scholarly journals Development of Digital Twins to Optimize Trauma Surgery and Postoperative Management. A Case Study Focusing on Tibial Plateau Fracture

2021 ◽  
Vol 9 ◽  
Author(s):  
Kévin Aubert ◽  
Arnaud Germaneau ◽  
Michel Rochette ◽  
Wenfeng Ye ◽  
Mathieu Severyns ◽  
...  
Keyword(s):  
Decision Making ◽  
Finite Element ◽  
Stress Distribution ◽  
Tibial Plateau ◽  
Postoperative Management ◽  
Patient Specific ◽  
Cortical Screw ◽  
Stabilization Methods ◽  
Digital Twins ◽  
Fracture Risks

Background and context: Surgical procedures are evolving toward less invasive and more tailored approaches to consider the specific pathology, morphology, and life habits of a patient. However, these new surgical methods require thorough preoperative planning and an advanced understanding of biomechanical behaviors. In this sense, patient-specific modeling is developing in the form of digital twins to help personalized clinical decision-making.Purpose: This study presents a patient-specific finite element model approach, focusing on tibial plateau fractures, to enhance biomechanical knowledge to optimize surgical trauma procedures and improve decision-making in postoperative management.Study design: This is a level 5 study.Methods: We used a postoperative 3D X-ray image of a patient who suffered from depression and separation of the lateral tibial plateau. The surgeon stabilized the fracture with polymethyl methacrylate cement injection and bi-cortical screw osteosynthesis. A digital twin of the patient’s fracture was created by segmentation. From the digital twin, four stabilization methods were modeled including two screw lengths, whether or not, to inject PMMA cement. The four stabilization methods were associated with three bone healing conditions resulting in twelve scenarios. Mechanical strength, stress distribution, interfragmentary strains, and fragment kinematics were assessed by applying the maximum load during gait. Repeated fracture risks were evaluated regarding to the volume of bone with stress above the local yield strength and regarding to the interfragmentary strains.Results: Stress distribution analysis highlighted the mechanical contribution of cement injection and the favorable mechanical response of uni-cortical screw compared to bi-cortical screw. Evaluation of repeated fracture risks for this clinical case showed fracture instability for two of the twelve simulated scenarios.Conclusion: This study presents a patient-specific finite element modeling workflow to assess the biomechanical behaviors associated with different stabilization methods of tibial plateau fractures. Strength and interfragmentary strains were evaluated to quantify the mechanical effects of surgical procedures. We evaluate repeated fracture risks and provide data for postoperative management.

scholarly journals A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

2018 ◽  
Vol 15 (138) ◽  
pp. 20170844 ◽  
Author(s):  
Liang Liang ◽  
Minliang Liu ◽  
Caitlin Martin ◽  
Wei Sun
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Deep Learning ◽  
Stress Distribution ◽  
Machine Learning Techniques ◽  
Von Mises Stress ◽  
Patient Specific ◽  
Stress Distributions ◽  
Element Analysis ◽  
Von Mises

Structural finite-element analysis (FEA) has been widely used to study the biomechanics of human tissues and organs, as well as tissue–medical device interactions, and treatment strategies. However, patient-specific FEA models usually require complex procedures to set up and long computing times to obtain final simulation results, preventing prompt feedback to clinicians in time-sensitive clinical applications. In this study, by using machine learning techniques, we developed a deep learning (DL) model to directly estimate the stress distributions of the aorta. The DL model was designed and trained to take the input of FEA and directly output the aortic wall stress distributions, bypassing the FEA calculation process. The trained DL model is capable of predicting the stress distributions with average errors of 0.492% and 0.891% in the Von Mises stress distribution and peak Von Mises stress, respectively. This study marks, to our knowledge, the first study that demonstrates the feasibility and great potential of using the DL technique as a fast and accurate surrogate of FEA for stress analysis.

