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Ao D, Li G, Shourijeh MS, Patten C, Fregly BJ. EMG-Driven Musculoskeletal Model Calibration With Wrapping Surface Personalization. IEEE Trans Neural Syst Rehabil Eng 2023; 31:4235-4244. [PMID: 37831559 PMCID: PMC10644710 DOI: 10.1109/tnsre.2023.3323516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Muscle forces and joint moments estimated by electromyography (EMG)-driven musculoskeletal models are sensitive to the wrapping surface geometry defining muscle-tendon lengths and moment arms. Despite this sensitivity, wrapping surface properties are typically not personalized to subject movement data. This study developed a novel method for personalizing OpenSim cylindrical wrapping surfaces during EMG-driven model calibration. To avoid the high computational cost of repeated OpenSim muscle analyses, the method uses two-level polynomial surrogate models. Outer-level models specify time-varying muscle-tendon lengths and moment arms as functions of joint angles, while inner-level models specify time-invariant outer-level polynomial coefficients as functions of wrapping surface parameters. To evaluate the method, we used walking data collected from two individuals post-stroke and performed four variations of EMG-driven lower extremity model calibration: 1) no calibration of scaled generic wrapping surfaces (NGA), 2) calibration of outer-level polynomial coefficients for all muscles (SGA), 3) calibration of outer-level polynomial coefficients only for muscles with wrapping surfaces (LSGA), and 4) calibration of cylindrical wrapping surface parameters for muscles with wrapping surfaces (PGA). On average compared to NGA, SGA reduced lower extremity joint moment matching errors by 31%, LSGA by 24%, and PGA by 12%, with the largest reductions occurring at the hip. Furthermore, PGA reduced peak hip joint contact force by 47% bodyweight, which was the most consistent with published in vivo measurements. The proposed method for EMG-driven model calibration with wrapping surface personalization produces physically realistic OpenSim models that reduce joint moment matching errors while improving prediction of hip joint contact force.
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Kedadria A, Benabid Y, Remil O, Benaouali A, May A, Ramtani S. A Shoulder Musculoskeletal Model with Three-Dimensional Complex Muscle Geometries. Ann Biomed Eng 2023; 51:1079-1093. [PMID: 37022653 DOI: 10.1007/s10439-023-03189-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/21/2023] [Indexed: 04/07/2023]
Abstract
Muscle structure is an essential component in typical computational models of the musculoskeletal system. Almost all musculoskeletal models represent muscle geometry using a set of line segments. The straight-line approach limits models' ability to accurately predict the paths of muscles with complex geometry. This approach needs knowledge of how the muscle changes shape and interacts with fundamental structures like muscles, bones, and joints that move. Moreover, the moment arms are supposed to be equivalent to all the fibers in the muscle. This study aims to create a shoulder musculoskeletal model that includes complex muscle geometries. We reconstructed the shape of fibers in the entire volume of six muscles adjacent to the shoulder using an automated technique. This method generates many fibers from the surface geometry of the skeletal muscle and its attachment areas. Highly discretized muscle representations for all muscles were created and used to simulate different shoulder movements. The moment arms of each muscle were calculated and validated against cadaveric measurements and models of the same muscles from the literature. We found that simulations using the developed musculoskeletal models generated more realistic geometries, which expands the physical representation of muscles compared to line segments. The shoulder musculoskeletal model with complex muscle geometry is created to increase the anatomical reality of models and the lines action of muscle fibers, and to be used for finite element investigations.
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Affiliation(s)
- Abderrazak Kedadria
- Mechanical System Design Laboratory, Ecole Militaire Polytechnique, Boite Postale 17, Commune de Bordj El Bahri, 16046, Algiers, Algeria
| | - Yacine Benabid
- Mechanical System Design Laboratory, Ecole Militaire Polytechnique, Boite Postale 17, Commune de Bordj El Bahri, 16046, Algiers, Algeria
| | - Oussama Remil
- Mechanical System Design Laboratory, Ecole Militaire Polytechnique, Boite Postale 17, Commune de Bordj El Bahri, 16046, Algiers, Algeria
| | - Abdelkader Benaouali
- Mechanical System Design Laboratory, Ecole Militaire Polytechnique, Boite Postale 17, Commune de Bordj El Bahri, 16046, Algiers, Algeria
| | - Abdelghani May
- Mechanical System Design Laboratory, Ecole Militaire Polytechnique, Boite Postale 17, Commune de Bordj El Bahri, 16046, Algiers, Algeria.
