Multiscale modelling workflows and applications

Introduction

MultiSim has integrated the ongoing musculoskeletal research within the University of Sheffield into the grand vision of the grant. This has resulted in the development of models at all scales and integration into a multi-scale platform, with three application workflows:

1. A workflow for the prediction of femoral fractures in osteoporotic patients. We have been able to show that patient-specific predictions of the risk of fracture in post-menopausal woman were more accurate with computer simulations than current clinical standard.
2. The development of computational tools for children musculoskeletal diseases such as the diagnosis of unexplained fractures in the child.
3. The development of a murine platform for the complete study of multiscale modelling and the possibility to validate the tools developed at each scale and their integration from the cell to the organ levels.

A general hypermodelling framework concept was constructed to enable multiscale modelling across space and time by defining inputs and outputs between scales within each application.

In addition, a general IT infrastructure is being developed to provide successful applications as an online service to external users by establishing a workflow of software applications using Taverna.

Download Multiscale Challenge diagram (PDF, 447KB). MultiSim's multiscale challenge: The workflow applications are linked to model scales that they depend on. The scales are: environment, population, body, organ, tissue, cell, molecular.

• The hypermodel links all the scales.
• Application 1, Prediction of osteoporotic fractures links population, body, organ and tissue scales.
• Application 2, Diagnosis of unexplained fractures in the child links body, organ and tissue scales.
• Application 3, murine model, links organ, tissue, cell and molecule scales.

The revised work package diagram (PDF,136 KB) shows how the original MultiSim work packages feed into the application workflows developed.

Application 1 Prediction of Osteoporotic Fractures and Application 3 Murine Model, have subsequently been developed into mature workflows illustrated in the two videos below.

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Application 1 workflow: Prediction of osteoporotic fracture

The video below shows how movement data and image data from image data from MRI and CT scans are be combined to develop musculoskeletal kinematic models and finite element models to predict the risk of fracture.

The Clinical workflow document (PDF, 782KB) provides a summary of the workflow and team that are developing it.

Publications related to Application 1

2023

Altai, Z., Montefiorie, E., Li, X. (2023), "Effect of Muscle Forces on Femur During Level Walking Using a Virtual Population of Older Women", In: Heifetz, A. (eds) High Performance Computing for Drug Discovery and Biomedicine. Methods in Molecular Biology, Vol 2716. Humana, New York, NY. 

Henson, W. H., Mazzà, C., Dall'Ara, E. (2023), "Deformable image registration based on single or multi-atlas methods for automatic muscle segmentation and the generation of augmented imaging datasets", PLoS One, 18(3): e0273446.  

2022

Aldieri, A., Terzini, M., Audenino, A. L., Bignardi, C., Paggiosi, M., Eastell, R., Viceconti, M., Bhattacharya, P. (2022), "Personalised 3D Assessment of Trochanteric Soft Tissues Improves Hip Fracture Classification Accuracy", Annals of Biomedical Engineering.

Benemerito, I., Montefiori, E., Marzo, A., Mazzà, C. (2022), "Reducing the complexity of musculoskeletal models using Gaussian process emulators", Applied Sciences, 12(24), 12932. 

Montefiori, E., Hayford, C. F., Mazzà, C. (2022), "Variations of lower-limb joint kinematics associated to the use of different ankle joint models", Journal of Biomechanics, 136, 111072.

2021

Altai, Z., Montefiori, E., van Veen, B., Paggiosi, M. A., McCloskey, E. V., Viceconti, M., Mazzà, C., Li, X. (2021), “Femoral neck strain prediction during level walking using a combined musculoskeletal and finite element model approach”, PLoS ONE, 16(2): e0245121.

Benemerito, I., Griffiths, W., Allsopp, J., Furnass, W., Bhattacharya, P., Marzo, A., Wood., S., Viceconti, M., Narracott, A. (2021), "Delivering computationally-intensive Digital Patient applications to the clinic: an exemplar solution to predict femoral bone strength from CT data", Computer Methods and Programs in Biomedicine, 208, 106200.

Bhattacharya, P., Li, Q., Lacroix, D., Kadirkamanathan, V., Viceconti, M. (2021), "A systematic approach to the scale separation problem in the development of multiscale models", PLoS One, 16(5): e0251297. 

Conconi, M., Montefiori, E., Sancisi, N., Mazzà, C. (2021), "Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency", Applied Sciences, 11(18), 8348. 

Martelli, S., Giorgi, M., Dall’Ara, E., Perilli, E (2021), “Damage tolerance and toughness of elderly human femora”, Acta Biomaterialia.

