Critical-sized cartilage defects in the equine carpus

Aim: The horse joint, due to its similarity with the human joint, is the ultimate model for translational articular cartilage repair studies. This study was designed to determine the critical size of cartilage defects in the equine carpus and serve as a benchmark for the evaluation of new cartilage treatment options. Material and Methods: Circular full-thickness cartilage defects with a diameter of 2, 4, and 8 mm were created in the left middle carpal joint and similar osteochondral (3.5 mm in depth) defects in the right middle carpal joint of 5 horses. Spontaneously formed repair tissue was examined macroscopically, with MR and mu CT imaging, polarized light microscopy, standard histology, and immunohistochemistry at 12 months. Results: Filling of 2 mm chondral defects was good (77.8 +/- 8.5%), but proteoglycan depletion was evident in Safranin-O staining and gadolinium-enhanced MRI (T-1Gd). Larger chondral defects showed poor filling (50.6 +/- 2.7% in 4 mm and 31.9 +/- 7.3% in 8 mm defects). Lesion filling in 2, 4, and 8 mm osteochondral defects was 82.3 +/- 3.0%, 68.0 +/- 4.6% and 70.8 +/- 15.4%, respectively. Type II collagen staining was seen in 9/15 osteochondral defects but only in 1/15 chondral defects. Subchondral bone pathologies were evident in 14/15 osteochondral samples but only in 5/15 chondral samples. Although osteochondral lesions showed better neotissue quality than chondral lesions, the overall repair was deemed unsatisfactory because of the subchondral bone pathologies. Conclusion: We recommend classifying 4 mm as critical osteochondral lesion size and 2 mm as critical chondral lesion size for cartilage repair research in the equine carpal joint model.Peer reviewe

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

Dual-contrast computed tomography enables detection of equine posttraumatic osteoarthritis in vitro

To prevent the progression of posttraumatic osteoarthritis, assessment of cartilage composition is critical for effective treatment planning. Posttraumatic changes include proteoglycan (PG) loss and elevated water content. Quantitative dual-energy computed tomography (QDECT) provides a means to diagnose these changes. Here, we determine the potential of QDECT to evaluate tissue quality surrounding cartilage lesions in an equine model, hypothesizing that QDECT allows detection of posttraumatic degeneration by providing quantitative information on PG and water contents based on the partitions of cationic and nonionic agents in a contrast mixture. Posttraumatic osteoarthritic samples were obtained from a cartilage repair study in which full-thickness chondral defects were created surgically in both stifles of seven Shetland ponies. Control samples were collected from three nonoperated ponies. The experimental (n = 14) and control samples (n = 6) were immersed in the contrast agent mixture and the distributions of the agents were determined at various diffusion time points. As a reference, equilibrium moduli, dynamic moduli, and PG content were measured. Significant differences (p < 0.05) in partitions between the experimental and control samples were demonstrated with cationic contrast agent at 30 min, 60 min, and 20 h, and with non-ionic agent at 60 and 120 min. Significant Spearman's rank correlations were obtained at 20 and 24 h (rho = 0.482-0.693) between the partition of cationic contrast agent, cartilage biomechanical properties, and PG content. QDECT enables evaluation of posttraumatic changes surrounding a lesion and quantification of PG content, thus advancing the diagnostics of the extent and severity of cartilage injuries

Embedded Quantitative MRI T_1ρ Mapping Using Non-Linear Primal-Dual Proximal Splitting

Quantitative MRI (qMRI) methods allow reducing the subjectivity of clinical MRI by providing numerical values on which diagnostic assessment or predictions of tissue properties can be based. However, qMRI measurements typically take more time than anatomical imaging due to requiring multiple measurements with varying contrasts for, e.g., relaxation time mapping. To reduce the scanning time, undersampled data may be combined with compressed sensing (CS) reconstruction techniques. Typical CS reconstructions first reconstruct a complex-valued set of images corresponding to the varying contrasts, followed by a non-linear signal model fit to obtain the parameter maps. We propose a direct, embedded reconstruction method for T1ρ mapping. The proposed method capitalizes on a known signal model to directly reconstruct the desired parameter map using a non-linear optimization model. The proposed reconstruction method also allows directly regularizing the parameter map of interest and greatly reduces the number of unknowns in the reconstruction, which are key factors in the performance of the reconstruction method. We test the proposed model using simulated radially sampled data from a 2D phantom and 2D cartesian ex vivo measurements of a mouse kidney specimen. We compare the embedded reconstruction model to two CS reconstruction models and in the cartesian test case also the direct inverse fast Fourier transform. The T1ρ RMSE of the embedded reconstructions was reduced by 37–76% compared to the CS reconstructions when using undersampled simulated data with the reduction growing with larger acceleration factors. The proposed, embedded model outperformed the reference methods on the experimental test case as well, especially providing robustness with higher acceleration factors

