SlideShare a Scribd company logo
5 How to fine-tune the
commissioning of a TPS
Stephen Gardner
Medical Physicist
June 18
Henry Ford Health System (Detroit, MI, USA)
1
Outline for today’s session
1. Spot checking your commissioning data
1. Using MPPG 5A report as a reference/outline for
photon beam model validation
2. Summary of validation tests
2. Tweaking TPS: DLG and MLC transmission
• Create a new “commissioning” machine in your TPS
• Compare to measured data and perform iterations of
DLG and MLC transmission adjustments
2
Learning Objectives: After this session, you will…
o Be able to perform a comprehensive but quick spot-check of
commissioning data
o Understand the detailed, step-by-step process of how to adjust
DLG and MLC transmission in the TPS, referencing their clinic’s
data
o Be able to execute the logistics and team communications
needed to safely fine-tune commissioning (e.g., creating a
separate “machine”)
1. Spot checking your
commissioning data
4
ZOOM POLL
The dosimetric leaf gap (DLG) represents:
A. The difference in the physical leaf end and the dosimetric field edge
B. The minimum gap that is possible for an MLC system
C. The width of the sweeping gap field used during measurements
D. The width of the penumbra of an MLC-defined field
5
ZOOM POLL
The dosimetric leaf gap (DLG) represents:
A. The difference in the physical leaf end and the dosimetric field edge
B. The minimum gap that is possible for an MLC system
C. The width of the sweeping gap field used during measurements
D. The width of the penumbra of an MLC-defined field
6
References/Guides for Photon Beam
Commissioning
o MPPG 5A has proven to be an extremely
helpful guide for commissioning photon
algorithms – published in 2015
• https://doi.org/10.1120/jacmp.v16i5.5768
o The strength of this document is that it
covers many aspects of algorithm
performance in a comprehensive, clear,
and concise way
o Scope of the document – gives
recommendations for:
• Data Acquisition and Processing
• Algorithm Validation (Photon and Electron)
– Basic model validation
– Heterogeneity correction validation (not
included in this lecture)
– IMRT/VMAT dose validation
7
MPPG 5A Breakdown
o Table 3
• Basic validation of beam model – comparison in beam configuration
workspace, dose normalization is accurate
o Table 4
• More in-depth validation of 3D-CRT delivery – measurements of dose
agreement in high-dose region, penumbra, and out-of-field region
o Table 5
• Summary of dose agreement tolerances
o Table 6 (N/A for this lecture) – heterogeneity correction
validation
o Table 7
• IMRT/VMAT Validation – including TG-119/Clinical Case validation
Table 3: Basic Model Validation
o Use Table 3 from the MPPG document to perform basic validation of the model:
• (5.1) Within the physics/beam config module, compare PDD and profile for large field (calculated
vs. measured)
• (5.2) Within a test plan in the TPS - calculate a plan using absolute dose calibration conditions
and ensure that you are calculating 1 cGy/MU at the calibration point (sanity check!)
• (5.3) Quick check of PDD and output factor (OF) – within a test plan in the TPS, compare
calculated PDD and OF to measured data
o Note – these tests don’t require any new measurements! Just some re
9
Table 3: Examples –
Test 5.1
o Test 5.1 – Within
the physics module
(beam
configuration
workspace),
compare the PDD
and profile –
measured vs.
calculated dose
10
Table 3: Examples – Test 5.2
o Test 5.2 – Calculate plan using
calibration geometry and
ensure dose at calibration
depth is 1 cGy/MU.
** For our clinic, the calibration
geometry is 10x10 cm2 field
size, 100 cm SSD, with
calibration depth at dmax.
11
Table 3: Examples – Test 5.3
o Test 5.3 – Calculate a plan in
the TPS that simulates
scanning data and compare
calculated vs. measured
• This requires the user to take
a line profile at the
appropriate depth
** For our clinic, this involved
calculating a plan at 100 SSD for
the relevant field size
Table 4: Basic Photon Beam Validation Summary
o To perform this set of validation tests, measure the absolute dose at several
points for each of these fields:
• Different depths (slightly beyond dmax, mid-range/10-15 cm depth, and deep/25-30 cm
depth)
• Different off-axis positions – high dose, penumbra, and low dose
13
Table 4: Examples - Test
o Test 5.4 – small MLC-defined
field (4x4 cm2 MLC field and
5x5 cm2 jaw)
o Test 5.5 – large MLC-defined
field with extensive blocking
o Test 5.6-5.7 – use same
aperture with different SSD
** For each of these, perform
measurements at high dose,
penumbra, low dose regions at
dmax depth, 10 cm depth, and
25 cm depth.
Test 5.4
Test 5.5
Tests 5.6-5.7
Table 5: Evaluation Methods and Tolerances
o Three different regions are specified: high dose, penumbra, and low
dose tail
• For high dose and low dose tail regions – tolerance is based on dose
difference (Percent)
• For penumbra – tolerance is based on distance to agreement (DTA)
Table 7: VMAT/IMRT Summary
o The IMRT/VMAT tests are in
addition to the tests in Table
3/4 from prior slides
o In my opinion - the most
important tests from this
group are the TG-119 tests
(7.3) and Clinical tests (7.4)
• These plans will be used to
validate and adjust the TPS
model as needed to ensure
optimal IMRT/VMAT delivery
Summary – Validation Testing
(Scanning/Open Field)
o Scanning Data –
• Verify profiles using flatness and symmetry for small, mid-size, and large field sizes
at dmax, 10 cm, and 30 cm depth
– For example: 4x4, 10x10, and 30x30 cm2 field sizes (you can verify additional field
sizes if warranted)
– Typically, we want to see symmetry < 1% and then flatness consistent with past
results (within 1% of baseline if available)
– Compare measurement to calculation in TPS to verify model behavior
• Verify PDD for small, mid-size, and large field sizes by comparing measured and
calculated doses
– While you are scanning these - include MLC-defined small field PDD to satisfy
MPPG 5A test 7.1 (if you have access to a small field detector such as diode)
o Output Factors – verify agreement between calculated and measured
output factors for a variety of field sizes, ranging from 3x3 to 40x40 cm2
• While you are measuring these - include MLC-defined small field OF to satisfy
MPPG 5A test 7.2 (again if you have access to a small field detector such as diode,
micro ion chamber, etc.)
TG-119 and Clinical Case PSQA
o TG-119 Planning Guide, Reporting Form, and
Structure Sets can be found on the AAPM website:
https://www.aapm.org/pubs/tg119/default.asp
o TG-119 data set includes DICOM CT, RT Structure
files as well as planning goals and instruction
document:
• C-Shape
• Mock HN plan
• Mock Prostate
• Multi-Target
o Additional plans for testing – representative plans
from previous patients
• Replan as needed with new machine/beam model
• Should include typical disease sites encountered at your
center – HN, Prostate, Lung, Brain, etc.
2. Tweaking TPS: DLG and MLC
transmission
19
Overview for this Section
o MLC DLG and Transmission – effect on the dose distribution
for various delivery modalities (static fields, IMRT, and VMAT)
o Practical Overview/Tips on MLC Parameter Adjustment
o Creating a new ‘commissioning’ machine for your testing
o How to adjust DLG and MLC Transmission - Detailed, step-by-
step process of how to adjust these within the TPS, referencing
their clinic’s data
o Practical dry-run of adjusting model parameters with realistic
clinical data
MLC DLG and Transmission –
Effect on the Dose Distribution for
Various Delivery Modalities
MLC DLG Effect – Static Fields
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16
Distance Along Profile (cm)
DLG =0.100 cm
DLG =0.200 cm
MLC Transmission Effect – Static Fields
0
20
40
60
80
100
0 2 4 6 8 10 12 14 16
Distance Along Profile (cm)
MLC_trans = 1.6%
MLC_trans = 2.5%
MLC DLG Effect –
IMRT Delivery
0
20
40
60
80
100
120
0 2 4 6 8 10 12 14 16 18 20
Relative
Dose
(%)
Distance Along Profile (cm)
DLG Effect - IMRT Delivery
DLG = 0.14 cm
DLG = 0.16 cm
DLG = 0.115 cm
MLC DLG Effect –
IMRT Delivery (cont’d)
0
20
40
60
80
100
120
8 9 10 11 12 13 14 15 16 17 18
Relative
Dose
(%)
Distance Along Profile (cm)
DLG Effect - IMRT Delivery
DLG = 0.14 cm
DLG = 0.16 cm
DLG = 0.115 cm
Change in
penumbra width
Change in high
dose magnitude
MLC Transmission Effect –
IMRT Delivery
20
30
40
50
60
70
80
90
100
110
0 2 4 6 8 10 12 14 16 18 20
Relative
Dose
(%)
Distance Along Profile (cm)
MLC Transmission Effect - IMRT Delivery
MLC_trans = 1.65%
MLC_trans = 1.85%
MLC DLG Effect (TG-119 C-Shape)
VMAT Delivery
0
20
40
60
80
100
120
0 2 4 6 8 10 12 14
Relative
Dose
(%)
Distance Along Profile (cm)
DLG Effect - VMAT Delivery
DLG = 0.14 cm
DLG = 0.16 cm
DLG = 0.115 cm
