successes and challenges in effectors and scanner control

Brigham and Women’s Hospital Image Guided Therapy Program


Successes and Challenges in Effectors and Scanner Control

Nobuhiko Hata, PhD

Brigham and Women’s Hospital


Issues

• Basic functions for Image Guided Therapy (visualization, image I/O, patient-to-image registration) are relatively easy to implement (thanks to VTK and ITK)

• Challenge 1: Develop and apply new medical image processing methods to enable new therapy options

• Challenge 2: Provide meeting point for robotics, medical image processing, and bio-physics


Objective

• Open source software 3D Slicer• Modular architecture for multiple IGT applic

ations• Integration to FDA-approved commercial sy

stems• Issues


Slicer

• 1996: Carl-Fredrick Westin (newly hired post-doc) and Noby Hata (SPL grad student) developed prototype using VTK-beta

• 1997: First MR-guided neurosurgery• Dave Gering (MIT grad student) re-design the soft

ware• Lauren O'Donnell (1999-), Steve Pieper (2001-)• Pis: Ron Kikinis, Ferenc Jolesz, Eric Grimson, Will

iam Wells III


Slicer 97


Multiple applications

• Software design to maximize function commonalities among applications– Brain (biopsy, craniotomy, NdYAG laser ablation)– Prostate (brachytherapy, biopsy)– Liver and kidney (Microwave, laser ablation)– Endoscopy (neuroendoscopy)


Neurosurgery

• DICOM image transfer• Visualization• Navigation

• Image registration


“Multi-modality” MRIg Surgery

Registration is the key-enabling technology


ACADEMIC RADIOLOGY 10 (12): 1442-1449 DEC 2003

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MR-guided Liver ablation Therapy


MRI-guided Thermal Therapy

•Comput Med Imaging Graph

•Image display

•DICOM transfer

•Thermal mapping

(modifying fMRI module)


MRI-guided prostate therapy

•DICOM image transfer•Rigid and non-rigid image registration•Planning•Scanner control

Radiology 220(1), 263-268, 2001


Slicer with Hitachi scanner

•DICOM image transfer•Patient-to-image registration•Navigation•Tumor segmentation for resection monitoring


Pituitary tumor in horizontal open-MRI

3D Slicer (Freeware)3D Slicer (Freeware)Navigation tool for image-guided therapyNavigation tool for image-guided therapy


Intraoperative Tumor Segmentation

• ITK-VTK-Slicer• Fuzzy connectivity• 30+ cases at 0.3T

Hitachi Horizontal gap scanner

Hata N, Muragaki Y, Inomata T, Maruyama T, Iseki H, Hori T, Dohi T. Intraoperative tumor segmentation and volume measurement in MRI-guided glioma surgery for tumor resection rate control. Acad Radiol. 2005;12(1):116-22.


Linking commercial navigation and research software

• 3D Slicer– Segmentation– Pre-Op to Intra-Op image re

gistration– Navigation

• Toshiba navigation (pre-commercial)

• TCP/IP peer-to-peer connection– Patient-to-image registratio

n result– Tracking data


Slicer for Surgical Robot

•Robot as tracking device


Slicer with Hitachi scanner


System Integration to Signa/SP• Off-the-shelf system + 3D Slicer

TPS MRT Workstation

BIT-3

10 Mbps

Image Transfer0.5fps

Image Transfer

0.5fpsSlicer


System Integration to Signa/SP• (Pre-) MR Slicer

TPS MRT Workstation

BIT-3

100 Mbps

Echo transfer128fps

Echo Transfer

128fpsSlierImage Transfer

32fpsRecon


• GE Medical Systems Signa Horizon LX System– Host

• SGI Workstation / MIPS Based Processor• IRIS Operating System (SGI)

– Transceiver, Processing and Storage (TPS)• VME / Motorola Based Processor• VxWorks (Wind River)

TPS

Host

Scanner


• Reconstruction WS– CPU: Intel Pentium4 2.8 GHz (i850 Chipset)– Memory: 512MB (PC1066 RIMM)– Graphics: nVIDIA GeForce4 MX440– OS: RedHat Linux 7.3, Kernel 2.4.18 with nVIDIA Graphics Driver

• Software– Real-time display of echo and k-space– Real-time image reconstruction– Navigator-echo based matching– Host control


MR Image reconstruction(+motion tracking)

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Slicer as Interface

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IGT software as an integration platformIGT software as an integration platform

RobotRobot

Pre-operative Pre-operative Diagnostic Diagnostic

ImagingImaging

ImageImageProcessingProcessing

Intra-Intra-operative operative imagingimaging

ImageImageProcessingProcessing

RegistrationRegistration

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serv

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Tracking probeTracking probe

Navig

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Navig

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Navig

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PhysicianPhysician

TreatmentTreatment PatientPatient


Issues

• Basic functions for Image Guided Therapy (visualization, image I/O, patient-to-image registration) are relatively easy to implement (thanks to VTK and ITK)

• Challenge 1: Develop and apply medical image processing technology to enable new therapy options

• Challenge 2: Provide meeting point for robotics, medical image processing, and bio-physics– Do not think IGT software as free navigation system– Think IGT software as an integration platform TO ENABLE NEW TH

ERAPY

successes and challenges in effectors and scanner control

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