CE-Therapy: Patient Motion: Adaptive RTDosimetry based ITV (Margin = 0.1 ~ 0.4 *Excursion) 4D...
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Page 1 Adaptive Management of Patient Adaptive Management of Patient Motion in Radiotherapy Motion in Radiotherapy Di Yan, D.Sc. Di Yan, D.Sc. William Beaumont Hospitals & Research Institute William Beaumont Hospitals & Research Institute CE CE-Therapy: Patient Motion: Adaptive RT Therapy: Patient Motion: Adaptive RT I. To learn the options of 4D planning II. To understand the sensitivity of 4D planning on motion uncertainties, as well as the methods for uncertainty management III. To learn the key components of adaptive treatment process and their functions Educational Objectives I. Geometry based and dosimetry based 4D planning for motion compensation II. Motion uncertainty and its dosimetric effect on 4D planning. The management options III. Key components and functions of adaptive treatment process Outlines
Transcript of CE-Therapy: Patient Motion: Adaptive RTDosimetry based ITV (Margin = 0.1 ~ 0.4 *Excursion) 4D...
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Adaptive Management of Patient Adaptive Management of Patient Motion in RadiotherapyMotion in Radiotherapy
Di Yan, D.Sc.Di Yan, D.Sc.William Beaumont Hospitals & Research InstituteWilliam Beaumont Hospitals & Research Institute
CECE--Therapy: Patient Motion: Adaptive RTTherapy: Patient Motion: Adaptive RT
I. To learn the options of 4D planning
II. To understand the sensitivity of 4D planning on motion uncertainties, as well as the methods for uncertainty management
III. To learn the key components of adaptive treatment process and their functions
Educational Objectives
I. Geometry based and dosimetry based 4D planning for motion compensation
II. Motion uncertainty and its dosimetric effect on 4D planning. The management options
III. Key components and functions of adaptive treatment process
Outlines
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4D Planning: Geometry Based ITV Construction
Patient specific target for motion compensation constructed using target motion excursion (Margin = 0.5*Excursion)
¤ determined using fluoroscopic image (Balter JM, et al. Med Phys 1994, 21:913)
¤ 4D CT or directly from a MPI image (Underberg Rene, et al. IJROBP 2005, 63:253-60)
Purely geometric compensation, no dose distribution is used in the margin designOverestimate the target margins significantly
Motion Effect in Dose Distribution
Motion blur effect of dose distribution has been demonstrated long time ago using the convolution approach, spatially invariant dose distribution + motion pdf (Leong J. PMB 1987, 32:327-37)
In reality, one should also consider the effect of patient internal density variation & the leave interplay effect if dose is delivered using the MLC based IMRT (Chui CS, et al. Med Phys 2003, 30:1736-46, & Bortfeld T, et al. Med Phys 2002, 47:2203-20)
4D Dose SummationTissue density distribution
VoI subvolume position Machine output
( ) udupdfxdxpdfuxD Mvvvvvvv ⋅⋅⋅⋅= ∫ ∫ )()(),,( ρ Apply the mean CT
xdxpdfuxD cMvvvvv ⋅⋅= ∫ )(),,( ρ Constant output
( ) dtuxdtdDvD
n
iTt ttvt
i
⋅= ∑ ∫=
∈1
)( ,,)( vvv ρ In time domain
( ) udupdfdxdxpdfuxD vvvvvvvvv ⋅⋅⋅⋅⋅= ∫ ∫ )(),(),,( ρρρ In freq domain
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4D Planning: Dose Based ITV Construction
