Acknowledgement
Therapy Continuing Education Course
Clinical Implementation of IMRT
for Lung Cancers
Physics
Physics colleagues
colleagues
–– Xiaochun
Xiaochun Wang,
Wang, PhD
PhD
–– Xiaodong
Xiaodong Zhang,
Zhang, PhD
PhD
–– Maria
Maria Jauregui
Jauregui
–– Lei
Lei Dong,
Dong, PhD
PhD
–– Siyoung
Siyoung Jang,
Jang, PhD
PhD
–– Radhe
Radhe Mohan,
Mohan, PhD
PhD
H.
H. Helen
Helen Liu,
Liu, PhD
PhD
Department
Department of
of Radiation
Radiation Physics,
Physics,
U.T.
U.T. MD
MD Anderson
Anderson Cancer
Cancer Center,
Center, Houston,
Houston, TX
TX
AAPM,
AAPM, Seattle,
Seattle, 2005
2005
Prerequisites:
Basic Concepts of IMRT
Overview
•• Introduction
Introduction
–– Clinical
Clinical Rationales
Rationales
–– Concerns
Concerns and
and Myths
Myths
–– Clinical
Clinical Applications
Applications
•• Methodology
Methodology
–– Patient
Patient Selection
Selection
–– Treatment
Treatment Simulation
Simulation
–– Target
Target Delineation
Delineation
–– Treatment
Treatment Planning
Planning
–– Plan
Plan Evaluation
Evaluation
•• Treatment
Treatment Verification
Verification and
and QA
QA
Oncology
Oncology colleagues
colleagues
–– Hussan
Murshed
Hussan Murshed,
Murshed,, MD
MD
–– Craig
Craig Stevens,
Stevens, MD
MD
–– Thomas
Thomas Guerrero,
Guerrero, MD
MD
–– ZhongXing
Liao
ZhongXing Liao,
Liao,, MD
MD
–– Joe
Joe Chang,
Chang, MD
MD
–– Melinda
Melinda Jeter,
Jeter, MD
MD
–– Ritsuko
Ritsuko Komaki,
Komaki, MD
MD
–– Jim
Jim Cox,
Cox, MD
MD
••
••
••
••
Intensity
Intensity modulation
modulation
Fluence
Fluence modulation
modulation (Open
(Open density
density matrix)
matrix)
Pencil
Pencil beam
beam or
or beamlets
beamlets
Beam
Beam delivery
delivery systems
systems
–– DMLC
DMLC
••
••
••
Delivery:
-shoot, sliding
step
Delivery: stepstep-shoot,
sliding window
window
Control
Control of
of Dose:
Dose: Control
Control points,
points, segments
segments
MUs
MUs in
in IMRT
IMRT
–– Compensators
Compensators
•• Inverse
Inverse planning
planning or
or treatment
treatment planning
planning
optimization
optimization
1
[Introduction]
[Clinical Rationales]
Comparison of IMRT vs 3D for NSCLC
Clinical Rationales
• The benefits of IMRT for Lung Cancers
IMRT
3D
–– Dose
Dose conformity
conformity to
to target
target volumes
volumes
–– Dose
Dose avoidance
avoidance to
to normal
normal structures
structures
•• Sharper
Sharper dose
dose gradient
gradient for
for adjacent
adjacent critical
critical organs:
organs:
spinal
spinal cord,
cord, esophagus,
esophagus, etc
etc
•• Dose
Dose sparing
sparing for
for parallel
parallel organs:
organs: lung,
lung, heart,
heart, liver
liver
Feasibility of sparing lung and other thoracic structures with intensitymodulated radiotherapy for non-small-cell lung cancer. IJROBP, 2004 Mar 15;58(4):1268-79.
•Murshed, Liu, Liao, et al, Dose and volume reduction for normal lung using intensity-modulated
radiotherapy for advanced-stage non-small-cell lung cancer. IJROB, 2004 Mar 15;58(4):1258-67.
