Needle insertion into soft tissue is one of the most common medical interventions. This study provides macroscopic and microscopic observations of needle-gel interactions. A gelatin mixture is used as a soft-tissue simulant. For the macroscopic studies, system parameters, such as insertion velocity, needle diameter, gel elasticity, needle tip shape (including bevel angle) and insertion motion profile, are varied, while the maximum insertion force and maximum needle deflection are recorded. The needle tip and gel interactions are observed using confocal microscopic images. Observations indicate that increasing the insertion velocity and needle diameter results in larger insertion forces and smaller needle deflections. Varying the needle bevel angle from 8 degrees to 82 degrees results in the insertion force increasing monotonically, while the needle deflection does not. These variations are due to the coupling between gel rupture and tip compression interactions, which are observed during microscopic studies. Increasing the gel elasticity results in larger insertion forces and needle deflections. Varying the tip shapes demonstrates that bevel-tipped needles produce the largest deflection, but insertion force does not vary among the tested tip shapes. Insertion with different motion profiles are performed. Results show that adding I Hz rotational motion during linear insertion decreases the needle deflection. Increasing the rotational motion from I Hz to 5 Hz decreases the insertion force, while the needle deflection remains the same. A high-velocity (250 mm/s and 300 mm/s) tapping during insertion yields no significant decrease in needle deflection and a slight increase in insertion force.

When a needle is inserted into soft tissue, interaction forces are developed at the needle tip and along the needle shaft. The needle tip force is due to cutting of the tissue, and the force along the needle shaft is due to friction between needle and tissue. In this study, the friction force is determined for needles inserted into a gelatine phantom at insertion velocities of 10 mm/s and 20 mm/s. The friction force is found to be dependent on the insertion velocity. The needle tip force is calculated using the friction and insertion force, and is used as input for a mechanics-based model which predicts the amount of needle deflection. In the model, the needle is considered to be a cantilever beam supported by springs which have needletissue interaction stiffness (Ke). The value of the interaction stiffness is evaluated by comparing results from experiments and simulation. A mechanical needle insertion device is used to insert needles. Needle deflection during insertion is determined using a needle tip tracking algorithm. Results of this study provide insight into the mechanics of needle-tissue interaction, and can be used in studies for robotically steering needles into soft tissue.

When a needle is inserted into soft tissue, interaction forces are developed at the needle tip and along the needle shaft. The needle tip force is due to cutting of the tissue, and the force along the needle shaft is due to friction between needle and tissue. In this study, the friction force is determined for needles inserted into a gelatine phantom at insertion velocities of 10 mm/s and 20 mm/s. The friction force is found to be dependent on the insertion velocity. The needle tip force is calculated using the friction and insertion force, and is used as input for a mechanics-based model which predicts the amount of needle deflection. In the model, the needle is considered to be a cantilever beam supported by springs which have needletissue interaction stiffness (Ke). The value of the interaction stiffness is evaluated by comparing results from experiments and simulation. A mechanical needle insertion device is used to insert needles. Needle deflection during insertion is determined using a needle tip tracking algorithm. Results of this study provide insight into the mechanics of needle-tissue interaction, and can be used in studies for robotically steering needles into soft tissue.

This study shows that a back-propagation neural network can be used to predict prostate deformation. Further, it is also demonstrated that a combination of ultrasound data, MR images and a neural network can be used as a framework for accurately predicting 3D prostate deformation in real time.

Accurate needle placement is important during percutaneous needle insertion procedures such as biopsy and brachytherapy. However, needle-tissue interactions may cause the needle to deviate from its intended path. In this paper, we have investigated the effects of insertion velocity, tip bevel angle and insertion profile on needle deflection in threedimensional space (in-plane and out-of-plane). Experiments are done using soft-tissue simulant and chicken liver. The needle tip is tracked during insertion using stereoscopic cameras and an electromagnetic tracker. Experimental results show that the in-plane and out-of-plane deflection decreases, as insertion velocity increases. Varying the bevel angle from 30°to 60°is shown to decrease the in-plane deflection, and increase the out-of-plane deflection. The addition of rotational motion during continuous linear insertion decreases both the in-plane and out-of-plane deflection. Tapping during insertion does not produce significant reduction in the in-plane or out-of-plane deflection. An increase in the insertion velocity from 10 mm/s to 300 mm/s during insertion into chicken liver results in the decrease and increase in the in-plane and out-of-plane deflection, respectively. A monotonic increase in the out-of-plane deflection as insertion velocity increases is probably caused by the needle slipping while penetrating the outer capsule of the liver. The results of this study can be used to develop an accurate model of needle-tissue interactions.