MLC DLG Effect (TG-119 C-Shape)
VMAT Delivery
90
92
94
96
98
100
102
104
0 2 4 6 8 10 12 14
Relative
Dose
(%)
Distance Along Profile (cm)
DLG Effect - VMAT Delivery
DLG = 0.14 cm
DLG = 0.16 cm
DLG = 0.115 cm
Smaller Change in
penumbra width
compared to IMRT
Smaller change
in high dose
compared to
IMRT
MLC Transmission Effect –
VMAT Delivery
10
20
30
40
50
60
70
80
90
100
110
0 2 4 6 8 10 12
Relative
Dose
(%)
Distance Along Profile (cm)
MLC Transmission Effect - VMAT Delivery
MLC_trans = 1.65%
MLC_trans = 1.85%
How to – create a new ‘commissioning’
machine in your TPS and adjust DLG/MLC
Transmission
o General idea is to…
• Create a copy of the machine
• Create a copy of the beam model
• Adjust DLG/MLC Transmission to improve agreement
Creating a ‘Commissioning’ Machine
o For ARIA Users, the
process is:
• RT Admin Workspace
– Step 1: Select
machine to copy ->
Insert -> Export
Machine…
– Step 2: Re-import
the machine you
just exported and
name it
appropriately
– Step 3: Rename
imported machine
something like
‘Test_Physics’
– Step 4: Ensure MLC
add-on information
matches the real
machine and enter
starting DLG/MLC
transmission values
Step 1: Export
Step 2: Re-import
Step 4: MLC Add-on
Material and DLG/MLC trans
Step 3: Update
Machine Name
Creating a copy of the
beam model for testing
o For ARIA Users, the process is:
• Beam Config Workspace
– Step 1: select the machine
(Test_Physics) / energy (6x) /
algorithm (AAA_11030) and right-click
-> New Beam Data…
– Step 2: setup copy of beam model
▪ Enter appropriate therapy unit name
▪ Select ‘Copy existing data to the
calculation model’
• DO NOT select ‘assign’
• Ensure that you have selected the correct
beam model to copy and click OK
– Step 3: Match and Assign Add-Ons –
select ‘In Use’ for open field and EDW
and select Automatic Match for All.
– Step 4: Spot check values for Gamma
Error Histogram and Output Factors
to verify consistency against clinical
machine and approve test model
(right-click on the model -> Approve)
Step 3: Match and assign
Add-ons
Step 2: Setup copy of
beam model
Step 1: select
model
Step 4:
Approve Model
Practical Overview/Tips on MLC Parameter
Adjustment
How do I adjust the DLG/MLC Transmission
Values?
o For ARIA v13 and later:
• RT Admin Workspace –
– **Note – this will define these values for all beam models for this machine**
– Go to ‘Radiation and Imaging Devices’
– Select the test physics machine and go to ‘MLC’ tab
– Enter values for MLC Transmission factor and DLG within the ‘Dosimetric
Properties’ section
o For ARIA v11 and earlier:
• Beam Configuration Workspace –
– Select the test physics beam model
– Go to Beam Data -> Dosimetric Data and enter MLC Transmission factor and
DLG
o For other TPS vendors – consult with the manual for instructions on
this process
Initial
Overview –
Iterative
Tweaking
Process
• Resource for TPS beam model validation – Medical Physics Practice Guideline 5.A
• MLC Parameter/Beam Model Optimization (like any optimization process) is
iterative
• The overall process goes something like:
1. Acquire initial measurements for MLC parameters -> input to TPS
2. Calculate Beam Model
3. Generate/calculate IMRT/VMAT plans for verification
• For conventional planning – use TG-119 dataset and some previous
clinical plans if available
• For SRS/SBRT planning – critical to use representative stereotactic
plans to validate the beam model!!!
• These treatment plans should meet the relevant clinical
goals/constraints to best simulate a typical IMRT/VMAT delivery
4. Acquire point dose measurements for verification IMRT/VMAT plans
• Proper detector selection is critical – ideal chamber is a small volume
ion chamber such as CC01 or PinPoint chamber
• High dose readings to simulate the target volume!
• Low dose readings to simulate critical organs at risk!
• The point dose measurements will the primary means for MLC
parameter selection
5. Acquire planar dose measurements using Gafchromic film or array device
• Compare results once MLC parameters are finalized from point dose
measurements
MLC
Parameter
Testing –
Practical Key
Points
• Key Points for Emphasis
• Use real IMRT/VMAT plans to validate the beam model/MLC parameter values
• TG-119 data sets
• Previous clinical cases
• Make sure the intended use of the linac is included in the test cases!
• Measurements should include both point and planar dose analysis
• My clinic preference – use point dose measurements for initial tweaking of
MLC parameters
• When is the model good enough?
• TG-119 utilized confidence limits for QA results
• High Dose Point Measurement → CL = ±4.5%
• Low Dose Point Measurement → CL = ±4.7%
• Planar Dose Measurement → Gamma(3%,3mm) > 87.6%
• TG-218 proposed tolerance limits and action limits for pre-treatment QA:
• Tolerance Limit:
• Ion Chamber Measurement <2%
• Gamma(3%,2mm) > 95%
• Action Limit:
• Ion Chamber Measurement <2%
• Gamma(3%,2mm) > 95%
• Investigate outliers for additional measurements
• Aim to get average percent difference close to 0% (Mean Perc. Diff.)
• Minimize spread in QA results (Standard Deviation Of Perc. Diff.)
• Compare to other institutions/literature with similar linac and TPS
• If possible – obtain independent audit of IMRT/VMAT delivery from another
physicist/institution
• How much can you tweak the TPS values?
• My preference – tweak as little as possible to get agreement that fulfills
clinical goals of the machine
MLC Parameters –
Interpreting Results
• Which way do I need to tweak the
value?
• Increasing DLG value
→ Increase in calculated dose
• Increasing MLC Transmission value
→ Increase in calculated dose
• Example:
• If plan dose is higher than measured
dose → the next step is to increase DLG
and/or MLC Transmission and re-
calculate
Example: Plan dose is higher
than film dose → consider
decreasing DLG and/or MLC
Transmission
DLG Adjust
Details – Test
Plan Process
1. Treatment Planning – Develop a good quality plan using the test plan
structure set. Have primary treatment planning staff generate the
plan if possible!
2. QA Plan – Map the plan from step 1 onto the appropriate phantom
• Need to perform both chamber measurement and a planar
dose/fluence measurement
• Planar dose measurement can be using film, detector array,
or even the EPID
• Phantom choices include:
• Solid Water slab phantom with place for chamber/film
• Acrylic phantom with place for chamber/film
• Detector array (MapCheck, ArcCheck, Delta4, Matrixx, etc.)
• EPID measurement (Portal Dosimetry)
3. Measure QA plan and compare to predicted dose from TPS
calculation
4. Compile all test plan results (IMRT and VMAT) before making any
adjustments
• Note – IMRT and VMAT trends can differ!!
Practical dry-run of adjusting model
parameters with realistic clinical data
o The background information for this example:
• TG-119 plans and Clinical Cases (IMRT and VMAT) for 10x
energy modewere measured with ion chamber in high dose
and lose dose region
• Starting point was the initial measured DLG value of 0.115
cm and MLC Transmission = 1.65%
• Total Case Breakdown
– TG-119: 3 IMRT and 3 VMAT
– Clinical Cases: 2 IMRT and 2 VMAT
MLC Parameter
Selection
Summary
Points – 10 MV
beam modeling
process
• Decision on MLC parameters such as DLG and
Leaf Transmission depend on:
• The clinical goals for the beam model:
• Which disease sites will be treated
routinely?
• Which modality will be used more
often – IMRT or VMAT?
• The trend in the data:
• Which parameter values will minimize
the percent difference between
planned and measured doses?
• Which parameter values will minimize
the spread in the results comparing
planned and measured doses?
• Which parameter values will minimize
outliers in the data?
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.115 cm)
[MLC_trans = 0.0185]
Perc. Diff.
C Shape 2.154 2.052 4.73%
H&N 2.100 2.095 0.24%
H&NSIB 2.176 2.135 1.86%
Prostate 1.988 1.957 1.54%
Prostate LN 1.968 1.946 1.11%
C Shape 2.481 2.470 0.45%
H&N 2.195 2.191 0.19%
H&NSIB 2.122 2.127 -0.22%
Prostate 1.997 1.977 1.02%
Prostate LN 1.893 1.937 -2.32%
VMAT Average 1.90%
VMAT St. Dev. 1.70%
IMRT Average -0.18%
IMRT St. Dev. 1.28%
Overall Average 0.86%
Overall St. Dev. 1.79%
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.115 cm)
[MLC_trans = 0.0185]
Perc. Diff.
C Shape 0.320 0.344 -7.51%
H&N 1.314 1.297 1.28%
H&NSIB 1.124 1.126 -0.18%
Prostate 1.322 1.279 3.22%
Prostate LN 0.890 0.874 1.80%
C Shape 0.489 0.520 -6.41%
H&N 1.316 1.331 -1.16%
H&NSIB 1.201 1.236 -2.94%
Prostate 1.650 1.630 1.18%
Prostate LN 1.136 1.163 -2.35%
VMAT Average -0.28%
VMAT St. Dev. 4.22%
IMRT Average -2.33%
IMRT St. Dev. 2.77%
Overall Average -1.31%
Overall St. Dev. 3.54%
IMRT
Results (TG-119 Table VII)- High Dose
VMAT
IMRT
