na-mic national alliance for medical image computing an integrated system for image-guided...

NA-MICNational Alliance for Medical Image Computing http://na-mic.org

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

Kevin Cleary, Ziv Yaniv, Georgetown University

Noby Hata, Brigham and Women’s Hospital

Enrique Campos-Nanez, George Washington University

National Alliance for Medical Image Computing http://na-mic.org

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)


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


Project OverviewGoal: Develop an open source workstation for liver RFA planning and treatment

based on IGSTK and Slicer.

Specific aims:1. Develop and evaluate semi-automatic segmentation techniques for the

liver, liver vasculature, and liver tumors. [Georgetown, BWH]

2. 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]

3. 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]

4. Validate the clinical feasibility of the system in a swine animal model. [Georgetown]


Year Aim 1

Software architecture

Aim 2Segmentation

Aim 3Treatment planning

Aim 4Integration /

phantom study

Aim 5Animal studies

1 Requirementsdocument complete,

Prototype architecturecomplete

Ribs, liver, tumor,vasculature

- manual segmentation

First stage algorithms complete

2 Complete gold standard –

database segmentation

Second stage algorithms complete –

port to open source

3 Semi-automatic segmentation

Evaluate on 10 data sets

Integrated system complete

Later years

Year Aim 1

Software architecture

Aim 2Segmentation

Aim 3Treatment planning

Aim 4Integration / phantom

study

Aim 5Animal studies

1 Requirements document complete

Ribs, liver, tumor algorithms complete

First stage algorithms complete

2 Prototype architecture complete

Vasculature complete Second stage algorithms complete

3 Evaluate on 10 data sets

Evaluate on 10 data sets

Integrated system complete

Later years

Proposed:

Actual:

Timeline


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


Path Planning• Pre-emptive goal programming approach based on

integer programming techniques using a discrete set of data points representing the tumor (uniform sampling):

1. Minimize needle insertions (trajectories), minimizes the number of punctures to the liver capsule, and the number of needle insertions.

2. Minimizing Ablations Given needle trajectories.

3. Minimizing Damage to Healthy Tissue


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


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


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

<?xml version="1.0" encoding="ISO-8859-1"?> <tracking_system type = "polaris vicra">

<refresh_rate> 20 </refresh_rate>

<serial_communication> <com_port>4</com_port> <baud_rate>115200</baud_rate> <data_bits>8</data_bits> <parity>N</parity> <stop_bits>1</stop_bits> <hand_shake>0</hand_shake> </serial_communication>

<tool usage = "reference"> <name> large reference </name>

…


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


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

na-mic national alliance for medical image computing an integrated system for image-guided...

Documents