We present a study in human-centered automation that has potential to reduce patient side effects from high dose rate brachytherapy (HDR-BT). To efficiently deliver radiation to the prostate while minimizing trauma to sensitive structures such as the penile bulb, we modified the Acubot-RND 7-axis robot to guide insertion of diamond-tip needles into desired skew-line geometric arrangements. We extend and integrate two algorithms: Needle Planning with Integer Programming (NPIP) and Inverse Planning with Integer Programming (IPIP) to compute skew-line needle and dose plans. We performed three physical experiments with anatomically correct phantom models to study performance: two with the robot and one control experiment with an expert human physician (coauthor Hsu) without the robot. All were able to achieve needle arrangements that meet the RTOG-0321 clinical dose objectives with zero trauma to the penile bulb. We analyze systematic and random errors in needle placement; total RMS error for the robot system operating without feedback ranged from 2.6 to 4.3 mm, which is comparable to the RMS error of 2.7 mm obtained in an earlier study for PPI-BT treatment using a robot with 3D ultrasound feedback.

Accurate insertion of needles to targets in 3D anatomy is required for numerous medical procedures. To reduce patient trauma, a "fireworks" needle insertion approach can be used in which multiple needles are inserted from a single small region on the patient's skin to multiple targets in the tissue. In this paper, we explore motion planning for "fireworks" needle insertion in 3D environments by developing an algorithm based on Rapidly-exploring Random Trees (RRTs). Given a set of targets, we propose an algorithm to quickly explore the configuration space by building a forest of RRTs and to find feasible plans for multiple steerable needles from a single entry region. We present two path selection algorithms with different optimality considerations to optimize the final plan among all feasible outputs. Finally, we demonstrate the performance of the proposed algorithm with a simulation based on a prostate cancer treatment environment.

Minimally invasive medical procedures such as biopsies, anesthesia drug injections, and brachytherapy cancer treatments require inserting a needle to a specific target inside soft tissues. This is difficult because needle insertion displaces and deforms the surrounding soft tissues causing the target to move during the procedure. To facilitate physician training and preoperative planning for these procedures, we develop a needle insertion motion planning system based on an interactive simulation of needle insertion in deformable tissues and numerical optimization to reduce placement error. We describe a 2-D physically based, dynamic simulation of needle insertion that uses a finite-element model of deformable soft tissues and models needle cutting and frictional forces along the needle shaft. The simulation offers guarantees on simulation stability for mesh modifications and achieves interactive, real-time performance on a standard PC. Using texture mapping, the simulation provides visualization comparable to ultrasound images that the physician would see during the procedure. We use the simulation as a component of a sensorless planning algorithm that uses numerical optimization to compute needle insertion offsets that compensate for tissue deformations. We apply the method to radioactive seed implantation during permanent seed prostate brachytherapy to minimize seed placement error.

To facilitate training and planning for medical procedures such as prostate brachytherapy, we are developing an interactive simulation of needle insertion and radioactive seed implantation in soft tissues. We describe a new 2D dynamic FEM model based on a reduced set of scalar parameters such as needle friction, sharpness, and velocity, where the mesh is updated to maintain element boundaries along the needle shaft and the effects of needle tip and frictional forces are simulated. The computational complexity of our model grows linearly with the number of elements in the mesh and achieves 24 frames per second for 1250 triangular elements on a 750 MHz PC. We use the simulator to characterize the sensitivity of seed placement error to physician-controlled and biological parameters. Results indicate that seed placement error is highly sensitive to physician-controlled parameters such as needle position, sharpness, and friction, and less sensitive to patient-specific parameters such as tissue stiffness and compressibility.

Medical procedures such as seed implantation, biopsies, and treatment injections require inserting a needle tip to a specific target location inside the human body. This is difficult because (1) needle insertion causes soft tissues to displace and deform, and (2) it is often difficult or impossible to obtain precise imaging data during insertion. We are developing a sensorless planning system for needle insertion that incorporates numerical optimization with a soft tissue simulation based on a dynamic FEM formulation that models the effects of needle tip and frictional forces using a 2D mesh. In this paper we describe a sensorless planning algorithm for radioactive seed implantation that computes needle insertion offsets that compensate for tissue deformations. We apply the method to seed implantation during permanent seed prostate brachytherapy to minimize seed placement error in simulation without relying on real-time imaging.