Results (TG-119 and Clinical Cases)- Low Dose
VMAT
Iteration 1 – DLG = 0.115 cm /
MLC_Trans = 1.65%
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0 1 2 3 4 5 6
Percent
Difference
Iteration #
VMAT - High Dose
IMRT - High Dose
VMAT - Low Dose
IMRT - Low Dose
Iteration 2 – DLG = 0.140 cm /
MLC_Trans = 1.65%
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.140 cm)
[MLC_trans = 0.0165]
Perc. Diff.
C Shape 2.154 2.048 4.91%
H&N 2.100 2.087 0.62%
H&NSIB 2.176 2.128 2.19%
Prostate 1.988 1.954 1.69%
Prostate LN 1.968 1.942 1.31%
C Shape 2.481 2.448 1.34%
H&N 2.195 2.173 1.01%
H&NSIB 2.122 2.113 0.44%
Prostate 1.997 1.974 1.17%
Prostate LN 1.893 1.921 -1.47%
VMAT Average 2.15%
VMAT St. Dev. 1.65%
IMRT Average 0.49%
IMRT St. Dev. 1.15%
Overall Average 1.32%
Overall St. Dev. 1.60%
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.140 cm)
[MLC_trans = 0.0165]
Perc. Diff.
C Shape 0.320 0.338 -5.64%
H&N 1.314 1.287 2.04%
H&NSIB 1.124 1.117 0.62%
Prostate 1.322 1.275 3.52%
Prostate LN 0.890 0.867 2.59%
C Shape 0.489 0.496 -1.50%
H&N 1.316 1.311 0.36%
H&NSIB 1.201 1.220 -1.61%
Prostate 1.650 1.626 1.43%
Prostate LN 1.136 1.149 -1.11%
VMAT Average 0.63%
VMAT St. Dev. 3.66%
IMRT Average -0.49%
IMRT St. Dev. 1.33%
Overall Average 0.07%
Overall St. Dev. 2.66%
IMRT
Results (TG-119 Table VII)- High Dose
VMAT
IMRT
Results (TG-119 and Clinical Cases)- Low Dose
VMAT
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0 1 2 3 4 5 6
Percent
Difference
Iteration #
VMAT - High Dose
IMRT - High Dose
VMAT - Low Dose
IMRT - Low Dose
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.115 cm)
[MLC_trans = 0.0165]
Perc. Diff.
C Shape 2.154 2.040 5.29%
H&N 2.100 2.074 1.24%
H&NSIB 2.176 2.116 2.74%
Prostate 1.988 1.945 2.14%
Prostate LN 1.968 1.932 1.82%
C Shape 2.481 2.385 3.88%
H&N 2.195 2.151 2.01%
H&NSIB 2.122 2.096 1.24%
Prostate 1.997 1.966 1.57%
Prostate LN 1.893 1.892 0.06%
VMAT Average 2.65%
VMAT St. Dev. 1.57%
IMRT Average 1.75%
IMRT St. Dev. 1.39%
Overall Average 2.20%
Overall St. Dev. 1.48%
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.115 cm)
[MLC_trans = 0.0165]
Perc. Diff.
C Shape 0.320 0.337 -5.33%
H&N 1.314 1.276 2.88%
H&NSIB 1.124 1.108 1.42%
Prostate 1.322 1.262 4.50%
Prostate LN 0.890 0.862 3.15%
C Shape 0.489 0.482 1.36%
H&N 1.316 1.290 1.96%
H&NSIB 1.201 1.203 -0.19%
Prostate 1.650 1.615 2.09%
Prostate LN 1.136 1.131 0.47%
VMAT Average 1.33%
VMAT St. Dev. 3.88%
IMRT Average 1.14%
IMRT St. Dev. 0.98%
Overall Average 1.23%
Overall St. Dev. 2.67%
IMRT
VMAT
IMRT
Results (TG-119 and Clinical Cases)- High Dose
Results (TG-119 and Clinical Cases)- Low Dose
VMAT
Iteration 3 – DLG = 0.140 cm /
MLC_Trans = 1.85%
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0 1 2 3 4 5 6
Percent
Difference
Iteration #
VMAT - High Dose
IMRT - High Dose
VMAT - Low Dose
IMRT - Low Dose
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.16 cm)
[MLC_trans = 0.0165]
Perc. Diff.
C Shape 2.154 2.056 4.54%
H&N 2.100 2.097 0.15%
H&NSIB 2.176 2.138 1.73%
Prostate 1.988 1.960 1.39%
Prostate LN 1.968 1.949 0.96%
C Shape 2.481 2.498 -0.68%
H&N 2.195 2.192 0.14%
H&NSIB 2.122 2.127 -0.22%
Prostate 1.997 1.981 0.82%
Prostate LN 1.893 1.943 -2.64%
VMAT Average 1.75%
VMAT St. Dev. 1.67%
IMRT Average -0.52%
IMRT St. Dev. 1.31%
Overall Average 0.62%
Overall St. Dev. 1.85%
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.16 cm)
[MLC_trans = 0.0165]
Perc. Diff.
C Shape 0.320 0.340 -6.26%
H&N 1.314 1.296 1.36%
H&NSIB 1.124 1.123 0.09%
Prostate 1.322 1.285 2.76%
Prostate LN 0.890 0.872 2.03%
C Shape 0.489 0.508 -3.96%
H&N 1.316 1.328 -0.93%
H&NSIB 1.201 1.234 -2.77%
Prostate 1.650 1.633 1.00%
Prostate LN 1.136 1.155 -1.64%
VMAT Average 0.00%
VMAT St. Dev. 3.64%
IMRT Average -1.66%
IMRT St. Dev. 1.88%
Overall Average -0.83%
Overall St. Dev. 2.86%
IMRT
Results (TG-119 Table VII)- High Dose
VMAT
IMRT
Results (TG-119 and Clinical Cases)- Low Dose
VMAT
Iteration 4 – DLG = 0.160 cm /
MLC_Trans = 1.65%
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0 1 2 3 4 5 6
Percent
Difference
Iteration #
VMAT - High Dose
IMRT - High Dose
VMAT - Low Dose
IMRT - Low Dose
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.16 cm)
[MLC_trans = 0.0185]
Perc. Diff.
C Shape 2.154 2.059 4.40%
H&N 2.100 2.105 -0.23%
H&NSIB 2.176 2.145 1.40%
Prostate 1.988 1.963 1.24%
Prostate LN 1.968 1.954 0.70%
C Shape 2.481 2.520 -1.57%
H&N 2.195 2.209 -0.63%
H&NSIB 2.122 2.141 -0.88%
Prostate 1.997 1.984 0.67%
Prostate LN 1.893 1.960 -3.53%
VMAT Average 1.50%
VMAT St. Dev. 1.74%
IMRT Average -1.19%
IMRT St. Dev. 1.54%
Overall Average 0.16%
Overall St. Dev. 2.10%
Plan Type
Measured Point
Dose (cGy)
Calculated Dose
(DLG = 0.16 cm)
[MLC_trans = 0.0185]
Perc. Diff.
C Shape 0.320 0.345 -7.83%
H&N 1.314 1.306 0.60%
H&NSIB 1.124 1.132 -0.71%
Prostate 1.322 1.289 2.46%
Prostate LN 0.890 0.879 1.24%
C Shape 0.489 0.531 -8.66%
H&N 1.316 1.348 -2.45%
H&NSIB 1.201 1.250 -4.11%
Prostate 1.650 1.637 0.76%
Prostate LN 1.136 1.173 -3.23%
VMAT Average -0.85%
VMAT St. Dev. 4.07%
IMRT Average -3.54%
IMRT St. Dev. 3.40%
Overall Average -2.19%
Overall St. Dev. 3.81%
IMRT
Results (TG-119 Table VII)- High Dose
VMAT
IMRT
Results (TG-119 and Clinical Cases)- Low Dose
VMAT
Iteration 5 – DLG = 0.160 cm /
MLC_Trans = 1.85%
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0 1 2 3 4 5 6
Percent
Difference
Iteration #
VMAT - High Dose
IMRT - High Dose
VMAT - Low Dose
IMRT - Low Dose
MLC Parameter Iteration Summary –
Graphical Analysis
-4.0%
-3.0%
-2.0%
-1.0%
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0 1 2 3 4 5 6
Percent
Difference
Iteration #
VMAT - High Dose
IMRT - High Dose
VMAT - Low Dose
IMRT - Low Dose
Final Value Chosen
for Planning
Summary – DLG Testing Plan Process
1. Treatment Planning – Develop a good quality plan using the test plan structure set. Have primary
treatment planning staff generate the plan if possible!
2. QA Plan – Map the plan from step 1 onto the appropriate phantom
• Need to perform both chamber measurement and a planar dose/fluence measurement
• Planar dose measurement can be using film, detector array, or even the EPID
• Phantom choices include:
• Solid Water slab phantom with place for chamber/film
• Acrylic phantom with place for chamber/film
• Detector array (MapCheck, ArcCheck, Delta4, Matrixx, etc.)
• EPID measurement (Portal Dosimetry)
3. Measure QA plan and compare to predicted dose from TPS calculation
4. Compile all test plan results (IMRT and VMAT) before making any adjustments
• Note – IMRT and VMAT trends can differ!!
Practical Tips – Adjusting Parameters on
Approved Beam Models
• If you have a beam model that is already approved and need to make adjustments for IMRT/VMAT
commissioning:
1. Use caution! Think about what could go wrong before making any adjustments. Discuss
with other physicists to make sure you have thought of everything that could come up.
2. Communicate! Once you have a plan, talk about it with relevant staff
3. Calculate! Plan out a time when you can perform the dose calculations with the
preliminary MLC DLG/Transmission values.
1. This may need to be done after-hours or on a weekend.
4. Reset! Depending on the workflow, make sure to reset the MLC parameters back to the
clinically approved values.
1. If you have multiple DLG/Transmission values you would like to test (multiple
iterations), this is the time to perform all iterations
5. Verify! Once you have reset the MLC parameters back to the original values, re-calculate a
set of test plans to verify constancy.
6. Compare! Once you have the calculations done, you can compare to the measured values
and determine optimal parameters
SRS/SBRT – You may need a
separate algorithm!
• My experience – the level of
modulation for conventional
IMRT/VMAT planning is quite
different than for SRS/SBRT
planning
• Typically, the optimal
DLG value for TG-119
planning is different
than for representative
SRS/SBRT cases
• Example at left: 6FFF
beam used for SRS/SBRT
delivery at one of our
• More data for this
example shown on
next slide
CONCLUSION
o A ‘commissioning’ machine can be created to test out the
parameters for the TPS model
o The TPS model will be adjusted based on comparison of
calculated and measured results for IMRT/VMAT plans
o A representative process for adjusting MLC parameters has
been shared for learning purposes
o The next lecture is transitions from commissioning and
adjusting the beam model to routine QA of treatment plans. The
topic is: “Patient-Specific and High-yield Machine QA for IMRT”
50
REFERENCES
o AAPM Task Group 119:
https://www.aapm.org/pubs/tg119/default.asp
o Medical Physics Practice Guidelines (MPPG) 5A:
https://doi.org/10.1120/jacmp.v16i5.5768
51
Thank you for your attention!