Quantitative magnetic resonance imaging of Scots pine seeds and the assessment of germination potential

Abstract The availability of Scots pine seeds (Pinus sylvestris L.) with high germinability is necessary for artificial forest regeneration. In this work, Scots pine seed orchard seeds were magnetic resonance (MR) imaged to noninvasively investigate the association of the anatomical images and quantitative relaxation times with the structure and germinability of the seeds. Relaxation time differences compared to the germination day were also investigated. The average whole seed relaxation times T₁ (two methods), T₂, and T₂ were 430 ± 59, 660 ± 20, 14 ± 1.7, and 0.83 ± 0.33 ms, respectively. It was observed that the seed structures had statistically significant (p &lt; 0.05) differences in relaxation times, while no differences could be observed in relation to the rate of seed germination. Furthermore, the obtained data were compared to radiographs. Empty seeds were observed to provide a minimal MRI signal, whereas intact and mechanically damaged seeds provided a profound signal with distinguishable structures. The mechanically hardest region, i.e., the seed coat, was not visible in MRI as opposed to radiographs. Some seeds determined to be mechanically damaged by radiography were able to germinate, and mechanical faults could be distinguished in MRI. As such, MRI can be seen complementary to the currently used methods to optimize seed sorting and to interpret germination potential.Résumé La disponibilité des semences de pin sylvestre (Pinus sylvestris L.) à haut pouvoir germinatif est nécessaire pour la régénération artificielle des forêts. Dans le présent ouvrage, les semences de verger de la semence de pin sylvestre ont été captées en image par RM (résonance magnétique) afin d’examiner de manière non invasive l’association des images anatomiques et des temps de relaxation quantitatifs avec la structure et le pouvoir germinatif des semences. La différence des temps de relaxation comparativement aux jours de germination a également été examinée. Les temps de relaxation complets des semences T₁ (deux méthodes), T₂ et T₂ étaient 430 ± 59, 660 ± 20, 14 ±1,7 et 0,83 ± 0,33 ms respectivement. On a observé que les structures des semences avaient des différences statistiques importantes (p &lt; 0,05) dans les temps de relaxation alors qu’aucune différence ne pouvait être observée relativement au taux de germination des semences. De plus, les données obtenues ont été comparées aux radiogrammes. On a observé que les semences vaines fournissaient un signal d’IRM minimal alors que les semences intactes et mécaniquement endommagées fournissaient un signal profond avec des structures reconnaissables. La région la plus dure mécaniquement, le tégument, n’était pas visible en IRM contrairement aux radiogrammes. Certaines semences déterminées comme étant mécaniquement endommagées par radiographie étaient en mesure de germer et les défauts mécaniques pouvaient être distingués en IRM. Ainsi, l’IRM peut être considérée comme étant complémentaire aux méthodes actuellement utilisées pour optimiser le triage des semences et pour interpréter le potentiel de germination

Dipolar Relaxation of Water Protons in the Vicinity of a Collagen-like Peptide

Quantitative magnetic resonance imaging is one of the few available methods for noninvasive diagnosis of degenerative changes in articular cartilage. The clinical use of the imaging data is limited by the lack of a clear association between structural changes at the molecular level and the measured magnetic relaxation times. In anisotropic, collagen-containing tissues, such as articular cartilage, the orientation dependency of nuclear magnetic relaxation can obscure the content of the images. Conversely, if the molecular origin of the phenomenon would be better understood, it would provide opportunities for diagnostics as well as treatment planning of degenerative changes in these tissues. We study the magnitude and orientation dependence of the nuclear magnetic relaxation due to dipole-dipole coupling of water protons in anisotropic, collagenous structures. The water-collagen interactions are modeled with molecular dynamics simulations of a small collagen-like peptide dissolved in water. We find that in the vicinity of the collagen-like peptide, the dipolar relaxation of water hydrogen nuclei is anisotropic, which can result in orientation-dependent relaxation times if the water remains dose to the peptide. However, the orientation-dependency of the relaxation is different from the commonly observed magic-angle phenomenon in articular cartilage MRI