[Clinical Rationales]
[Introduction]
Comparison of IMRT vs 3D for NSCLC
80
•• IMRT
IMRT spreads
spreads low
low dose
dose volume
volume for
for lung
lung and
and
normal
normal tissues
tissues
70
Percent lung volume
Concerns and Myths
60
–– Lung
(5
Lung parenchyma
parenchyma may
may be
be sensitive
sensitive to
to low
low doses
doses (5(5-20
Gy
20 Gy)
Gy))
–– Use
Use of
of multiple
multiple IMRT
IMRT beams
beams (( >> 6)
6) may
may result
result in
in
increase
-dose volume
low
increase of
of lowlow-dose
volume to
to normal
normal tissues
tissues
–– The
The effect
effect depends
depends on
on
50
40
30
20
10
V5-3D
V5-IMRT
V10-3D
V10-IMRT
V20-3D V20-IMRT
••
••
••
Beam
Beam angle
angle selection
selection
Inverse
Inverse planning
planning process
process
Type
Type of
of leaf
leaf sequences,
sequences, leaf
leaf leakage,
leakage, MU
MU efficiency
efficiency
*Comparison based sliding-window technique, IMRT results will be improved further with step-shoot technique.
2
[Introduction]
Concerns and Myths
•• Inter-fractional organ
Inter
intra
Inter-- and
and intraintra-fractional
organ motion
motion
–– Respiratory
Respiratory motion
motion can
can be
be aa significant
significant source
source of
of
uncertainty
uncertainty for
for target
target delineation
delineation
–– Interplay
Interplay effect
effect between
between tumor
tumor motion
motion and
and leaf
leaf
motion
motion may
may increase
increase dosimetry
dosimetry uncertainty
uncertainty
•• The
The effect
effect maybe
maybe minor
minor for
for treatment
treatment courses
courses with
with large
large
numbers
numbers of
of fractions
fractions
–– Respiratory
Respiratory motion
motion may
may affect
affect dose
dose to
to normal
normal
structures
structures (lung,
(lung, heart,
heart, esophagus,
esophagus, cord,
cord, etc)
etc)
–– Patient
Patient anatomies
anatomies may
may change
change during
during treatment
treatment
courses
courses
[Introduction]
Clinical Applications
[Introduction]
Concerns and Myths
• Complexity of treatment planning and
delivery
–– Simulation
Simulation and
and planning
planning process
process requires
requires
experience
experience and
and more
more effort/time
effort/time
–– Increase
Increase of
of treatment
treatment and
and delivery
delivery time
time may
may
reduce
reduce patient
patient compliance
compliance and
and comfort
comfort
–– More
More challenges
challenges in
in QA
QA and
and dosimetry
dosimetry
verification
verification compared
compared to
to 3DCRT
3DCRT
[Clinical Applications]
Non-small cell lung cancers
•• Lung
Lung cancers
cancers
–– Non-small cell
Non
Non-small
cell lung
lung cancer
cancer
Single Lesion
Multiple Hilar Lesions
•• Superior
Superior sulcus
sulcus tumors:
tumors: improvement
improvement of
of target
target conformity
conformity
and
and sparing
sparing of
of spinal
spinal cord
cord
•• Advanced
Advanced stage
stage (stage
(stage III,
III, IV):
IV): improvement
improvement of
of target
target
coverage
coverage and
and sparing
sparing of
of lung
lung and
and other
other OARs
OARs
–– Small
Small cell
cell lung
lung cancer
cancer
•• Limited
Limited and
and advanced
advanced stage:
stage: same
same as
as above
above
•• Mesothelioma
Mesothelioma
–– Improvement
Improvement of
of target
target coverage
coverage and
and sparing
sparing of
of
contra-lateral lung,
contra
contra-lateral
lung, liver,
liver, kidneys,
kidneys, cord,
cord, heart
heart
3
[Methodology]
[Clinical Applications]
Patient Selection
Lung cancers
Superior Sulcus Tumors
Mesotheliomas
•• Patient
Patient selection
selection based
based on
on disease
