18th of March, 2017
Recent Trend of IMRT
Department of Radiation Oncology
Seoul National University Hospital
Jong Min Park, Ph.D.
[email protected]
IMRT and VMAT
Modulation of photon beam
• Key feature of VMAT (or IMRT)  photon beam modulation
– IMRT  by modulation of MLC positions
– VMAT  by simultaneous modulation of MLC positions, gantry
rotation speed and MU
• High modulation  large diff. btw. plan and delivery
– Increase of mechanical uncertainty
– Increase of small or irregular fields  inaccurate calculation of
dose distributions in the TPS
• Therefore, pre-treatment QA  labor intensive
• Modulation index evaluate the “degree of photon beam
modulation”
Pre-treatment QA vs. MI
• Pre-treatment QA  labor intensive
• MI could get rid of highly-modulated plan in
planning level  sparing of resources in the clinic
Previous MIs for VMAT
•
MCSv by Masi et al. (modulation complexity score for VMAT, 2013)
•
LTMCS by Masi et al. (leaf-travel modulation complexity score, 2013)
•
MI by Li and Xing (2013)
•
MI by Park et al. (2015)
– Masi L, Doro R, Favuzza V et al. Impact of plan parameters on the dosimetric
accuracy of volumetric modulated arc therapy Med Phys 40, 071718, 2013
– Masi L, Doro R, Favuzza V et al. Impact of plan parameters on the dosimetric
accuracy of volumetric modulated arc therapy Med Phys 40, 071718, 2013
– Li R and Xing L. An adaptive planning strategy for station parameter optimized
radiation therapy (SPORT): Segmentally boosted VMAT Med Phys 40 050701, 2013
– JM Park, SY Park and H Kim. Modulation index for VMAT considering both
mechanical and dose calculation uncertainties Phys Med Biol 60, 7101-7125, 2015
MCS by McNiven (2010)
MCS by McNiven (cont’d)
•
•
•
•
MCS evaluates
–
Segment shape, area, weight
–
–
–
Only evaluate with N (the number of open leaves constituting the beam)
pos = coordinates of the leaf positions
posmax = <max(posN∈n) – min(posN∈n)>leaf bank
–
𝐿𝑆𝑉𝑠𝑒𝑔𝑚𝑒𝑛𝑡 =<
LSV (Leaf Sequence Variability)
𝑁×𝑝𝑜𝑠𝑚𝑎𝑥
>𝑙𝑒𝑓𝑡 𝑏𝑎𝑛𝑘 ×<
𝑁 (𝑝𝑜𝑠
𝑚𝑎𝑥 −(𝑝𝑜𝑠𝑛 −𝑝𝑜𝑠𝑛+1 )
𝑛=1
𝑁×𝑝𝑜𝑠𝑚𝑎𝑥
AAV (Aperture Area Variability)
–
A = the number of leaves in the leaf bank
–
𝐴𝐴𝑉𝑠𝑒𝑔𝑚𝑒𝑛𝑡 =
𝐴 <𝑝𝑜𝑠 >
𝑎 𝑙𝑒𝑓𝑡 𝑏𝑎𝑛𝑘 −<𝑝𝑜𝑠𝑎 >𝑟𝑖𝑔ℎ𝑡 𝑏𝑎𝑛𝑘
𝑎=1
𝐴 <max(𝑝𝑜𝑠 )>