More Related Content

What's hot

SBRT IN LIVER TUMOURS- DR UPASNA.pptx
SBRT IN LIVER TUMOURS- DR UPASNA.pptxSBRT IN LIVER TUMOURS- DR UPASNA.pptx
SBRT IN LIVER TUMOURS- DR UPASNA.pptx
Upasna Saxena
 
Lung sbrt ppt
Lung  sbrt pptLung  sbrt ppt
Lung sbrt ppt
Dr. Rituparna Biswas
 
Comparative study of aaa and pbc (1)
Comparative study of aaa and pbc (1)Comparative study of aaa and pbc (1)
Comparative study of aaa and pbc (1)
Rahim Gohar
 
Plan evaluation in RADIOTHERAPY
Plan evaluation in RADIOTHERAPYPlan evaluation in RADIOTHERAPY
Plan evaluation in RADIOTHERAPY
Kanhu Charan
 
Craniospinal irradiation
Craniospinal irradiationCraniospinal irradiation
Craniospinal irradiation
Swarnita Sahu
 
Mind the Gap: Dealing with Interruptions in Radiotherapy Treatment
Mind the Gap: Dealing with Interruptions in Radiotherapy TreatmentMind the Gap: Dealing with Interruptions in Radiotherapy Treatment
Mind the Gap: Dealing with Interruptions in Radiotherapy Treatment
Victor Ekpo
 
IMRT and 3D CRT in cervical Cancers
IMRT and 3D CRT in cervical CancersIMRT and 3D CRT in cervical Cancers
IMRT and 3D CRT in cervical Cancers
Santam Chakraborty
 
craniospinal irradiation
craniospinal irradiation craniospinal irradiation
craniospinal irradiation
Mohammad Ashour
 
Basics of linear quadratic model
Basics of linear quadratic modelBasics of linear quadratic model
Basics of linear quadratic model
Ajeet Gandhi
 
Srs and sbrt 2 dr.kiran
Srs and sbrt 2 dr.kiranSrs and sbrt 2 dr.kiran
Srs and sbrt 2 dr.kiran
Kiran Ramakrishna
 
LUNG SBRT A LITERATURE REVIEW
LUNG SBRT A LITERATURE REVIEWLUNG SBRT A LITERATURE REVIEW
LUNG SBRT A LITERATURE REVIEW
Kanhu Charan
 
ICRU 83
ICRU 83ICRU 83
Gap correction
Gap correctionGap correction
Gap correction
Kiran Ramakrishna
 
SBRT Contouring Guidelines
SBRT  Contouring  GuidelinesSBRT  Contouring  Guidelines
SBRT Contouring Guidelines
Dr Rushi Panchal
 
Linear Accelerator Acceptance, Commissioning and Annual QA
Linear Accelerator Acceptance, Commissioning and Annual QALinear Accelerator Acceptance, Commissioning and Annual QA
Linear Accelerator Acceptance, Commissioning and Annual QAMiami Cancer Institute
 
Evaluation of radiotherapy treatment planning
Evaluation of radiotherapy treatment planningEvaluation of radiotherapy treatment planning
Evaluation of radiotherapy treatment planning
Amin Amin
 
Intensity Modulated Radiation Therapy (IMRT)
Intensity Modulated Radiation Therapy (IMRT)Intensity Modulated Radiation Therapy (IMRT)
Intensity Modulated Radiation Therapy (IMRT)
Dilshad KP
 
Total body irradiation
Total body irradiationTotal body irradiation
Total body irradiation
Rahim Gohar
 
Respiration motion management
Respiration motion managementRespiration motion management
Respiration motion management
Kiran Ramakrishna
 
4dct (2012)
4dct (2012)4dct (2012)
4dct (2012)
Parminder S. Basran
 

What's hot (20)

SBRT IN LIVER TUMOURS- DR UPASNA.pptx
SBRT IN LIVER TUMOURS- DR UPASNA.pptxSBRT IN LIVER TUMOURS- DR UPASNA.pptx
SBRT IN LIVER TUMOURS- DR UPASNA.pptx
 
Lung sbrt ppt
Lung  sbrt pptLung  sbrt ppt
Lung sbrt ppt
 
Comparative study of aaa and pbc (1)
Comparative study of aaa and pbc (1)Comparative study of aaa and pbc (1)
Comparative study of aaa and pbc (1)
 
Plan evaluation in RADIOTHERAPY
Plan evaluation in RADIOTHERAPYPlan evaluation in RADIOTHERAPY
Plan evaluation in RADIOTHERAPY
 
Craniospinal irradiation
Craniospinal irradiationCraniospinal irradiation
Craniospinal irradiation
 
Mind the Gap: Dealing with Interruptions in Radiotherapy Treatment
Mind the Gap: Dealing with Interruptions in Radiotherapy TreatmentMind the Gap: Dealing with Interruptions in Radiotherapy Treatment
Mind the Gap: Dealing with Interruptions in Radiotherapy Treatment
 
IMRT and 3D CRT in cervical Cancers
IMRT and 3D CRT in cervical CancersIMRT and 3D CRT in cervical Cancers
IMRT and 3D CRT in cervical Cancers
 
craniospinal irradiation
craniospinal irradiation craniospinal irradiation
craniospinal irradiation
 
Basics of linear quadratic model
Basics of linear quadratic modelBasics of linear quadratic model
Basics of linear quadratic model
 
Srs and sbrt 2 dr.kiran
Srs and sbrt 2 dr.kiranSrs and sbrt 2 dr.kiran
Srs and sbrt 2 dr.kiran
 
LUNG SBRT A LITERATURE REVIEW
LUNG SBRT A LITERATURE REVIEWLUNG SBRT A LITERATURE REVIEW
LUNG SBRT A LITERATURE REVIEW
 
ICRU 83
ICRU 83ICRU 83
ICRU 83
 
Gap correction
Gap correctionGap correction
Gap correction
 
SBRT Contouring Guidelines
SBRT  Contouring  GuidelinesSBRT  Contouring  Guidelines
SBRT Contouring Guidelines
 
Linear Accelerator Acceptance, Commissioning and Annual QA
Linear Accelerator Acceptance, Commissioning and Annual QALinear Accelerator Acceptance, Commissioning and Annual QA
Linear Accelerator Acceptance, Commissioning and Annual QA
 
Evaluation of radiotherapy treatment planning
Evaluation of radiotherapy treatment planningEvaluation of radiotherapy treatment planning
Evaluation of radiotherapy treatment planning
 
Intensity Modulated Radiation Therapy (IMRT)
Intensity Modulated Radiation Therapy (IMRT)Intensity Modulated Radiation Therapy (IMRT)
Intensity Modulated Radiation Therapy (IMRT)
 
Total body irradiation
Total body irradiationTotal body irradiation
Total body irradiation
 
Respiration motion management
Respiration motion managementRespiration motion management
Respiration motion management
 
4dct (2012)
4dct (2012)4dct (2012)
4dct (2012)
 

Similar to IMRT_VMAT_Session 5_How to fine-tune the commissioning of a TPS.pptx

LINAC COMMSSN.ppt
LINAC COMMSSN.pptLINAC COMMSSN.ppt
LINAC COMMSSN.ppt
BBAdhikari
 
080924 Measurement System Analysis Re Sampling
080924 Measurement System Analysis Re Sampling080924 Measurement System Analysis Re Sampling
080924 Measurement System Analysis Re Sampling
rwmill9716
 
Adapting to Adaptive
Adapting to AdaptiveAdapting to Adaptive
Adapting to Adaptive
Angelo Tinazzi
 
Measurement Procedures for Design and Enforcement of Harm Claim Thresholds
Measurement Procedures for Design and Enforcement of Harm Claim ThresholdsMeasurement Procedures for Design and Enforcement of Harm Claim Thresholds
Measurement Procedures for Design and Enforcement of Harm Claim Thresholds
Pierre de Vries
 
CT Dose Notifications and Alerts AAPM 2014
CT Dose Notifications and Alerts AAPM 2014CT Dose Notifications and Alerts AAPM 2014
CT Dose Notifications and Alerts AAPM 2014
KeLu25
 
6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
Bibhuti Prasad Nanda
 
LVTS - Image Resolution Monitor for Litho-Metrology
LVTS - Image Resolution Monitor for Litho-MetrologyLVTS - Image Resolution Monitor for Litho-Metrology
LVTS - Image Resolution Monitor for Litho-Metrology
Vladislav Kaplan
 
ch01.pdf
ch01.pdfch01.pdf
ch01.pdf
HaneenWaleed3
 
Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...
Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...
Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...
IRJET Journal
 
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process Capability
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process CapabilityJavier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process Capability
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process Capability
J. García - Verdugo
 
ARIMA Model.ppt
ARIMA Model.pptARIMA Model.ppt
ARIMA Model.ppt
KaushikRaghavan4
 
ARIMA Model for analysis of time series data.ppt
ARIMA Model for analysis of time series data.pptARIMA Model for analysis of time series data.ppt
ARIMA Model for analysis of time series data.ppt
REFOTDEBuea
 
