VMAT and IMRT Flashcards
1
Q
what is fielf in field?
A
forward-planned IMRT
-leaves modulate the beam intensity; leaves are static while gantry rotates and while beam is delivered
-dose not delivered while gantry moves
2
Q
what is step and shoot
A
like fif but inverse planned
IMRT
-dose not delivered while gantry moves
3
Q
what is sliding window
A
inverse planned IMRT where the leaves are moving as dose is being delivered
-dose not delivered while gantry moves
The first leaf is always moving. To decrease the intensity at a location, the 2nd leaf will move with it (to get a downward slope). Hence the complexity of the first leaf determines the max leaf speed for that slice. To get an upward slope, the first leaf has to move faster.
4
Q
what is varied in VMAT to achieve the desired dose distribution?
A
dose rate first, then gantry speed
5
Q
fluence based optimization vs aperture based optimization
A
-IMRT may be either or
-VMAT is aperture based
-if fluence based, a separate leaf sequencing step is necessary
6
Q
what are dynamic conformal arcs?
A
MLCs change shape with moving target
7
Q
difference between IMRT and VMAT dose distribution
A
• Compared to IMRT, a VMAT distribution will generally be similar for the dose levels > 50%. However, the VMAT plan will generally have lower doses distributed more uniformly throughout the normal tissue due to having beams coming in from all directions
8
Q
If you can’t use acurods, what should you use for a lesion in lung?
A
TG 101 doesn’t allow for pencil beam to be used in inhomgeneous regions
-if can’t have acuros at least use AAA
-uses point dose-spread kernels, which perform density scaling for the distance between the interaction point and the calculation point, thereby assuming that electrons travel in a straight line along this direction.
9
Q
explain volumetric normalization
A
-used by VMAT- want certain volume to get certain % of dose- can adjust final normalization to make plan hotter/colder by 2 %
-not like 3DCRT where we normalize to a point (but still plan such that X volume receives Y dose)
10
Q
Does VMAT require a CT?
A
yes because beams are coming in from all directions
In contrast, with IMRT, can potentially use BEV images
11
Q
• Describe the process of progressive resolution optimization used in VMAT as described by Otto. How has this been implemented in the Eclipse planning system?
A
o Continuous gantry and MLC leaf motion is modelled by a coarse sampling of discrete gantry angles and MLC apertures. VMAT involves progressively increasing the gantry and MLC position sampling resolution as the optimization progresses. Later on in the optimization, smaller changes in MLC position and MU weight per gantry angle are allowable due to the mechanical and efficiency constraints which limit variation in dose rate and MLC aperture shape from one gantry angle to the next. Each iteration involves randomly choosing a MLC leaf or MU weight to modify. If the change is allowable given the constraints, then the dose distribution and cost function are calculated. If the cost is reduced, then the change is accepted. Transition to the next level is determined by how much the cost function has plateaued as a function of time.
o In Eclipse, there are four levels of optimization, with more gantry angles at higher levels. The number of control points remains fixed throughout optimization. Within PO (which has replaced PRO), dose is quickly calculated (for the purpose of calculating the cost function) using MRDC (multiple resolution dose calculation). In MRDC, variable gantry angle resolution and multi resolution scatter computation is used.
MRDC is within PO/PRO- like AAA but resolution is variable
12
Q
ou have been assigned the project of implementing VMAT for head and neck treatment in a facility that does not yet use this technique. How would go about it? What resources (human, equipment, etc.) would you need?
A
o Would need to do a series of end-to-end tests to make sure entire process from simulation to delivery is running properly.
o Testing synchronization of gantry position, leaf position and dose rate.
o MLC leaf positioning accuracy, reproducibility.
o Dosimetry tests (e.g., flatness, symmetry and output as a function of gantry speed & dose rate)
o Since it is no longer step and shoot, must expand Q&A routine to account for the fact that the beam is on while the gantry rotates, and while the MLC (and possibly also the collimator, depending on implementation) is moving.
o Verify mechanical constraints on the machine (VMAT optimizer requires this information).
o Interruption/resumption tests
o Leaf leakage characterization (interleaf, through leaves, through leaf ends)
o Absolute dose measurements with a calibrated ion chamber to make sure TPS calculates dose properly to a point.
o Compare plan objectives obtainable with VMAT to plan objectives achievable with old method (e.g., IMRT) to ensure that acceptable plan quality is achievable; comparison with VMAT treatments from the literature.