Montefiori, E., Hayford, C. F., Mazzà, C. (Preprint), "Variations of lower-limb joint kinematics associated to the use of different ankle joint models", Available at Social Science Research Network (SSRN).

Taylor, M., Viceconti, M., Bhattacharya, P., Xinshan, L. (2021), "Finite element analysis informed variable selection for femoral neck fracture risk  prediction", Journal of the Mechanical Behavior of Biomedical Materials, 118, 104434.

van Gelder, L., M., A., Angelini, L., Buckley, E., E., Mazzà, C.  (2021), "A Proposal for a Linear Calculation of Gait Asymmetry", Symmetry, 13(9), 1560.

2020

Altai, Z., Viceconti, M., Li, X., Offiah, A. C. (2020), “Investigating Rolling as Mechanism for Humeral Fractures in Non-Ambulant Infants: A Preliminary Finite Element Study”, Clinical Radiology, 75 (1), 78.e9-78.e16. 

Benemerito, I., Modenese, L., Montefiori, E., Mazzà, C., Viceconti, M., Lacroix, D., Guo, L. (2020), “An extended discrete element method for the estimation of contact pressure at the ankle joint during stance phase”, Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. White Rose Research Online link.   

Montefiori, E., Kalkman, B. M., Henson, W. H., Paggiosi, M. A., McCloskey, E. V., Mazzà, C. (2020), “MRI-based anatomical characterisation of limb muscles in post-menopausal woman”, PLoS ONE.

Ryan, M., Barnett, L., Rochester, J., Wilkinson, J. M., Dall’Ara, E. (2020), “A new approach to comprehensively evaluate the morphological properties of the human femoral head: example of application to osteoarthritic joint”, Scientific Reports, 10, Article number: 5538.

Ryan, M., Oliviero, S., Costa, M. C., Wilkinson, J. M., Dall’Ara, E. (2020), “Heterogeneous strain distribution in the subchondral bone of osteoarthritic femoral heads measured with digital volume correlation”, Materials, 13(20), 4619.

van Veen, B. C., Mazzà, C., Viceconti, M. (2020), “The uncontrolled manifold theory can explain only part of the inter-trial variability of knee contact force during level walking”, IEEE Transactions on Neural Systems & Rehabilitation Engineering, 28 (8).

Wang, N., Niger, C., Li, N., Richards, G. O., Skerry, T. M. (2020), “Cross-species RNA-Seq study comparing transcriptome signatures of enriched osteocyte populations in the tibia and skull”, Frontiers in Endocrinology, 11, p 693.

Winsor, C., Li, X., Qasim, M., Henak, C. R., Pickhardt, P. J., Ploeg, H., Viceconti, M. (2020), “Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses”, Bone, 115759.

Yang, W., Lacroix, D., Tan, L. P., Chen, J. (2021), “Revealing the nanoindentation response of a single cell using a 3D structural finite element model”, Journal of Materials Research.

2019

Altai, Z., Qasim, M., Li, X., Viceconti, M. (2019), “The Effect of Boundary and Loading Conditions on Patient Classification Using Finite Element Predicted Risk of Fracture”, Clinical Biomechanics, 68, pp 137-143.

Montefiori, E., Modenese, L., Di Marco, R., Magni-Manzoni, S., Malattia, C., Petrarca, M., Ronchetti, A., de Horatio, L. T., van Dijkhuizen, P., Wang, A., Wesarg, S., Viceconti, M., Mazzà, C.; MD-PAEDIGREE Consortium (2019), “An image-based kinematic model of the tibiotalar and subtalar joints and its application to gait analysis in children with Juvenile Idiopathic Arthritis”, Journal of Biomechanics, 85, pp 27-36.

Montefiori, E., Modenese, L., Di Marco, R., Magi-Manzoni, S., Malattia, C., Petrarca, M., Ronchetti, A., Tanturri de Horatio, L., van Dijkhuizen, P., Wang, A., Wesarg, S., Viceconti, M., Mazzà, C. for the MD-PAEDIGREE Consortium (2019), “Linking joint impairments and gait biomechanics in patients with Juvenile Idiopathic Arthritis”, Annals of Biomedical Engineering, 47 (11), pp 2155-2167.

van Veen, B. C., Montefiori, E., Modenese, L., Mazzà, C., Viceconti, M. (2019), “Muscle Recruitment Strategies Can Reduce Joint Loading During Level Walking”, Journal of Biomechanics, 97, 109368.