ARIMA Model.ppt
ARIMA Model.pptARIMA Model.ppt
ARIMA Model.ppt
PatriaYunita
 
Sequential estimation of_discrete_choice_models
Sequential estimation of_discrete_choice_modelsSequential estimation of_discrete_choice_models
Sequential estimation of_discrete_choice_models
YoussefKitane
 
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
Bibhuti Prasad Nanda
 
Quality assurance of treatment planning system by Rahim Gohar
Quality assurance of treatment planning system by Rahim GoharQuality assurance of treatment planning system by Rahim Gohar
Quality assurance of treatment planning system by Rahim Gohar
Rahim Gohar
 

Similar to IMRT_VMAT_Session 5_How to fine-tune the commissioning of a TPS.pptx (20)

LINAC COMMSSN.ppt
LINAC COMMSSN.pptLINAC COMMSSN.ppt
LINAC COMMSSN.ppt
 
080924 Measurement System Analysis Re Sampling
080924 Measurement System Analysis Re Sampling080924 Measurement System Analysis Re Sampling
080924 Measurement System Analysis Re Sampling
 
Adapting to Adaptive
Adapting to AdaptiveAdapting to Adaptive
Adapting to Adaptive
 
Measurement Procedures for Design and Enforcement of Harm Claim Thresholds
Measurement Procedures for Design and Enforcement of Harm Claim ThresholdsMeasurement Procedures for Design and Enforcement of Harm Claim Thresholds
Measurement Procedures for Design and Enforcement of Harm Claim Thresholds
 
I M R Tintro
I M R TintroI M R Tintro
I M R Tintro
 
CT Dose Notifications and Alerts AAPM 2014
CT Dose Notifications and Alerts AAPM 2014CT Dose Notifications and Alerts AAPM 2014
CT Dose Notifications and Alerts AAPM 2014
 
100018718.ppt
100018718.ppt100018718.ppt
100018718.ppt
 
6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
6Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
 
LVTS - Image Resolution Monitor for Litho-Metrology
LVTS - Image Resolution Monitor for Litho-MetrologyLVTS - Image Resolution Monitor for Litho-Metrology
LVTS - Image Resolution Monitor for Litho-Metrology
 
ch01.pdf
ch01.pdfch01.pdf
ch01.pdf
 
Sheikh-Bagheri_etal
Sheikh-Bagheri_etalSheikh-Bagheri_etal
Sheikh-Bagheri_etal
 
Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...
Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...
Enabling Value added Product (UTR) Rolling using Artificial Intelligence base...
 
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process Capability
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process CapabilityJavier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process Capability
Javier Garcia - Verdugo Sanchez - Six Sigma Training - W1 Process Capability
 
ARIMA Model.ppt
ARIMA Model.pptARIMA Model.ppt
ARIMA Model.ppt
 
ARIMA Model for analysis of time series data.ppt
ARIMA Model for analysis of time series data.pptARIMA Model for analysis of time series data.ppt
ARIMA Model for analysis of time series data.ppt
 
ARIMA Model.ppt
ARIMA Model.pptARIMA Model.ppt
ARIMA Model.ppt
 
Sequential estimation of_discrete_choice_models
Sequential estimation of_discrete_choice_modelsSequential estimation of_discrete_choice_models
Sequential estimation of_discrete_choice_models
 
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
Six sigma-in-measurement-systems-evaluating-the-hidden-factory (2)
 
Quality assurance of treatment planning system by Rahim Gohar
Quality assurance of treatment planning system by Rahim GoharQuality assurance of treatment planning system by Rahim Gohar
Quality assurance of treatment planning system by Rahim Gohar
 
Session 9 radiation oncology
Session 9 radiation oncologySession 9 radiation oncology
Session 9 radiation oncology
 

Recently uploaded

HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...
HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...
HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...
GL Anaacs
 
BRACHYTHERAPY OVERVIEW AND APPLICATORS
BRACHYTHERAPY OVERVIEW  AND  APPLICATORSBRACHYTHERAPY OVERVIEW  AND  APPLICATORS
BRACHYTHERAPY OVERVIEW AND APPLICATORS
Krishan Murari
 
Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...
Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...
Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...
Savita Shen $i11
 
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists  Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Saeid Safari
 
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...
kevinkariuki227
 
ARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTS
ARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTSARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTS
ARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTS
Dr. Vinay Pareek
 
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness JourneyTom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
greendigital
 
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
Triangles of Neck and Clinical Correlation by Dr. RIG.pptxTriangles of Neck and Clinical Correlation by Dr. RIG.pptx
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
Dr. Rabia Inam Gandapore
 
KDIGO 2024 guidelines for diabetologists
KDIGO 2024 guidelines for diabetologistsKDIGO 2024 guidelines for diabetologists
KDIGO 2024 guidelines for diabetologists
د.محمود نجيب
 
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Oleg Kshivets
 
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
How STIs Influence the Development of Pelvic Inflammatory Disease.pptxHow STIs Influence the Development of Pelvic Inflammatory Disease.pptx
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
FFragrant
 
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?Report Back from SGO 2024: What’s the Latest in Cervical Cancer?
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?
bkling
 
Non-respiratory Functions of the Lungs.pdf
Non-respiratory Functions of the Lungs.pdfNon-respiratory Functions of the Lungs.pdf
Non-respiratory Functions of the Lungs.pdf
MedicoseAcademics
 
NVBDCP.pptx Nation vector borne disease control program
NVBDCP.pptx Nation vector borne disease control programNVBDCP.pptx Nation vector borne disease control program
NVBDCP.pptx Nation vector borne disease control program
Sapna Thakur
 
For Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #Girls
For Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #GirlsFor Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #Girls
For Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #Girls
Savita Shen $i11
 
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdf
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfMANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdf
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdf
Jim Jacob Roy
 
Alcohol_Dr. Jeenal Mistry MD Pharmacology.pdf
Alcohol_Dr. Jeenal Mistry MD Pharmacology.pdfAlcohol_Dr. Jeenal Mistry MD Pharmacology.pdf
Alcohol_Dr. Jeenal Mistry MD Pharmacology.pdf
Dr Jeenal Mistry
 
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidadeNovas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Prof. Marcus Renato de Carvalho
 
Superficial & Deep Fascia of the NECK.pptx
Superficial & Deep Fascia of the NECK.pptxSuperficial & Deep Fascia of the NECK.pptx
Superficial & Deep Fascia of the NECK.pptx
Dr. Rabia Inam Gandapore
 
Sex determination from mandible pelvis and skull
Sex determination from mandible pelvis and skullSex determination from mandible pelvis and skull
Sex determination from mandible pelvis and skull
ShashankRoodkee
 

Recently uploaded (20)

HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...
HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...
HOT NEW PRODUCT! BIG SALES FAST SHIPPING NOW FROM CHINA!! EU KU DB BK substit...
 
BRACHYTHERAPY OVERVIEW AND APPLICATORS
BRACHYTHERAPY OVERVIEW  AND  APPLICATORSBRACHYTHERAPY OVERVIEW  AND  APPLICATORS
BRACHYTHERAPY OVERVIEW AND APPLICATORS
 
Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...
Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...
Phone Us ❤85270-49040❤ #ℂall #gIRLS In Surat By Surat @ℂall @Girls Hotel With...
 
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists  Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists
 
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...
 
ARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTS
ARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTSARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTS
ARTHROLOGY PPT NCISM SYLLABUS AYURVEDA STUDENTS
 
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness JourneyTom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journey
 
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
Triangles of Neck and Clinical Correlation by Dr. RIG.pptxTriangles of Neck and Clinical Correlation by Dr. RIG.pptx
Triangles of Neck and Clinical Correlation by Dr. RIG.pptx
 
KDIGO 2024 guidelines for diabetologists
KDIGO 2024 guidelines for diabetologistsKDIGO 2024 guidelines for diabetologists
KDIGO 2024 guidelines for diabetologists
 
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...
 
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
How STIs Influence the Development of Pelvic Inflammatory Disease.pptxHow STIs Influence the Development of Pelvic Inflammatory Disease.pptx
How STIs Influence the Development of Pelvic Inflammatory Disease.pptx
 
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?Report Back from SGO 2024: What’s the Latest in Cervical Cancer?
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?
 