| | - Salah Ramtani
- Université Sorbonne Paris Nord, CSPBA-LBPS, UMR CNRS 7244, Inst Galilee, 99 Ave JB Clement, Villetaneuse, France
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Peiffer M, Burssens A, Duquesne K, Last M, De Mits S, Victor J, Audenaert EA. Personalised statistical modelling of soft tissue structures in the ankle. Comput Methods Programs Biomed 2022; 218:106701. [PMID: 35259673 DOI: 10.1016/j.cmpb.2022.106701] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 01/20/2022] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND OBJECTIVE Revealing the complexity behind subject-specific ankle joint mechanics requires simultaneous analysis of three-dimensional bony and soft-tissue structures. 3D musculoskeletal models have become pivotal in orthopedic treatment planning and biomechanical research. Since manual segmentation of these models is time-consuming and subject to manual errors, (semi-) automatic methods could improve the accuracy and enlarge the sample size of personalised 'in silico' biomechanical experiments and computer-assisted treatment planning. Therefore, our aim was to automatically predict ligament paths, cartilage topography and thickness in the ankle joint based on statistical shape modelling. METHODS A personalised cartilage and ligamentous prediction algorithm was established using geometric morphometrics, based on an 'in-house' generated lower limb skeletal model (N = 542), tibiotalar cartilage (N = 60) and ankle ligament segmentations (N = 10). For cartilage, a population-averaged thickness map was determined by use of partial least-squares regression. Ligaments were wrapped around bony contours based on iterative shortest path calculation. Accuracy of ligament path and cartilage thickness prediction was quantified using leave-one-out experiments. The novel personalised thickness prediction was compared with a constant cartilage thickness of 1.50 mm by use of a paired sample T-test. RESULTS Mean distance error of cartilage and ligament prediction was 0.12 mm (SD 0.04 mm) and 0.54 mm (SD 0.05 mm), respectively. No significant differences were found between the personalised thickness cartilage and segmented cartilage of the tibia (p = 0.73, CI [-1.60 .10-17, 1.13 .10-17]) and talus (p = 0.95, CI[ -1.35 .10-17, 1.28 .10-17]). For the constant thickness cartilage, a statistically significant difference was found in 89% and 92% of the tibial (p < 0.001, CI [0.51, 0.58]) and talar (p < 0.001, CI [0.33, 0.40]) cartilage area. CONCLUSIONS In this study, we described a personalised prediction algorithm of cartilage and ligaments in the ankle joint. We were able to predict cartilage and main ankle ligaments with submillimeter accuracy. The proposed method has a high potential for generating large (virtual) sample sizes in biomechanical research and mitigates technological advances in computer-assisted orthopaedic surgery.
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Affiliation(s)
- M Peiffer
- Department of Orthopaedics and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, Ghent 9000, Belgium; Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, Ghent 9000, Belgium.
| | - A Burssens
- Department of Orthopaedics and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, Ghent 9000, Belgium; Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, Ghent 9000, Belgium
| | - K Duquesne
- Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, Ghent 9000, Belgium
| | - M Last
- Department of Orthopaedics and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, Ghent 9000, Belgium
| | - S De Mits
- Department of Reumatology, Ghent University Hospital, Corneel Heymanslaan 10, Ghent 9000, Belgium; Department of Podiatry, Artevelde University of Applied Sciences, Voetweg 66, Ghent 9000, Belgium
| | - J Victor
- Department of Orthopaedics and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, Ghent 9000, Belgium; Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, Ghent 9000, Belgium
| | - E A Audenaert
- Department of Orthopaedics and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, Ghent 9000, Belgium; Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, Ghent 9000, Belgium; Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge CB2 0QQ, UK; Department of Electromechanics, Op3Mech research group, University of Antwerp, Groenenborgerlaan 171, 2020, Antwerp, Belgium
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Audenaert EA, Khanduja V, Claes P, Malviya A, Steenackers G. Mechanics of Psoas Tendon Snapping. A Virtual Population Study. Front Bioeng Biotechnol 2020; 8:264. [PMID: 32292780 PMCID: PMC7118580 DOI: 10.3389/fbioe.2020.00264] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 03/13/2020] [Indexed: 12/24/2022] Open
Abstract
Internal snapping of the psoas tendon is a frequently reported condition, especially in young adolescents involved in sports. It is defined as an increased tendon excursion over bony or soft tissue prominence causing local irritation and inflammation of the tendon leading to groin pain and often is accompanied by an audible snap. Due to the lack of detailed dynamic visualization means, the exact mechanism of the condition remains poorly understood and different theories have been postulated related to the etiology and its location about the hip. In the present study we simulated psoas tendon behavior in a virtual population of 40,000 anatomies and compared tendon movement during combined abduction, flexion and external rotation and back to neutral extension and adduction. At risk phenotyopes for tendon snapping were defined as the morphologies presenting with excess tendon movement. There were little differences in tendon movement between the male and female models. In both populations, abnormal tendon excursion correlated with changes in mainly the femoral anatomy (male r = 0.72, p < 0.001, female r = 0.66, p < 0.001): increased anteversion and valgus as well as a decreasing femoral offset and ischiofemoral distance. The observed combination of shape components correlating with excess tendon movement in essence presented with a medial positioning of the minor trochanter. This finding suggest that psoas snapping and ischiofemoral impingement are possibly two presentations of a similar underlying rotational dysplasia of the femur.
