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Models for breathing trajectory variations Gregory C. Sharp Massachusetts General Hospital Feb 19, 2010 MASSACHUSETTS GENERAL HOSPITAL RADIATION ONCOLOGY
Problem statement How should we incorporate breathing trajectory variations into 4-D planning ?
Problem statement Primary trajectory is volumetric –4D-CT Trajectory variations are non-volumetric –Implanted fiducials –Radiography and fluoroscopy –Electromagnetic transponders –Population statistics
Outline Dosimetry model Motion model Population model
Dosimetry model Problem statement: How to compute dose to a moving target if we don’t have a CT?
Dosimetry model Answer: “Geometric dose model” Dose is fixed in space Target moves within dose cloud
Geometric dose model doesn’t work for protons
Dosimetry model Because of range effects
Dosimetry model Modified geometric dose model –Use radiological depth instead of position
Dosimetry model Radiological depth of anatomic points are assumed constant
Dosimetry model Modified geometric model –Treat each beam separately –Project 3D trajectory to 2D –Could be used for photons as well
Motion model Primary trajectory: from 4D-CT
Motion model Trajectory variations: position change / time
Motion model Motion model = primary + variations
Motion model Variations have a probability distribution
Motion model Integration over known variation curve yields specific histogram of displacements
Trajectory variation histogram is applied to each phase separately
Caveats: –No “interplay” effect (beams delivered in sequence) –Amplitude variations neglected
Population model Data sources –Hokkaido RTRT –IRIS radiographic –IRIS fluoro burst –SBRT CBCT (pre/post)
Population model (1/4) Hokkaido RTRT –~20 lung cancer patients –Hypofractionated (early stage) –Orthogonal stereo fluoroscopy –Gated treatment –Mixed motion amplitudes (up to 30 mm)
Population model (1/4)
* Take with a grain of salt Drift Magnitude
Population model (2/4) IRIS Radiographs –10 lung cancer patients –Standard fractionation (esp. stage III) –Orthogonal gated radiographs (exhale) –Gated RT –Large motion amplitudes (> 10 mm motion)
Maximum of Diaphragm Vertebral landmark Lateral View
Population model (2/4) This study – Median = 0.55 cm Yorke (JACMP ‘2005) – = 0.63 cm – Mean = 0.42 cm
Population model (2/4) * Take with a grain of salt Drift Magnitude
Population model (3/4) IRIS Fluoro –4 liver cancer patients –Orthogonal fluoroscopy –Gated RT –Large motion amplitudes (> 10 mm)
Clip 1 Clip 2 Clip 3 RPM
SI = 5 mm AP = 2 mm LR = 2 mm 90 secs20 secs80 secs 4 minutes CLIP #2: Exhale baseline drift
Population model (3/4) * Take with a grain of salt Drift Magnitude
Population model (4/4) SBRT CBCT –~15 lung cancer patients –Hypofractionated (early stage) –Pre-tx and post-tx CBCT –SBRT –Mixed motion amplitudes (range unknown)
Population model * Take with a grain of salt Drift Magnitude
Summary Dosimetry model –Geometric model –Modified geometric model Motion model –Motion = primary + variations –Motion variations map to dose variation Population model –WIP
END OF SLIDE SHOW
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