disease characteristics
characteristics
–– Nearby
Nearby critical
critical structures
structures
–– Complex
Complex target
target volumes
volumes
–– Suitable
Suitable target
target size
size
•• IMRT
IMRT may
may not
not offer
offer significant
significant advantage
advantage over
over 3DCRT
3DCRT for
for small
small
lesions
lesions (earlier
(earlier stage)
stage) or
or extremely
extremely large
large lesions
lesions (late
(late stage)
stage)
–– Primary
Primary NSCLC
NSCLC stage
stage III
III lesions
lesions are
are ideal
ideal candidates
candidates for
for
IMRT
IMRT
[Methodology]
[Methodology]
Patient Selection
• Patient selection based on organ motion
–– Immobile
Immobile tumors
tumors are
are preferred
preferred for
for IMRT
IMRT ((
tumor
tumor motion
motion << 0.5
0.5 cm)
cm)
–– For
For mobile
mobile tumors,
tumors, effects
effects of
of tumor
tumor motion
motion
needs
needs to
to be
be considered
considered with
with adequate
adequate
margins
margins and
and dosimetric
dosimetric impact
impact on
on other
other
structures
structures
Treatment Simulation
•• CT
CT simulation
simulation
PET/CT suite with in-room laser
–– Patient
Patient preparation
preparation
••
••
••
Immobilization
Immobilization device
device
Marking
Marking skin
skin
Breathing
Breathing training
training
(optional)
(optional)
–– PET/CT
PET/CT
•• CT
CT attenuation
attenuation correction
correction
•• Regular
Regular PET
PET
–– CT
CT
•• Freebreathing
Freebreathing CT
CT (to
(to be
be
obselete)
)
obselete
obselete)
•• 4DCT
4DCT
–– Data
Data transfer
transfer
4
[Methodology]
Treatment Simulation
[Methodology]
Target Delineation
•• Patient
Patient Setups
Setups and
and Immobilization
Immobilization
–– 4DCT
4DCT :: Assess
Assess tumor/anatomy
tumor/anatomy motion
motion
–– PET/CT:
PET/CT: Assess
Assess target
target extension
extension and
and
nodal
nodal involvement
involvement
–– Alpha
Alpha cradle
cradle
•• Stereotactic
Stereotactic bodybag
bodybag maybe
maybe preferred
preferred
for
for improved
improved precision
precision
––
––
––
––
Wing
Wing board
board
Head
Head holder
holder (optional)
(optional)
TT-bar
-bar and
and arm
arm up
up position
position
Reference
Reference markers
markers are
are placed
placed near
near
carina
carina with
with relatively
relatively stable
stable anatomy
anatomy
–– Isocenter
shift
based
on
planning
Isocenter shift based on planning CT
CT
–– Position
Position variations
variations
•• Arm
Arm down
down or
or setup
setup similar
similar to
to head&neck
head&neck
cases
cases can
can be
be customized
customized for
for special
special
situations
situations
[Methodology]
Target Delineation
• Margins of target volumes
–– GTV
GTV
–– iGTV
iGTV == U[GTV
U[GTVii]] (from
(from all
all respiratory
respiratory phases
phases
and
and PET/CT)
PET/CT)
–– ITV
ITV == iCTV
iCTV == iGTV
iGTV ++ microscopic
microscopic expansion
expansion
–– PTV
PTV == ITV
ITV ++ setup
setup uncertainty
uncertainty
[Methodology]
Treatment Planning
• Inverse planning for lung IMRT
–– IMRT
IMRT Inverse
Inverse Planning
Planning
•• Region-ofROIs))
Region
of-interests (ROIs
((ROIs)
Region-of-interests
•• Fluence
Fluence optimization
optimization
•• MLC
MLC sequences
sequences
–– Plan
Plan Evaluation
Evaluation
–– Beam
Beam configuration
configuration
5
[Methodology]
Inverse Planning
•• Optimization
Optimization engine
engine
–– Specification
Specification of
of objective
objective functions
functions (costs)
(costs)
•• Distance
Distance between
between current
current solution
solution to
to the
the desired
desired one
one
–– Free
Free parameters
parameters for