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Affiliation(s)
- Emmanuel A Audenaert
- Department of Orthopedic Surgery and Traumatology, Ghent University Hospital, Ghent, Belgium.,Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, United Kingdom.,Op3Mech Research Group, Department of Electromechanics, University of Antwerp, Antwerp, Belgium.,Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Vikas Khanduja
- Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, United Kingdom
| | - Peter Claes
- Medical Imaging Research Center (MIRC), University Hospitals Leuven, Leuven, Belgium.,Department of Electrical Engineering/Processing Speech and Images, KU Leuven, Leuven, Belgium.,Department of Human Genetics, KU Leuven, Leuven, Belgium.,Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, VIC, Australia
| | - Ajay Malviya
- Department of Orthopedic Surgery and Traumatology, Northumbria National Health Service Foundation Trust, Newcastle upon Tyne, United Kingdom.,Department of Regenerative Medicine, Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Gunther Steenackers
- Op3Mech Research Group, Department of Electromechanics, University of Antwerp, Antwerp, Belgium
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Modenese L, Kohout J. Automated Generation of Three-Dimensional Complex Muscle Geometries for Use in Personalised Musculoskeletal Models. Ann Biomed Eng 2020; 48:1793-804. [PMID: 32185569 DOI: 10.1007/s10439-020-02490-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 03/04/2020] [Indexed: 12/12/2022]
Abstract
The geometrical representation of muscles in computational models of the musculoskeletal system typically consists of a series of line segments. These muscle anatomies are based on measurements from a limited number of cadaveric studies that recently have been used as atlases for creating subject-specific models from medical images, so potentially restricting the options for personalisation and assessment of muscle geometrical models. To overcome this methodological limitation, we propose a novel, completely automated technique that, from a surface geometry of a skeletal muscle and its attachment areas, can generate an arbitrary number of lines of action (fibres) composed by a user-defined number of straight-line segments. These fibres can be included in standard musculoskeletal models and used in biomechanical simulations. This methodology was applied to the surfaces of four muscles surrounding the hip joint (iliacus, psoas, gluteus maximus and gluteus medius), segmented on magnetic resonance imaging scans from a cadaveric dataset, for which highly discretised muscle representations were created and used to simulate functional tasks. The fibres’ moment arms were validated against measurements and models of the same muscles from the literature with promising outcomes. The proposed approach is expected to improve the anatomical representation of skeletal muscles in personalised biomechanical models and finite element applications.