Non-respiratory Functions of the Lungs.pdf
Non-respiratory Functions of the Lungs.pdfNon-respiratory Functions of the Lungs.pdf
Non-respiratory Functions of the Lungs.pdf
 
NVBDCP.pptx Nation vector borne disease control program
NVBDCP.pptx Nation vector borne disease control programNVBDCP.pptx Nation vector borne disease control program
NVBDCP.pptx Nation vector borne disease control program
 
For Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #Girls
For Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #GirlsFor Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #Girls
For Better Surat #ℂall #Girl Service ❤85270-49040❤ Surat #ℂall #Girls
 
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdf
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdfMANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdf
MANAGEMENT OF ATRIOVENTRICULAR CONDUCTION BLOCK.pdf
 
Alcohol_Dr. Jeenal Mistry MD Pharmacology.pdf
Alcohol_Dr. Jeenal Mistry MD Pharmacology.pdfAlcohol_Dr. Jeenal Mistry MD Pharmacology.pdf
Alcohol_Dr. Jeenal Mistry MD Pharmacology.pdf
 
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidadeNovas diretrizes da OMS para os cuidados perinatais de mais qualidade
Novas diretrizes da OMS para os cuidados perinatais de mais qualidade
 
Superficial & Deep Fascia of the NECK.pptx
Superficial & Deep Fascia of the NECK.pptxSuperficial & Deep Fascia of the NECK.pptx
Superficial & Deep Fascia of the NECK.pptx
 
Sex determination from mandible pelvis and skull
Sex determination from mandible pelvis and skullSex determination from mandible pelvis and skull
Sex determination from mandible pelvis and skull
 