13
Q
what makes VMAT unique from previous implementations of therapies involving continuous gantry motion while beam is on?
A
VMAT involves progressively increasing the gantry and MLC position sampling as the optimization progresses
14
Q
why do you need to sometimes rewind to an earlier level with VMAT?
A
less samples, more parameter flexibility, less constraint sometimes required to achieve bigger changes
15
Q
Approaches to IMRT
A
-optimize fluence, then figure out MLC leaf sequence needed
- or else, start with BEVs with apertures and equal dose rates. At each optimization step, change MU weight or MLC leaf position
16
Q
Max MLC leaf speed, collimator jaw speed, and gantry speed
A
2.5 cm/s for MLC/jaws, and 6 degrees/s
17
Q
why is it good for jaws to track with MLC leaves?
A
minimizes effect of inter-leaf, midleaf leakage
18
Q
does optimization prefer to change dose rate or gantry speed?
A
dose rate
gantry has a lot of inertia-lass resort
19
Q
definition of cost function
A
sum of terms that are quadratic dose differences multiplied by a priority value
20
Q
when does progression to next optimization level occur in PO/PRO?
A
when cost function has plateaud
-at higher levels, plateus moer quickly because due to mechanical contraints smaller changes are possible
21
Q
how are MU weights of new MLC positions related to their neighbours?
A
-positions are linearly interpolated from adjacent samples
-MU weights of new samples are a function of MU of neighbours
22
Q
when does progression to next optimization level occur per Otto?
A
doesn’t consider levels
-considers exponential more iterations between sample additions when there are fewer samples
-doesn’t consider plateauing of cost functions
23
Q
Does optimization per Otto use simulated annealing?
A
No
24
Q
who used simulated annealing
A
IMRT- optimizaions that don’t have progressive sampling (i.e. used fixed number of samples)
25
how densely do you need to sample to ensure < 5 % of volume has dose errors > 3 %
1 degree for gantry rotation, and 0.5 cm for MLC leaf motions is required
26
advantages of aperture based optimization
-reduce modulation
-consider contraints at time of optimization; don't need extra step
27
why is more rigid immobilization required in IMRT?
higher dose gradients- setup accuracy more vital compared to ex. POP
28
is error in contouring more or less rlevant in IMRT vs 3DCRT?
more, because the contours directly control the result
in 3DCRT, contours were only spatial guides
29
how are PTV and PRV margins determined?
based on population statistics of comparisons between the planning CT (obtained from CT-sim) and daily pre-treatment verification CTs obtained over the course of treatment
30
how do parotids change over course of treatment?
translate ~1 mm/week medially and undergo ~20% volume loss over Tx course
31
difference between forward and inverse planning
o Forward planning:
Set beam orientations, weights, modifiers
Forward dose calculation
Check if PTV and OAR dose volume constraints are satisfied – return to step 1 if not
o Inverse planning:
Set beam orientations: choose treatment ports (IMRT) or range of gantry angles (VMAT)
Specify desired dose volume constraints for PTV(s), OAR(s) – specify optimization objectives for contoured structures, including tuning structures/pseudocontours (not representative of a real anatomical structure; used to guide the optimizer to the desired solution).