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Shuman BR, Goudriaan M, Desloovere K, Schwartz MH, Steele KM. Muscle Synergy Constraints Do Not Improve Estimates of Muscle Activity From Static Optimization During Gait for Unimpaired Children or Children With Cerebral Palsy. Front Neurorobot 2019; 13:102. [PMID: 31920612 PMCID: PMC6927914 DOI: 10.3389/fnbot.2019.00102] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 11/25/2019] [Indexed: 01/02/2023] Open
Abstract
Neuromusculoskeletal simulation provides a promising platform to inform the design of assistive devices or inform rehabilitation. For these applications, a simulation must be able to accurately represent the person of interest, such as an individual with a neurologic injury. If a simulation fails to predict how an individual recruits and coordinates their muscles during movement, it will have limited utility for informing design or rehabilitation. While inverse dynamic simulations have previously been used to evaluate anticipated responses from interventions, like orthopedic surgery or orthoses, they frequently struggle to accurately estimate muscle activations, even for tasks like walking. The simulated muscle activity often fails to represent experimentally measured muscle activity from electromyographic (EMG) recordings. Research has theorized that the nervous system may simplify the range of possible activations used during dynamic tasks, by constraining activations to weighted groups of muscles, referred to as muscle synergies. Synergies are altered after neurological injury, such as stroke or cerebral palsy (CP), and may provide a method for improving subject-specific models of neuromuscular control. The aim of this study was to test whether constraining simulation to synergies could improve estimated muscle activations compared to EMG data. We evaluated modeled muscle activations during gait for six typically developing (TD) children and six children with CP. Muscle activations were estimated with: (1) static optimization (SO), minimizing muscle activations squared, and (2) synergy SO (SynSO), minimizing synergy activations squared using the weights identified from EMG data for two to five synergies. While SynSO caused changes in estimated activations compared to SO, the correlation to EMG data was not higher in SynSO than SO for either TD or CP groups. The correlations to EMG were higher in CP than TD for both SO (CP: 0.48, TD: 0.36) and SynSO (CP: 0.46, TD: 0.26 for five synergies). Constraining activations to SynSO caused the simulated muscle stress to increase compared to SO for all individuals, causing a 157% increase with two synergies. These results suggest that constraining simulated activations in inverse dynamic simulations to subject-specific synergies alone may not improve estimation of muscle activations during gait for generic musculoskeletal models.
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Affiliation(s)
- Benjamin R. Shuman
- Department of Mechanical Engineering, University of Washington, Seattle, WA, United States
| | - Marije Goudriaan
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Kaat Desloovere
- Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
- Clinical Motion Analysis Laboratory, University Hospitals Leuven (Pellenberg), Lubbeek, Belgium
| | - Michael H. Schwartz
- James R. Gage Center for Gait and Motion Analysis, Gillette Children’s Specialty Healthcare, Saint Paul, MN, United States
- Orthopaedic Surgery, Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Katherine M. Steele
- Department of Mechanical Engineering, University of Washington, Seattle, WA, United States
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Audenaert EA, Khanduja V, Bauwens C, Van Hoof T, Pattyn C, Steenackers G. A discrete element model to predict anatomy of the psoas muscle and path of the tendon: Design implications for total hip arthroplasty. Clin Biomech (Bristol, Avon) 2019; 70:186-191. [PMID: 31526958 DOI: 10.1016/j.clinbiomech.2019.09.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Revised: 09/05/2019] [Accepted: 09/08/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND The accurate estimation of a muscle's line of action is a fundamental requirement in computational modelling. We present a novel anatomical muscle wrapping technique and demonstrate its clinical use on the evaluation of the Psoas muscle mechanics in hip arthroplasty. METHODS A volume preserving, spring model to parameterize muscle anatomy changes during motion is presented. Validation was performed by a CT scan of a cadaver model in multiple positions. The predicted psoas musculotendinous path was compared with the actual imaging findings. In a second stage, psoas kinetics were compared between a conventional versus a resurfacing hip arthroplasty during gait. FINDINGS Anatomy prediction error was found to be 2.12 mm on average (SD 1.34 mm). When applied to psoas mechanics during walking, the muscle was found to wrap predominantly around the femoral head providing a biomechanically efficient and nearly constant moment arm for flexion during the entire gait cycle. However, this advantage was found to be lost in small diameter hip arthroplasty designs resulting in an important mechanical disadvantage. The moment arm for flexion, was on average 36% (SD 0.03%) lower in the small diameter conventional hip arthroplasty as compared to the large diameter head of the hip resurfacing and this difference was highly significant. (p < 0.001). INTERPRETATION Despite the shortcomings of an "in silico" and cadaveric study, our findings are in accordance with previous clinical and gait studies. Furthermore, the findings are strongly in favour of large diameter implant designs, warranting their further development and optimisation.
