bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.08.31.748225

Embedding wear assessment in musculoskeletal simulation: A proof-of-concept application to total hip arthroplasty

Abstract

Predicting wear in artificial joints requires integrating joint dynamics, contact mechanics and progressive surface evolution, yet these processes are often treated separately. In total hip arthroplasty (THA), finite-element approaches remain the reference standard, but they are computationally demanding and usually rely on boundary conditions from independent musculoskeletal (MSK) models, hindering consistent coupling and feedback between wear progression and movement dynamics. As a single-subject proof of concept, we present a computational framework that embeds wear estimation within forward MSK simulations through OpenSim-MATLAB integration. Contact variables are computed using an elastic-foundation formulation, and wear is updated through the Archard law, enabling cyclic prediction of contact mechanics and surface evolution within a single workflow at practical computational cost. The framework was evaluated in one subject with right THA during five activities of daily living and numerically benchmarked against finite-element simulations. A long-term walking analysis of 4 million cycles was also performed to assess geometry updating. Across tasks, peak contact pressures remained within 7% of finite-element predictions. Linear wear depth and volumetric loss showed maximum deviations of 16% and 13%, respectively. Accounting for progressive geometry changes yielded a maximum wear depth about 31% lower than linear extrapolation. These preliminary results support the framework's computational feasibility and numerical consistency for the tested case; nevertheless, multi-subject evaluation is required before broader predictive or clinical use.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Di Pietro, A., Mattei, L., Di Puccio, F.. 2026-09-02. Embedding wear assessment in musculoskeletal simulation: A proof-of-concept application to total hip arthroplasty. https://doi.org/10.64898/2026.08.31.748225

Cite the original work for its findings. Save a collection to share your selection of sources.

Discover connections

Connections use source metadata and explicit phrase matches, not verified experimental comparisons.

KEEP EXPLORING

Related preprints

A single-plane electrical impedance tomography framework for integrated liver and kidney assessment

Chronic liver and kidney diseases frequently coexist, but their assessment typically requires separate clinical workflows involving serum-based estimated glomerular filtration rate (eGFR) testing and liver elastography-based controlled attenuation parameter (CAP). Electrical impedance tomography (EIT) has recently shown promise for providing portable, non-invasive proxies for both reference measurements. However, existing multi-organ EIT assessment still requires different acquisition protocols for each organ. To simplify this procedure, we assessed the feasibility of a single-plane EIT framework for reconstructing organ-specific images and estimating liver and kidney health from one abdominal belt placement. Across diverse abdominal belt locations, opposite-plane deviation was significantly greater for eGFREIT estimates (2.92%; IQR, 0.46-12.53%) than for CAPEIT estimates (0.94%; IQR, 0.66-1.70%) (p < 0.01). For both organs, compared to images acquired at the conventional organ-specific planes, image correlation significantly decreased (both, p < 0.05) and normalized root mean squared error significantly increased (both, p < 0.05) at the furthest imaging plane, with these differences being numerically larger for the kidney. Together, these results supported the kidney plane as the preferred location for multi-organ assessment. Test-retest evaluation after belt removal and reapplication demonstrated that the correlation between two repeated CAPEIT estimates was just as strong at the kidney plane (R2 = 0.98, p < 0.001) as it was at the conventional liver plane (R2 = 0.97, p < 0.001). Finally, in an independent clinical cohort, kidney-plane CAPEIT estimates were significantly higher in participants with a high metabolic liver-risk profile (i.e. diabetes and high blood pressure) (p < 0.005). CAPEIT estimates also distinguished high and low metabolic risk groups with an AUC of 0.756. Together, these findings support the feasibility of a portable multi-organ EIT imaging framework capable of extracting complementary liver and kidney information from a single belt placement.

bioengineering↗

Live Spatial Transcriptomics Enables Longitudinal Tissue Mapping

Spatial transcriptomics has become an important technology in biomedical research by preserving the spatial context of gene expression in tissues and enabling the study of cellular states and interactions in situ. However, most existing methods provide only static snapshots of individual tissue specimens, requiring inference of the molecular dynamics underlying development, disease progression, and therapeutic response from different specimens rather than direct tracking in the same living tissue. Here, we introduce Live Spatial Transcriptomics (Live-ST), a technology that enables longitudinal, transcriptome-wide profiling of living tissue. Live-ST combines electroporation-based intracellular sampling and spatial barcoding to enable repeated, spatially resolved mRNA measurements in intact living tissue through next-generation sequencing. We demonstrate its capabilities by (i) benchmarking spatial mRNA capture in patterned two-dimensional cell systems, (ii) spatially profiling transcriptomes in intact, patient-derived living melanoma tissues while preserving tissue viability, and (iii) longitudinally tracking drug-response dynamics within the tumor microenvironment. Together, Live-ST enables repeated, non-destructive measurements of spatial gene expression, providing a new framework for studying dynamic tissue biology in native physiological and pathological contexts.

bioengineering↗

Mesoscale Soft Robotics for Mechanically Perturbing and Functionally Monitoring Responses in Human Organoids

Human organoids represent promising models for studies of significance to the biology and medical communities. Of the existing approaches for monitoring organoids, none offers the ability to apply programmable mechanical forces while simultaneously recording multi-modal physiological responses, of relevance to phenomena spanning from traumatic brain injuries to cardiac rhythm disorders. Here, we present a mesoscale soft robotic organoid interface that enables programmable delivery of forces to organoids of diverse shapes, and to map electrophysiological activity and mechanical responses. The platform combines actuation elements with integrated sensors for quantitative measurement and control. Studies using this technology reveal that spheroidal cortical organoids exhibit distinct responses to mechanical trauma, including silencing, recovery, and changes in neuronal firing patterns. Additional experiments on cardiac ring tissues demonstrate that sustained stretching induces beat-to-beat rhythm variability and altered conduction. The results establish a framework for investigating force-triggered transitions between physiological and disease-like states in human tissue models.

bioengineering↗