for optimization
optimization
•• beamlet
beamlet intensity
intensity
–– Search
Search engine
engine
•• Deterministic
Deterministic approaches
approaches (Gradient
(Gradient based)
based)
•• Stochastic
Stochastic approaches
approaches
•• Interface
Interface with
with optimization
optimization engine
engine
–– Objective
Objective functions/constraints
functions/constraints
–– Solution
Solution output
output and
and evaluation
evaluation of
of results
results
[Inverse Planning]
Inverse Planning by Iterative Planning
• Problem
–– Each
Each patient
patient is
is unique
unique
–– Appropriate
Appropriate objectives
objectives are
are difficult
difficult to
to foresee
foresee
–– Inverse
-errors
trial
Inverse planning
planning involve
involve many
many trialtrial-errors
• Solution
–– Feedback
Feedback guided,
guided, stepwise
stepwise progressive,
progressive,
iterative
iterative planning
planning
[Methodology]
Inverse Planning
•• Secrets
Secrets of
of inverse
inverse planning
planning for
for lung
lung IMRT
IMRT
–– Objective
Objective functions
functions are
are the
the steering
steering wheels
wheels for
for the
the
optimization
optimization engine
engine
–– Planners
Planners need
need to
to know
know the
the behavior
behavior of
of the
the
optimization
optimization engine
engine and
and effects
effects of
of choosing
choosing objective
objective
functions
functions
–– Planners
Planners need
need to
to know
know how
how to
to make
make compromises
compromises
among
among conflicting
conflicting goals
goals
•• Tumor
Tumor vs.
vs. lung
lung
•• Different
Different OARs:
OARs: lung,
lung, heart,
heart, cord,
cord, esophagus,
esophagus, tissue
tissue
[Inverse Planning]
ROIs specific for Lung IMRT
•• In
In addition
addition to
to ROIs
ROIs that
that are
are needed
needed for
for regular
regular
3D
3D planning,
planning, it
it will
will be
be helpful
helpful to
to have
have the
the
following
following ROIs
ROIs to
to drive
drive the
the inverse
inverse planning:
planning:
–– PTV_Expanded:
PTV_Expanded: PTV
PTV ++ 1~2
1~2 cm
cm margin
margin
–– PTV_Moat:
PTV_Moat: 1~2
1~2 cm
cm moat
moat outside
outside PTV_Expanded
PTV_Expanded
–– Normal
Normal tissue:
tissue: skin
skin contracted
contracted until
until PTV_moat
PTV_moat
–– Cord_Expanded:
Cord_Expanded: cord
cord ++ 1cm
1cm margin
margin
–– Esophagus_Expanded:
Esophagus_Expanded: esophagus
esophagus ++ 1cm
1cm margin
margin
–– Other
Other hot
hot spots
spots (at
(at the
the end
end of
of the
the planning)
planning)
*Method is more specific to Pinnacle and similar systems
6
[Inverse Planning]
[Inverse Planning]
ROIs specific for IMRT
Inverse Planning by Iterative Planning
Step
Step 1.
1. Start
Start by
by using
using default
default objective
objective function
function templates
templates
that
that include:
include:
••
••
••
••
PTV
PTV_moat
Tissue
••
••
••
••
CTV:
CTV: min
min dose
dose
PTV:
PTV: min
min dose,
dose, max
max dose,
dose, (uniform
(uniform dose)
dose)
PTV
PTV moat:
moat: max
max dose
dose
Total
Total lung:
lung:
–– V5
(60%)
V5 (60%)
–– V10
V10 (45%)
(45%)
–– V20
V20 (35%)
(35%)
–– Mean
)
Gy
Mean lung
lung dose
dose (15
(15 Gy)
Gy)
Cord_Exp:
Cord_Exp: max
max dose
dose (45Gy)
(45Gy)
Heart:
Heart: V45
V45 (30%)
(30%)
Esophagus_Exp:
Esophagus_Exp: V45
V45 (30%)
(30%)
Normal
Normal tissue:
tissue: max
max dose
dose or
or V20
V20
–– Disadvantage:
Disadvantage: increase
increase of
of parameter
parameter space
space
[Inverse Planning]
Demo of an Example Case
[Inverse Planning]
Inverse Planning by Iterative Planning
• insert
Step 2:
Assign equal weighting to all
objectives.