Inverse plan using optimization techniques e.g., VMAT
Forward dose calculation
Check if PTV and OAR dose volume constraints are satisfied – return to step 1 or 2 if not
32
what can cost functions include?
target: actual dose- prescription dose, minimum and maximum dose (latter are step functions)
OAR: DVH constraints, max constraints (step functions)
33
determinist vs stochastic optimization methods
• Gradient-based optimization methods are deterministic; can get stuck in local minimum. Simulated annealing optimization is stochastic (doesn’t necessarily yield the same answer every time); can escape from local minimum
-does this by once in awhile accepting a solution that increases the cost function
34
max dose volume
0.03 cc or 0.1 cc
-need VOI to be at least one voxel
35
what happens to dose outside of contoured OARs?
has to be looked at after optimization
VMAT considers it with NTO (normal tissue optimization)
36
benefits for VMAT vs IMRT
-faster (2 min vs 10 min)
less chance of patient movement and intra-fraction physiological motion
37
downside of VMAT
more time consuming to plan and QA
38
why do we sometimes us 90 colli?
bilateral disease
using 90, some leaves can go in between the targets and improve conformity
think of treating vertebrae that wrap around the cord- can get half of bone with one arc and cover cord with MLC, and other half with another arc (cover cord with MLC)
39
why can't colli be at 0?
doesn't smear out the inter-leaf leakage
40
what is volumetric normalization?
-in VMAT, 95% of PTV sould get 100% of prescription dose
41
comparison of VMAT and IMRT dose distrubtion
generaly similar for isodose > 50 %
VMAT plan will generally have lower doses distributed more uniformly throughout the normal tissue due to having beams coming in from all directions
42
difference between VMAT and previous implementations of therapies involving continuous gantry motion while the beam is on
VMAT involves progressively increasing the gantry and MLC position sampling as the optimization progresses
Issue with using full gantry range is that we are limited by MLC motion constraints between discrete gantry positions. Hpwever, if we don't sample enough of the range we won't get a good plan or a good indication of the dose distrubtion (discrete approximation not a good approximation of continuous case)
o To tackle this tradeoff, VMAT uses progressive sampling of gantry and MLC positions.
o Sometimes need to rewind to earlier level (with less samples, more parameter flexibility, less constraint) to achieve more drastic changes. Bigger adjustments are made in leaf sequencing during the initial phases of optimization.
43
classic approach to IMRT/VMAT and alternative approach
classic: optimize fluence maps, then figure out MLC leaf sequence needed to achieve this fluence
alternative: start with a series of BEV aperture shapes that are conformed to target minus OAR (e.g., prostate excluding rectum). This is what is used by VMAT. Initially, dose rates for all segments are equal. At each optimization step, either MU weight of a particular segment, or a MLC leaf position (these are the two optimization parameters that are adjusted) is changed.
44
types of constraints for VMAT optimization
o Mechanical constraints ensure that the aperture shapes and MU weights are physically achievable: e.g., overlapping of opposing leaves and nega
o Efficiency constraints: MLC leaf motion and MU weight constraints that ensure continuous and timely treatment delivery – want to avoid gantry deceleration; want to rotate gantry at maximum possible speed as much as possible. Need to consider maximum travel speed of leaves (2.5 cm/s) and maximum gantry rotation (6 deg/s), max allowable dose rate [these limits are values for Truebeam].
Also note the collimator jaws maximum speed is 2.5 cm/s (same max speed as MLC leaves). In our clinic, our collimator jaws track with the MLC leaves to ensure the smallest possible aperture, to minimize the amount of interleaf, intraleaf and leaf end leakage (due to leaf pairs not being able to be perfectly closed) that reaches the patient.
Otto seems to ignore max allowable change in dose rate between control points. This assumes that dose rate can change fast enough that we don’t need to worry about it as a constraint.
tive MU weights are not physically possible.
45
what happens during each VMAT iteration?
o Each iteration involves randomly choosing a MLC leaf or MU weight to modify. If the change is allowable given the mechanical and efficiency constraints, then the dose distribution and cost function are calculated. If the cost is reduced, then the change is accepted.
46
why is changing gantry speed last resort?
gantry has a lot of inertia- difficult to slow down
also increased treatment time
but can be used to get more MU per degree
47
simple definition of cost function
sum of terms that are quadratic dose differences multiplied by a priority value
48
where do new samples in VMAT get their MLC positions and weights from?