𝑎 𝑙𝑒𝑓𝑡 𝑏𝑎𝑛𝑘∈𝑏𝑒𝑎𝑚 −<max(𝑝𝑜𝑠𝑎 )>𝑟𝑖𝑔ℎ𝑡 𝑏𝑎𝑛𝑘∈𝑏𝑒𝑎𝑚
𝑎=1
MCS (Modulation Complexity Score)
–
𝑀𝐶𝑆𝑏𝑒𝑎𝑚 =
•
–
𝐼
𝑖=1 𝐴𝐴𝑉𝑠𝑒𝑔𝑚𝑒𝑛𝑡 𝑖
× 𝐿𝑆𝑉𝑠𝑒𝑔𝑚𝑒𝑛𝑡 𝑖 ×
I = number of segments in the beam
𝑀𝐶𝑆𝑝𝑙𝑎𝑛 =
•
•
𝑁 (𝑝𝑜𝑠
𝑚𝑎𝑥 −(𝑝𝑜𝑠𝑛 −𝑝𝑜𝑠𝑛+1 )
𝑛=1
𝐽
𝑗=1 𝑀𝐶𝑆𝑏𝑒𝑎𝑚 𝑗
×
𝑀𝑈𝑏𝑒𝑎𝑚 𝑗
𝑀𝑈𝑝𝑙𝑎𝑛
J = number of beams in the total plan
No modulation = 1, extreme modulation = 0
𝑀𝑈𝑠𝑒𝑔𝑚𝑒𝑛𝑡 𝑖
𝑀𝑈𝑏𝑒𝑎𝑚
>𝑟𝑖𝑔ℎ𝑡 𝑏𝑎𝑛𝑘
MCS Values
Gamma passing rate vs. MCS
Evaluation of VMAT Modulation with LT,
MCSv, MU, LTMCS by Masi (2013)
Evaluation of VMAT Modulation with LT,
MCSv, MU, LTMCS by Masi (cont’d)
• According to the modulation degree and QA results,
authors are suggesting finer CP angular spacing
• LT (Leaf Travel)
– For each leaf, the entire travel over the VMAT arc and
averaged over all in-field moving leaves
• MCSv
– MCS by CP rather than segment
• LTMCS
– LTi = (1000-LT)/1000 (1000 mm as maximum travel)
– LTMCS = LTi ✕ MCSv
MCSv
• 𝐿𝑆𝑉𝑐𝑝 =
𝑁−1
𝑛=1
𝑁−1
𝑛=1
𝑝𝑜𝑠𝑚𝑎𝑥 − 𝑝𝑜𝑠𝑛 −𝑝𝑜𝑠𝑛+1
(𝑁−1)×𝑝𝑜𝑠𝑚𝑎𝑥
𝑝𝑜𝑠𝑚𝑎𝑥 − 𝑝𝑜𝑠𝑛 −𝑝𝑜𝑠𝑛+1
(𝑁−1)×𝑝𝑜𝑠𝑚𝑎𝑥
• 𝐴𝐴𝑉𝑐𝑝 =
• 𝑀𝐶𝑆𝑎𝑟𝑐 =
×
𝑙𝑒𝑓𝑡𝑏𝑎𝑛𝑘
𝑟𝑖𝑔ℎ𝑡𝑏𝑎𝑛𝑘
𝐴
𝑎=1
𝑝𝑜𝑠𝑎 𝑙𝑒𝑓𝑡𝑏𝑎𝑛𝑘 − 𝑝𝑜𝑠𝑎 𝑟𝑖𝑔ℎ𝑡𝑏𝑎𝑛𝑘
𝐴
𝑎=1 max(𝑝𝑜𝑠𝑎 ) 𝑙𝑒𝑓𝑡𝑏𝑎𝑛𝑘∈𝑎𝑟𝑐 − max(𝑝𝑜𝑠𝑎 ) 𝑟𝑖𝑔ℎ𝑡𝑏𝑎𝑛𝑘∈𝑎𝑟𝑐
𝐼−1
𝑖=1
𝐴𝐴𝑉𝑐𝑝𝑖 +𝐴𝐴𝑉𝑐𝑝𝑖+1
2
• High modulation  MCSv = 0
• Low modulation  MCSv =1
×
𝐿𝑆𝑉𝑐𝑝𝑖 +𝐿𝑆𝑉𝑐𝑝𝑖+1
2
×
𝑀𝑈𝑐𝑝𝑖,𝑖+1
𝑀𝑈𝑎𝑟𝑐
LTMCS
• Entire travle =
𝑁
𝑛=1
• LT =
𝐼
𝑖=1
𝑝𝑜𝑠𝑛,𝑖 −𝑝𝑜𝑠𝑛,𝑖+1 𝑙𝑒𝑓𝑡𝑏𝑎𝑛𝑘 + 𝑝𝑜𝑠𝑛,𝑖 −𝑝𝑜𝑠𝑛,𝑖+1 𝑟𝑖𝑔ℎ𝑡𝑏𝑎𝑛𝑘
2∙𝑁
(1000−𝐸𝑛𝑡𝑖𝑟𝑒 𝑡𝑟𝑎𝑣𝑙𝑒)
1000
• LTMCS = LT × 𝑀𝐶𝑆𝑎𝑟𝑐
• High modulation  LTMCS = 0
• Low modulation  LTMCS =1
Gamma passing rate vs. indicators
Correlations
MI by Li and Xing (2013)
MI by Li and Xing
• MI s =
𝑘=−𝐾…
𝐾,𝑘≠0
60
𝑖=1
𝑥𝑖𝐴 𝑠 − 𝑥𝑖𝐴 (𝑠 + 𝑘) + 𝑥𝑖𝐵 𝑠 − 𝑥𝑖𝐵 (𝑠 +
SPORT
SPORT with MI
HN case
Liver and prostate case
Dose-rate variation on RA by
Nicolini (2010)
Dose-rate variation on RA by
Nicolini (cont’d)
• Dose rate vs. modulation degree
– Modulation degree evaluation
• Mean aperture/CP
• MU/fraction
• BOT
• Dose rate vs. Delivery accuracy
– Delivery accuracy evaluation
•
•
•
•
•
MU SD
% dose SD
Δ gantry angle
MLC mean RMS
MLC max RMS
• Dose rate vs. 2D QA
• Dose rate vs. Plan quality
Results
QA Results
• Conclusion: RA is robust
MIt
• MIt (MItotal)
– Analyze the variations of MLC speeds and
accelerations, gantry speeds and dose rates
• Focused on the speed and acceleration