Step 3:
•Run 1 search iteration only;
•Evaluate current solution
which is similar to a 3D plan;
•Adjust the objectives
accordingly and their
associated costs.
Step
Step 44 and
and beyond:
beyond: to
to balance
balance the
the priorities
priorities and
and
conflicting
conflicting goals
goals
–– Evaluate
Evaluate optimization
optimization solution
solution
–– Re-adjust objective
Re
Re-adjust
objective functions
functions and
and their
their costs
costs
–– Objectives
Objectives with
with the
the highest
highest costs
costs will
will be
be pushed
pushed
down
down first
first during
during the
the next
next iteration
iteration loop
loop
–– Follow
Follow the
the sequence
sequence of
of priority
priority and
and organ
organ sensitivity
sensitivity
A.
A. Target
Target coverage
coverage
B.
B. Lung
Lung dose/volume
dose/volume
C.
C. Heart,
Heart, esophagus,
esophagus, cord
cord
D.
D. Normal
Normal tissues,
tissues, hot
hot spot
spot
–– Continue
Continue based
based on
on existing
existing solution
solution
7
[Inverse Planning]
Demo of an Example Case
Iterative feed-back
guided inverse planning
• insert
•Number of optimization
iterations does not have to
exceed 5 ~ 8 for gradient
algorithms
•Choose the battle wisely,
the key issue is to set
appropriate objectives
•Upon completion of each
run, critically assess the
results and re-adjust
objectives and costs, and
rerun upon existing results
[Inverse Planning]
Plan Evaluation
[Inverse Planning]
Plan Evaluation
•• Isodoses
Isodoses
–– Target
Target conformity
conformity vs.
vs. hot
hot spots
spots
–– Dose
ROIs
Dose avoidance
avoidance to
to ROIs,
ROIs,, particularly
particularly lung
lung
–– Spread
-dose volume
low
Spread of
of lowlow-dose
volume to
to lung
lung and
and normal
normal tissue
tissue
•• DVHs
DVHs
–– Evaluate
Evaluate whether
whether objectives/constraints
objectives/constraints being
being placed
placed
properly
properly
–– Adjust
Adjust objectives
objectives ifif reoptimization
reoptimization is
is required
required
•• Other
Other biological
biological parameters
parameters
–– Mean
Mean dose
dose or
or EUD
EUD for
for lung
lung
–– NTCP
NTCP
[Inverse Planning]
MLC Sequence Conversion
•• Deliverable
Deliverable plans
plans are
are often
often degraded
degraded from
from
fluence-optimized plan
fluence
fluence-optimized
plan
•• May
May have
have to
to reoptimize
reoptimize plan
plan due
due to
to degradation
degradation of
of
leaf
leaf conversion
conversion
•• On
On Pinnacle:
Pinnacle: May
May perform
perform direct
direct segment
segment
optimization
optimization for
for converted
converted plan.
plan. IfIf this
this is
is
necessary,
adjust
objective
functions
necessary, adjust objective functions first
first before
before
reoptimization
reoptimization
•• Minor
Minor manual
manual adjustment
adjustment to
to segments
segments can
can be
be
helpful
helpful to
to reduce
reduce cold/hot
cold/hot spots
spots
•• Direct
Direct leaf
leaf sequence
sequence optimization
optimization is
is another
another
option
option
8
[Inverse Planning]
[Inverse Planning]
MLC Sequence Conversion
•• Balance
MUs
Balance between
between delivery
delivery efficiency
efficiency (#segments
(#segments and
and MUs)
MUs))
vs.
