Models for breathing trajectory variations
Models for breathingtrajectory variationsGregory C. SharpMassachusetts General HospitalFeb 19, 2010
MASSACHUSETTSGENERAL HOSPITALRADIATION ONCOLOGY
1Problem statementHow should we incorporate breathing trajectory variations into 4-D planning ?
2Problem statementPrimary trajectory is volumetric4D-CTTrajectory variations are non-volumetricImplanted fiducialsRadiography and fluoroscopyElectromagnetic transpondersPopulation statistics
3OutlineDosimetry modelMotion modelPopulation model
4Dosimetry modelProblem statement:How to compute dose to a moving target if we dont have a CT?
5Dosimetry modelAnswer: Geometric dose modelDose is fixed in spaceTarget moves within dose cloud
6Dosimetry model
7Dosimetry model
8Dosimetry model
9Dosimetry modelGeometric dose model doesnt work for protons
10Dosimetry modelBecause of range effects
11
Dosimetry modelModified geometric dose modelUse radiological depth instead of position
12Dosimetry modelRadiological depth of anatomic points are assumed constant
13Dosimetry modelModified geometric modelTreat each beam separatelyProject 3D trajectory to 2DCould be used for photons as well
14Motion modelPrimary trajectory: from 4D-CT
15Motion modelTrajectory variations: position change / time
16Either change in exhale position, or change in COM positionNote: no change in motion amplitudeMotion modelMotion model = primary + variations
17Motion modelVariations have a probability distribution
18Motion modelIntegration over known variation curve yields specific histogram of displacements
19Motion model
20Motion model
21Motion modelTrajectory variation histogram is applied to each phase separately
22Motion model
23Motion modelCaveats:No interplay effect (beams delivered in sequence)Amplitude variations neglected
24Population modelData sourcesHokkaido RTRTIRIS radiographicIRIS fluoro burstSBRT CBCT (pre/post)
25Population model (1/4)Hokkaido RTRT~20 lung cancer patientsHypofractionated (early stage)Orthogonal stereo fluoroscopyGated treatmentMixed motion amplitudes (up to 30 mm)
26Population model (1/4)
27Population model (1/4)
28Population model (1/4)
29Population model (1/4)
* Take with a grain of saltDrift Magnitude
30Population model (2/4)IRIS Radiographs10 lung cancer patientsStandard fractionation (esp. stage III)Orthogonal gated radiographs (exhale)Gated RTLarge motion amplitudes (> 10 mm motion)
31
Maximum of Diaphragm
Vertebral landmarkLateral View
32
33Population model (2/4)This study Median s = 0.55 cmYorke (JACMP 2005) m = 0.63 cm Mean s = 0.42 cm
34
35Population model (2/4)
* Take with a grain of saltDrift Magnitude
36Population model (3/4)IRIS Fluoro4 liver cancer patientsOrthogonal fluoroscopyGated RTLarge motion amplitudes (> 10 mm)
37
38
Clip 1Clip 2Clip 3RPM
39
SI = 5 mmAP = 2 mmLR = 2 mm90 secs20 secs80 secs4 minutesCLIP #2: Exhale baseline drift
40Population model (3/4)
* Take with a grain of saltDrift Magnitude
41Population model (4/4)SBRT CBCT~15 lung cancer patientsHypofractionated (early stage)Pre-tx and post-tx CBCTSBRTMixed motion amplitudes (range unknown)
42Population model
* Take with a grain of saltDrift Magnitude
43SummaryDosimetry modelGeometric modelModified geometric modelMotion modelMotion = primary + variationsMotion variations map to dose variationPopulation modelWIP
44END OF SLIDE SHOW45Motion modelDosimetry can be either probabilistic or deterministic
+
46Chart24.29353.56495.19185.49584.36184.36215.64755.2559.54973.84018.7447.08325.90016.47886.16337.06215.1625.42747.28746.9631
APLateralPatient NumberStandard Deviation (mm)Standard Deviation Graph
Sheet1Patient#StandardDeviation AP14.29353.564925.19185.495834.36184.362145.64755.25559.54973.840168.7447.083275.90016.478886.16337.062195.1625.4274107.28746.9631
Sheet100000000000000000000
APLateralPatient NumberStandard Deviation (mm)Standard Deviation Graph
Sheet2
Sheet3
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Day of TreatmentDisplacement Between Diaphragm and Bone (mm)Patient 1, AP View
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