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Di Pietro A, Bersani A, Curreli C, Di Puccio F. AST: An OpenSim-based tool for the automatic scaling of generic musculoskeletal models. Comput Biol Med 2024; 175:108524. [PMID: 38688126 DOI: 10.1016/j.compbiomed.2024.108524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 04/22/2024] [Accepted: 04/24/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND AND OBJECTIVES The paper introduces a tool called Automatic Scaling Tool (AST) designed for improving and expediting musculoskeletal (MSK) simulations based on generic models in OpenSim. Scaling is a crucial initial step in MSK analyses, involving the correction of virtual marker locations on a model to align with actual experimental markers. METHODS The AST automates this process by iteratively adjusting virtual markers using scaling and inverse kinematics on a static trial. It evaluates the root mean square error (RMSE) and maximum marker error, implementing corrective actions until achieving the desired accuracy level. The tool determines whether to scale a segment with a marker-based or constant scaling factor based on checks on RMSE and segment scaling factors. RESULTS Testing on three generic MSK models demonstrated that the AST significantly outperformed manual scaling by an expert operator. The RMSE for static trials was one order of magnitude lower, and for gait tasks, it was five times lower (8.5 ± 0.76 mm vs. 44.5 ± 7.5 mm). The AST consistently achieved the desired level of accuracy in less than 100 iterations, providing reliable scaled MSK models within a relatively brief timeframe, ranging from minutes to hours depending on model complexity. CONCLUSIONS The paper concludes that AST can greatly benefit the biomechanical community by quickly and accurately scaling generic models, a critical first step in MSK analyses. Further validation through additional experimental datasets and generic models is proposed for future tests.
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Affiliation(s)
- Andrea Di Pietro
- Department of Civil and Industrial Engineering, University of Pisa, Italy.
| | - Alex Bersani
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Italy; Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Cristina Curreli
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Francesca Di Puccio
- Department of Civil and Industrial Engineering, University of Pisa, Italy; Center for Rehabilitative Medicine "Sport and Anatomy", University of Pisa, Italy
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Di Martino A, Geraci G, Brunello M, D'Agostino C, Davico G, Curreli C, Traina F, Faldini C. Hip-spine relationship: clinical evidence and biomechanical issues. Arch Orthop Trauma Surg 2024; 144:1821-1833. [PMID: 38472450 PMCID: PMC10965652 DOI: 10.1007/s00402-024-05227-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Accepted: 02/15/2024] [Indexed: 03/14/2024]
Abstract
The hip-spine relationship is a critical consideration in total hip arthroplasty (THA) procedures. While THA is generally successful in patient, complications such as instability and dislocation can arise. These issues are significantly influenced by the alignment of implant components and the overall balance of the spine and pelvis, known as spinopelvic balance. Patients with alteration of those parameters, in particular rigid spines, often due to fusion surgery, face a higher risk of THA complications, with an emphasis on complications in instability, impingement and dislocation. For these reasons, over the years, computer modelling and simulation techniques have been developed to support clinicians in the different steps of surgery. The aim of the current review is to present current knowledge on hip-spine relationship to serve as a common platform of discussion among clinicians and engineers. The offered overview aims to update the reader on the main critical aspects of the issue, from both a theoretical and practical perspective, and to be a valuable introductory tool for those approaching this problem for the first time.
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Affiliation(s)
- Alberto Di Martino
- Ist Orthopaedic Department, IRCCS-Istituto Ortopedico Rizzoli, Via Giulio Cesare Pupilli, 1, 40136, Bologna, Italy.
- Department of Biomedical and Neuromotor Science-DIBINEM, University of Bologna, 40136, Bologna, Italy.