vs. dose
dose gradient
gradient (conformity
(conformity and
and avoidance)
avoidance)
•• In
In general,
general, #segment/beam
#segment/beam should
should be
be << 20
20 for
for lung
lung plans,
plans, itit
is
is not
not necessary
necessary to
to exceed
exceed more
more than
than 30
30 segments/beam
segments/beam
•• Treatment
Treatment planning
planning system
system may
may not
not be
be adequate
adequate to
to
compute
compute dose
dose accurately
accurately for
for plans
plans with
with MU
MU efficiency
efficiency <<
25%
25%
MU_efficiency =
Fractional_prescription_dose (cGy)
sum(average_MU_per_angle)
Beam Configuration
•• 6MV
6MV photon
photon beams
beams are
are preferred
preferred choice
choice
•• 18MV
18MV beams
beams should
should be
be avoided
avoided if
if possible
possible
–– Electron
Electron disequilibrium
disequilibrium
–– Neutron
Neutron production
production
•• Coplanar
Coplanar beams
beams are
are more
more practical
practical and
and easy
easy for
for
planning
planning
•• Noncoplanar
Noncoplanar beams
beams may
may offer
offer additional
additional
choices
choices for
for beam
beam angle
angle optimization
optimization
Total_MU_per_angle
average_MU_per_angle =
Num_beam_per_angle
[Inverse Planning]
[Inverse Planning]
Beam Configuration
•• Placing
Placing of
of beam
beam angles
angles should
should carefully
carefully consider
consider
planning
planning priorities
priorities for
for normal
normal structures
structures
Beam Configuration
5B-IMRT
5B-IMRT
9B-IMRT
9B-IMRT
–– PTV
PTV is
is not
not sensitive
sensitive to
to the
the beam
beam angles
angles
–– Lung
Lung is
is the
the determining
determining factor
factor for
for selecting
selecting beam
beam angles
angles
–– Heart
Heart is
is more
more sensitive
sensitive to
to angle
angle selection
selection than
than esophagus
esophagus and
and
cord
cord
••
••
44-6
-6 beams
beams should
should be
be sufficient
sufficient for
for lung
lung IMRT
IMRT
Excessive
Excessive beams
beams will
will reduce
reduce MU
MU efficiency
efficiency and
and
delivery
delivery complexity/time
complexity/time
•• Experience
from
3DCRT
on
optimal
angles
can
Experience from 3DCRT on optimal angles can be
be
extended
extended to
to IMRT
IMRT
•Use of 4-6 beams can
achieve essentially
equivalent plan quality
compared to 9 beams
•Use of fewer beams
require beam angle
optimization that
minimize lung dosevolume
9
[Methodology]
[Inverse Planning]
Beam Configuration
•MUs and #segments
increase with #beams
1400
200
N u m S eg m en ts
1200
MUs
1000
800
600
400
•Reduction of #beams
improves delivery
efficiency and lowdose leakage
150
100
50
200
0
0
3D
IMRT 5
IMRT 7
IMRT 9
3D
IMRT 5
IMRT 7
IMRT 9
•Compromise between
#beams and likelihood
of hotspots
[Treatment Verification]
Dosimetry QA
• Sources of dose calculation uncertainties
–– Tissue
Tissue inhomogeneities
inhomogeneities
–– Beam
Beam modeling
modeling
–– MLC
MLC modeling
modeling
–– Dose
Dose calculation
calculation algorithms
algorithms
•• Pencil-beam algorithms
Pencil
Pencil-beam
algorithms
•• Convolution
Convolution algorithms
algorithms
Treatment Delivery and QA
•• QA
QA procedure
procedure should
should be
be similar
similar to
to other
other sites
sites
•• Frequent
Frequent imaging
imaging maybe
maybe needed
needed to
to ensure
ensure
accuracy
accuracy and
and precision
precision of
of patient
patient positioning
positioning
•• Dosimetry
Dosimetry issues
issues specific
specific to
to lung
lung cancers
cancers
–– More
More significant
significant tissue
tissue inhomogeneities
inhomogeneities
–– Large
Large field
field sizes
sizes and
and high
high degree
degree of
of intensity
intensity
modulation
modulation
–– Low
Low doses
doses in
in lung
lung and
and normal
normal tissues
tissues maybe
maybe more
more
difficult
difficult to
to compute
compute accurately
accurately by
by conventional
conventional
treatment
treatment planning
planning systems
systems
[Treatment Verification]
Dosimetry QA
• Commissioning/Implementation of lung