Dose convolution with motion pdf measured at treatment simulationPerform the margin calculation iteratively by adjusting beam aperture
Courtesy Dr Liang from WBH
Effect of The Prescription Dose
Target margin is strongly dependent on the prescription dose point
Therapeutic ratio could be future increased by reducing treatment beam aperture & allowing higher heterogeneity dose in the target (Engelsman M, et al. IJROBP 2001, 51:1290-8)
85% of the iso
M1 = 7.7 mm
3 cm
70% of the iso
M1 = 4.1 mm
3 cm
Inter-patient Heterogeneity
M1 = 7.5 mm M2 = 5.6 mm
M1 = 2.9 mm M2 = 2.6 mm
2.5 cm
Target margin depends on the dose distribution which greatly relies on the tumor location
With respect to the prescription dose of 75% ~ 95%, Target Margin = 0.1 ~ 0.4*Excursion
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4D Planning: 4D Inverse Planning
Similar to 3D Inverse Planning, but Include the motionpdf from m-phase 4D CT in the 4D dose summation (Alexei Trofimov, et al. PMB 2005, 2779-98)
∫ ⋅⋅⋅= ρρρ vvvvvvv dxdxpdfuxDvD cv ),(),,()( )(
muxDuxD cmmc ),,(),,( 11vvvvvv ρρ +⋅⋅⋅+
=
( )VoIsvuvDFu
c
c
Opt ∈,),(}{
v
v
Zhang P, et al. submitted to IJROBP
4D Planning Methods for Motion CompensationGeometry based ITV (Margin = 0.5*Excursion), Dosimetry based ITV (Margin = 0.1 ~ 0.4*Excursion)
4D inverse planning (Margin = 2 mm)
All 4D planning methods perform treatment planning adaptable to patient motion measured at the pre-treatment simulation alone, but not those during the treatment delivery
4D Planning Methods: Summary
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Clinical Observations
Significant inter-treatment baseline variation & breathing pattern (cycle to cycle) variation (in time domain), but relatively small variation in motion standard deviation (in frequency domain). (Geoff Hugo, et al. Radiother Oncol 2006, 78:326-331. Jan-Jakob Sonke, et al. IJROBP 2008, 70:590-8)
Intra-treatment baseline drift is limited within small group (5%~10%) of patients
Dose response related variations (volume shrinkage, baseline position change, relative distance change, et al)could be significant after the first few weeks of treatment resulting significant dose variation in normal organs
Tx 1
Tx 2
Tx n
…
Uncertainties of Motion pdfVariations between the reference motion pdfr and those during the treatment deliveries, pdftx
SI D
ispl
acem
ent
µ
Systemic Error, µ , for the entire treatment
1µ 2µ nµ
Systemic error, µk , for each treatment
Uncertainties of Motion pdfUncertainty depends on the motion management
0 %
5 %
1 0 %
1 5 %
2 0 %
2 5 %
-2 -1 .5 -1 -0 .5 0 0 .5 1 1 .5 2 2 .5S I D ire c t io n (c m )
Mot
ion
R e fe re n c eM e a n C o rre c tio nB o n e C o rre c t io nN o C o rre c tio n
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-12%
-10%
-8%
-6%
-4%
-2%
0%
2%
7.2
Target (SI Direction)
∆D
ose
MeanCorrectionBoneCorrectionNoCorrection 0.26.2
2.00.12.00.0(mm)(mm)
−∆∆ σµ
Large Motion pdf Variation
0 %
5 %
1 0 %
1 5 %
2 0 %
2 5 %
-2 -1 0 1 2 3
S I D irc tio n io n (c m )
Mot
ion
R e fe re n c eM e a n C o rre c tio nB o n e C o rre c tio nN o C o rre c tio n
-40%
-35%
-30%
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
7.2 7.7 8.2 8.7 9.2 9.7
Target SI Directin
∆D
ose
MeanCorrection
BoneCorrection
NoCorrection 1.00.125.00.102.00.0(mm)(mm)
−∆∆ σµ
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Motion Uncertainty Management