| | - Giuseppe Geraci
- Ist Orthopaedic Department, IRCCS-Istituto Ortopedico Rizzoli, Via Giulio Cesare Pupilli, 1, 40136, Bologna, Italy
- Department of Biomedical and Neuromotor Science-DIBINEM, University of Bologna, 40136, Bologna, Italy
| | - Matteo Brunello
- Ist Orthopaedic Department, IRCCS-Istituto Ortopedico Rizzoli, Via Giulio Cesare Pupilli, 1, 40136, Bologna, Italy
- Department of Biomedical and Neuromotor Science-DIBINEM, University of Bologna, 40136, Bologna, Italy
| | - Claudio D'Agostino
- Ist Orthopaedic Department, IRCCS-Istituto Ortopedico Rizzoli, Via Giulio Cesare Pupilli, 1, 40136, Bologna, Italy
- Department of Biomedical and Neuromotor Science-DIBINEM, University of Bologna, 40136, Bologna, Italy
| | - Giorgio Davico
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy
| | - Cristina Curreli
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Francesco Traina
- Department of Biomedical and Neuromotor Science-DIBINEM, University of Bologna, 40136, Bologna, Italy
- Ortopedia-Traumatologia e Chirurgia Protesica e dei Reimpianti di Anca e di Ginocchio, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Cesare Faldini
- Ist Orthopaedic Department, IRCCS-Istituto Ortopedico Rizzoli, Via Giulio Cesare Pupilli, 1, 40136, Bologna, Italy
- Department of Biomedical and Neuromotor Science-DIBINEM, University of Bologna, 40136, Bologna, Italy
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Aldieri A, Curreli C, Szyszko JA, La Mattina AA, Viceconti M. Credibility assessment of computational models according to ASME V&V40: Application to the Bologna Biomechanical Computed Tomography solution. Comput Methods Programs Biomed 2023; 240:107727. [PMID: 37523955 DOI: 10.1016/j.cmpb.2023.107727] [Citation(s) in RCA: 0] [Impact Index Per Article: 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: 01/27/2023] [Revised: 07/17/2023] [Accepted: 07/18/2023] [Indexed: 08/02/2023]
Abstract
BACKGROUND AND OBJECTIVE When a computational model aims to be adopted beyond research purposes, e.g. to inform a clinical or regulatory decision, trust must be placed in its predictive accuracy. This practically translates into the need to demonstrate its credibility. In fact, prior to its adoption for regulatory purposes, an in silico methodology should be proven credible enough for the scope. This has become especially relevant as, although evidence of the safety and efficacy of new medical products or interventions has been traditionally provided to the regulator experimentally, i.e., in vivo or ex vivo, recently the idea to inform a regulatory decision in silico has made its way in the regulatory scenario. While a harmonised technical standard is currently missing in the EU regulatory system, in 2018 the ASME issued V&V40-2018, where a risk-based framework to assess the credibility of a computational model through the performance of predefined credibility activities is provided. The credibility framework is here applied to Bologna Biomechanical Computed Tomography (BBCT) solution, which predicts the absolute risk of fracture at the femur for a subject. BBCT has recently been the object of a qualification advice request to the European Medicine Agency. METHODS The full implementation of ASME V&V40-2018 framework on BBCT is shown. Starting from BBCT proposed context of use the whole credibility plan is presented and the credibility activities (Verification, Validation, Applicability) described together with the achieved credibility levels. RESULTS BBCT risk is judged medium, and the credibility levels achieved considered acceptable. The uncertainties intrinsically present in the material properties assignment affected BBCT predictions to the highest extent. CONCLUSIONS This work provides the practical application of the ASME V&V40-2018 risk-based credibility assessment framework, which could be applied to demonstrate model credibility in any field and support future regulatory submissions and foster the adoption of In Silico Trials.
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Affiliation(s)
- Alessandra Aldieri
- PolitoBIOMedLab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Italy; Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy.
| | - Cristina Curreli
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Itlay
| | - Julia Aleksandra Szyszko
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Itlay
| | - Antonino Amedeo La Mattina
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Itlay
| | - Marco Viceconti
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy; Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Itlay
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4
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Curreli C, Di Salvatore V, Russo G, Pappalardo F, Viceconti M. A Credibility Assessment Plan for an In Silico Model that Predicts the Dose-Response Relationship of New Tuberculosis Treatments. Ann Biomed Eng 2023; 51:200-210. [PMID: 36115895 PMCID: PMC9483464 DOI: 10.1007/s10439-022-03078-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2022] [Accepted: 09/06/2022] [Indexed: 01/13/2023]
Abstract
Tuberculosis is one of the leading causes of death in several developing countries and a public health emergency of international concern. In Silico Trials can be used to support innovation in the context of drug development reducing the duration and the cost of the clinical experimentations, a particularly desirable goal for diseases such as tuberculosis. The agent-based Universal Immune System Simulator was used to develop an In Silico Trials environment that can predict the dose-response of new therapeutic vaccines against pulmonary tuberculosis, supporting the optimal design of clinical trials. But before such in silico methodology can be used in the evaluation of new treatments, it is mandatory to assess the credibility of this predictive model. This study presents a risk-informed credibility assessment plan inspired by the ASME V&V 40-2018 technical standard. Based on the selected context of use and regulatory impact of the technology, a detailed risk analysis is described together with the definition of all the verification and validation activities and related acceptability criteria. The work provides an example of the first steps required for the regulatory evaluation of an agent-based model used in the context of drug development.
