Frontier Engineering: Progression Grant in Modelling complex and partially identified engineering problems. Application to the musculoskeletal system.
Lead Research Organisation:
University of Sheffield
Department Name: Mechanical Engineering
Abstract
Traditional engineering ignores complex interactions across several space-time scales, which does not fit the context of modelling of biological systems where scales overlap and the inherent complexity of multi-scale interaction cannot be avoided. For this reason, in the previously funded MultiSim project, we established a computational platform for the investigation of musculoskeletal disorders, which we successfully applied to the prediction of the risk of fracture in osteoporotic and osteopenic women, and to the pre-clinical investigation of bone remodelling in animal models to assess the effect of new treatments. Full exploitation of this platform, however, is limited by the fact that most of the MultiSim activities evolved around skeletal health only. MultiSim2 will allow us to expand the focus of our Centre to include an equivalently robust and detailed modelling of the skeletal muscles to predict the effects of pathologies such as sarcopenia or neurodegenerative diseases. To do so, we will develop new approaches for better imaging, characterisation and modelling of the muscles and of their interaction with the skeletal system. In our murine work, we will focus on developing noninvasive longitudinal imaging techniques and computational models to support the reduction and partial replacement of the use of mice in musculoskeletal research. We will measure longitudinal changes in muscle properties by using a micro-magnetic resonance imaging (microMRI) system and advanced image processing to predict tissue changes over time. These measurements will be integrated to a framework of available tools to obtain bone properties at high resolution with in vivo micro-Computed Tomography (microCT) and to co-register all the acquired data in space and time. We will use our human models to predict physiological and pathological changes of muscle volumes and masses, variations in muscle fibres, tendon geometric and elastic properties and changes associated with degeneration in the neuromotor control. The comprehensive assessment of changes in different musculoskeletal tissues (bone, muscles, tendons) over time in both patients and animals will allow us to create a combined experimental and computational framework to better understand and model the effect of diseases and to optimise future treatments.
Planned Impact
Computational modelling is widely employed across most engineering domains, and Computational Medicine is increasingly predicting personalised healthcare outcomes. MultiSim has been a significant and successful engineering initiative that has tackled a major issue affecting computational medicine, namely the complexity of building models of physiology that span multiple length-scales, requiring the interconnection of disparate systems. This outcome is already proliferating across academia, and being actively considered for commercial and regulatory use. In MultiSim2 we intend to accelerate the uptake of the technology, by adding to the existing bone biomechanics system a similar mechanism for the complete representation of muscle, allowing us to build an impressive keynote demonstrator that describes sarcopenia (loss of skeletal muscle with age) and can also be applied to many neurodegenerative conditions.
MultiSim is an enabling technology with significant impact across academic, industrial, clinical and socio-economic domains. MultiSim2 will enable the framework to be applied immediately to various categories of problem, employing industrial and clinical pathways to bring socio-economic benefit, which include:
- Sarcopenia, for which we will support developments of new understanding and biomarkers;
- Neurodegenerative diseases, like Motor Neurone Disease, where our integrated muscle models will allow investigation of innovative therapeutic possibilities.
- Revision of long-term care strategies, where our enhanced multiscale prediction will allow to explore changes in population distribution between early and late stage disease
- Longitudinal Studies, where we will explore how our measurement and modelling platform can be used to reduce, even replace, animal studies.
- Comorbidities, where by facilitating the combination of separate disease models, we will offer safe and simple investigative possibilities, where clinical trials bring risk and poor recruitment.
Academic Impact Pathways will entail: publications in peer-reviewed journals and talks at scientific conferences; encouragement of Direct Uptake of our existing web services; organisation of "Modelathons" to promote multi-scale modelling among young researchers; organisation of Creativity@Home events to pursue collective creative discovery on multiscale modelling problems; collaborative dissemination to promote outreach to other EPSRC Frontier Centres and Engineering Networks; securing future funding to enable implementation of an extended series of modelling improvements to fulfil the goals of Healthy Ageing and a Healthy Nation.
Industrial Impact Pathways will leverage on ongoing activities from the Insigneo Institute for in silico Medicine, targeting drug developers, medical device designers, regulatory agencies and technology transfer.
Clinical Impact Pathways will seek increased engagement with clinical experts in musculoskeletal care, to improve understanding, extend dialogue, and identify clinical targets of importance to patients. This will leverage on the links that our group has with the UK's clinical networks, with support groups and charitably-supported communities.
Socioeconomic Impact Pathways will entail the continuous assessment of the market potential for each of the proposed developments, and the likely economic justification for their introduction, with dedicated socioeconomic and industrial assessment of change management within healthcare.
Additional Impact Pathway Activities will target Domain Migration (through internal dissemination activities) and optimisation of Knowledge, Standards, IP, Open Access processes to optimise the use of data and digital tools to further research and patient care.
MultiSim is an enabling technology with significant impact across academic, industrial, clinical and socio-economic domains. MultiSim2 will enable the framework to be applied immediately to various categories of problem, employing industrial and clinical pathways to bring socio-economic benefit, which include:
- Sarcopenia, for which we will support developments of new understanding and biomarkers;
- Neurodegenerative diseases, like Motor Neurone Disease, where our integrated muscle models will allow investigation of innovative therapeutic possibilities.
