2009 Summer Project Week Prostate Robotics

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Key Investigators

  • BWH: Junichi Tokuda, Nobuhiko Hata
  • JHU: Sam Song, Nathan Cho
  • AMS: Jack Blevins, Clif Burdette
  • WPI: Gregory Fischer
  • Queen's: Andras Lasso

Objective

We will perform a mock-up procedure to validate our software / hardware system for MRI-guided transperineal prostate intervention.


Approach, Plan

The software system consists of three sub-components: a) control software for the needle placement robot, b) software to control a closed-bore whole body 3T MRI scanner (GE Excite HD 3T, GE Healthcare), and c) open-source surgical navigation software (3D Slicer, http://www.slicer.org/). The core component of the software system is 3D Slicer, running on a Linux-based workstation, that serves as an integrated environment for calibration, surgical planning, image guidance and device monitoring and control. The 3D Slicer communicates with the other components through 100 Base-T Ethernet to exchange data and commands using an open network communication protocol, OpenIGTLink. We developed a software module in 3D Slicer that offers all features uniquely required for MR-guided robotic prostate intervention, as follows: 1) management of the ‘workphase’ of the all components in the system; 2) treatment planning by placing target points on the pre-operative 3D images loaded on the 3D Slicer and robot control based on the plan; 3) registration of the robot and patient coordinate systems; 4) integrated visualization of real-time 2D image, preoperative 3D image, and visualization of the current needle position on the 3D viewer of 3D Slicer.

Progress

Software for the fiber tracking and statistical analysis along the tracts has been implemented. The statistical methods for diffusion tensors are implemented as ITK code as part of the DTI Software Infrastructure project. The methods have been validated on a repeated scan of a healthy individual. This work has been published as a conference paper (MICCAI 2005) and a journal version (MEDIA 2006). Our recent IPMI 2007 paper includes a nonparametric regression method for analyzing data along a fiber tract.

References