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Affiliation(s)
- Cristina Curreli
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy.
| | | | - Giulia Russo
- Department of Drug and Health Sciences, University of Catania, Catania, Italy
- Mimesis srl, Catania, Italy
| | | | - Marco Viceconti
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy
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5
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Pappalardo F, Wilkinson J, Busquet F, Bril A, Palmer M, Walker B, Curreli C, Russo G, Marchal T, Toschi E, Alessandrello R, Costignola V, Klingmann I, Contin M, Staumont B, Woiczinski M, Kaddick C, Salvatore VD, Aldieri A, Geris L, Viceconti M. Toward a Regulatory Pathway for the Use of in Silico Trials in The Ce Marking of Medical Devices. IEEE J Biomed Health Inform 2022; 26:5282-5286. [PMID: 35951559 DOI: 10.1109/jbhi.2022.3198145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
In Silico Trials methodologies will play a growing and fundamental role in the development and de-risking of new medical devices in the future. While the regulatory pathway for Digital Patient and Personal Health Forecasting solutions is clear, it is more complex for In Silico Trials solutions, and therefore deserves a deeper analysis. In this position paper, we investigate the current state of the art towards the regulatory system for in silico trials applied to medical devices while exploring the European regulatory system toward this topic. We suggest that the European regulatory system should start a process of innovation: in principle to limit distorted quality by different internal processes within notified bodies, hence avoiding that the more innovative and competitive companies focus their attention on the needs of other large markets, like the USA, where the use of such radical innovations is already rapidly developing.
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6
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Russo G, Di Salvatore V, Caraci F, Curreli C, Viceconti M, Pappalardo F. How can we accelerate COVID-19 vaccine discovery? Expert Opin Drug Discov 2021; 16:1081-1084. [PMID: 34058925 PMCID: PMC8204312 DOI: 10.1080/17460441.2021.1935861] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/25/2021] [Indexed: 12/24/2022]
Affiliation(s)
- Giulia Russo
- Department of Drug and Health Sciences, University of Catania, Catania, Italy
- Oasi Research Institute, IRCCS, Troina, Italy
| | - Valentina Di Salvatore
- Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy
| | - Filippo Caraci
- Department of Drug and Health Sciences, University of Catania, Catania, Italy
- Oasi Research Institute, IRCCS, Troina, Italy
| | - Cristina Curreli
- Department of Industrial Engineering, Alma Mater Studiorum, University of Bologna, Bologna, Italy
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Marco Viceconti
- Department of Industrial Engineering, Alma Mater Studiorum, University of Bologna, Bologna, Italy
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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7
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Curreli C, Di Puccio F, Davico G, Modenese L, Viceconti M. Using Musculoskeletal Models to Estimate in vivo Total Knee Replacement Kinematics and Loads: Effect of Differences Between Models. Front Bioeng Biotechnol 2021; 9:703508. [PMID: 34395407 PMCID: PMC8357266 DOI: 10.3389/fbioe.2021.703508] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [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: 04/30/2021] [Accepted: 06/23/2021] [Indexed: 01/29/2023] Open
Abstract
Total knee replacement (TKR) is one of the most performed orthopedic surgeries to treat knee joint diseases in the elderly population. Although the survivorship of knee implants may extend beyond two decades, the poor outcome rate remains considerable. A recent computational approach used to better understand failure modes and improve TKR outcomes is based on the combination of musculoskeletal (MSK) and finite element models. This combined multiscale modeling approach is a promising strategy in the field of computational biomechanics; however, some critical aspects need to be investigated. In particular, the identification and quantification of the uncertainties related to the boundary conditions used as inputs to the finite element model due to a different definition of the MSK model are crucial. Therefore, the aim of this study is to investigate this problem, which is relevant for the model credibility assessment process. Three different generic MSK models available in the OpenSim platform were used to simulate gait, based on the experimental data from the fifth edition of the "Grand Challenge Competitions to Predict in vivo Knee Loads." The outputs of the MSK analyses were compared in terms of relative kinematics of the knee implant components and joint reaction (JR) forces and moments acting on the tibial insert. Additionally, the estimated knee JRs were compared with those measured by the instrumented knee implant so that the "global goodness of fit" was quantified for each model. Our results indicated that the different kinematic definitions of the knee joint and the muscle model implemented in the different MSK models influenced both the motion and the load history of the artificial joint. This study demonstrates the importance of examining the influence of the model assumptions on the output results and represents the first step for future studies that will investigate how the uncertainties in the MSK models propagate on disease-specific finite element model results.