variations
• Designed by adopting z(f) of MI by Webb S
– Webb S Use of a quantitative index of beam modulation to characterize
dose conformality: illustration by a comparison of full beamlet IMRT, fewsegment IMRT (fsIMRT) and conformal unmodulated radiotherapy Phys
Med Biol 2013;48:2051-62
MIt (cont’d)
•
𝐺𝑆𝑖 =
𝐺𝑎𝑛𝑡𝑟𝑦 𝑎𝑛𝑔𝑙𝑒𝑖 −𝐺𝑎𝑛𝑡𝑟𝑦 𝑎𝑛𝑔𝑙𝑒𝑖+1
𝑇𝑖𝑚𝑒𝑖
•
𝐷𝑅𝑖 =
𝑀𝑈𝑖 −𝑀𝑈𝑖+1
𝑇𝑖𝑚𝑒𝑖
•
𝐺𝐴𝑖 = 𝐺𝑆𝑖 − 𝐺𝑆𝑖+1
•
𝐷𝑅𝑉𝑖 = 𝐷𝑅𝑖 − 𝐷𝑅𝑖+1
•
𝑊𝐺𝐴,𝑖+1 =
𝛽
𝐺𝐴
− 𝛾𝑖
1+(𝛽−1)∙𝑒
– β = a constant which determines the range of WGA,i (in this study, β = 2, thereby WGA,i
could have a value from 1 to 2)
– γ = a constant which determines the speed of convergence to the maximum value of
WGA,i (γ = 2 in this study)
•
𝑊𝑀𝑈,𝑖+1 =
𝛽
𝐷𝑅𝑉𝑖
1+(𝛽−1)∙𝑒 𝛾
MIt (cont’d)
•
𝑀𝐿𝐶 𝑠𝑝𝑒𝑒𝑑𝑖 =
•
𝑀𝐿𝐶 𝑎𝑐𝑐𝑒𝑙𝑖 =
•
𝑧𝑡𝑜𝑡𝑎𝑙 𝑓 =
•
•
•
•
•
•
•
𝑀𝐿𝐶 𝑠𝑝𝑒𝑒𝑑𝑖−𝑀𝐿𝐶 𝑠𝑝𝑒𝑒𝑑𝑖+1
𝑇𝑖𝑚𝑒𝑖
1
𝑁𝑐𝑝 −2
∙
𝑁𝑐𝑝
{𝑁
𝑖=1 𝑖
𝑀𝐿𝐶
> 𝑓𝜎𝑀𝐿𝐶 𝑠𝑝𝑒𝑒𝑑 𝑜𝑟
𝑠𝑝𝑒𝑒𝑑 𝑖
𝑀𝐿𝐶 𝑎𝑐𝑐𝑒𝑙𝑖 > 𝛼𝑓𝜎𝑀𝐿𝐶 𝑎𝑐𝑐𝑒𝑙
𝑓;
∙ 𝑊𝐺𝐴,𝑖 ∙ 𝑊𝑀𝑈,𝑖 }
where f = 0.01, 0.02…2
σMLC speed = standard deviation of the MLC speedi
Ncp is the total number of CPs for a given VMAT plan
α = weighting factor for the acceleration which is 1/Timei acquired empirically
σMLC accel = standard deviation of MLC acceli
N(f; MLC speedi > fσMLC speed or MLC acceli > αfσMLC accel) is a count of the number of changes for
which MLC speedi > fσMLC speed or changes for which MLC acceli > αfσMLC accel
𝑘
𝑧
0 𝑡𝑜𝑡𝑎𝑙
k = 0.2, 0.5, 1, 2 in this study
𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 MI𝑡 =
•
•
𝑀𝐿𝐶𝑖 −𝑀𝐿𝐶𝑖+1
𝑇𝑖𝑚𝑒𝑖
𝑀𝐼𝑡 =
120
𝑛=1 𝑖𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙
𝑓 𝑑𝑓
𝑀𝐼𝑡 𝑛
Gantry Rotation Speed vs. Dose Rate
Thinning algorithm
• Peels off the boundary of some structures to make thinline representations by iterative deletions of pixels while
preserving the connectivity of the image patterns
• Popular in the field of image processing and
pattern recognition
• Various applications such as fingerprint
classification, measurements of soil cracking
patterns, printed circuit board inspection and so on
Aperture index (AI)
• Assumption
– Irregular fields consisting of several narrow
rectangular fields or small fields would
become thin-line patterns faster by peeling off
the boundary of field apertures than would
