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Navigation in Robotic
Radiosurgery
Achim Schweikard
beam
Stereotactic Radiosurgery
Conventional Procedure
Stereotaxic Frame
Arc motion
Local Anesthesia
Concept
Image-Guidance
Camera A Camera B
BKS
LCS
Source B Source A
T
Robot System
Robot System
Tumors in the chest or abdomen move due to respiration
Respiratory Motion
Respriatory Motion
Safety Margin
Tumor
Beam
Robotic Arm
Robotic Arm
Volume of Sphere:
4/3 r3
Hysteresis
Previous Work
HD Kubo, BC Hill: Respiration gated radiotherapy treatment: a technical study. Phys. Med. Biol. 1996; 41: 83-91.
T Tada et. al.:Lung cancer: Intermittent radiation synchronized with respiratory motion. Radiology, 1998; 207:779-783.
MR Sonntag, ZW Lai: Characterization of respiratory motion for pediatric conformal 3D therapy. Med. Phys. 1996: 23: 1082.
Image-Guidance
Camera A Camera B
BKS
LCS
Source B Source A
T
Stereo X-Ray Camera System
Camera A Camera B
Gold fiducial
Infrared Tracking
Correlation
Correlation
DART
System Overview
Correlation external chest vs. external abdomen
Motion Table Phantom Study(Overall Accuracy)
Robot Tracking
Prediction
Phantom Study
First Patient Treatment
Measured Target Excursionvs. Correlation Error
Follow-up Study
Four months follow-up
Treatment
Synchrony
Major Challenges
Fiducial-less tracking
Implanting of Gold Fiducials
Respiration
Courtesy Paul Sellars, JHU
Fiducial-Less Tracking: Principle
Compute or acquire 4D CT
Principle
Compute or acquire 4D CT
Compute DRRs (2D Projections)
Principle
Compute or acquire 4D CT
Compute DRRs (2D Projections)
Live Shots (2D x-ray pair)
Principle
Compute or acquire 4D CT
Compute DRRs (2D Projections)
Live Shots (2D x-ray pair)
Find the DRR that best matches live shots
Principle
„Ground truth“
Principle
i.e. Tumor position with time stamp
Principle
Thus: same ground truth information as in fiducial-based tracking is available
Principle
Correlation + Prediction
real-time target position
Principle
CT-ScanInhalation
CT-ScanExhalation
IntermediateCT-Scan 1
IntermediateCT-Scan n...
„4D CT“
Best match determines respiratory state and therefore tumor position
Results Registration
Implementation Uses Intensity-based rigid registration 2D/3D Optimization with the Hooke-Jeeves Pattern-
Search Uses hardware-accelerated volume-rendering
based on texture mapping as DRR generation technique
Used metrics are correlation coefficient and mutual information
Results 7D RegistrationRegistration results with DRRs from synth. scan 40 % inhaled
0,00
0,20
0,40
0,60
0,80
1,00
1,20
1,40
1,60
1,80
CT Scans (real and synthetic)
MI
Val
ues
Results 7D RegistrationRegistration results with DRRs from original scan max. inhaled
0,00
0,20
0,40
0,60
0,80
1,00
1,20
CT Scans (real and synthetic)
MI
Val
ues
Results single 2D/3D Registration
Computing time
10 seconds per registration
Conclusion
Feasible w.r.t. computing time
Feasibility w.r.t accuracy and reliability not yet established