Robust Planning (Timothy Chan, et al. PMB 2006, 51:2567-83)
¤ include the bounds of motion uncertainties (previously determined) in the pre-treatment planning
¤ If motion variations are within the bounds, the treatment plan needs no modification
¤ However, the treated volume can be quite large, if generic variation, specifically the systematic variation, is considered
Cha
nge
in T
he M
ean
Tar
get P
ositi
on (m
m)
-2 0
-1 5
-1 0
-5
0
5
1 0
1 5
2 0
Se ssio n 1 Sessio n 2 Se ssio n 3 S essio n 4 S essio n 5 Se ssio n 6 Se ssio n 7 Sessio n 8
P a tien t 1 P a tien t 2P a tien t 3 P a tien t 4P a tien t 5 P a tien t 6P a tien t 7 P a tien t 8P a tien t 9 P a tien t 1 0
G. Hugo, Radiother Oncol, 2006, 78:326-331
Clinical Observation: Baseline Variation
σ = 6.7 mm
Cha
nge
in st
anda
rd d
evia
tion
(mm
)
-2 0
-1 5
-1 0
-5
0
5
1 0
1 5
2 0
S e ssio n 1 S essio n 2 S essio n 3 S essio n 4 S e ss io n 5 S ess io n 6 S ess io n 7 S e ssio n 8
P a tien t 1 P a tien t 2P a tien t 3 P a tien t 4P a tien t 5 P a tien t 6P a tien t 7 P a tien t 8P a tien t 9 P a tien t 1 0
G. Hugo, Radiother Oncol, 2006, 78:326-331
Clinical Observation: SD Variation
σ = 1.7 mm
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Motion Uncertainty Management
Adaptive Management¤ Modify the treatment plan to cope with the patient
specific variations while the treatment is running
¤ Identify characteristics of individual motion to provide a proper decision for baseline correction or adaptive planning modification
¤ Dose feedback to support the adaptive planning evaluation & modification
Model Identification Adaptive Control (MIAC) Radiotherapy Process
TREATMENTDELIVERY SYSTEM
ADAPTIVE PLANNING
Goals
MOTIONIDENTIFICATION
ADJUSTMENTMECHANISM
Plan
Delivered Dose feedback
Adaptive Motion Management
Motion Identification & Management¤ Baseline Variation – detected and corrected
using onboard CBCT directly (G. Hugo, IJROBP 2007, 69:1634-41)
¤ The pdf Pattern Variation – detected using fluoroscopic image, CB projection images or a surrogate such as surface motion detection
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-12
-8
-4
0
4
8
120 5 10 15 20 25 30
Time (second)
Sup
.<--
- Tum
or P
ositi
on (m
m) -
-->I
nf.
Ref 0.0 (4.5)
Port -3.5 (4.0) 0%
2%
4%
6%
8%
10%
-10-50510
Pro
babi
lity Ref 0.0 (4.5)
Port -3.5(4.0)
Ref or DRFRef or DRF kV FluorokV Fluoro
Online Motion Verification (CB Fluoro Imaging)
Courtesy Dr Liang from WBH
CB Projection
Online Motion Verification (CB Projection Imaging)
Courtesy Dr Hugo from WBH
Adaptive Motion Management
Adaptive Planning Modification ¤ Dose feedback + 4D robust inverse planning¤ Include all pre-measured pdfs in the planning
∫ ⋅⋅⋅⋅−+
=
− ρρρ vvvvvvv
v
dxdxpdfuxdkn
vDuvD
kcv
kcn
),(),,()(
)(),(
1)(
( )VoIsvuvDFu
cn
c
Opt ∈,),(}{
v
v
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The most important issue in managing patient motion is to eliminate the baseline variation
Daily CBCT imaging localization & correction could be the most efficient method to perform this task
Intra-treatment motion pdf variation can be detected using CB fluoro, CB projection imaging or (maybe) a surface surrogate. This detection is used to guide the selection of the adjustments
Adaptive planning modification = Dose Feedback + 4D Robust Inverse Planning
Adaptive Motion Management: Summary
