An Integrated System for ImageGuided Radiofrequency Ablation RFA of Liver Tumors

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An Integrated System for Image-Guided
Radiofrequency Ablation (RFA) of Liver Tumors

• Kevin Cleary, Ziv Yaniv, Georgetown University
• Noby Hata, Brigham and Womens Hospital
• Enrique Campos-Nanez, George Washington
  University

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Liver tumor RFA

• Liver cancer that cannot be resected due to
  extent and location of the disease or concurrent
  medical conditions.
• Introduce localized RF energy directly to tumor,
  typically through expanding metal tines within a
  small gauge insulated needle.

LeVeen probe
Before (left) and after (right)
treatment (courtesy of Brad Wood, MD, NIH CC)
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Overlapping Burns

• Large tumors can be treated with overlapping
  spherical zones
• Hard to visualize the overlapping areas
• Lack of real-time image guidance requires
  repeated insertions to hit the target lesion and
  establish sufficient margins

From Dodd, Soulen et al. 2000
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Project Overview

• Goal Develop an open source workstation for
  liver RFA planning and treatment based on IGSTK
  and Slicer.
• Specific aims
• Develop and evaluate semi-automatic segmentation
  techniques for the liver, liver vasculature, and
  liver tumors. Georgetown, BWH
• Develop a path planning module for evaluating
  alternative paths to the liver tumor and
  incorporating multiple overlapping placements as
  needed for larger tumors. George Washington
  University
• Integrate the two capabilities developed above
  along with electromagnetic tracking of the RFA
  probe to provide a complete software environment
  for liver tumor planning, visualization, and
  execution. Georgetown, BWH
• Validate the clinical feasibility of the system
  in a swine animal model. Georgetown

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Timeline
Proposed
Actual
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SegmentationGold Standard Database

• Collected approximately 50 CT liver images from
  Georgetown University Hospital
• Followed Health Insurance Portability and
  Accountability Act (HIPAA) rules for
  anonymization of data
• Medical student segmented 32 livers using
  ITK-SNAP under supervision of attending
  interventional radiologist
• Next step is to segment tumors

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Path Planning

• Pre-emptive goal programming approach based on
  integer programming techniques using a discrete
  set of data points representing the tumor
  (uniform sampling)
• Minimize needle insertions (trajectories),
  minimizes the number of punctures to the liver
  capsule, and the number of needle insertions.
• Minimizing Ablations Given needle trajectories.
• Minimizing Damage to Healthy Tissue

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Path Planning Status

• Currently implemented using commercial software
  Xpress-MP (Fair Issac dash optimization)
• Worked well in preliminary swine feasibility
  studies
• Now porting to open source Gnu Linear Programming
  (GLPK) package
• Initial results from porting are extremely slow
  compared to commercial package
• Requires further evaluation

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Integration

• Initial implementation started at IGT Project
  Week in December 2008 in Boston
• Tracking data is broadcast from IGSTK components
  using OpenIGTLink protocol
• Program resides in IGSTK sandbox and supports
  FLTK GUI and command line mode

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Integration (continued)

• Specify configuration using xml files
• Supports multiple tools and broadcasting data to
  multiple computers
• Supports the use of a Dynamic Reference Frame. If
  specified all broadcasted transformations will be
  relative to the DRF (DRF transformation is not
  sent)
• Will present at SPIE Medical Imaging 2009 in
  Orlando in February

lt?xml version"1.0" encoding"ISO-8859-1"?gt
lttracking_system type "polaris vicra"gt
ltrefresh_rategt 20 lt/refresh_rategt
ltserial_communicationgt ltcom_portgt4lt/com_por
tgt ltbaud_rategt115200lt/baud_rategt
ltdata_bitsgt8lt/data_bitsgt ltparitygtNlt/paritygt
ltstop_bitsgt1lt/stop_bitsgt
lthand_shakegt0lt/hand_shakegt
lt/serial_communicationgt lttool usage
"reference"gt ltnamegt large reference lt/namegt

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Next steps

• Goal is to create a Slicer3 workflow based
  interface for navigated RFA (Nav-RFA)
• Requirements document developed by Georgetown and
  sent to BWH
• Slicer will be configured with the following
  modules
• Data manage scene graph
• EM Segmenter potentially used for automatic
  segmentation (maybe not in
  the initial setup)
• Editor manual segmentation and modification of
  automated segmentation.
• Fiducials marking the fiducials.
• Linear registration fiducial based registration.
• OpenIGTLink tracking
• This will create a skeleton end to end workflow
  where we can fill in individual pieces and
  improve as we go

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Summary

• Goal is to develop an integrated system for RFA
  of liver tumors
• Progress is good but vigilance needs to continue
• Open source implementation of optimization is one
  concern