Adult Spine Deformity (ASD) is a degenerative condition of the adult spine leading to altered spine curvatures and mechanical balance. Computational approaches, like Finite Element (FE) Models have been proposed to explore the etiology or the treatment of ASD, through biomechanical simulations. However, while the personalization of the models is a cornerstone, personalized FE models are cumbersome to generate. To cover this need, we share a virtual cohort of 16807 thoracolumbar spine FE models with different spine morphologies, presented in an online user-interface platform (SpineView). To generate these models, EOS images are used, and 3D surface spine models are reconstructed. Then, a Statistical Shape Model (SSM), is built, to further adapt a FE structured mesh template for both the bone and the soft tissues of the spine, through mesh morphing. Eventually, the SSM deformation fields allow the personalization of the mean structured FE model, leading to generate FE meshes of thoracolumbar spines with different morphologies. Models can be selectively viewed and downloaded through SpineView, according to personalized user requests of specific morphologies characterized by the geometrical parameters: Pelvic Incidence; Pelvic Tilt; Sacral Slope; Lumbar Lordosis; Global Tilt; Cobb Angle; and GAP score. Data quality is assessed using visual aids, correlation analyses, heatmaps, network graphs, Anova and t-tests, and kernel density plots to compare spinopelvic parameter distributions and identify similarities and differences. Mesh quality and ranges of motion have been assessed to evaluate the quality of the FE models. This functional repository is unique to generate virtual patient cohorts in ASD.
Knee osteoarthritis (KOA) diagnosis is based on symptoms, assessed through questionnaires such as the WOMAC. However, the inconsistency of pain recording and the discrepancy between joint phenotype and symptoms highlight the need for objective biomarkers in KOA diagnosis. To this end, we study relationships among clinical and molecular data in a cohort of women (n=51) with Kellgren-Lawrence grade 2–3 KOA through Support Vector Machine (SVM) and a regulation network model (RNM). Clinical descriptors (i.e., pain catastrophism (CA); depression (DE); functionality (FU); joint pain (JP); rigidity (RI); sensitization (SE); synovitis (SY)) are used to classify patients. A Youden's test is performed for each classifier to determine optimal binarization thresholds for the descriptors. Thresholds are tested against patient stratification according to baseline WOMAC data from the Osteoarthritis Initiative, and the mean accuracy is 0.97. For our cohort, the data used as SVM inputs are KOA descriptors, synovial fluid (SL) proteomic measurements (n=25), and transcription factors (TF) activation obtained from RNM [2] stimulated with the SL measurements. The relative weights after classification reflect input importance. The performance of each classifier is evaluated through AUC-ROC analysis. The best classifier with clinical data is CA (AUC = 0.9), highly influenced by FU and SE, suggesting that kinesophobia is involved in pain perception. With SL input, leptin strongly influences every classifier, suggesting the importance of low-grade inflammation. When TF are used, the mean AUC is limited to 0.608, which can be related to the pleomorphic behaviour of osteoarthritic chondrocytes. Nevertheless, FU has an AUC of 0.7 with strong importance of FOXO downregulation. Though larger and longitudinal cohorts are needed, this unique combination of SVM and RNM shall help to map objectively KOA descriptors.
Intervertebral discs (IVD) provide flexibility to the back and ensure functional distributions of the spinal loads. They are avascular, and internal diffusion-dependent metabolic transport is vital to supply nutrients to disc cells1, but interactions with personalized IVD shapes and mechanics remain poorly explored. Poromechanical finite element models of seven personalized lumbar IVD geometries, with mean heights ranging from 8 to 16 mm were coupled with a reactive oxygen, glucose and lactate transport model linked with tissue deformations and osmosis . In previous studies, reduced formulations of the divergence of the solute flux (∇ .
Intervertebral disc (IVD) degeneration is a pathological process often associated with chronic back pain and considered a leading cause of disability worldwide1. During degeneration, progressive structural and biochemical changes occur, leading to blood vessel and nerve ingrowth and promoting discogenic pain2. In the last decades, several cytokines have been applied to IVD cells in vitro to investigate the degenerative cascade. Particularly, IL-10 and IL-4 have been predicted as important anabolic factors in the IVD according to a regulatory network model based in silico approach3. Thus, we aim to investigate the potential presence and anabolic effect of IL-10 and IL-4 in human NP cells (in vitro) and explants (ex vivo) under hypoxia (5% O2) after a catabolic induction. Primary human NP cells were expanded, encapsulated in 1.2% alginate beads (4 × 106 cells/ml) and cultured for two weeks in 3D for phenotype recovery while human NP explants were cultured for five days. Afterwards, both alginate and explant cultures were i) cultured for two days and subsequently treated with 10 ng/ml IL-10 or IL-4 (single treatments) or ii) stimulated with 0.1 ng/ml IL-1β for two days and subsequently treated with 10 ng/ml IL-10 or IL-4 (combined treatments). The presence of IL-4 receptor, IL-4 and IL-10 was confirmed in human intact NP tissue (Fig 1). Additionally, IL-4 single and combined treatments induced a significant increase of proinflammatory protein secretion in vitro (Fig. 2A-C) and ex vivo (Fig. 2D and E). In contrast, no significant differences were observed in the secretome between IL-10 single and combined treatments compared to control group. Overall, IL-4 containing treatments promote human NP cell and explant catabolism in contrast to previously reported IL-4 anti-inflammatory performance4. Thus, a possible pleiotropic effect of IL-4 could occur depending on the IVD culture and environmental condition.
