Surgical Needle Insertion and Radioactive Seed Implantation: Simulation and Sensitivity Analysis

<Fall 2001 ~ present> 
Ron Alterovitz and Ken Goldberg
IEOR & EECS Departments
UC Berkeley
Jean Pouliot, Richard Taschereau, and I-Chow Joe Hsu
Dept. of Radiation Oncology
UC San Francisco


To facilitate training and planning for surgical procedures such as prostate brachytherapy, we are developing new models for 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, and a 7-phase insertion sequence where the FEM mesh is updated to maintain element boundaries along the needle shaft. 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 750Mhz PC. We use the simulator to characterize the sensitivity of seed placement error to surgical and biological parameters. Results indicate that seed placement error is highly sensitive to surgeon-controlled parameters such as needle position, sharpness, and friction, and less sensitive to patient-specific parameters such as tissue stiffness and compressibility.

(a) Human prostate with target implant location

(b) Needle insertion

(c) Needle reaches target

(d) Seed implanted at target

(e) Needle extraction

(f) Seed placement error
Simulation of needle insertion based on an ultrasound image of a human prostate cancer patient. Frame (a) outlines the prostate (in green) and the target implant location (small white dot) which is fixed in the world frame. Our simulation places a radioactive seed (large green disc) at this location (d). After needle extraction and tissue retraction, the placement Error, the distance between the target and resulting seed location shown in (f), is 30% of the width of the prostate. Needle plans that compensate for tissue deformation can reduce placement errors like these that damage healthy tissue and fail to kill cancerous cells.


Human surgery is increasingly based on minimally invasive techniques that operate inside the body through narrow openings, reducing disturbance to healthy tissue, minimizing risk of infection, and speeding recovery. A fast and accurate computer simulation of this type of surgery can facilitate surgeon training, optimize surgical procedures before the patient enters the operating room, and assist in real-time re-planning during surgery as data is collected.

Brachytherapy, a type of minimally invasive surgery, allows surgeons to insert radioactive seeds into cancerous tumors. It is usually applied to treat prostate cancer. The post-procedure radioactive dose distribution should minimize healthy tissue damage while maximizing the destruction of cancerous tissue. Normally, a seed placement plan is created by a dosimetrist who gives the surgeon relative coordinates for seed implantation within the prostate. Multiple seeds and biodegradable spacers are loaded into a needle that the surgeon inserts horizontally into the patient. Seeds and spacers are ejected from the needle when the depth specified by the dosimetrist is reached. Unfortunately, inserting and retracting a needle in soft tissues causes the tissues to deform: ignoring these deformations during the implantation results in misplaced seeds. A dynamic simulation model can facilitate surgery planning by allowing a surgeon or optimizing planner to determine how surgeon-controlled parameters and patient-specific parameters will affect seed placement.


  • R. Alterovitz, J. Pouliot, R. Taschereau, I.C. Hsu, and K. Goldberg. Surgical Needle Insertion and Radioactive Seed Implantation: Simulation and Sensitivity Analysis. Submitted to IEEE ICRA 2003.
  • R. Alterovitz, J. Pouliot, R. Taschereau, I.C. Hsu, and K. Goldberg. Simulating Needle Insertion and Radioactive Seed Implantation for Prostate Brachytherapy. MMVR11 - NextMed: Health Horizon, 11th Annual Medicine Meets Virtual Reality Conference, Newport Beach, California. January 2003.
  • R. Alterovitz and K. Goldberg. Comparing Algorithms for Soft Tissue Deformation: Accuracy Metrics and Benchmarks. 2002.