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Affiliation(s)
- Cristina Curreli
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Francesca Di Puccio
- Dipartimento di Ingegneria Civile e Industriale, Università di Pisa, Pisa, Italy
| | - Giorgio Davico
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | - Luca Modenese
- Department of Civil and Environmental Engineering, Imperial College London, London, United Kingdom
| | - Marco Viceconti
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy.,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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8
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Curreli C, Pappalardo F, Russo G, Pennisi M, Kiagias D, Juarez M, Viceconti M. Verification of an agent-based disease model of human Mycobacterium tuberculosis infection. Int J Numer Method Biomed Eng 2021; 37:e3470. [PMID: 33899348 PMCID: PMC8365724 DOI: 10.1002/cnm.3470] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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: 11/18/2020] [Revised: 03/23/2021] [Accepted: 04/23/2021] [Indexed: 05/12/2023]
Abstract
Agent-based models (ABMs) are a powerful class of computational models widely used to simulate complex phenomena in many different application areas. However, one of the most critical aspects, poorly investigated in the literature, regards an important step of the model credibility assessment: solution verification. This study overcomes this limitation by proposing a general verification framework for ABMs that aims at evaluating the numerical errors associated with the model. A step-by-step procedure, which consists of two main verification studies (deterministic and stochastic model verification), is described in detail and applied to a specific mission critical scenario: the quantification of the numerical approximation error for UISS-TB, an ABM of the human immune system developed to predict the progression of pulmonary tuberculosis. Results provide indications on the possibility to use the proposed model verification workflow to systematically identify and quantify numerical approximation errors associated with UISS-TB and, in general, with any other ABMs.
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Affiliation(s)
- Cristina Curreli
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
| | | | - Giulia Russo
- Department of Drug and Health Sciences, University of Catania, Catania, Italy
- Mimesis srl, Catania, Italy
| | - Marzio Pennisi
- Computer Science Institute, DiSIT, University of Eastern Piedmont, Alessandria, Italy
| | - Dimitrios Kiagias
- School of Mathematics & Statistics and Insigneo and Institute for in silico Medicine, University of Sheffield, Sheffield, UK
| | - Miguel Juarez
- School of Mathematics & Statistics and Insigneo and Institute for in silico Medicine, University of Sheffield, Sheffield, UK
| | - Marco Viceconti
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna, Bologna, Italy
- Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna, Italy
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9
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Viceconti M, Emili L, Afshari P, Courcelles E, Curreli C, Famaey N, Geris L, Horner M, Jori MC, Kulesza A, Loewe A, Neidlin M, Reiterer M, Rousseau CF, Russo G, Sonntag SJ, Voisin EM, Pappalardo F. Possible Contexts of Use for In Silico trials methodologies: a consensus- based review. IEEE J Biomed Health Inform 2021; 25:3977-3982. [PMID: 34161248 DOI: 10.1109/jbhi.2021.3090469] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The term In Silico Trial indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative.