- Revision of long-term care strategies, where our enhanced multiscale prediction will allow to explore changes in population distribution between early and late stage disease
- Longitudinal Studies, where we will explore how our measurement and modelling platform can be used to reduce, even replace, animal studies.
- Comorbidities, where by facilitating the combination of separate disease models, we will offer safe and simple investigative possibilities, where clinical trials bring risk and poor recruitment.
Academic Impact Pathways will entail: publications in peer-reviewed journals and talks at scientific conferences; encouragement of Direct Uptake of our existing web services; organisation of "Modelathons" to promote multi-scale modelling among young researchers; organisation of Creativity@Home events to pursue collective creative discovery on multiscale modelling problems; collaborative dissemination to promote outreach to other EPSRC Frontier Centres and Engineering Networks; securing future funding to enable implementation of an extended series of modelling improvements to fulfil the goals of Healthy Ageing and a Healthy Nation.
Industrial Impact Pathways will leverage on ongoing activities from the Insigneo Institute for in silico Medicine, targeting drug developers, medical device designers, regulatory agencies and technology transfer.
Clinical Impact Pathways will seek increased engagement with clinical experts in musculoskeletal care, to improve understanding, extend dialogue, and identify clinical targets of importance to patients. This will leverage on the links that our group has with the UK's clinical networks, with support groups and charitably-supported communities.
Socioeconomic Impact Pathways will entail the continuous assessment of the market potential for each of the proposed developments, and the likely economic justification for their introduction, with dedicated socioeconomic and industrial assessment of change management within healthcare.
Additional Impact Pathway Activities will target Domain Migration (through internal dissemination activities) and optimisation of Knowledge, Standards, IP, Open Access processes to optimise the use of data and digital tools to further research and patient care.
Publications
Cheong VS
(2021)
The Role of the Loading Condition in Predictions of Bone Adaptation in a Mouse Tibial Loading Model.
in Frontiers in bioengineering and biotechnology
Cheong VS
(2021)
Positive interactions of mechanical loading and PTH treatments on spatio-temporal bone remodelling.
in Acta biomaterialia
Conconi M
(2021)
Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency
in Applied Sciences
Dall'Ara E
(2022)
A practical guide for in situ mechanical testing of musculoskeletal tissues using synchrotron tomography.
in Journal of the mechanical behavior of biomedical materials
Dall'Ara E
(2022)
Digital volume correlation for the characterization of musculoskeletal tissues: Current challenges and future developments.
in Frontiers in bioengineering and biotechnology
Hayford CF
(2021)
Effectiveness of Global Optimisation and Direct Kinematics in Predicting Surgical Outcome in Children with Cerebral Palsy.
in Life (Basel, Switzerland)
Hayford CF
(2020)
Predicting longitudinal changes in joint contact forces in a juvenile population: scaled generic versus subject-specific musculoskeletal models.
in Computer methods in biomechanics and biomedical engineering
| Title | Angels of the North |
| Description | MultiSim's (EP/K03877X/1 & EP/S032940/1) Director, Claudia Mazzà has been collaborating with dancer and choreographer Freddie Garland, Tenfoot Dance Company, in her continuing project 'Women's Movement 100: Angels of the North' to create a filmed performance about women's suffrage, emancipation and health for the University of Sheffield's Festival of the Mind. Watch the resulting podcast (https://festivalofthemind.sheffield.ac.uk/2020/spiegeltent/womens-movement-100-podcast/) and film (https://festivalofthemind.sheffield.ac.uk/2020/spiegeltent/womens-movement-100-film/). Data captured at Insigneo's Motion Capture and Virtual Reality Laboratory from some of the dancers involved in the Women's Movement 100 can be seen as delicate, abstracted moving dots and tracing lines superimposed over portions of the film, reflecting the movements used by the dancers in the film. Women's Movement 100: Angels of the North One-hundred women from local communities and further afield took part in this project, which gives artistic form to the patterns and waves of the women's movement over the last century, as explored in Department of History Professor, Julie Gottlieb's research. Women's Movement 100 refers to both political and physical movement. The biomechanics of the female physical movement is an important component of MultiSim's research. Freddie and some of her dancers started to explore their choreography in the motion capture laboratory with MultiSim and Mobilise-D (EU Horizon 2020 grant agreement No 820820) researchers: Erica Montefiori, Kirsty Scott and Tecla Bonci. Early results of this collaboration were presented at the University of Sheffield's 2020 Festival of the Mind in September. |
| Type Of Art | Film/Video/Animation |
| Year Produced | 2020 |
| Impact | Collaboration with dancer and choreographer Freddie Garland and Julie Gottlieb, Professor of Modern History at the University of Sheffield. Wide exposure of project to broad non-technical audience. This activity was reported on the MultiSim website: https://www.sheffield.ac.uk/multisim-insigneo/news /angels-north. A website has since been developed from this project to allow wider access to its outputs: https://womensmovement100.co.uk/. The video has been made available for International Women's Day on the Newly launched University of Sheffield Player: https://player.sheffield.ac.uk/events/womens-movement-100-angels-north-0. |
| URL | https://womensmovement100.co.uk/ |