Viceconti, M., Ascani, D., Mazzà, C. (2019), “Pre-operative Prediction of Soft Tissue Balancing in Knee Arthoplasty Part 1: Effect of Surgical Parameters During Level Walking”, Journal of Orthopaedic Research.

2018

Bhattacharya, P., Altai, Z., Qasim, M., Viceconti, M. (2018), “A Multiscale Model to Predict Current Absolute Risk of Femoral Fracture in a Postmenopausal Population”, Biomechanics and Modeling in Mechanobiology, 18 (2), pp 301-318.

Di Marco, R., Scalona, E., Pacilli, A., Cappa, P., Mazzà, C., Rossi, S. (2018), “How to choose and interpret similarity indices to quantify the variability in gait joint kinematics”, International Biomechanics, 5 (1), pp 1‑8.

Modenese, L., Montefiori, E., Wang, A., Wesarg, S., Viceconti, M., Mazzà, C. (2018), “Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling”, Journal of Biomechanics, 16 (3), pp 216-223.

Shahabpoor, E., Pavic, A. (2018), “Estimation of Vertical Walking Ground Reaction Force in Real-life Environment from Single IMU Sensor”, Journal of Biomechanics.

Shahapoor, E., Pavic, A., Brownjohn, J. M. W., Billings, S. A., Guo, L., Bocian, M. (Published), “Real-Life Measurement of Tri-Axial Walking Ground Reaction Forces Using Optimal Network of Wearable Inertial Measurement Units”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26 (6). Open version (PDF, 2.5MB)

Tagliapietra, L., Modenese, L., Reggiani, M., Ceseracciu, E., Mazzà, C. (2018), “Validation of a model-based inverse kinematics approach based on wearable inertial sensors”, Computer Methods in Biomechanics and Biomedical Engineering.

Tamburini, P., Storm, F., Buckley, C., Bisi, M. C., Stagni, R., Mazzà, C (2018), “Moving from laboratory to real life conditions: influence on the assessment of variability and stability of gait”, Gait and Posture, 59, pp 248-252.

Viceconti, M., Qasim, M., Bhattacharya, P., Li. X. (2018), “Are CT-Based Finite Element Model Predictions of Femoral Bone Strengthening Clinically Useful?”, Current Osteoporosis Reports.

2017

Dall’Ara, E., Eastell, R., Viceconti, M., Pahr, D., Yang, L. (2016), “Experimental Validation of DXA-based Finite Element models for prediction of femoral strength”, Journal of the Mechanical Behavior of Biomedical Materials, 63, pp 17-25.

Guo, Y., Storm, F., Zhao, Y., Billings, S. A., Pavic, A., Mazzà, C., Guo, L. (2017), “A New Proxy Measurement Algorithm with Applications to Vertical Ground Reaction Forces with Wearable Sensors”, Sensors, 17 (10), pp 2181-2195.

Hannah I., Montefiori E., Modenese L., Prinold, J., Viceconti M., Mazzà C. (2017), “Sensitivity of a juvenile subject-specific musculoskeletal model of the ankle joint to the variability of operator dependent input”, Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine, 231 (5), pp415-422.

Moissenet, F., Modenese, L., Dumas, R. (2017), “Alterations of musculoskeletal models for a more accurate estimation of lower limb joint contact forces during normal gait: A systematic review”, Journal of Biomechanics, 63, pp 8-20.

Shahabpoor, E., Pavic, A. (2017), “Measurement of Walking Ground Reactions in Real-Life Environments: A Systematic Review of Techniques and Technologies”, Sensors, 17 (9), 2085.

2016

Hannah, I., Sawacha, Z., Guiotto, A., Mazzà, C. (2016), “Relationship between sagittal plane kinematics, foot morphology and vertical forces applied to three regions of the foot”, International Biomechanics, 3 (1), pp 50-56.

Lamberto, G., Martelli, S., Cappozzo, A., Mazzà, C. (2016), “To what extent is joint and muscle mechanics predicted by musculoskeletal models sensitive to soft tissue artefacts?”, Journal of Biomechanics, Available online 24 August 2016.

Qasim, M., Farinella, G., Zhang, J., Li, X., Yang, L., Eastell, R., Viceconti, M. (2016), “Patient-Specific Finite Element Estimated Femur Strength as a Predictor of the Risk of Hip Fracture: The Effect of Methodological Determinants”, Osteoporosis International, 27 (9), pp 2815-2822.