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Di Puccio F, Curreli C, Gagliani M, Mattei L. In silico re-foundation of strain-based healing assessment of fractures treated with an external fixator. J Mech Behav Biomed Mater 2021; 121:104619. [PMID: 34198040 DOI: 10.1016/j.jmbbm.2021.104619] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 05/10/2021] [Accepted: 05/28/2021] [Indexed: 01/08/2023]
Abstract
In the last decades, the literature has demonstrated a renewed interest in finding quantitative and non-invasive techniques for the assessment of bone fractures, by replacing X-ray images. Many different approaches have been proposed from ultrasounds to vibrations. This study aims to numerically assess the foundation of a method firstly proposed in 70' years, based on strain gauges measurements on external fixators for fracture healing monitoring. The theoretical basis consists in the load transfer from the fixator to the bone caused by the callus stiffening during healing. The feasibility is questioned since the level of fixator strain and its variation in invivo conditions should be high enough to be detectable by the sensors. A finite element model of a fractured tibia phantom treated with a monolateral external fixator was developed and validated experimentally. Then, this reference model was used to simulate bone healing and to investigate the sensitivity of virtual strain measurements to callus geometry and loading conditions. The analysis of load distribution among fixator components and their strain maps allowed to identify optimum strain gauges locations which resulted on the pins more distant from the callus, regardless of the simulated conditions. Even in the worst case of a very thin (3 mm) transverse callus in constrained compression conditions, the strain level (≈100 με/100 N) and its variation per week (-50 με/100 N/wk) resulted measurable in the first healing phase, before plateau conditions occurring after about 6 weeks from fixation. A thicker callus causes higher strain levels and can significantly improve measurements, whilst the callus orientation and the loading conditions have a minor effect. However, in case of a free compression loading, also the rods could provide useful indications if sensorized. The results support the method applicability in invivo conditions for the considered test case. Further investigations will be addressed to evaluate the effect of the fixator structure and configuration as well as of patient specific healing timing on the method sensitivity.
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Affiliation(s)
- Francesca Di Puccio
- Department of Civil and Industrial Engineering, Università di Pisa, Largo Lucio Lazzarino 2, 56122, Pisa, Italy.
| | - Cristina Curreli
- Department of Civil and Industrial Engineering, Università di Pisa, Largo Lucio Lazzarino 2, 56122, Pisa, Italy.
| | - Matteo Gagliani
- Department of Civil and Industrial Engineering, Università di Pisa, Largo Lucio Lazzarino 2, 56122, Pisa, Italy.
| | - Lorenza Mattei
- Department of Civil and Industrial Engineering, Università di Pisa, Largo Lucio Lazzarino 2, 56122, Pisa, Italy.
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11
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Viceconti M, Curreli C, Bottin F, Davico G. Effect of Suboptimal Neuromuscular Control on the Risk of Massive Wear in Total Knee Replacement. Ann Biomed Eng 2021; 49:3349-3355. [PMID: 34076785 PMCID: PMC8671275 DOI: 10.1007/s10439-021-02795-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [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: 01/30/2021] [Accepted: 05/12/2021] [Indexed: 11/21/2022]
Abstract
The optimal neuromuscular control (muscle activation strategy that minimises the consumption of metabolic energy) during level walking is very close to that which minimises the force transmitted through the joints of the lower limbs. Thus, any suboptimal control involves an overloading of the joints. Some total knee replacement patients adopt suboptimal control strategies during level walking; this is particularly true for patients with co-morbidities that cause neuromotor control degeneration, such as Parkinson’s Disease (PD). The increase of joint loading increases the risk of implant failure, as reported in one study in PD patients (5.44% of failures at 9 years follow-up). One failure mode that is directly affected by joint loading is massive wear of the prosthetic articular surface. In this study we used a validated patient-specific biomechanical model to estimate how a severely suboptimal control could increase the wear rate of total knee replacements. Whereas autopsy-retrieved implants from non-PD patients typically show average polyethylene wear of 17 mm3 per year, our simulations suggested that a severely suboptimal control could cause a wear rate as high as of 69 mm3 per year. Assuming the risk of implant failure due to massive wear increase linearly with the wear rate, a severely suboptimal control could increase the risk associated to that failure mode from 0.1% to 0.5%. Based on these results, such increase would not be not sufficient to justify alone the higher incidence rate of revision in patients affected by Parkinson’s Disease, suggesting that other failure modes may be involved.