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Affiliation(s)
- E A Audenaert
- Department of Orthopedic Surgery and Traumatology, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge CB2 0QQ, UK; Department of Electromechanics, Op3Mech research group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium; Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - V Khanduja
- Department of Trauma and Orthopedics, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Hills Road, Cambridge CB2 0QQ, UK
| | - C Bauwens
- Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - T Van Hoof
- Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - C Pattyn
- Department of Human Structure and Repair, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - G Steenackers
- Department of Electromechanics, Op3Mech research group, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium
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Yokota F, Otake Y, Takao M, Ogawa T, Okada T, Sugano N, Sato Y. Automated muscle segmentation from CT images of the hip and thigh using a hierarchical multi-atlas method. Int J Comput Assist Radiol Surg 2018; 13:977-86. [PMID: 29626280 DOI: 10.1007/s11548-018-1758-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 03/27/2018] [Indexed: 10/17/2022]
Abstract
PURPOSE Patient-specific quantitative assessments of muscle mass and biomechanical musculoskeletal simulations require segmentation of the muscles from medical images. The objective of this work is to automate muscle segmentation from CT data of the hip and thigh. METHOD We propose a hierarchical multi-atlas method in which each hierarchy includes spatial normalization using simpler pre-segmented structures in order to reduce the inter-patient variability of more complex target structures. RESULTS The proposed hierarchical method was evaluated with 19 muscles from 20 CT images of the hip and thigh using the manual segmentation by expert orthopedic surgeons as ground truth. The average symmetric surface distance was significantly reduced in the proposed method (1.53 mm) in comparison with the conventional method (2.65 mm). CONCLUSION We demonstrated that the proposed hierarchical multi-atlas method improved the accuracy of muscle segmentation from CT images, in which large inter-patient variability and insufficient contrast were involved.
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Viceconti M, Cobelli C, Haddad T, Himes A, Kovatchev B, Palmer M. In silico assessment of biomedical products: The conundrum of rare but not so rare events in two case studies. Proc Inst Mech Eng H 2017; 231:455-466. [PMID: 28427321 DOI: 10.1177/0954411917702931] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
In silico clinical trials, defined as "The use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention," have been proposed as a possible strategy to reduce the regulatory costs of innovation and the time to market for biomedical products. We review some of the the literature on this topic, focusing in particular on those applications where the current practice is recognized as inadequate, as for example, the detection of unexpected severe adverse events too rare to be detected in a clinical trial, but still likely enough to be of concern. We then describe with more details two case studies, two successful applications of in silico clinical trial approaches, one relative to the University of Virginia/Padova simulator that the Food and Drug Administration has accepted as possible replacement for animal testing in the preclinical assessment of artificial pancreas technologies, and the second, an investigation of the probability of cardiac lead fracture, where a Bayesian network was used to combine in vivo and in silico observations, suggesting a whole new strategy of in silico-augmented clinical trials, to be used to increase the numerosity where recruitment is impossible, or to explore patients' phenotypes that are unlikely to appear in the trial cohort, but are still frequent enough to be of concern.
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Affiliation(s)
- Marco Viceconti
- 1 Department of Mechanical Engineering, INSIGNEO Institute for in silico Medicine, The University of Sheffield, Sheffield, UK
| | - Claudio Cobelli
- 2 Department of Information Engineering, University of Padova, Padova, Italy
| | | | | | - Boris Kovatchev
- 4 Center for Diabetes Technology, The University of Virginia, Charlottesville, VA, USA
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Abstract
Biomedical research and clinical practice are struggling to cope with the growing complexity that the progress of health care involves. The most challenging diseases, those with the largest socioeconomic impact (cardiovascular conditions; musculoskeletal conditions; cancer; metabolic, immunity, and neurodegenerative conditions), are all characterized by a complex genotype-phenotype interaction and by a "systemic" nature that poses a challenge to the traditional reductionist approach. In 2005 a small group of researchers discussed how the vision of computational physiology promoted by the Physiome Project could be translated into clinical practice and formally proposed the term Virtual Physiological Human. Our knowledge about these diseases is fragmentary, as it is associated with molecular and cellular processes on the one hand and with tissue and organ phenotype changes (related to clinical symptoms of disease conditions) on the other. The problem could be solved if we could capture all these fragments of knowledge into predictive models and then compose them into hypermodels that help us tame the complexity that such systemic behavior involves. In 2005 this was simply not possible-the necessary methods and technologies were not available. Now, 10 years later, it seems the right time to reflect on the original vision, the results achieved so far, and what remains to be done.
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Affiliation(s)
- Marco Viceconti
- Department of Mechanical Engineering and Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield S1 3JD, United Kingdom;
| | - Peter Hunter
- Auckland Bioengineering Institute, University of Auckland, Auckland 1142, New Zealand
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Hoffmann M, Haering D, Begon M. Comparison between line and surface mesh models to represent the rotator cuff muscle geometry in musculoskeletal models. Comput Methods Biomech Biomed Engin 2017. [DOI: 10.1080/10255842.2017.1340463] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Marion Hoffmann
- Institute of Biomedical Engineering, University of Montreal, Montreal, Canada
| | | | - Mickaël Begon
- Institute of Biomedical Engineering, University of Montreal, Montreal, Canada
- Department of Kinesiology, University of Montreal, Montreal, Canada
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