Storm, F., Buckley, C., Mazzà, C. (2016), “Gait event detection in indoor and outdoor settings: accuracy of two inertial sensors based methods”, Gait and Posture, 50, pp 42-46.

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Application 3 workflow: Murine model

The video below shows how the murine models developed in MultiSim can be used to improve the current preclinical assessment of new interventions through better experiments, better endpoints and validated multiscale models.

The Pre-clinical workflow document (PDF, 445KB) below provides a summary of the workflow and team that are developing it.

Publications related to Application 3

2023

Karali, A., Dall'Ara, E., Zekonyte, J., Kao, A. P., Blunn, G., Tozzi, G. (2023), "Effect of radiation-induced damage of trabecular bone tissue evaluated using indentation and digital volume correlation", Journal of the Mechanical Behavior of Biomedical Materials, 138, 105636.

Oliviero, S., Millard, E., Chen, Z., Rayson, A., Roberts, B. C., Ismail, H. M. S., Bellantuono, I., Dall'Ara, E. (2023), "Accuracy of in vivo microCT imaging in assessing the microstructural properties of the mouse tibia subchondral bone", Frontiers in Endocrinology, 13, 1016321.

2022

Dall'Ara, E., Bodely, A. J., Isaksson, H., Tozzi, G. (2022), "A practical guide for in situ mechanical testing of musculoskeletal tissues using synchrotron tomography", Journal of the Mechanical Behavior of Biomedical Materials, 133, 105297.

Dall'Ara, E., Tozzi, G. (2022), "Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments", Frontiers in Bioengineering and Biotechnology, 10, 1010056. 

Oliviero, S., Cheong, V. S., Roberts, B. C., Diaz, C. A. O., Griffiths, W., Bellantuono, I., Dall'Ara, E. (2022), "Reproducibility of Densitometric and Biomechanical Assessment of the Mouse Tibia From In Vivo Micro-CT Images", Frontiers in Endocrinology, 13, 915938.

2021

Cheong, V. S., Kadirkamanathan, V., Dall'Ara, E. (2021), "The role of the loading condition in predictions of bone adaptation in a mouse tibial loading model", Frontiers in Bioengineering and Biotechnology, 9, pp 461.

Cheong, V. S., Roberts, B. C., Kadirkamanathan, V., Dall'Ara, E. (2021), "Positive interactions of mechanical loading and PTH treatments on spatio-temporal bone remodelling", Acta Biomaterialia, 136, pp 291-305.

Oliviero, S., Owen, R., Reilly, G. C., Bellantuono, I., Dall’Ara, E. (2021), “Optimization of the failure criterion in micro-Finite Element models of the mouse tibia for the non-invasive prediction of its failure load in preclinical applications”, Journal of the Mechanical Behavior of Biomedical Materials, 113 (104190).

Oliviero, S., Roberts, M., Owen, R., Reilly, G. C., Bellantuono, I., Dall’Ara, E. (2021), “Non-invasive prediction of the mouse tibia mechanical properties from microCT images: comparison between different Finite Element models”, Biomechanics and Modelling in Mechanobiology.

2020

Ascolani, G., Skerry, T. M., Lacroix, D., Dal’Ara, E., Shuaib, A. (2020), “Analysis of mechanotransduction dynamics during combined mechanical stimulation and modulation of the extracellular-regulated kinase cascade uncovers hidden information within the signalling noise”, Interface Focus, 11(1): 20190136.

Ascolani, G., Skerry, T. M., Lacroix, D., Dal’Ara, E., Shuaib, A. (2020), “Revealing hidden information in osteoblast’s mechanotransduction through analysis of time patterns of critical events”, BMC Bioinformatics, 21 (114). 

Cheong, V. S., Roberts, B. C., Kadirkamanathan, V., Dall’Ara, E. (2020), “Bone remodelling in the mouse tibia is spatio-temporally modulated by oestrogen deficiency and external mechanical loading: a combined in vivo/in silico study”, Acta Biomaterialia, 116, pp 302-317.

Costa, M. C., Bresani Campello, L. B., Ryan, M., Rochester, J., Viceconti, M., Dall’Ara, D. (2020), “Effect of size and location of simulated lytic lesions on the structural properties of human vertebral bodies, a micro-finite element study”, Bone Reports, 12, 100257. 

Kusins, J., Knowles, N., Columbus, M., Oliviero, S., Dall’Ara, E., Athwal, G. S., Ferreira, L. M. (2020), “The Application of Digital Volume Correlation (DVC) to Evaluate Strain Predictions Generated by Finite Element Models of the Osteoarthritic Humeral Head”, Annals of Biomedical Engineering.

