
strains, and fluid pressures of knee joint cartilage compared
to those of the MRI-based models. This study provides a new
methodology for the analysis of knee joint and cartilage
mechanics
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
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