| Description | Please refer to EP/K03877X/1 for previous outcomes recorded against the award which this grant has stemmed from. We are developing a new healthcare technology that can account for the fact that biological tissues span a number of scales in terms of space and time. For example, the human body will respond to its environment by adapting to it and reducing (e.g. astronauts) or increasing (e.g. athletes) its bone mass. This process involves molecular, cell, tissue response over a time scale that differs for each space scale. In this grant, we are developing a framework that can simulate tissue adaptation for a number of cases. For example, we are now able to predict the risk of femoral bone fracture in osteoporotic patients with more accuracy than conventional clinical practice. We have developed a novel computational and experimental approach to test the effect of a new drug or medical device on bone response in a in vivo mouse pre-clinical testing context. The clinical workflow has been extended to include the effects of skeletal muscles to improve its predictions and extend its application to diseases that affect both bone and muscle, such as sarcopenia and neurodegenerative diseases. The pre-clinical workflow has extended its analysis of the changes in different musculoskeletal tissues (bone, muscles, tendons) over time to better understand and model the effect of diseases and to optimise future treatments. |
| Exploitation Route | We have developed a number of online services available through a web portal to any clinician or researcher. For example, we have developed the CT2S service which enables to predict the risk of bone fracture in a patient-specific manner for osteoporotic patient once the user uploads CT data from the patient. We are also developing an online service based on High Resolution peripheral Quantitative Computed Tomography (HRpQCT) to calculate the bone stiffness and regions of bone weakening. We have now also completed the definition of a methodology for combining medical images and gait analysis data, which allows us to understand how much force each muscle is producing to allow a person to walk. This has been fully described in a published paper and a step-by-step guide has been shared on FigShare, together with relevant datasets to allow other researchers to replicate our results. We have also launched a new type of event called 'Modelathon' in which PhD students and Research Associates can participate during 3 days to solve a multiscale problem defined by our team. This enables the participants to get acquainted to multiscale modelling and develop further technologies later on for their own challenges. |
| Sectors | Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology |
| URL | https://www.sheffield.ac.uk/multisim-insigneo |
| Description | Public Outreach: We have collaborated with a local choreographer and contributed to her ongoing project promoting women emancipation and health: Women's Movement 100: Angels of the North, which was shown as part of the University of Sheffield's 2020 Festival of the Mind. Staff Development: We have developed our researchers creative thinking through a CLEAR IDEAS workshop. Research Community Engagement: We have engaged the research community in Sandpit event to seed new project proposals. The outputs of the MultiSim project (EP/K03877X/1) were taken forward with the Progression Award MultiSim2 (EP/S032940/1). The following statement covers the impact of the combined projects. Webservices: We have developed a number of online services available through a web portal to any clinician or researcher. For example: 1) We have developed the CT2S service which enables to predict the risk of bone fracture in a patient-specific manner for osteoporotic patient once the user uploads CT data from the patient. This service is open to any clinician or company and we are currently in discussion with some for its use. 2) We have developed the BoneDVC web-application has been used by other groups including the University of Bologna (Italy), Vienna University of Technology (Austria), Western University Canada (Canada), and Flinders University Adelaide (Australia). Clinical Workflow: Musculoskeletal models to aid in clinical decision-making in children with Cerebral Palsy The use of musculoskeletal models in clinical settings is limited although they have shown potential for augmenting evidence for surgical intervention decisions. By showing that our musculoskeletal modelling approach can perform at par with the current method used to quantify outcomes after surgery (1), we are together with partners at the Sheffield Children's Hospital Gait Laboratory looking into using these models to identify biomarkers for predicting outcomes after surgery (2). Based on this information, surgeons can identify and select candidates for surgery who would most likely benefit from the intervention. References: (1) C. F. Hayford, E. Pratt, J. P. Cashman, O. G. Evans, and C. Mazzà, "Effectiveness of Global Optimisation and Direct Kinematics in Predicting Surgical Outcome in Children with Cerebral Palsy," Life, vol. 11, no. 12, p. 1306, 2021. [Online]. Available: https://www.mdpi.com/2075-1729/11/12/1306. (2) C. F. Hayford, E. Pratt, J. P. Cashman, O. G. Evans, and C. Mazzà, "Role of Pre-surgery Muscle-tendon lengths on the outcome of Femoral Derotation Osteotomy". In preparation. |
| First Year Of Impact | 2022 |
| Sector | Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology |
| Impact Types | Societal |
| Title | Augmented images associated segmentations |
| Description | The labels of 37 lower limb muscles associated with the augmented images. Muscles are labelled in ascending order: 1 adductor brevis 2 adductor longus 3 adductor magnus 4 biceps femoris caput breve 5 biceps femoris caput longum 6 extensor digitorum longus 7 extensor hallucis longus 8 flexor digitorum longus 9 flexor hallucis longus 10 gastrocnemius lateralis 11 gastrocnemius medialis 12 gemellus superior 13 gluteus maximus 14 gluteus medius 15 gluteus minimus 16 gracilis 17 iliacus 18 obturator externus 19 obturator internus 20 pectineus 21 peroneus brevis 22 peroneus longus 23 piriformis 24 popliteus 25 psoas 26 quadratus femoris 27 rectus femoris 28 sartorius 29 semimembranosus 30 semitendinosus 31 soleus 32 tensor fasciae latae 33 tibialis anterior 34 tibialis posterior 35 vastus intermedius 36 vastus lateralis 37 vastus medialis Those that were used in the study and proved repeatably segmentable are as follows: 1 adductor brevis 2 adductor longus 3 adductor magnus 4 biceps femoris caput breve 5 biceps femoris caput longum 6 gastrocnemius lateralis 7 gastrocnemius medialis 8 gluteus maximus 9 gracilis 10 iliacus 11 peroneus brevis 12 peroneus longus 13 rectus femoris 14 sartorius 15 semimembranosus 16 semitendinosus 17 soleus 18 tensor fasciae latae 19 tibialis anterior 20 tibialis posterior 21 vastus intermedius 22 vastus lateralis 23 vastus medialis |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Exposure of dataset to research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Augmented_images_associated_segmentations/20440203/1 |