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This study investigates the relationships between Intervertebral Disc (IVD) morphology and biomechanics using patient-specific (PS) finite element (FE) models and poromechanical simulations. 169 3D lumbar IVD shapes from the European project MySpine (FP7-269909), spanning healthy to Pfirrmann grade 4 degeneration, were obtained from MRIs. A Bayesian Coherent Point Drift algorithm aligned meshes to a previously validated structural FE mesh of the IVD. After mesh quality analyses and Hausdorff distance measurements, mechanical simulations were performed: 8 and 16 hours of sleep and daytime, respectively, applying 0.11 and 0.54 MPa of pressure on the upper cartilage endplate (CEP). Simulation results were extracted from the anterior (ATZ) and posterior regions (PTZ) and the center of the nucleus pulposus (CNP). Data mining was performed using Linear Regression, Support Vector Machine, and eXtreme Gradient Boosting techniques. Mechanical variables of interest in DD, such as pore fluid velocity (FLVEL), water content, and swelling pressure, were examined. The morphological variables of the simulated discs were used as input features. Local morphological variables significantly impacted the local mechanical response. The local disc heights, respectively in the mid (mh), anterior (ah), and posterior (ph) regions, were key factors in general. Additionally, fluid transport, reflected by FLVEL, was greatly influenced (r2 0.69) by the shape of the upper and lower cartilage endplates (CEPs). This study suggests that disc morphology affects Mechanical variables of interest in DD. Attention should be paid to the antero-posterior distribution and local effects of disc heights. Surprisingly, the CEP morphology remotely affected the fluid transport in NP volumes around mid-height, and mechanobiological implications shall be explored. In conclusion, patient-specific IVD modeling has strong potential to unravel important correlations between IVD phenotypes and local tissue regulation.
Osteoarthritis (OA) leads to articular cartilage degradation, following complex dysregulation of chondrocyte's metabolism towards a catabolic state. Mechanical and biochemical signals are involved and need to be considered to understand the condition. Regulatory network-based models (RNM) successfully simulated the biological activity of the chondrocyte and the transduction of mechanical signals at the molecular and cell levels. However, the knowledge gap between single-cell regulation and intercellular communication in tissue volumes hinders the interpretability of such models at larger scales. Accordingly, a novel tissue-level biochemical model is proposed. We hypothesise that it is possible to simulate interacting network effects through the transport of diluted species in a finite-element model, to grasp relevant dynamics of cell and tissue regulation in OA. Chondrocyte RNM equations were translated into a reaction term of 18 multi-species diffusion model (e.g., 3 anti-inflammatory and 8 pro-inflammatory interleukins, 3 pro-anabolic and 1 pro-catabolic growth factors, 2 nociceptive factors and 2 pro-inflammatory cytokines). Elements with RNM reaction terms represented the chondrocytes and were distributed randomly through the model, according to known cellular density in the knee cartilage, and could both react to and produce diffusive entities through the pericellular matrix, associated with reduced diffusion coefficients. The model was constructed over a 2D square of 0.47 mm sides considered to be in the middle of the cartilage, so boundary conditions were settled as periodic. Different simulations were initialised with initial concentrations of either healthy or pro-OA mediators. Preliminary results showed that, independently of the initial conditions, the chondrocytes successfully evolved into anabolic states, in absence of sustained pro-catabolic external stimulations, in contrast to single-cell RNM [2]. Our intercellular model suggests that paracrine communication may increase robustness towards cartilage maintenance, and future tests shall reveal new OA dynamics.
Intervertebral disc (IVD) degeneration (IDD) involves imbalance between the anabolic and the catabolic processes that regulate the extracellular matrix of its tissues. These processes are complex, and improved integration of knowledge is needed. Accordingly, we present a nucleus pulposus cell (NPC) regulatory network model (RNM) that integrates critical biochemical interactions in IVD regulation and can replicate experimental results. The RNM was built from a curated corpus of 130 specialized journal articles. Proteins were represented as nodes that interact through activation and inhibition edges. Semi-quantitative steady states (SS) of node activations were calculated. Then, a full factorial sensitivity analysis (SA) identified which out of the RNM 15 cytokines, and 4 growth factors affected most the structural proteins and degrading enzymes. The RNM was further evaluated against metabolic events measured in non-healthy human NP explant cultures, after 2 days of 1ng/ml IL-1B catabolic induction. The RNM represented successfully an anabolic basal SS, as expected in normal IVD. IL-1B was able to increase catabolic markers and angiogenic factors and decrease matrix proteins. Such activity was confirmed by the explant culture measurements. The SA identified TGF-β and IL1RA as the two most powerful rescue mediators. Accordingly, TGFβ signaling-based IDD treatments have been proposed and IL-1RA gene therapy diminished the expression of proteases. It resulted challenging to simulate rescue strategies by IL-10, but interestingly, IL-1B could not induce IL-10 expression in the explant cultures. Our RNM was confronted to independent in vitro measurements and stands for a unique model, to integrate soluble protein signaling and explore IDD.
An organ culture experiment was simulated to explore the mechanisms that can link cell death to mechanical overload in the intervertebral disc. Coupling cell nutrition and tissue deformations led to altered metabolic transport that largely explained cell viability measurements. Part of intervertebral disc (IVD) maintenance relies on limited nutrient availability to the cells and on mechanical loads, but effective implication of these two factors is difficult to quantify. Theoretical models have helped to understand the link between solute transport and cell nutrition in deforming IVD, but omitted the direct link between tissue mechanics and cell metabolism. Hence, we explored numerically the relation between disc mechanics and cell death in relation to an organ culture experiment.Summary Statement
Introduction