regular or large fields
• Application of the thinning algorithm to
field apertures at every CP of VMAT plans
Application of the thinning
algorithm to a field aperture
Design of AI
• Field apertures at each CP were generated
– With DICOM-RT formatted VMAT file
• Application of the thinning algorithm to field
apertures
• After 10 times application of the thinning
algorithm, every apertures in this study
became thin-line structures
Design of AI (cont’d)
• After 2 times application, we counted line pixels
– Definition of line pixel in this study = the pixels which were
not affected by the application of the thinning algorithm
• 𝐴𝑝𝑒𝑟𝑡𝑢𝑟𝑒 𝑖𝑛𝑑𝑒𝑥𝑖 𝐴𝐼𝑖 =
2
𝑛(𝑥)𝑖 𝑑𝑥
0
10
𝑛(𝑥)𝑖 𝑑𝑥
0
×
10
𝑛(10)𝑖 𝑑𝑥
0
2
𝑛(10)𝑖 𝑑𝑥
0
– AIi = an aperture index at ith CP
– x = an iteration number of the applications of the thinning algorithm
– n(x)i = the number of line pixels by x applications of the thinning algorithm / the
number of line pixels after 10 applications of the thinning algorithm at ith CP
• Smaller or more irregular fields  AI value becomes 1
• Larger or more regular fields  AI value becomes 0
Line pixel number difference
Design of weighting factor
• 𝑊𝐴𝐼,𝑖 =
𝛽
1+(𝛽−1)∙𝑒
−
𝐴𝐼𝑖
𝛾
– β = a constant which determines the range of WAI,i (in this study, β was
set to 2)
– γ = a constant which determines the speed of convergence to the
maximum value of WAI,i (γ was set to 2 in this study)
• AIi = 0 (regular field)  WAI,i = 1
• AIi = 1 (irregular field)  WAI,i =
• 1 < WAI,i < 1.25 in this study
2 𝑒
𝑒+1
(≈ 1.24)
Comprehensive MI (MIc)
• 𝑧𝑐 𝑓 =
1
𝑁𝑐𝑝 −2
∙
𝑁𝑐𝑝
𝑖=1
𝑁𝑖 (𝑓; 𝑀𝐿𝐶 𝑠𝑝𝑒𝑒𝑑𝑖 > 𝑓𝜎𝑀𝐿𝐶 𝑠𝑝𝑒𝑒𝑑
∙ 𝑊𝐺𝐴,𝑖+1 ∙
𝑜𝑟 𝑀𝐿𝐶 𝑎𝑐𝑐𝑒𝑙𝑖 > 𝛼𝑓𝜎𝑀𝐿𝐶 𝑎𝑐𝑐𝑒𝑙 )
Correlation analysis
• A total of 52 VMAT plans
• 22 prostate and 30 head and neck (H&N) VMAT plans
– 4 H&N VMAT plans were clinically unacceptable
• Global gamma passing rates with 2%/2 mm of 88.2%, 81.6%, 79.3%
and 71.5%
• VMAT delivery accuracy
– Both global and local gamma passing rates
– Mechanical parameter differences
– DV parameter differences between original plans and the plans
reconstructed with log file
• Correlation analysis between the values of MI and VMAT
delivery accuracy
Values of MIs
Prostate VMAT
H&N VMAT
p
MIt (f = 0.5)
16.3 ± 3.8
