Dataset Information

In Silico Optimization of Femoral Fixator Position and Configuration by Parametric CAD Model.

ABSTRACT: Structural analysis, based on the finite element method, and structural optimization, can help surgery planning or decrease the probability of fixator failure during bone healing. Structural optimization implies the creation of many finite element model instances, usually built using a computer-aided design (CAD) model of the bone-fixator assembly. The three most important features of such CAD models are: parameterization, robustness and bidirectional associativity with finite elements (FE) models. Their significance increases with the increase in the complexity of the modeled fixator. The aim of this study was to define an automated procedure for the configuration and placement of fixators used in the treatment of long bone fractures. Automated and robust positioning of the selfdynamisable internal fixator on the femur was achieved and sensitivity analysis of fixator stress on the change of major design parameters was performed. The application of the proposed methodology is considered to be beneficial in the preparation of CAD models for automated structural optimization procedures used in long bone fixation.

SUBMITTER: Korunovic N

PROVIDER: S-EPMC6679040 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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In Silico Optimization of Femoral Fixator Position and Configuration by Parametric CAD Model.

Korunovic Nikola N Marinkovic Dragan D Trajanovic Miroslav M Zehn Manfred M Mitkovic Milorad M Affatato Saverio S

Materials (Basel, Switzerland) 20190722 14

Structural analysis, based on the finite element method, and structural optimization, can help surgery planning or decrease the probability of fixator failure during bone healing. Structural optimization implies the creation of many finite element model instances, usually built using a computer-aided design (CAD) model of the bone-fixator assembly. The three most important features of such CAD models are: parameterization, robustness and bidirectional associativity with finite elements (FE) mode ...[more]

PMID: 31336577

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Project description:PurposeTo examine the ability of surgeons to identify the osseous landmarks associated with the femoral anterior cruciate ligament (ACL) footprint and locate optimal tunnel placement on 3-dimensional (3D) printed models compared with intraoperative placement.MethodsTwelve sports fellowship-trained orthopaedic surgeons were asked to identify a femoral landmark and an ACL footprint on 10 different 3D printed knees. The 3D models were made based on 20 real patients with different anatomical morphology who later received ACL reconstructive surgery using independent drilling. ImageJ software was used to quantify the measurements, which were then analyzed using descriptive statistics.ResultsOverall, none of the surgeons were able to consistently identify the junction of the bony ridges. The mean error per participant ranged from 2.81 to 7.34 mm in the proximal direction (P = 3.30e-05) and from 2.42 to 8.05 mm in the posterior direction (P =4.88e-12). None of the surgeons were able to appropriately identify the center of the femoral footprint on the anatomic 3D models. The difference between the center of the footprint surgeons identified on the 3D model and the tunnel graft location in surgery was significantly different (P = .0046). On average, the magnitude of the error when the surgeons performed the actual surgery was 3.72 ± 2.43 mm, whereas on the 3D models it was 5.82 ± 1.97 mm.ConclusionsExperienced sports fellowship-trained orthopaedic surgeons were unable to correctly identify the junction of the intercondylar and bifurcate ridges and the native ACL footprint on 3D models. Operatively placed tunnels were more accurate implying that looking either through a scope or soft-tissue landmarks play a significant role in surgeons ACL footprint localization.Clinical relevanceThe graft position for ACL reconstruction plays an important role on the kinematics of the knee. This paper shows that soft tissue landmarks are needed to provide reliable reference points for reconstruction.

Dataset Information

In Silico Optimization of Femoral Fixator Position and Configuration by Parametric CAD Model.

Publications

In Silico Optimization of Femoral Fixator Position and Configuration by Parametric CAD Model.

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