RESUMO
Modelling of needle insertion in soft tissue has developed significant interest in recent years due to its application in robot-assisted minimally invasive surgeries such as biopsies and brachytherapy. However, this type of surgery requires real-time feedback and processing which complex computational models may not be able to provide. In contrast to the existing mechanics-based kinetic models, a simple multilayer tissue model using a Coupled Eulerian Lagrangian based Finite Element method has been developed using the dynamic principle. The model simulates the needle motion for flexible hollow bevel-angled needle (15° and 30°, 22 Gauge) insertion into porcine liver tissue, which includes material parameters obtained from unconfined compression testing of porcine liver tissue. To validate simulation results, needle insertion force and cutting force within porcine liver tissue were compared with corresponding experimental results obtained from a custom-built needle insertion system. For the 15° and 30° bevel-angle needles, the percentage error for cutting force (mean) of each needle compared to computational model, were 18.7% and 11.9% respectively. Varying the needle bevel angle from 30° to 15° results in an increase of the cutting force, but insertion force does not vary among the tested bevel angles. The validation of this computationally efficient multilayer Finite Element model can help engineers to better understand the biomechanical behaviour of medical needle inside soft biological tissue. Ultimately, this multilayer approach can help advance state-of-art clinical applications such as robot-assisted surgery that requires real-time feedback and processing. STATEMENT OF SIGNIFICANCE: The significance of the work is in confirming the effectiveness of multilayer material based finite element (FE) method to model biopsy needle insertion into soft biological porcine liver tissue. A multilayer Coupled Eulerian Lagrangian (CEL) based FE modelling technique allowed testing of heterogeneous, non-linear viscoelastic porcine liver tissue in a system, so direct comparison of needle tissue interaction forces on the intrinsic material (tissue) behaviour could be made. To the best of the authors' knowledge, the present research investigates for the first time modelling of a three dimensional (3D) hollow needle insertion using a multilayer stiffness model of biological tissue using FE based CEL method and presents a comparison of simulation results with experimental data.
Assuntos
Agulhas , Punções , Animais , Biópsia por Agulha , Simulação por Computador , Fígado , Modelos Biológicos , SuínosRESUMO
BACKGROUND: A thorough understanding of cutting-edge geometry and cutting forces of hollow biopsy needles are required to optimise needle tip design to improve fine needle aspiration procedures. OBJECTIVES: To incorporate the dynamics of needle motion in a model for flexible hollow bevel tipped needle insertion into a biological mimetic soft-gel using parameters obtained from experimental work. Additionally, the models will be verified against corresponding needle insertion experiments. METHODS: To verify simulation results, needle deflection and insertion forces were compared with corresponding experimental results acquired with an in-house developed needle insertion mechanical system. Additionally, contact stress distribution on needles from agar gel for various time scales were also studied. RESULTS: For the 15°, 30°, 45°, 60° bevel angle needles, and 90° blunt needle, the percentage error in needle deflection of each needle compared to experiments, were 7.3%, 9.9%, 8.6%, 7.8%, and 9.7% respectively. Varying the bevel angle at the needle tip demonstrates that the needle with a lower bevel angle produces the largest deflection, although the insertion force does not vary too much among the tested bevel angles. CONCLUSION: This experimentally verified computer-based simulation model could be used as an alternative tool for better understanding the needle-tissue interaction to optimise needle tip design towards improved biopsy efficiency.