44.7 ± 6.3
< 0.001
MIc (f = 0.2)
11.3 ± 2.6
33.9 ± 4.7
< 0.001
MIc (f = 0.5)
19.3 ± 4.8
53.3 ± 7.7
< 0.001
MIc (f = 1.0)
29.4 ± 8.0
66.8 ± 9.3
< 0.001
MIc (f = 2.0)
35.9 ± 10.0
68.4 ± 9.6
< 0.001
MCSv
0.57 ± 0.11
0.47 ± 0.09
< 0.001
LTMCS
0.37 ± 0.09
0.21 ± 0.06
< 0.001
MISPORT
212444 ± 695859
1637761 ± 2356322
0.008
Global gamma passing rates
2%/2 mm
Modulation index
1%/2 mm
2%/1 mm
rs
p
rs
p
rs
p
MIt (f = 0.5)
-0.715
< 0.001
-0.841
< 0.001
-0.593
< 0.001
MIc (f = 0.2)
-0.680
< 0.001
-0.822
< 0.001
-0.568
< 0.001
MIc (f = 0.5)
-0.728
< 0.001
-0.847
< 0.001
-0.617
< 0.001
MIc (f = 1.0)
-0.717
< 0.001
-0.836
< 0.001
-0.580
< 0.001
MIc (f = 2.0)
-0.712
< 0.001
-0.806
< 0.001
-0.579
< 0.001
MCSv
0.466
< 0.001
0.466
< 0.001
0.556
< 0.001
LTMCS
0.525
< 0.001
0.577
< 0.001
0.514
< 0.001
MISPORT
-0.734
< 0.001
-0.795
< 0.001
-0.716
< 0.001
Local gamma passing rates
2%/2 mm
Modulation index
1%/2 mm
2%/1 mm
rs
p
rs
p
rs
p
MIt (f = 0.5)
-0.763
< 0.001
-0.766
< 0.001
-0.734
< 0.001
MIc (f = 0.2)
-0.740
< 0.001
-0.755
< 0.001
-0.706
< 0.001
MIc (f = 0.5)
-0.765
< 0.001
-0.767
< 0.001
-0.748
< 0.001
MIc (f = 1.0)
-0.756
< 0.001
-0.745
< 0.001
-0.720
< 0.001
MIc (f = 2.0)
-0.719
< 0.001
-0.703
< 0.001
-0.693
< 0.001
MCSv
0.357
0.009
0.315
0.023
0.611
< 0.001
LTMCS
0.424
0.002
0.422
0.002
0.589
< 0.001
MISPORT
-0.642
< 0.001
-0.658
< 0.001
-0.772
< 0.001
Mechanical parameter differences
MLC errors
Modulation index
Gantry angle errors
MU errors
rs
p
rs
p
rs
p
MIt (f = 0.5)
0.816
< 0.001
-0.687
< 0.001
-0.230
0.102
MIc (f = 0.2)
0.846
< 0.001
-0.678
< 0.001
-0.231
0.100
MIc (f = 0.5)
0.800
< 0.001
-0.712
< 0.001
-0.243
0.083
MIc (f = 1.0)
0.750
< 0.001
-0.718
< 0.001
-0.283
0.042
MIc (f = 2.0)
0.684
< 0.001
-0.759
< 0.001
-0.303
0.029
MCSv
-0.448
0.001
0.784
< 0.001
0.256
0.067
LTMCS
-0.643
< 0.001
0.798
< 0.001
0.188
0.181
MISPORT
0.707
< 0.001
-0.787
< 0.001
-0.224
0.111
DV differences of prostate VMAT
MIt
(f = 0.5)
MIc
(f = 0.2)
MIc
(f = 0.5)
MIc
(f = 1)
MIc
(f = 2)
MCSv
LTMCS
D95%
0.570
(0.006)
0.481
(0.023)
0.602
(0.003)
0.636
(0.001)
0.704
(<0.001)
-
-
-
D5%
0.461
(0.031)
0.447
(0.037)
0.498
(0.018)
0.469
(0.028)
0.451
(0.035)
-0.588
(0.004)
-0.536
(0.010)
-
Min.