| Title | Augmented lower limb MR images |
| Description | The dataset contains 69 augmented images of the lower limb, generated using deformable image registration. The images have been checked for anatomical feasibility and are openly available for download. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Exposure of dataset to research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Augmented_lower_limb_MR_images/20440164/1 |
| Title | Data for MicroCT-based MicroFE of human vertebrae |
| Description | This file contains the results collected in the study: "Effect of size and location of simulated lytic lesions on the structural properties of human vertebral bodies, a micro-finite element study" by "M.C. Costa, L.B. Bresani Campello, M. Ryan, J. Rochester, M. Viceconti, E. Dall'Ara" published in Bone Reports:https://doi.org/10.1016/j.bonr.2020.100257.In order to access the original raw files the reader can contact the the corresponding author (Dr Enrico Dall'Ara, e.dallara@sheffield.ac.uk). The files are stored in the University of Sheffield file-store at the link:https://web-unidrive.sheffield.ac.uk/shared/bone_biomechanics1/Projects/15_METVERT/DD_SimulatedMetastases/ |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with the research community. |
| URL | https://figshare.shef.ac.uk/articles/Data_for_MicroCT-based_MicroFE_of_human_vertebrae/11958954 |
| Title | Data for manuscript titled "A systematic approach to the scale separation problem in the development of multiscale models" |
| Description | The following files are included: Patient60y.vtk, an anonymised data file (in VTK unstructured grid format) for a proximal femur, which is used as input to the multiscale model illustrated in §2.3 of the main manuscript The proximal femur data corresponds to a subject aged 60 years at the time of clinical presentationThe data file contains the proximal femur geometry, discretised using tetrahedral elements possessing heterogeneous element-wise volumetric bone mineral density (vBMD)Units for the fields in the data file are given in the Readme.txt file Figs1and4.pvsm, a state file in the open-source viewer Paraview format. It contains the image manipulations needed to convert the data in Patient60y.vtk to that in Fig 1 of the main manuscriptIt also contains the code to convert the vBMD data to that corresponding to age 70 y, as shown in Fig 4 of the main manuscriptThis dataset contains data in only processed and anonymised form. It is derived from an original dataset that was collected under the project UK MRC grant G0601272. Ethics approval was obtained for this project from the relevant local ethics committee in Sheffield. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with the research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_manuscript_titled_A_systematic_approach_to_the... |
| Title | Data for manuscript titled "A systematic approach to the scale separation problem in the development of multiscale models" |
| Description | The following files are included: Patient60y.vtk, an anonymised data file (in VTK unstructured grid format) for a proximal femur, which is used as input to the multiscale model illustrated in §2.3 of the main manuscript The proximal femur data corresponds to a subject aged 60 years at the time of clinical presentationThe data file contains the proximal femur geometry, discretised using tetrahedral elements possessing heterogeneous element-wise volumetric bone mineral density (vBMD)Units for the fields in the data file are given in the Readme.txt file Figs1and4.pvsm, a state file in the open-source viewer Paraview format. It contains the image manipulations needed to convert the data in Patient60y.vtk to that in Fig 1 of the main manuscriptIt also contains the code to convert the vBMD data to that corresponding to age 70 y, as shown in Fig 4 of the main manuscriptThis dataset contains data in only processed and anonymised form. It is derived from an original dataset that was collected under the project UK MRC grant G0601272. Ethics approval was obtained for this project from the relevant local ethics committee in Sheffield. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset made available to the research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_manuscript_titled_A_systematic_approach_to_the... |
| Title | Data for manuscript titled "Personalised 3D assessment of trochanteric soft tissues improves hip fracture classification accuracy" |
| Description | This dataset contain the three-dimensional characterisation of soft tissue thickness (STT) in the near hip region. The data is for 94 British postmenopausal subjects. Of these subjects, 47 had suffered a hip fracture, and the remaining 47 were age, height and weight matched controls. STT was measured from proximal femur CT images, and is defined as the distance between the femur surface and the skin layer along a specific fall impact direction with origin at the femur head centre. For each subject, STT was measured along 33 impact orientations.For more information, see the preprint of the manuscript at: https://doi.org/10.17605/OSF.IO/DZMKHThe dataset is presented in Microsoft Excel format, named STTdata.xlsx. Columns in the table refer to an individual subject, and rows contains the following data fields:- patients label- fracture status- BMI (in kg/m2)- soft-tissue thickness (in mm) as estimated using BMI at the point of the greater trochanter- soft-tissue thickness as measured using CT for the various impact orientations considered in the manuscriptA README.txt file is also provided and contains the above information. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_manuscript_titled_Personalised_3D_assessment_o... |