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Affiliation(s)
- Marco Viceconti
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna (IT), Bologna, Italy. .,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna (IT), Via di Barbiano 1/10, 40136, Bologna, Italy.
| | - Cristina Curreli
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna (IT), Bologna, Italy.,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna (IT), Via di Barbiano 1/10, 40136, Bologna, Italy
| | - Francesca Bottin
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna (IT), Bologna, Italy.,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna (IT), Via di Barbiano 1/10, 40136, Bologna, Italy
| | - Giorgio Davico
- Department of Industrial Engineering, Alma Mater Studiorum - University of Bologna (IT), Bologna, Italy.,Medical Technology Lab, IRCCS Istituto Ortopedico Rizzoli, Bologna (IT), Via di Barbiano 1/10, 40136, Bologna, Italy
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12
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Juárez MA, Pennisi M, Russo G, Kiagias D, Curreli C, Viceconti M, Pappalardo F. Generation of digital patients for the simulation of tuberculosis with UISS-TB. BMC Bioinformatics 2020; 21:449. [PMID: 33308156 PMCID: PMC7733699 DOI: 10.1186/s12859-020-03776-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 09/22/2020] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND The STriTuVaD project, funded by Horizon 2020, aims to test through a Phase IIb clinical trial one of the most advanced therapeutic vaccines against tuberculosis. As part of this initiative, we have developed a strategy for generating in silico patients consistent with target population characteristics, which can then be used in combination with in vivo data on an augmented clinical trial. RESULTS One of the most challenging tasks for using virtual patients is developing a methodology to reproduce biological diversity of the target population, ie, providing an appropriate strategy for generating libraries of digital patients. This has been achieved through the creation of the initial immune system repertoire in a stochastic way, and through the identification of a vector of features that combines both biological and pathophysiological parameters that personalise the digital patient to reproduce the physiology and the pathophysiology of the subject. CONCLUSIONS We propose a sequential approach to sampling from the joint features population distribution in order to create a cohort of virtual patients with some specific characteristics, resembling the recruitment process for the target clinical trial, which then can be used for augmenting the information from the physical the trial to help reduce its size and duration.
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Affiliation(s)
- Miguel A. Juárez
- School of Mathematics and Statistics, University of Sheffield, Sheffield, S3 7RH UK
| | - Marzio Pennisi
- Computer Science Institute, DiSIT, University of Eastern Piedmont, Alessandria, Italy
| | - Giulia Russo
- Department of Drug Sciences, University of Catania, Catania, Italy
| | - Dimitrios Kiagias
- School of Mathematics and Statistics, University of Sheffield, Sheffield, S3 7RH UK
| | - Cristina Curreli
- Department of Industrial Engineering, University of Bologna, Bologna, Italy
| | - Marco Viceconti
- Department of Industrial Engineering, University of Bologna, Bologna, Italy
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Viceconti M, Juarez MA, Curreli C, Pennisi M, Russo G, Pappalardo F. Credibility of In Silico Trial Technologies-A Theoretical Framing. IEEE J Biomed Health Inform 2019; 24:4-13. [PMID: 31670687 DOI: 10.1109/jbhi.2019.2949888] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Different research communities have developed various approaches to assess the credibility of predictive models. Each approach usually works well for a specific type of model, and under some epistemic conditions that are normally satisfied within that specific research domain. Some regulatory agencies recently started to consider evidences of safety and efficacy on new medical products obtained using computer modelling and simulation (which is referred to as In Silico Trials); this has raised the attention in the computational medicine research community on the regulatory science aspects of this emerging discipline. But this poses a foundational problem: in the domain of biomedical research the use of computer modelling is relatively recent, without a widely accepted epistemic framing for model credibility. Also, because of the inherent complexity of living organisms, biomedical modellers tend to use a variety of modelling methods, sometimes mixing them in the solution of a single problem. In such context merely adopting credibility approaches developed within other research communities might not be appropriate. In this paper we propose a theoretical framing for assessing the credibility of a predictive models for In Silico Trials, which accounts for the epistemic specificity of this research field and is general enough to be used for different type of models.
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