IMRT_VMAT_Session 5_How to fine-tune the commissioning of a TPS.pptx

  • 1. 5 How to fine-tune the commissioning of a TPS Stephen Gardner Medical Physicist June 18 Henry Ford Health System (Detroit, MI, USA) 1
  • 2. Outline for today’s session 1. Spot checking your commissioning data 1. Using MPPG 5A report as a reference/outline for photon beam model validation 2. Summary of validation tests 2. Tweaking TPS: DLG and MLC transmission • Create a new “commissioning” machine in your TPS • Compare to measured data and perform iterations of DLG and MLC transmission adjustments 2
  • 3. Learning Objectives: After this session, you will… o Be able to perform a comprehensive but quick spot-check of commissioning data o Understand the detailed, step-by-step process of how to adjust DLG and MLC transmission in the TPS, referencing their clinic’s data o Be able to execute the logistics and team communications needed to safely fine-tune commissioning (e.g., creating a separate “machine”)
  • 4. 1. Spot checking your commissioning data 4
  • 5. ZOOM POLL The dosimetric leaf gap (DLG) represents: A. The difference in the physical leaf end and the dosimetric field edge B. The minimum gap that is possible for an MLC system C. The width of the sweeping gap field used during measurements D. The width of the penumbra of an MLC-defined field 5
  • 6. ZOOM POLL The dosimetric leaf gap (DLG) represents: A. The difference in the physical leaf end and the dosimetric field edge B. The minimum gap that is possible for an MLC system C. The width of the sweeping gap field used during measurements D. The width of the penumbra of an MLC-defined field 6
  • 7. References/Guides for Photon Beam Commissioning o MPPG 5A has proven to be an extremely helpful guide for commissioning photon algorithms – published in 2015 • https://doi.org/10.1120/jacmp.v16i5.5768 o The strength of this document is that it covers many aspects of algorithm performance in a comprehensive, clear, and concise way o Scope of the document – gives recommendations for: • Data Acquisition and Processing • Algorithm Validation (Photon and Electron) – Basic model validation – Heterogeneity correction validation (not included in this lecture) – IMRT/VMAT dose validation 7
  • 8. MPPG 5A Breakdown o Table 3 • Basic validation of beam model – comparison in beam configuration workspace, dose normalization is accurate o Table 4 • More in-depth validation of 3D-CRT delivery – measurements of dose agreement in high-dose region, penumbra, and out-of-field region o Table 5 • Summary of dose agreement tolerances o Table 6 (N/A for this lecture) – heterogeneity correction validation o Table 7 • IMRT/VMAT Validation – including TG-119/Clinical Case validation
  • 9. Table 3: Basic Model Validation o Use Table 3 from the MPPG document to perform basic validation of the model: • (5.1) Within the physics/beam config module, compare PDD and profile for large field (calculated vs. measured) • (5.2) Within a test plan in the TPS - calculate a plan using absolute dose calibration conditions and ensure that you are calculating 1 cGy/MU at the calibration point (sanity check!) • (5.3) Quick check of PDD and output factor (OF) – within a test plan in the TPS, compare calculated PDD and OF to measured data o Note – these tests don’t require any new measurements! Just some re 9
  • 10. Table 3: Examples – Test 5.1 o Test 5.1 – Within the physics module (beam configuration workspace), compare the PDD and profile – measured vs. calculated dose 10
  • 11. Table 3: Examples – Test 5.2 o Test 5.2 – Calculate plan using calibration geometry and ensure dose at calibration depth is 1 cGy/MU. ** For our clinic, the calibration geometry is 10x10 cm2 field size, 100 cm SSD, with calibration depth at dmax. 11
  • 12. Table 3: Examples – Test 5.3 o Test 5.3 – Calculate a plan in the TPS that simulates scanning data and compare calculated vs. measured • This requires the user to take a line profile at the appropriate depth ** For our clinic, this involved calculating a plan at 100 SSD for the relevant field size
  • 13. Table 4: Basic Photon Beam Validation Summary o To perform this set of validation tests, measure the absolute dose at several points for each of these fields: • Different depths (slightly beyond dmax, mid-range/10-15 cm depth, and deep/25-30 cm depth) • Different off-axis positions – high dose, penumbra, and low dose 13
  • 14. Table 4: Examples - Test o Test 5.4 – small MLC-defined field (4x4 cm2 MLC field and 5x5 cm2 jaw) o Test 5.5 – large MLC-defined field with extensive blocking o Test 5.6-5.7 – use same aperture with different SSD ** For each of these, perform measurements at high dose, penumbra, low dose regions at dmax depth, 10 cm depth, and 25 cm depth. Test 5.4 Test 5.5 Tests 5.6-5.7
  • 15. Table 5: Evaluation Methods and Tolerances o Three different regions are specified: high dose, penumbra, and low dose tail • For high dose and low dose tail regions – tolerance is based on dose difference (Percent) • For penumbra – tolerance is based on distance to agreement (DTA)
  • 16. Table 7: VMAT/IMRT Summary o The IMRT/VMAT tests are in addition to the tests in Table 3/4 from prior slides o In my opinion - the most important tests from this group are the TG-119 tests (7.3) and Clinical tests (7.4) • These plans will be used to validate and adjust the TPS model as needed to ensure optimal IMRT/VMAT delivery
  • 17. Summary – Validation Testing (Scanning/Open Field) o Scanning Data – • Verify profiles using flatness and symmetry for small, mid-size, and large field sizes at dmax, 10 cm, and 30 cm depth – For example: 4x4, 10x10, and 30x30 cm2 field sizes (you can verify additional field sizes if warranted) – Typically, we want to see symmetry < 1% and then flatness consistent with past results (within 1% of baseline if available) – Compare measurement to calculation in TPS to verify model behavior • Verify PDD for small, mid-size, and large field sizes by comparing measured and calculated doses – While you are scanning these - include MLC-defined small field PDD to satisfy MPPG 5A test 7.1 (if you have access to a small field detector such as diode) o Output Factors – verify agreement between calculated and measured output factors for a variety of field sizes, ranging from 3x3 to 40x40 cm2 • While you are measuring these - include MLC-defined small field OF to satisfy MPPG 5A test 7.2 (again if you have access to a small field detector such as diode, micro ion chamber, etc.)
  • 18. TG-119 and Clinical Case PSQA o TG-119 Planning Guide, Reporting Form, and Structure Sets can be found on the AAPM website: https://www.aapm.org/pubs/tg119/default.asp o TG-119 data set includes DICOM CT, RT Structure files as well as planning goals and instruction document: • C-Shape • Mock HN plan • Mock Prostate • Multi-Target o Additional plans for testing – representative plans from previous patients • Replan as needed with new machine/beam model • Should include typical disease sites encountered at your center – HN, Prostate, Lung, Brain, etc.
  • 19. 2. Tweaking TPS: DLG and MLC transmission 19
  • 20. Overview for this Section o MLC DLG and Transmission – effect on the dose distribution for various delivery modalities (static fields, IMRT, and VMAT) o Practical Overview/Tips on MLC Parameter Adjustment o Creating a new ‘commissioning’ machine for your testing o How to adjust DLG and MLC Transmission - Detailed, step-by- step process of how to adjust these within the TPS, referencing their clinic’s data o Practical dry-run of adjusting model parameters with realistic clinical data
  • 21. MLC DLG and Transmission – Effect on the Dose Distribution for Various Delivery Modalities
  • 22. MLC DLG Effect – Static Fields 0 20 40 60 80 100 0 2 4 6 8 10 12 14 16 Distance Along Profile (cm) DLG =0.100 cm DLG =0.200 cm
  • 23. MLC Transmission Effect – Static Fields 0 20 40 60 80 100 0 2 4 6 8 10 12 14 16 Distance Along Profile (cm) MLC_trans = 1.6% MLC_trans = 2.5%
  • 24. MLC DLG Effect – IMRT Delivery 0 20 40 60 80 100 120 0 2 4 6 8 10 12 14 16 18 20 Relative Dose (%) Distance Along Profile (cm) DLG Effect - IMRT Delivery DLG = 0.14 cm DLG = 0.16 cm DLG = 0.115 cm
  • 25. MLC DLG Effect – IMRT Delivery (cont’d) 0 20 40 60 80 100 120 8 9 10 11 12 13 14 15 16 17 18 Relative Dose (%) Distance Along Profile (cm) DLG Effect - IMRT Delivery DLG = 0.14 cm DLG = 0.16 cm DLG = 0.115 cm Change in penumbra width Change in high dose magnitude
  • 26. MLC Transmission Effect – IMRT Delivery 20 30 40 50 60 70 80 90 100 110 0 2 4 6 8 10 12 14 16 18 20 Relative Dose (%) Distance Along Profile (cm) MLC Transmission Effect - IMRT Delivery MLC_trans = 1.65% MLC_trans = 1.85%
  • 27. MLC DLG Effect (TG-119 C-Shape) VMAT Delivery 0 20 40 60 80 100 120 0 2 4 6 8 10 12 14 Relative Dose (%) Distance Along Profile (cm) DLG Effect - VMAT Delivery DLG = 0.14 cm DLG = 0.16 cm DLG = 0.115 cm
  • 28. MLC DLG Effect (TG-119 C-Shape) VMAT Delivery 90 92 94 96 98 100 102 104 0 2 4 6 8 10 12 14 Relative Dose (%) Distance Along Profile (cm) DLG Effect - VMAT Delivery DLG = 0.14 cm DLG = 0.16 cm DLG = 0.115 cm Smaller Change in penumbra width compared to IMRT Smaller change in high dose compared to IMRT
  • 29. MLC Transmission Effect – VMAT Delivery 10 20 30 40 50 60 70 80 90 100 110 0 2 4 6 8 10 12 Relative Dose (%) Distance Along Profile (cm) MLC Transmission Effect - VMAT Delivery MLC_trans = 1.65% MLC_trans = 1.85%
  • 30. How to – create a new ‘commissioning’ machine in your TPS and adjust DLG/MLC Transmission o General idea is to… • Create a copy of the machine • Create a copy of the beam model • Adjust DLG/MLC Transmission to improve agreement
  • 31. Creating a ‘Commissioning’ Machine o For ARIA Users, the process is: • RT Admin Workspace – Step 1: Select machine to copy -> Insert -> Export Machine… – Step 2: Re-import the machine you just exported and name it appropriately – Step 3: Rename imported machine something like ‘Test_Physics’ – Step 4: Ensure MLC add-on information matches the real machine and enter starting DLG/MLC transmission values Step 1: Export Step 2: Re-import Step 4: MLC Add-on Material and DLG/MLC trans Step 3: Update Machine Name
  • 32. Creating a copy of the beam model for testing o For ARIA Users, the process is: • Beam Config Workspace – Step 1: select the machine (Test_Physics) / energy (6x) / algorithm (AAA_11030) and right-click -> New Beam Data… – Step 2: setup copy of beam model ▪ Enter appropriate therapy unit name ▪ Select ‘Copy existing data to the calculation model’ • DO NOT select ‘assign’ • Ensure that you have selected the correct beam model to copy and click OK – Step 3: Match and Assign Add-Ons – select ‘In Use’ for open field and EDW and select Automatic Match for All. – Step 4: Spot check values for Gamma Error Histogram and Output Factors to verify consistency against clinical machine and approve test model (right-click on the model -> Approve) Step 3: Match and assign Add-ons Step 2: Setup copy of beam model Step 1: select model Step 4: Approve Model
  • 33. Practical Overview/Tips on MLC Parameter Adjustment
  • 34. How do I adjust the DLG/MLC Transmission Values? o For ARIA v13 and later: • RT Admin Workspace – – **Note – this will define these values for all beam models for this machine** – Go to ‘Radiation and Imaging Devices’ – Select the test physics machine and go to ‘MLC’ tab – Enter values for MLC Transmission factor and DLG within the ‘Dosimetric Properties’ section o For ARIA v11 and earlier: • Beam Configuration Workspace – – Select the test physics beam model – Go to Beam Data -> Dosimetric Data and enter MLC Transmission factor and DLG o For other TPS vendors – consult with the manual for instructions on this process
  • 35. Initial Overview – Iterative Tweaking Process • Resource for TPS beam model validation – Medical Physics Practice Guideline 5.A • MLC Parameter/Beam Model Optimization (like any optimization process) is iterative • The overall process goes something like: 1. Acquire initial measurements for MLC parameters -> input to TPS 2. Calculate Beam Model 3. Generate/calculate IMRT/VMAT plans for verification • For conventional planning – use TG-119 dataset and some previous clinical plans if available • For SRS/SBRT planning – critical to use representative stereotactic plans to validate the beam model!!! • These treatment plans should meet the relevant clinical goals/constraints to best simulate a typical IMRT/VMAT delivery 4. Acquire point dose measurements for verification IMRT/VMAT plans • Proper detector selection is critical – ideal chamber is a small volume ion chamber such as CC01 or PinPoint chamber • High dose readings to simulate the target volume! • Low dose readings to simulate critical organs at risk! • The point dose measurements will the primary means for MLC parameter selection 5. Acquire planar dose measurements using Gafchromic film or array device • Compare results once MLC parameters are finalized from point dose measurements