| Title | Data for paper "A novel approach to evaluate the effects of artificial bone focal lesion on the threedimensional strain distributions within the vertebral body" |
| Description | Data used in the paper : "A novel approach to evaluate the effects of artificial bone focal lesion on the threedimensionalstrain distributions within the vertebral body"byMarco Palanca, Giulia de Donno, Enrico Dall'Araaccepted for publication in PlosOne, 2021.We share here an example of microCT images collected for porcine vertebrae in the undeformed and deformed state, before and after having induced a mechanical lesion in the anterior side of the bone:Specimen1_Intact_Scan1_unloaded_4241.dcmSpecimen1_Intact_Scan2_loaded_4245.dcmSpecimen1_Lesion_Scan1_unloaded_4369.dcmSpecimen1_Lesion_Scan2_loaded_4370.dcmThe images are used to run Digital Volume Correlation with BoneDVC (https://bonedvc.insigneo.org/dvc/). Example of results from the DVC are reported in:DVC_Intact_results_xyz.txtDVC_Intact_output_map_xyz.txtDVC_Lesion_results_xyz.txtDVC_Lesion_output_map_xyz.txtIn each DVC folder the following data are reported:_output_map.txt (displacement components)_results_xyz.txt (strain components)The whole dataset is stored at:https://web-unidrive.sheffield.ac.uk/shared/bone_biomechanics1/Projects/19_METASPINE_EU_ED/In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk) and/or Dr Marco Palanca (m.palanca@sheffield.ac.uk). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset available to research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_paper_A_novel_approach_to_evaluate_the_effects... |
| Title | Data for paper "Is a wearable sensor based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with Multiple Sclerosis" |
| Description | This repository has been created to support the paper "Is a wearable sensor based characterisation of gait robust enough to overcome differences between measurement protocols? A multi-centric pragmatic study in patients with Multiple Sclerosis". The excel file includes both demographic and clinical information of each participant (1st worksheet) and the gait outcomes extracted from the wearable sensors for each participant (mean and SD values, 2nd worksheet). For details email l.angelini@sheffield.ac.uk |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_paper_Is_a_wearable_sensor_based_characterisat... |
| Title | Data for paper "MRI-based anatomical characterisation of lower-limb muscles in older women" |
| Description | This Figshare contains:1. additional material.docx, including supplementary information associated with the paper "MRI-based anatomical characterisation of lower-limb muscles in older women";2. Segmentations for the eleven subjects in the study labelled as MC17, MC18, MC19, MC20, MC22, MC24, MC25, MC26, MC27, MC28, MC29 (corresponding to Subject 1 to 11, respectively, see additional material for details):a. bone and soft tissue (skin) segmentations as stl files;b. muscle segmentations as stl files;3. Muscle centrelines as vtk files. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_paper_MRI-based_anatomical_characterisation_of... |
| Title | Data for paper "Modeling Musculoskeletal Dynamics During Gait: Evaluating the Best Personalization Strategy Through Model Anatomical Consistency" |
| Description | This repository contains the data and models used to generate the results reported in the paper "Modeling Musculoskeletal Dynamics During Gait: Evaluating the Best Personalization Strategy Through Model Anatomical Consistency".Ethical approval for the studies was obtained from the local ethical comittees.The 'Data_for_paper' folder contains 10 folders, one for each participant of the study (Subject1, ..., Subject10). Please, note that for some participants bi-lateral data are available, while for others only one body side was collected. Body sides are denoted by "_R/L" in the name of folders and models.Within each of these folders, two sets of models are available: Model1 contains the models generated under the scenario referred to as M1 in the paper; Model2 contains the models where ligament and cartilage forces were accounted for while simulating gait. Input data are available as well in folders "Data_L/R".A .doc file containing all the additional results mentioned in the paper is made available as well. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Data made available for research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_paper_Modeling_Musculoskeletal_Dynamics_During... |
| Title | Data for the article "Effectiveness of global optimisation and direct kinematics in predicting surgical outcome in children with cerebral palsy." |
| Description | This Figshare contains data for reproducing results reported in the paper titled "Effectiveness of Global Optimisation and Direct Kinematics in Predicting Surgical Outcome in Children with Cerebral Palsy".The folder contains:1. kinematic data for Cerebral Palsy (CP) and Typically Developing (TD) groups. Each file has data for both mGen and PiG kinematics2. pre and post-surgery ages for CP group for selecting appropriate age-matched control group.2. excel file with specification of limbs that received the FDO and the non-3D data judgement of outcome. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_article_Effectiveness_of_global_optimisati... |
| Title | Data for the article "Effectiveness of global optimisation and direct kinematics in predicting surgical outcome in children with cerebral palsy." |
| Description | This Figshare contains data for reproducing results reported in the paper titled "Effectiveness of Global Optimisation and Direct Kinematics in Predicting Surgical Outcome in Children with Cerebral Palsy".The folder contains:1. kinematic data for Cerebral Palsy (CP) and Typically Developing (TD) groups. Each file has data for both mGen and PiG kinematics2. pre and post-surgery ages for CP group for selecting appropriate age-matched control group.2. excel file with specification of limbs that received the FDO and the non-3D data judgement of outcome. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_article_Effectiveness_of_global_optimisati... |
| Title | Data for the paper: "Bone remodelling in the mouse tibia is spatio-temporally modulated by oestrogen deficiency and external mechanical loading: a combined in vivo/ in silico study" |