-
-
-
-
-
-
-
-
0.439
(0.041)
0.428
(0.047)
0.490
(0.021)
0.473
(0.026)
0.484
(0.022)
0.442
(0.039)
0.498
(0.018)
0.442
(0.040)
0.515
(0.014)
-0.661
(0.001)
-0.520
(0.013)
-0.664
(0.001)
-0.502
(0.017)
0.485
(0.022)
Rectal wall
D20%
0.653
(0.001)
0.617
(0.002)
0.644
(0.001)
0.650
(0.001)
0.519
(0.013)
-0.425
(0.049)
-0.460
(0.031)
0.497
(0.019)
Rectal wall
Mean.
0.609
(0.003)
0.646
(0.001)
0.582
(0.004)
0.508
(0.016)
-
-0.423
(0.050)
-
0.587
(0.004)
Bladder
Mean.
0.496
(0.019)
0.519
(0.013)
0.514
(0.014)
0.515
(0.014)
-
-
-
0.625
(0.002)
Femoral head
D50%
-
-
-
-
-
-
-
-
Femoral head
Mean.
0.460
(0.031)
0.474
(0.026)
0.456
(0.033)
0.432
(0.045)
-
-
-
0.429
(0.047)
No. of rs
(p<0.05)
8
7
8
8
5
5
4
5
Max.
Mean.
-
MISPORT
-
DV differences of H&N VMAT
MIt
(f = 0.5)b
MIc
(f = 0.2)c
MIc
(f = 0.5)
MIc
(f = 1)
MIc
(f = 2)
MCSvd
LTMCSe
MISPORTf
D95%n
0.423
(0.020)
-
0.448
(0.013)
0.534
(0.002)
0.515
(0.004)
-0.385
(0.036)
-
0.374
(0.042)
D5%
0.506
(0.004)
0.420
(0.021)
0.520
(0.003)
0.624
(<0.001)
0.606
(<0.001)
-
-
-
Max.o
-
-
-
-
-
Mean.p
0.398
(0.030)
0.511
(0.004)
0.368
(0.046)
0.574
(0.001)
-
0.494
(0.006)
0.399
(0.029)
0.588
(0.001)
-
-
-
D95%
0.442
(0.014)
0.376
(0.041)
0.393
(0.032)
-
-
-
-
-
0.401
(0.028)
0.376
(0.040)
-
D5%
0.424
(0.020)
0.385
(0.035)
Min.q
-
-
-
-
-
-
-
-
-
-
0.367
(0.046)
0.463
(0.010)
0.445
(0.014)
-
-
-
Mean.
-
-
0.353
(0.050)
D95%
0.441
(0.017)
-
0.487
(0.007)
0.631
(<0.001)
0.669
(<0.001)
-0.407
(0.028)
-
0.441
(0.017)
D5%
-
-
0.421
(0.023)
0.592
(0.001)
0.580
(0.001)
-0.496
(0.006)
-0.380
(0.042)
0.442
(0.016)
0.509
(0.005)
0.444
(0.016)
0.451
(0.014)
0.495
(0.006)
0.464
(0.011)
0.498
(0.006)
0.596
(0.001)
0.477
(0.009)
0.571
(0.001)
-
-
-
-
-
-
-
-
0.399
(0.032)
0.569
(0.001)
0.594
(0.001)
-0.476
(0.009)
-0.410
(0.027)
0.437
(0.018)
0.531
(0.003)
0.530
(0.003)
0.436
(0.018)
0.539
(0.002)
0.446
(0.015)
0.546
(0.002)
-0.576
(0.001)
-
0.593
(0.001)
-
-
-
Min.
Max.
Mean.
SCr Max.
BSs Max.
0.459
(0.012)
0.553
(0.002)
-
0.463
(0.010)
P(R)t Mean.
-
-
-
P(L) Mean.
-
-
-
-
-
-
-0.405
(0.027)
-
-
-
-
-
-0.392
(0.043)
-
-
-
-0.447
(0.019)
-
-
-
-
Lens (R) u Max.
-
-
-
-0.378
(0.050)
OCv Max.
-
-
-
-0.410
(0.033)
ON(R)w Max.
-
-
-
-
-
-
0.392
(0.043)
ON(L) Max.
-
-
-
-0.403
(0.037)
-0.427
(0.026)
0.499
(0.008)
0.429
(0.026)
-0.446
(0.020)
No. of rs
p<0.05
9
5
12
17
17
7
4
7
Conclusions
• Modulation degree affects VMAT plan delivery
accuracy
• Evaluation of VMAT delivery accuracy
–
–
–
–
Gamma method
Linac log file analysis
DVH diff. btw. plan and reconstructed plan
MI
• More powerful tool is needed for pre-treatment
VMAT QA
Thank you for your attention