  • 36. MLC Parameter Testing – Practical Key Points • Key Points for Emphasis • Use real IMRT/VMAT plans to validate the beam model/MLC parameter values • TG-119 data sets • Previous clinical cases • Make sure the intended use of the linac is included in the test cases! • Measurements should include both point and planar dose analysis • My clinic preference – use point dose measurements for initial tweaking of MLC parameters • When is the model good enough? • TG-119 utilized confidence limits for QA results • High Dose Point Measurement → CL = ±4.5% • Low Dose Point Measurement → CL = ±4.7% • Planar Dose Measurement → Gamma(3%,3mm) > 87.6% • TG-218 proposed tolerance limits and action limits for pre-treatment QA: • Tolerance Limit: • Ion Chamber Measurement <2% • Gamma(3%,2mm) > 95% • Action Limit: • Ion Chamber Measurement <2% • Gamma(3%,2mm) > 95% • Investigate outliers for additional measurements • Aim to get average percent difference close to 0% (Mean Perc. Diff.) • Minimize spread in QA results (Standard Deviation Of Perc. Diff.) • Compare to other institutions/literature with similar linac and TPS • If possible – obtain independent audit of IMRT/VMAT delivery from another physicist/institution • How much can you tweak the TPS values? • My preference – tweak as little as possible to get agreement that fulfills clinical goals of the machine
  • 37. MLC Parameters – Interpreting Results • Which way do I need to tweak the value? • Increasing DLG value → Increase in calculated dose • Increasing MLC Transmission value → Increase in calculated dose • Example: • If plan dose is higher than measured dose → the next step is to increase DLG and/or MLC Transmission and re- calculate Example: Plan dose is higher than film dose → consider decreasing DLG and/or MLC Transmission
  • 38. DLG Adjust Details – Test Plan Process 1. Treatment Planning – Develop a good quality plan using the test plan structure set. Have primary treatment planning staff generate the plan if possible! 2. QA Plan – Map the plan from step 1 onto the appropriate phantom • Need to perform both chamber measurement and a planar dose/fluence measurement • Planar dose measurement can be using film, detector array, or even the EPID • Phantom choices include: • Solid Water slab phantom with place for chamber/film • Acrylic phantom with place for chamber/film • Detector array (MapCheck, ArcCheck, Delta4, Matrixx, etc.) • EPID measurement (Portal Dosimetry) 3. Measure QA plan and compare to predicted dose from TPS calculation 4. Compile all test plan results (IMRT and VMAT) before making any adjustments • Note – IMRT and VMAT trends can differ!!
  • 39. Practical dry-run of adjusting model parameters with realistic clinical data o The background information for this example: • TG-119 plans and Clinical Cases (IMRT and VMAT) for 10x energy modewere measured with ion chamber in high dose and lose dose region • Starting point was the initial measured DLG value of 0.115 cm and MLC Transmission = 1.65% • Total Case Breakdown – TG-119: 3 IMRT and 3 VMAT – Clinical Cases: 2 IMRT and 2 VMAT
  • 40. MLC Parameter Selection Summary Points – 10 MV beam modeling process • Decision on MLC parameters such as DLG and Leaf Transmission depend on: • The clinical goals for the beam model: • Which disease sites will be treated routinely? • Which modality will be used more often – IMRT or VMAT? • The trend in the data: • Which parameter values will minimize the percent difference between planned and measured doses? • Which parameter values will minimize the spread in the results comparing planned and measured doses? • Which parameter values will minimize outliers in the data?
  • 41. Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.115 cm) [MLC_trans = 0.0185] Perc. Diff. C Shape 2.154 2.052 4.73% H&N 2.100 2.095 0.24% H&NSIB 2.176 2.135 1.86% Prostate 1.988 1.957 1.54% Prostate LN 1.968 1.946 1.11% C Shape 2.481 2.470 0.45% H&N 2.195 2.191 0.19% H&NSIB 2.122 2.127 -0.22% Prostate 1.997 1.977 1.02% Prostate LN 1.893 1.937 -2.32% VMAT Average 1.90% VMAT St. Dev. 1.70% IMRT Average -0.18% IMRT St. Dev. 1.28% Overall Average 0.86% Overall St. Dev. 1.79% Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.115 cm) [MLC_trans = 0.0185] Perc. Diff. C Shape 0.320 0.344 -7.51% H&N 1.314 1.297 1.28% H&NSIB 1.124 1.126 -0.18% Prostate 1.322 1.279 3.22% Prostate LN 0.890 0.874 1.80% C Shape 0.489 0.520 -6.41% H&N 1.316 1.331 -1.16% H&NSIB 1.201 1.236 -2.94% Prostate 1.650 1.630 1.18% Prostate LN 1.136 1.163 -2.35% VMAT Average -0.28% VMAT St. Dev. 4.22% IMRT Average -2.33% IMRT St. Dev. 2.77% Overall Average -1.31% Overall St. Dev. 3.54% IMRT Results (TG-119 Table VII)- High Dose VMAT IMRT Results (TG-119 and Clinical Cases)- Low Dose VMAT Iteration 1 – DLG = 0.115 cm / MLC_Trans = 1.65% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 0 1 2 3 4 5 6 Percent Difference Iteration # VMAT - High Dose IMRT - High Dose VMAT - Low Dose IMRT - Low Dose
  • 42. Iteration 2 – DLG = 0.140 cm / MLC_Trans = 1.65% Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.140 cm) [MLC_trans = 0.0165] Perc. Diff. C Shape 2.154 2.048 4.91% H&N 2.100 2.087 0.62% H&NSIB 2.176 2.128 2.19% Prostate 1.988 1.954 1.69% Prostate LN 1.968 1.942 1.31% C Shape 2.481 2.448 1.34% H&N 2.195 2.173 1.01% H&NSIB 2.122 2.113 0.44% Prostate 1.997 1.974 1.17% Prostate LN 1.893 1.921 -1.47% VMAT Average 2.15% VMAT St. Dev. 1.65% IMRT Average 0.49% IMRT St. Dev. 1.15% Overall Average 1.32% Overall St. Dev. 1.60% Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.140 cm) [MLC_trans = 0.0165] Perc. Diff. C Shape 0.320 0.338 -5.64% H&N 1.314 1.287 2.04% H&NSIB 1.124 1.117 0.62% Prostate 1.322 1.275 3.52% Prostate LN 0.890 0.867 2.59% C Shape 0.489 0.496 -1.50% H&N 1.316 1.311 0.36% H&NSIB 1.201 1.220 -1.61% Prostate 1.650 1.626 1.43% Prostate LN 1.136 1.149 -1.11% VMAT Average 0.63% VMAT St. Dev. 3.66% IMRT Average -0.49% IMRT St. Dev. 1.33% Overall Average 0.07% Overall St. Dev. 2.66% IMRT Results (TG-119 Table VII)- High Dose VMAT IMRT Results (TG-119 and Clinical Cases)- Low Dose VMAT -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 0 1 2 3 4 5 6 Percent Difference Iteration # VMAT - High Dose IMRT - High Dose VMAT - Low Dose IMRT - Low Dose
  • 43. Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.115 cm) [MLC_trans = 0.0165] Perc. Diff. C Shape 2.154 2.040 5.29% H&N 2.100 2.074 1.24% H&NSIB 2.176 2.116 2.74% Prostate 1.988 1.945 2.14% Prostate LN 1.968 1.932 1.82% C Shape 2.481 2.385 3.88% H&N 2.195 2.151 2.01% H&NSIB 2.122 2.096 1.24% Prostate 1.997 1.966 1.57% Prostate LN 1.893 1.892 0.06% VMAT Average 2.65% VMAT St. Dev. 1.57% IMRT Average 1.75% IMRT St. Dev. 1.39% Overall Average 2.20% Overall St. Dev. 1.48% Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.115 cm) [MLC_trans = 0.0165] Perc. Diff. C Shape 0.320 0.337 -5.33% H&N 1.314 1.276 2.88% H&NSIB 1.124 1.108 1.42% Prostate 1.322 1.262 4.50% Prostate LN 0.890 0.862 3.15% C Shape 0.489 0.482 1.36% H&N 1.316 1.290 1.96% H&NSIB 1.201 1.203 -0.19% Prostate 1.650 1.615 2.09% Prostate LN 1.136 1.131 0.47% VMAT Average 1.33% VMAT St. Dev. 3.88% IMRT Average 1.14% IMRT St. Dev. 0.98% Overall Average 1.23% Overall St. Dev. 2.67% IMRT VMAT IMRT Results (TG-119 and Clinical Cases)- High Dose Results (TG-119 and Clinical Cases)- Low Dose VMAT Iteration 3 – DLG = 0.140 cm / MLC_Trans = 1.85% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 0 1 2 3 4 5 6 Percent Difference Iteration # VMAT - High Dose IMRT - High Dose VMAT - Low Dose IMRT - Low Dose
  • 44. Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.16 cm) [MLC_trans = 0.0165] Perc. Diff. C Shape 2.154 2.056 4.54% H&N 2.100 2.097 0.15% H&NSIB 2.176 2.138 1.73% Prostate 1.988 1.960 1.39% Prostate LN 1.968 1.949 0.96% C Shape 2.481 2.498 -0.68% H&N 2.195 2.192 0.14% H&NSIB 2.122 2.127 -0.22% Prostate 1.997 1.981 0.82% Prostate LN 1.893 1.943 -2.64% VMAT Average 1.75% VMAT St. Dev. 1.67% IMRT Average -0.52% IMRT St. Dev. 1.31% Overall Average 0.62% Overall St. Dev. 1.85% Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.16 cm) [MLC_trans = 0.0165] Perc. Diff. C Shape 0.320 0.340 -6.26% H&N 1.314 1.296 1.36% H&NSIB 1.124 1.123 0.09% Prostate 1.322 1.285 2.76% Prostate LN 0.890 0.872 2.03% C Shape 0.489 0.508 -3.96% H&N 1.316 1.328 -0.93% H&NSIB 1.201 1.234 -2.77% Prostate 1.650 1.633 1.00% Prostate LN 1.136 1.155 -1.64% VMAT Average 0.00% VMAT St. Dev. 3.64% IMRT Average -1.66% IMRT St. Dev. 1.88% Overall Average -0.83% Overall St. Dev. 2.86% IMRT Results (TG-119 Table VII)- High Dose VMAT IMRT Results (TG-119 and Clinical Cases)- Low Dose VMAT Iteration 4 – DLG = 0.160 cm / MLC_Trans = 1.65% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 0 1 2 3 4 5 6 Percent Difference Iteration # VMAT - High Dose IMRT - High Dose VMAT - Low Dose IMRT - Low Dose
  • 45. Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.16 cm) [MLC_trans = 0.0185] Perc. Diff. C Shape 2.154 2.059 4.40% H&N 2.100 2.105 -0.23% H&NSIB 2.176 2.145 1.40% Prostate 1.988 1.963 1.24% Prostate LN 1.968 1.954 0.70% C Shape 2.481 2.520 -1.57% H&N 2.195 2.209 -0.63% H&NSIB 2.122 2.141 -0.88% Prostate 1.997 1.984 0.67% Prostate LN 1.893 1.960 -3.53% VMAT Average 1.50% VMAT St. Dev. 1.74% IMRT Average -1.19% IMRT St. Dev. 1.54% Overall Average 0.16% Overall St. Dev. 2.10% Plan Type Measured Point Dose (cGy) Calculated Dose (DLG = 0.16 cm) [MLC_trans = 0.0185] Perc. Diff. C Shape 0.320 0.345 -7.83% H&N 1.314 1.306 0.60% H&NSIB 1.124 1.132 -0.71% Prostate 1.322 1.289 2.46% Prostate LN 0.890 0.879 1.24% C Shape 0.489 0.531 -8.66% H&N 1.316 1.348 -2.45% H&NSIB 1.201 1.250 -4.11% Prostate 1.650 1.637 0.76% Prostate LN 1.136 1.173 -3.23% VMAT Average -0.85% VMAT St. Dev. 4.07% IMRT Average -3.54% IMRT St. Dev. 3.40% Overall Average -2.19% Overall St. Dev. 3.81% IMRT Results (TG-119 Table VII)- High Dose VMAT IMRT Results (TG-119 and Clinical Cases)- Low Dose VMAT Iteration 5 – DLG = 0.160 cm / MLC_Trans = 1.85% -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 0 1 2 3 4 5 6 Percent Difference Iteration # VMAT - High Dose IMRT - High Dose VMAT - Low Dose IMRT - Low Dose
  • 46. MLC Parameter Iteration Summary – Graphical Analysis -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 0 1 2 3 4 5 6 Percent Difference Iteration # VMAT - High Dose IMRT - High Dose VMAT - Low Dose IMRT - Low Dose Final Value Chosen for Planning
  • 47. Summary – DLG Testing Plan Process 1. Treatment Planning – Develop a good quality plan using the test plan structure set. Have primary treatment planning staff generate the plan if possible! 2. QA Plan – Map the plan from step 1 onto the appropriate phantom • Need to perform both chamber measurement and a planar dose/fluence measurement • Planar dose measurement can be using film, detector array, or even the EPID • Phantom choices include: • Solid Water slab phantom with place for chamber/film • Acrylic phantom with place for chamber/film • Detector array (MapCheck, ArcCheck, Delta4, Matrixx, etc.) • EPID measurement (Portal Dosimetry) 3. Measure QA plan and compare to predicted dose from TPS calculation 4. Compile all test plan results (IMRT and VMAT) before making any adjustments • Note – IMRT and VMAT trends can differ!!
  • 48. Practical Tips – Adjusting Parameters on Approved Beam Models • If you have a beam model that is already approved and need to make adjustments for IMRT/VMAT commissioning: 1. Use caution! Think about what could go wrong before making any adjustments. Discuss with other physicists to make sure you have thought of everything that could come up. 2. Communicate! Once you have a plan, talk about it with relevant staff 3. Calculate! Plan out a time when you can perform the dose calculations with the preliminary MLC DLG/Transmission values. 1. This may need to be done after-hours or on a weekend. 4. Reset! Depending on the workflow, make sure to reset the MLC parameters back to the clinically approved values. 1. If you have multiple DLG/Transmission values you would like to test (multiple iterations), this is the time to perform all iterations 5. Verify! Once you have reset the MLC parameters back to the original values, re-calculate a set of test plans to verify constancy. 6. Compare! Once you have the calculations done, you can compare to the measured values and determine optimal parameters
  • 49. SRS/SBRT – You may need a separate algorithm! • My experience – the level of modulation for conventional IMRT/VMAT planning is quite different than for SRS/SBRT planning • Typically, the optimal DLG value for TG-119 planning is different than for representative SRS/SBRT cases • Example at left: 6FFF beam used for SRS/SBRT delivery at one of our • More data for this example shown on next slide
  • 50. CONCLUSION o A ‘commissioning’ machine can be created to test out the parameters for the TPS model o The TPS model will be adjusted based on comparison of calculated and measured results for IMRT/VMAT plans o A representative process for adjusting MLC parameters has been shared for learning purposes o The next lecture is transitions from commissioning and adjusting the beam model to routine QA of treatment plans. The topic is: “Patient-Specific and High-yield Machine QA for IMRT” 50
  • 51. REFERENCES o AAPM Task Group 119: https://www.aapm.org/pubs/tg119/default.asp o Medical Physics Practice Guidelines (MPPG) 5A: https://doi.org/10.1120/jacmp.v16i5.5768 51 Thank you for your attention!