| Description | Data used in the paper : "Bone remodelling in the mouse tibia is spatio-temporally modulated by oestrogen deficiency and external mechanical loading: a combined in vivo/ in silico study"byVee San Cheong, Bryant Roberts, Visakan Kadirkamanathan, Enrico Dall'Arapublished in Acta BiomaterialiaWe share here an example of in vivo microCT images collected for a mouse that underwent ovariectomy at week 14 of age and mechanical loading at week 19 and 21 of age. In vivo 3D microCT images of the mouse tibia have been acquired at week 14, 18, 20, and 22 of age. The registered and cropped images are reported here.In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_Bone_remodelling_in_the_mouse_tibia_... |
| Title | Data for the paper: "Development of subject-specific finite element models of the mouse knee joint for preclinical applications" |
| Description | Data for the paper: "Development of subject-specific finite element models of the mouse knee joint for preclinical applications"by:Sahnd Zanjani-Pour, Mario Giorgi, Enrico Dall'Arapublished in:Frontiers in Bioengineering and Biotechnology (Biomechanics) https://www.frontiersin.org/articles/10.3389/fbioe.2020.558815/abstractMicroCT images of the native bones and PTA stained bones have been reported after registrations. These images were used to create the finite element models of the mouse knee joint including bone, cartilage, and idealised meniscus as described in the paper. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_Development_of_subject-specific_fini... |
| Title | Data for the paper: "Non-invasive prediction of the mouse tibia mechanical properties from microCT images: comparison between different finite element models" |
| Description | Data used in the paper: "Non-invasive prediction of the mouse tibia mechanical properties from microCT images: comparison between different finite element models"Oliviero, Owen, Reilly, Bellantuono, Dall'Arapublished in BMMBWe share here an example of ex vivo microCT image used for the assessment, and the results obtained from the different analyses.Short description of the files included:-microFE_results.xlsx includes:Stiffness estimated for each specimen with microFE models, and correlations with experimental data.Failure load estimated with microFE models, and correlations with experimental data, for each model type:Hexahedral Homogeneous modelsHexahedral models with subject-specific modulusTedrahedral Homogenous modelsTetrahedral models with subject-specific modulusHexahedral Heterogeneous modelsTetrahedral Homogeneous models -microCT data:Example of a segmented microCT image used as input for the microFE model (Specimen1, C57BL/6J, wild type, 16 weeks of age, right tibia).In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_Non-invasive_prediction_of_the_mouse... |
| Title | Data for the paper: "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" |
| Description | Data used in the paper: "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"Oliviero, Owen, Reilly, Bellantuono, Dall'Arapublished in JMBBMWe share here an example of ex vivo microCT image used for the assessment, and the results obtained from the different analyses.Short description of the files included:Densitometric_and_morphometric_parameters.xlsx includes:-Densitometric parameters, and correlations with experimental mechanical data, calculated for each specimen and each region of interestTotal = total volume of interest (80% of tibia length)10 Longitudinal sections: section 1 corresponds to proximal tibia, section 10 corresponds to distal tibiaSectors: anterior (A), posterior (P), medial (M) and lateral (L)-Morphometric parameters calculated for each specimen, and correlations with experimental mechanical data. -microFE_results.xlsx includes:Stiffness estimated for each specimen with microFE models, and correlations with experimental data.Failure load estimated with microFE models, and correlations with experimental data, for each failure criterion:Pistoia methodCompression: tibia fails when a portion of the nodes (failure volume) reaches a critical compressive (third principal) strain levelTension: tibia fails when a portion of the nodes reaches a critical tensile (first principal) strain levelCompression&Tension: tibia fails when a portion of the nodes reaches a critical strain, either in tension or in compressionSections: tibia fails when the median first principal strain or third principal strain in one section (tibia divided into ten portions) or in one sector (tibia divided into ten sections and each section divided into anterior and posterior partitions; 20 portions in total) reaches a critical strain level -microCT data:Example of a segmented microCT image used as input for the microFE model (Specimen1, C57BL/6J, wild type, 16 weeks of age, right tibia).In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_Optimization_of_the_failure_criterio... |
| Title | Data for the paper: "PTH(1-34) treatment and/or mechanical loading have different osteogenic effects on the trabecular and cortical bone in the ovariectomized C57BL/6 mouse" |
| Description | Link to the data used in:Roberts, Arredondo Carrera, Zanjani-pour, Boudiff, Wang, Gartland and Dall'AraPTH(1-34) treatment and/or mechanical loading have different osteogenic effects on the trabecular and cortical bone in the ovariectomized C57BL/6 mouseScientific Reports 10, 8889 (2020).All the procedures were performed under a British Home Office licence (PF61050A3) and in compliance with the Animal (Scientific Procedures) Act 1986.The images and data are too large to be uploaded in ORDA. The whole dataset can be assessed at: https://web-unidrive.sheffield.ac.uk/shared/multisim2/WP7/PTH_Loading/. Please contact the senior author at: e.dallara@sheffield.ac.uk or the Project Management Office at: pmo@insigneo.org if you are interested in working on the files.In this repository we have uploaded only the result file obtained from assessment of the microCT images. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_PTH_1-34_treatment_and_or_mechanical... |
| Title | Data for the paper: "Patient-specific finite element models of posterior pedicle screw fixation: effect of screw's size and geometry" |
