Phantoms are common substitutes for soft tissues in biomechanical research and are usually tuned to match tissue properties using standard testing protocols at small strains. However, the response due to complex tool-tissue interactions can differ depending on the phantom and no comprehensive comparative study has been published to date, which could aid researchers to select suitable materials. In this work, gelatin, a common phantom in literature, and a composite hydrogel developed at Imperial College, were matched for mechanical stiffness to porcine brain, and the interactions during needle insertions within them were analyzed. Specifically, we examined insertion forces for brain and the phantoms; we also measured displacements and strains within the phantoms via a laser-based image correlation technique in combination with fluorescent beads. It is shown that the insertion forces for gelatin and brain agree closely, but that the composite hydrogel better mimics the viscous nature of soft tissue. Both materials match different characteristics of brain, but neither of them is a perfect substitute. Thus, when selecting a phantom material, both the soft tissue properties and the complex tool-tissue interactions arising during tissue manipulation should be taken into consideration. These conclusions are presented in tabular form to aid future selection.
The mobility of soft tissue can cause inaccurate needle insertions. Particularly in steering applications that employ thin and flexible needles, large deviations can occur between pre-operative images of the patient, from which a procedure is planned, and the intra-operative scene, where a procedure is executed. Although many approaches for reducing tissue motion focus on external constraining or manipulation, little attention has been paid to the way the needle is inserted and actuated within soft tissue. Using our biologically inspired steerable needle, we present a method of reducing the disruptiveness of insertions by mimicking the burrowing mechanism of ovipositing wasps. Internal displacements and strains in three dimensions within a soft tissue phantom are measured at the needle interface, using a scanning laser-based image correlation technique. Compared to a conventional insertion method with an equally sized needle, overall displacements and strains in the needle vicinity are reduced by 30% and 41%, respectively. The results show that, for a given net speed, needle insertion can be made significantly less disruptive with respect to its surroundings by employing our biologically inspired solution. This will have significant impact on both the safety and targeting accuracy of percutaneous interventions along both straight and curved trajectories.
During minimally invasive surgical procedures, it is often important to deliver needles to particular tissue volumes. Needles, when interacting with a substrate, cause deformation and target motion. To reduce reliance on compensatory intra-operative imaging, a needle design and novel delivery mechanism is proposed. Three-dimensional finite element simulations of a multi-segment needle inserted into a pre-existing crack are presented. The motion profiles of the needle segments are varied to identify methods that reduce target motion. Experiments are then performed by inserting a needle into a gelatine tissue phantom and measuring the internal target motion using digital image correlation. Simulations indicate that target motion is reduced when needle segments are stroked cyclically and utilise a small amount of retraction instead of being held stationary. Results are confirmed experimentally by statistically significant target motion reductions of more than 8% during cyclic strokes and 29% when also incorporating retraction, with the same net insertion speed. By using a multi-segment needle and taking advantage of frictional interactions on the needle surface, it is demonstrated that target motion ahead of an advancing needle can be substantially reduced.
Robotic-assisted steered needles aim to accurately control the deflection of the flexible needle’s tip to achieve accurate path following. In doing so, they can decrease trauma to the patient, by avoiding sensitive regions while increasing placement accuracy. This class of needle presents more complicated kinematics compared to straight needles, which can be exploited to produce specific motion profiles via careful controller design and tuning. Motion profiles can be optimized to minimize certain conditions such as maximum tissue deformation and target migration, which was the goal of the formalized cyclic, low-level controller for a Programmable Bevel-tip Needle (PBN) presented in this work. PBNs are composed of a number of interlocked segments that are able to slide with respect to one another. Producing a controlled, desired offset of the tip geometry leads to the corresponding desired curvature of the PBN, and hence desired path trajectory of the system. Here, we propose a cyclical actuation strategy, where the tip configuration is achieved over a number of reciprocal motion cycles, which we hypothesize will reduce tissue deformation during the insertion process. A series of in vitro, planar needle insertion experiments are performed in order to compare the cyclic controller performance with the previously used direct push controller, in terms of targeting accuracy and tissue deformation. It is found that there is no significant difference between the target tracking performance of the controllers, but a significant decrease in axial tissue deformation when using the cyclic controller.
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