Rakowski, A. G., Veličković P., Dall’Ara E., Liò P. (2020), “ChronoMID – Cross-modal neural networks for 3-D temporal medical imaging data”, PLoS ONE, 15 (2), e0228962. 

Roberts, B. C., Arrendondo Carrera, H. M., Zanjani-pour, S., Boudiff, M., Wang, N., Gartland, A., Dall’Ara, E. (2020), “PTH(1-34) treatment and/or mechanical loading have different osteogenic effects on the trabecular and cortical bone in the ovariectomized C57BL/6 mouse”, Scientific Reports, 10, Article number: 8889.

Zanjani-Pour, S., Giorgi, M., Dall’Ara, E. (2020), “Development of subject specific finite element models of the mouse knee joint for preclinical applications”, Frontiers in Bioengineering and Biotechnology, 8: 558815.

2019

Cheong, V. S., Campos Marin, A., Lacroix, D., Dall’Ara, E. (2019), “A novel algorithm to predict bone changes in the mouse tibia properties under physiological conditions”, Biomechanics and Modeling in Mechanobiology.

Giorgi, M., Sotirou, V., Franchini, N., Conigliaro, S., Biganardi, C., Nowlan, N. C., Dall’Ara, E., (2019), “Prenatal growth map of the mouse knee joint by means of deformable registration technique”, PLoS One, 14 (1): e0197947.

Oliviero, S., Giorgi, M., Laud, P. J., Dall’Ara, E. (2019), “Effect of repeated in vivo microCT imaging on the properties of the mouse tibia”, PLoS One, 14 (11): e0225127. 

Roberts, B. C., Giorgi, M., Oliviero, S., Wang, N., Boudiffa, M., Dall’Ara, E. (2019), “The longitudinal effects of ovariectomy on the morphometric, densitometric and mechanical properties in the murine tibia: a comparison between two mouse strains”, Bone, 127, pp 260-270.

Shuaib, A., Motan, D., Bhattacharya, P., McNabb, A., Skerry, T. M., Lacroix, D. (2019), “Heterogeneity in The Mechanical Properties of Integrins Determines Mechanotransduction Dynamics in Bone Osteoblasts”, Scientific Reports, 9, Article number: 13113.

Zhang, Y., Dall’Ara, E., Viceconti, M., Kadirkamanathan, V. (2019), “A new method to monitor bone geometry changes at different spatial scales in the longitudinal in vivo μCT studies of mice bones”, PLoS One, 14(7): e0219404.

2018

Oliviero, S., Giorgi, M., Dall’Ara, E. (2018), “Validation of Finite Element models of the Mouse Tibia using Digital Volume Correlation”, Journal of the Mechanical Behavior of Biomedical Materials, 86, pp 172–184.

2017

Dall’Ara, E., Peña-Fernández, M., Palanca, M., Giorgi, M., Cristofolini, L., Tozzi, G. (2017), “Precision of DVC approaches for strain analysis 1 in bone imaged with μCT at different dimensional levels”, Frontiers in Materials: Mechanics of Materials, 4, Article 31.

Oliviero, S., Y., Lu, Y., Viceconti, M., Dall’Ara, E. (2017), “Effect of integration time on the morphometric, densitometric and mechanical properties of the mouse tibia”, Journal of Biomechanics, 65, pp 203-211.

Lu, Y., Boudiffa, M., Dall’Ara, E., Liu, Y., Bellantuono, I., Viceconti, M. (2017), “Longitudinal effects of Parathyroid Hormone treatment on morphological, densitometric and mechanical properties of mouse tibia”, Journal of the Mechanical Behavior of Biomedical Materials, 75, pp 244-251.

2016

Giorgi, M., Verbruggen, S. W., Lacroix, D. (2016), “In silico bone mechanobiology: Modelling a multi-faceted biological system”, WIREs Systems Biology and Medicine, 8 (6), pp 485-505.

Lu, Y., Boudiffa, M., Dall’Ara, E., Bellantuono, I., Viceconti, M. (2016), “Development of a protocol to quantify local bone adaptation over space and time: Quantification of reproducibility”, Journal of Biomechanics, 49 (10), pp 2095-2099.

Wittkowske, C., Reilly, G. C., Lacroix, D., Perrault, C. M. (2016), “In vitro bone cell models: Impact of fluid shear stress on bone formation”, Frontiers in Bioengineering and Biotechnology, 4 (87), 22 pages.