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Published byLillian Lively Modified about 1 year ago

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Models for breathing trajectory variations Gregory C. Sharp Massachusetts General Hospital Feb 19, 2010 MASSACHUSETTS GENERAL HOSPITAL RADIATION ONCOLOGY

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Problem statement How should we incorporate breathing trajectory variations into 4-D planning ?

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Problem statement Primary trajectory is volumetric –4D-CT Trajectory variations are non-volumetric –Implanted fiducials –Radiography and fluoroscopy –Electromagnetic transponders –Population statistics

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Outline Dosimetry model Motion model Population model

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Dosimetry model Problem statement: How to compute dose to a moving target if we don’t have a CT?

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Dosimetry model Answer: “Geometric dose model” Dose is fixed in space Target moves within dose cloud

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Dosimetry model

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Geometric dose model doesn’t work for protons

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Dosimetry model Because of range effects

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Dosimetry model Modified geometric dose model –Use radiological depth instead of position

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Dosimetry model Radiological depth of anatomic points are assumed constant

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Dosimetry model Modified geometric model –Treat each beam separately –Project 3D trajectory to 2D –Could be used for photons as well

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Motion model Primary trajectory: from 4D-CT

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Motion model Trajectory variations: position change / time

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Motion model Motion model = primary + variations

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Motion model Variations have a probability distribution

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Motion model Integration over known variation curve yields specific histogram of displacements

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Motion model

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Trajectory variation histogram is applied to each phase separately

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Motion model

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Caveats: –No “interplay” effect (beams delivered in sequence) –Amplitude variations neglected

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Population model Data sources –Hokkaido RTRT –IRIS radiographic –IRIS fluoro burst –SBRT CBCT (pre/post)

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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)

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Population model (1/4)

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* Take with a grain of salt Drift Magnitude

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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)

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Maximum of Diaphragm Vertebral landmark Lateral View

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Population model (2/4) This study – Median = 0.55 cm Yorke (JACMP ‘2005) – = 0.63 cm – Mean = 0.42 cm

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Population model (2/4) * Take with a grain of salt Drift Magnitude

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Population model (3/4) IRIS Fluoro –4 liver cancer patients –Orthogonal fluoroscopy –Gated RT –Large motion amplitudes (> 10 mm)

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Clip 1 Clip 2 Clip 3 RPM

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SI = 5 mm AP = 2 mm LR = 2 mm 90 secs20 secs80 secs 4 minutes CLIP #2: Exhale baseline drift

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Population model (3/4) * Take with a grain of salt Drift Magnitude

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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)

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Population model * Take with a grain of salt Drift Magnitude

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Summary Dosimetry model –Geometric model –Modified geometric model Motion model –Motion = primary + variations –Motion variations map to dose variation Population model –WIP

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END OF SLIDE SHOW

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Motion model Dosimetry can be either probabilistic or deterministic +

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