IMRT procedure
–– Intensity
Intensity verification
verification
•• Ion
Ion chamber
chamber in
in water
water phantom
phantom
•• Film
Film in
in solid
solid water
water phantom
phantom
–– In-vitro dosimetry
In
In-vitro
dosimetry
•• TLDs
TLDs in
in anthropomorphic
anthropomorphic phantoms
phantoms
–– Monte
Monte Carlo
Carlo calculations
calculations
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[Treatment Verification]
[Treatment Verification]
Phantom Measurements
Phantom Measurements
•Comparison of Pinnacle calculations (v6.2) vs. TLD
measurements for lung IMRT cases from high to low
dose regions
[Treatment Verification]
Monte Carlo Based QA
•Comparison of Corvus calculations (v4; v5) with Monte
Carlo simulation for mesothelioma cases
MCS – Total Dose 50 Gy
Diff = MCS - Corvus
[Methodology]
Dosimetry Verification
•• Ensure
Ensure dose
dose calculation
calculation accuracy
accuracy
•• in
in high-medium
high-medium dose
dose region
region
•• using
using the
the types
types of
of leaf
leaf sequences
sequences generated
generated within
within the
the
planning
planning system
system itself
itself
• Treatment
Treatment planning
planning systems
systems may
may underestimate
underestimate
dose
dose in
in low
low dose
dose region
region
•• Strongly
Strongly depends
depends on
on beam
beam modeling
modeling and
and MLC
MLC
modeling
modeling (leaf
(leaf transmission,
transmission, leakage)
leakage)
•• Effects
Effects is
is more
more prominent
prominent for
for beams
beams with
with low
low MU
MU
efficiency,
efficiency, I.e.
I.e. greater
greater leakage
leakage
5500 5000 4000 3000 2000 1000 cGy
< -500 - 250 250 > 500 cGy
-10% -5% +5% +10%
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[Treatment Verification]
Dosimetry Verifications
•• Tissue
Tissue inhomogeneity
inhomogeneity may
may not
not be
be aa significant
significant
cause
cause of
of error
error for
for lung
lung IMRT,
IMRT, even
even using
using PencilPencilbeam
beam algorithms
algorithms (based
(based on
on Corvus
Corvus results)
results)
•• QA
QA for
for single
single IMRT
IMRT beam
beam may
may not
not be
be adequate,
adequate,
composite
composite dose
dose distribution
distribution is
is more
more sensitive
sensitive to
to
dose
dose errors
errors
•• Monte
Carlo
simulation
is
a
powerful/effective
Monte Carlo simulation is a powerful/effective
tool
tool for
for IMRT
IMRT QA
QA
•• Provide
Provide independent
independent MU
MU and
and dose
dose distribution
distribution
verification
verification
•• However,
However, MCS
MCS can
can also
also be
be subjective
subjective to
to beam
beam
parameters
parameters used
used for
for IMRT
IMRT
•• Also
requires
rigorous
commissioning
process
Also requires rigorous commissioning process
Summary
1.
1. IMRT
IMRT can
can be
be an
an effective
effective treatment
treatment modality
modality for
for managing
managing
advanced
advanced stage
stage NSCLC
NSCLC and
and other
other suitable
suitable lung
lung cancers
cancers
(superior
sulcus
meso
(superior sulcus,
sulcus,, meso,
meso,, etc)
etc)
2.
2. Patient
Patient candidates
candidates need
need to
to be
be identified
identified to
to maximize
maximize
benefits
benefits of
of IMRT
IMRT
3.
3. Target
Target delineation
delineation and
and organ
organ motion
motion need
need to
to be
be carefully
carefully
considered
considered during
during simulation
simulation
4.
-dose volume
Low
4. LowLow-dose
volume of
of lung
lung and
and normal
normal tissue
tissue need
need to
to be
be
reduced
reduced when
when planning
planning for
for beam
beam angles
angles and
and dose
dose
distributions
distributions
5.
5. Dosimetry
Dosimetry accuracy
accuracy should
should be
be validated
validated for
for each
each treatment
treatment
planning
planning system
system
Questions & Discussions
Contact: Helen Liu,
Unit 94, Radiation Physics,
UT-MDACC, 1515 Holcombe Blvd
Houston, TX 77584
hliu@mdanderson.org
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