A Novel Dynamic Bone Stress Evaluation Method of Postoperative Proximal Femur During Gait by Using Elastic Multi Body Analysis Based on Finite Element Analysis

2017 ◽  
Author(s):  
Yukiko Nakamura ◽  
Kazuhiko Adachi ◽  
Nungna Wi ◽  
Mitsuaki Noda
Keyword(s):  
Finite Element ◽  
Stress Distribution ◽  
Boundary Conditions ◽  
Hip Joint ◽  
Proximal Femur ◽  
Dynamic Stress ◽  
Fe Analysis ◽  
Patient Specific ◽  
Time Varying ◽  
Multi Body

A proximal femur fracture due to osteoporosis is one of serious health care problems in aging societies. Osteosynthesis with pin or screw type of implants, such as Hansson pin (HP), Dual SC Screw (DSCS), is widely used for femoral neck fracture treatment in Japan. Unfortunately, some complications such as secondary fractures, especially peri-prosthetic fractures, may occur during postoperative rehabilitation period. In order to reveal the potential cause of the postoperative fracture from the viewpoint of the biomechanics, authors had already performed the dynamic stress analysis of the treated proximal femur based on finite element (FE) analysis. The final goal of our project is to establish the reliable postoperative bone fracture risk assessment method in response to the daily activity including mainly walking. The aim of this study is to propose a novel elastic multi body analysis method based on FE analysis for proximal femur biomechanics. Patient-specific 3D left hip joint FE model was constructed from an elderly female volunteer’s CT images. The model consists of the pelvis, proximal femur, cartilage and DSCS, as multi bodies. The dynamic loading and boundary conditions were applied to the model for simulating a gait motion. Direction and magnitude of the loads varies in response to the gait motion. The time dependent loading forces; hip contact, gluteus medius, gluteus maximus, tensor fasciae latae and adductor, acting around the hip joint was obtained by inverse dynamic analysis of a human gait using in-house lower-limb musculoskeletal model. These loading and boundary conditions for simulating the gait motion are the major technical advantages of the proposed multi body analysis comparing with the conventional static FE analysis. Time varying stress distribution during the gait was evaluated by using dynamic explicit method via ABAQUS. In order to visually demonstrate dynamic stress distribution, we examined the time varying von Mises stresses at the representative points located on the cortical surface of the proximal femur; femoral head, fracture surface and around the lateral insertion holes. The results indicate significant increase of the stresses around the proximal lateral insertion holes for DSCS treatment. Maximum stress values are good agreement with the previous static FE analysis, on the other hand, these biomechanical discussions based on the stress time histories are only obtained from the proposed method. It is indicated that the proposed method is feasible to support the better pre- and postoperative clinical decisions, which is the main contribution of this study.

scholarly journals Biomechanical behavior of periodontally compromised dento-alveolar complex before and after regenerative therapy - a proof of concept

2020 ◽  
pp. 116-116
Author(s):  
Natasa Nikolic-Jakoba ◽  
Milena Barac ◽  
Ksenija Zelic ◽  
Arso Vukicevic ◽  
Gordana Jovicic ◽  
...  
Keyword(s):  
Finite Element ◽  
Stress Distribution ◽  
Bone Loss ◽  
Periodontal Therapy ◽  
Patient Specific ◽  
Regenerative Therapy ◽  
Biomechanical Behavior ◽  
Regenerative Periodontal Therapy ◽  
The Impact ◽  
Occlusal Load

Introduction/Objective. Finite element analysis (FEA) is mathematical method which can be used for the assessment of biomechanical behavior of dento-alveolar complex. The objective was to analyze biomechanical behavior changes of teeth and supporting tissues under occlusal load in cases of horizontal and vertical alveolar bone loss, to assess potential impact of tooth displacement and altered stress distribution on further damage, and to evaluate the impact of regenerative periodontal therapy. Methods. Three patient-specific three-dimensional-Finite-Element (3D FE) models were developed from the acquired cone beam computed tomography, comprising the patient's upper left canine, first and second premolar, and adjacent bone. Model 1 represented horizontal bone loss; Model 2 included intrabony defect along distal aspect of tooth #24. Model 3 represented situation six months after the regenerative periodontal surgery. Displacement, Von Mises, and principal stresses were evaluated through FEA, under moderate vertical occlusal load. Results. FEA demonstrated that in model with vertical bone loss significant tooth displacement was present, even though the clinically evident tooth mobility was absent. Biomechanical behavior and stress distribution of teeth and surrounding tissues under moderate occlusal load was much more altered in case with vertical bone loss in comparison with horizontal bone loss. Six months following the regenerative therapy, the values of all evaluated parameters were noticeable reduced. Conclusion. Regenerative periodontal therapy improved the biomechanical characteristics of the affected teeth and the related periodontal structures.

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