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Item type:Publication, Access status: without files , No pressure, no diamonds? - Static vs. dynamic compressive in-situ loading to evaluate human articular cartilage functionality by functional MRIBiomechanical Magnetic Resonance Imaging (MRI) of articular cartilage, i.e. its imaging under loading, is a promising diagnostic tool to assess the tissue's functionality in health and disease. This study aimed to assess the response to static and dynamic loading of histologically intact cartilage samples by functional MRI and pressure-controlled in-situ loading. To this end, 47 cartilage samples were obtained from the medial femoral condyles of total knee arthroplasties (from 24 patients), prepared to standard thickness, and placed in a standard knee joint in a pressure-controlled whole knee-joint compressive loading device. Cartilage samples' responses to static (i.e. constant), dynamic (i.e. alternating), and no loading, i.e. free-swelling conditions, were assessed before (δ ), and after 30 min (δ ) and 60 min (δ ) of loading using serial T1ρ maps acquired on a 3.0T clinical MRI scanner (Achieva, Philips). Alongside texture features, relative changes in T1ρ (Δ , Δ ) were determined for the upper and lower sample halves and the entire sample, analyzed using appropriate statistical tests, and referenced to histological (Mankin scoring) and biomechanical reference measures (tangent stiffness). Histological, biomechanical, and T1ρ sample characteristics at δ were relatively homogenous in all samples. In response to loading, relative increases in T1ρ were strong and significant after dynamic loading (Δ = 10.3 ± 17.0%, Δ = 21.6 ± 21.8%, p = 0.002), while relative increases in T1ρ after static loading and in controls were moderate and not significant. Generally, texture features did not demonstrate clear loading-related associations underlying the spatial relationships of T1ρ. When realizing the clinical translation, this in-situ study suggests that serial T1ρ mapping is best combined with dynamic loading to assess cartilage functionality in humans based on advanced MRI techniques.Publicationtype: Journal Article64 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage compositionBackground: Articular cartilage degeneration is the hallmark change of osteoarthritis, a severely disabling disease with high prevalence and considerable socioeconomic and individual burden. Early, potentially reversible cartilage degeneration is characterized by distinct changes in cartilage composition and ultrastructure, while the tissue's morphology remains largely unaltered. Hence, early degenerative changes may not be diagnosed by clinical standard diagnostic tools. Methods: Against this background, this study introduces a novel method to determine the tissue composition non-invasively. Our method involves quantitative MRI parameters (i.e., T , T , T and T maps), compositional reference measurements (i.e., microspectroscopically determined local proteoglycan [PG] and collagen [CO] contents) and machine learning techniques (i.e., artificial neural networks [ANNs] and multivariate linear models [MLMs]) on 17 histologically grossly intact human cartilage samples. Results: Accuracy and precision were higher in ANN-based predictions than in MLM-based predictions and moderate-to-strong correlations were found between measured and predicted compositional parameters. Conclusion: Once trained for the clinical setting, advanced machine learning techniques, in particular ANNs, may be used to non-invasively determine compositional features of cartilage based on quantitative MRI parameters with potential implications for the diagnosis of (early) degeneration and for the monitoring of therapeutic outcomes.Publicationtype: Journal ArticleScopus© Citations 13 67 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A serial multiparametric quantitative magnetic resonance imaging study to assess proteoglycan depletion of human articular cartilage and its effects on functionality(2020-09-15); ; ; ; Water, collagen, and proteoglycans determine articular cartilage functionality. If altered, susceptibility to premature degeneration is increased. This study investigated the effects of enzymatic proteoglycan depletion on cartilage functionality as assessed by advanced Magnetic Resonance Imaging (MRI) techniques under standardized loading. Lateral femoral condylar cartilage-bone samples from patients undergoing knee replacement (n = 29) were serially imaged by Proton Density-weighted and T1, T1ρ, T2, and T2* mapping sequences on a clinical 3.0 T MRI scanner (Achieva, Philips). Using pressure-controlled indentation loading, samples were imaged unloaded and quasi-statically loaded to 15.1 N and 28.6 N, and both before and after exposure to low-concentrated (LT, 0.1 mg/mL, n = 10) or high-concentrated trypsin (HT, 1.0 mg/mL, n = 10). Controls were not treated (n = 9). Responses to loading were assessed for the entire sample and regionally, i.e. sub- and peri-pistonally, and zonally, i.e. upper and lower sample halves. Trypsin effects were quantified as relative changes (Δ), analysed using appropriate statistical tests, and referenced histologically. Histological proteoglycan depletion was reflected by significant sub-pistonal decreases in T1 (p = 0.003) and T2 (p = 0.008) after HT exposure. Loading-induced changes in T1ρ and T2* were not related. In conclusion, proteoglycan depletion alters cartilage functionality and may be assessed using serial T1 and T2 mapping under loading.Publicationtype: Journal ArticleScopus© Citations 13 186 384 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Functional MRI Mapping of Human Meniscus Functionality and its Relation to Degeneration(Macmillan Publishers Limited, part of Springer Nature, 2020-02-12); ; ; ; Meniscus pathology may promote early osteoarthritis. This study assessed human meniscus functionality (i.e. its response to loading) ex vivo based on quantitative T1, T1ρ, and T2 mapping as a function of histological degeneration and loading. Forty-five meniscus samples of variable degeneration were harvested from the lateral meniscus body region of 45 patients during total knee arthroplasties. Samples underwent serial mapping on a 3.0-T MRI scanner (Achieva, Philips) using a force-controlled and torque-inducing compressive loading device. Samples were measured at three loading positions, i.e. unloaded, loaded to 2 bar (compression force 37 N) and 4 bar (69 N). Histology (Pauli classification) and biomechanics (Elastic Modulus) served as references. Based on histology, samples were trichotomized as grossly intact (n = 14), mildly degenerative (n = 16), and moderate-to-severely degenerative (n = 15) and analyzed using appropriate parametric and non-parametric tests. For T1, we found loading-induced decreases in all samples, irrespective of degeneration. For T1ρ, zonal increases in intact (apex) and decreases in degenerative samples (base) were found, while for T2, changes were ambiguous. In conclusion, force-controlled loading and serial MR imaging reveal response-to-loading patterns in meniscus. Zonal T1ρ response-to-loading patterns are most promising in differentiating degeneration, while T1 and T2 aren’t clearly related to degeneration.and may provide an imaging-based indication of functional tissue properties.Publicationtype: Journal ArticleScopus© Citations 13 211 373