| Description | Data used in the paper: "Patient-specific finite element models of posterior pedicle screw fixation: effect of screw's size and geometry"Sensale, Vendeuvre, Schilling, Grupp, Rochette and Dall'Ara published in Frontiers Bioengineering and BiotechnologyWe share here the results and one example of FE models for the implanted vertebrae.Short description of the files included:-) the results of the paper are reported in "Results_file.xlsx". In this file, there are different sheets:.NumElements_CompTime - this contains the number of elements and computational time to solve the FE models, reported in Table 2 and 3;.MeshConvergenceStudy - this contains the results of the Mesh convergence study reported in Figure 3..Sensitivity Deflection - Stress AND Sensitivity Strain - these contain the results of the sensitivity analysis reported in Table 4, 5 and 6;.Correlation - this contains the results of the correlation analysis reported in Figure 6;-) In the "Frequency_plot_files" folder, the result files for the frequency plots reported in Figure 7 are reported:.MinStrainMeshPoints(...).txt - these files contains the values of minimum principal strain used in the frequency plots in Figure 7.-) The "Example_Model" folder contains an example of the models used in the sensitivity analysis for Patient #3 with simplified pedicle screw with diamter D6.5mm and length L45mmThe folder contains:- the Ansys workbench 2020R2 project file corresponding to the model in the name of the folder;- the corresponding geometry SpaceClaim file;- the Ansys cdb mesh file exported from Bonemat;- the calibration xml file used in Bonemat;- the Ansys apdl command snippet used in Mechanical to build an heterogeneous model of the bone.In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with the research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_Patient-specific_finite_element_mode... |
| Title | Data for the paper: "Positive interactions of mechanical loading and PTH treatments on spatio-temporal bone remodelling" |
| Description | Data used in the paper : "Bone remodelling in the mouse tibia is spatio-temporally modulated by oestrogen deficiency and external mechanical loading: a combined in vivo/ in silico study"byVS Cheong, BC Roberts, V Kadirkamanathan, E Dall'Ara (2021)published in Acta BiomaterialiaWe share here an example of in vivo microCT images collected for a mouse that underwent the following interventions:-ovariectomy at week 14 of age - mechanical loading at week 19 and 21 of age.- injections of Parathyroid hormone (PTH; 5 days per week) between weeks 18 and 22 of ageIn vivo 3D microCT images of the mouse tibia have been acquired at week 14, 18, 20, and 22 of age.The registered and cropped images are reported here.In case the reader is interested in the whole database they should contact Dr Enrico Dall'Ara (e.dallara@sheffield.ac.uk). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Data made available to research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Data_for_the_paper_Positive_interactions_of_mechanical_... |
| Title | Dataset behind the results of: Automatic methods of hoof-on and -off detection in horses using wearable inertial sensors during walk and trot on asphalt, sand and grass |
| Description | This dataset contains the data behind the results of the associated paper. It includes the timing of gait events as detected by the different methods explored in the paper, for a group of horses at walk and trot. A ReadMe file explains fully the layout of the data and naming conventions used. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Data made available to research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Dataset_behind_the_results_of_Automatic_methods_of_hoof... |
| Title | Femoral neck strain prediction during level walking using a combined musculoskeletal and finite element model approach |
| Description | The full of set of data contains; peak first and third principal strains at the femoral neck as predicted by the FE model, hip and knee joint contact forces personolised by the body weight, and Gluteus Medius muscle forces as calculated by the musculoskeletal model. Those are reported for the five cases and along the 100% of one gait cycle.The study was approved by the Health Research Authority of East of England (Cambridgeshire and Hertfordshire Research Ethics Committee, reference 16/EE/0049). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Data shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Femoral_neck_strain_prediction_during_level_walking_usi... |
| Title | Multi atlas registration code |
| Description | A Matlab script to combine segmentations resulting from single atlas registration results into one multi-atlas segmentation. Required: X number of RGB images, red and green channels being the target and registered images respectively (of size n*m or n*m*p). X number of segmented images with Y number of classes (of size n*m or n*m*p). documentation inclued in script. Additionally, a set of example inputs are included for ease of use (number of classes = 34). |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Exposure of code to the research community. |
| URL | https://figshare.shef.ac.uk/articles/software/Multi_atlas_registration_code/21763982 |
| Title | Registration inputs |
| Description | Registration inputs for the paper titled: Deformable image registration based on single or multi-atlas methods for automatic muscle segmentation and the generation of augmented imaging datasets fixed (red channel), moving (green channel), and fixed segmentations (blue channel) are combined in one easy to use 3D dicom file. There are 20 combinations presented, with each of 5 subjects used as both the fixed and the moving subject. The results.xcel file highlights the numerical results for the automatic segmentation we found using an in house registration toolkit. If one would like to test others, simply download and register the fixed and moving images, and apply the deformation to the blue channel segmentations. See read me for details. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2022 |
| Provided To Others? | Yes |
| Impact | Exposure of dataset to research community. |
| URL | https://figshare.shef.ac.uk/articles/dataset/Registration_inputs/21739733/1 |
| Title | Supplementary Material: A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems |
| Description | OVERVIEW:This is a stereophotogrammetric quality control check developed by K.Scott and shared to assist in the adoption of the methods of the associated paper: https://doi.org/10.3390/s21248223. This function in the "matlab code" folder compiles the processing required to complete the quality control check as explained in the material and methods of the paper.To ensure easy adoption to different labs and calibration objects, the functions have been refined to allow for easy adaption. Please read the accompanying commented notes in the script first.This function has been created for adaption and therefore editing is allowed based on the MIT License agreement. DISCLAIMER:The current function relies on the open-source C3D reader, Biomechanical ToolKit (BTK). Reference: https://doi.org/10.1016/j.cmpb.2014.01.012.PLEASE ENSURE TO DOWNLOAD THIS TOOLKIT PRIOR TO USE OR AMEND CODE TO FIT PREFFERED C3D READER. Link to BTK download: https://code.google.com/archive/p/b-tk/Version: 1.1Date completed: 09/12/2021 |
| Type Of Material | Database/Collection of data |
| Year Produced | 2021 |
| Provided To Others? | Yes |
| Impact | Dataset shared with research community. |
| URL | https://figshare.shef.ac.uk/articles/software/Supplementary_Material_A_Quality_Control_Check_to_Ensu... |
| Description | CLEAR IDEAS Workshop |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Professional Practitioners |
| Results and Impact | MultiSim2 goes 'Beyond Academia' with a CLEAR IDEAS Workshop On Wednesday, 23rd October, our MultiSim2 project hosted a Clear Ideas workshop: Beyond Academia. The workshop was attended by the MultiSim2 team and Insigneo Associate Members from the IMSB (Integrated Musculo-Skeletal Biomechanics) group explored how to take their research Beyond Academia to the clinic, industry and the public. This workshop was funded through EPSRC's Creativity@Home initiative, to bring creative thinking workshops and skills to the Engineering and Physical Science research community. Dr Kamal Birdi facilitated this creative thinking CLEAR IDEAS workshop to address these topics and, in the process, demonstrate the creative thinking skills and techniques behind this framework. Three groups, each focusing one of the three Beyond Academia aspects, worked through the steps of Illuminate, Diagnose, Erupt, Assess and Select, to better understand the challenges of taking research beyond academia and develop creative solutions to address them. During the process they were exposed to creative thinking techniques, such as using the analogy of your favourite restaurant, movie or holiday to create solutions or how a world of smart, little people would solve their problems for them, and translating these ideas back to the real world. At the end of the workshop the teams shared their ideas for demonstrating the benefits of computer modelling to clinicians, improving the quality of software through bug fixing competitions, and using student projects to develop the public facing websites. |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www.sheffield.ac.uk/multisim-insigneo/news/multisim2-goes-beyond-academia-clear-ideas-worksh... |
| Description | Modelathon 2020 |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Aim of Modelathon: To engage researchers in the field of musculoskeletal and cardiovascular research with the principles and practice of multiscale modelling through addressing an authentic research challenge using both industrial and open source research tools and frameworks. To raise the profile of the project amongst the academic community and industry. The MultiSim Modelathon brings together PhD and PostDoc researchers in the field of Multi-Scale Modelling and Biomechanical Engineering, from around the world, to compete in teams against one another to solve a complex multi-scale modelling problem. This three-day event is based on the concept of a hackathon event where different teams work on a challenging problem to 'hack' a computer code. Here there is no 'hacking' but 'modelling'. The teams competed to solve a challenging multi-scale biomechanical problem within the musculoskeletal system using state-of-the-art techniques and software. Industry members and multi-scale experts supported the event, including software providers and Ansys, Simpleware, Materialise and Simulia. They supported the Modelathon by providing licences for the academic developers preparing and testing the challenges before the event, and the Modelathon participants during the event. They provided expertise and technical support during the event to encourage participants to make the most of the software available and sponsored the events to subsidise the costs to the participants. In 2017, a scene-setting one-day symposium was added to the Modelathon. The 2018 and 2020 offerings of the Modelathon were co-sponsored and supported by OATech+, and focused on the clinical problem of osteoarthritis in the hip and knee joints respectively. Each year the Modelathon attracts approximately 25 researchers. |
| Year(s) Of Engagement Activity | 2020 |
| URL | http://multisim-insigneo.org/modelathon/ |
| Description | MultiSim2 Sandpit |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Other audiences |
| Results and Impact | Research leaders from the Multiscale Computational Medicine research community were gathered for an online sandpit event to generate and explore ideas for new project proposals. Forty-Two academics registered, and five groups of were formed around the following themes: 1) Ageing, sarcopenia and fracture risk; 2) Developmental Biomechanics; 3) Multiscale modelling and co-morbidities; 4) Multiscale models and Artificial Intelligence: Group 1 (MSK); 5) Multiscale models and Artificial Intelligence: Group 2 (CV). A professional facilitator, Becky Stelairos, Research in Focus, with experience of holding online Sandpits, was engaged for the event. The event which consisted of two morning discussions, held on Monday, 5th July and Thursday, 8th July, with offline questions to consider before and the meetings. The purpose was to seed consortia and proposals in the areas of the themes. |
| Year(s) Of Engagement Activity | 2021 |
| URL | https://www.sheffield.ac.uk/multisim-insigneo/events |