• The new samples have MLC positions linearly interpolated from adjacent samples. MU weights of new samples are a function of MU of neighbours (which are not weighted equally due to unequal sampling intervals as new samples are added)
49
how many optimization levels does Varian have?
4
In the photon optimization algorithm (PO) used in Eclipse, transition to the next level happens when the cost function has reached a suitable plateau as a function of number of iterations.
50
what happens to cost function at higher levels of optimization?
• At higher levels (more samples, increased number of optimizable gantry positions, more restricted MLC leaf position changes), cost function may plateau more quickly since due to mechanical/efficiency constraints, smaller changes in MLC, MU weight are allowable.
51
how does Otto deal with iterations and sample numbers?
o Otto suggests an optimization schedule where there are exponentially more iterations between sample additions when there are fewer samples. Unlike PO, Otto does not use levels, and does not consider plateauing of the cost function.
• Each time a sample is added, the cost is recalculated. This new sample will perturb the optimization, resulting in a temporary increase in cost. The magnitude of this effect is larger when there are fewer samples – hence the exponential decrease in number of iterations between sample additions described above.
52
describe simulated annealing
VMAT as defined by Otto does not use simulated annealing
help ensure optimization is not trapped in local minimum by accepting some MLC leaf and MU weight changes that result in a cost increase
53
what sampling interval is required to ensure < 5% of volume has dose error > 3%,
sampling of 1 degree for gantry rotation, and 0.5 cm for MLC leaf motions is required
54
how are pulses used in linacs to change dose rate?
o DC power supply provides DC power to pulsed modulator which includes pulse forming network, which produces flat topped pulses of ~5 microseconds, with ~5 ms interpulse duration. These pulses are delivered to the magnetron/klystron (Truebeams use klystron) and to the electron gun. Amplified microwaves from the klystron are then injected into the waveguide along with electrons from the electron gun.
o The C series linacs (ix, ex) modify the dose rate by dropping or including pulses, while pulse width remains fixed. On Trubeams, the pulse width is modified. In fact, for the 2.5x beam, in order to obtain adequate dose rate with such a low energy beam, the pulses must be very long; almost the same length as the pulse interval itself, such that the beam is almost continuous.
In brief- clinac drops or adds in pulses
true beam modifies pulse width
pulse frequency, f, and pulse width, τ, respectively. In case of an ideal LINAC, the beam intensity or dose rate is linearly proportional to the value of f and τ.
55
what is MRDC
• Multiresolution dose calculation algorithm (MRDC) is used to quickly estimate dose inside the PO. At the end of the optimization, the final dose is calculated using AAA. AAA is also used to calculate an intermediate dose after level 3 of the optimization. This step improves the accuracy of the optimization so that the final dose distribution determined by the optimizer at the end of level 4 more closely matches the actual final dose distribution calculated by AAA.
• MRDC (multiple resolution dose calculation) is used for fast dose estimation inside the PO.
uses superposition-convolution technique, which is similar to AAA except that variable resolution is used (dose calculated at lower levels is especially not accurate).
Takes into account heterogeneity corrections.
As the optimizer progresses through the levels of optimization, more segments are added so that each segment covers a smaller range and the model more closely approximates continuous gantry motion, and the resulting dose distribution is more accurate.
Also, multi-resolution scatter computation is used (not used in AAA) – finer resolution is used closer to the location of the primary interaction.
Point spread functions are obtained from MC sims.
56
diffeernce between PRO and PO
PRO used point cloud model(resolution is inverselt proportional to size of structure - larger structure = larger grid)
PO uses voxel based model
57
what do smoothing objectives do?
minimize the difference between neighbouring (from one segment to the next) fluence values.
58
what is MU objective
adds penalty to cost function when total number of MU exceeds some value. Typically, 2-6 MU per cGy is normal (i.e. 4 times dose per fraction). High number of MU is indicative of a complex plan, with lots of MLC modulation. Since MLC leaves are not modelled in a highly accurate manner (tongue and groove effect, and rounded leaf ends are both modelled in an approximate way), a high degree of MLC modulation can lead to inaccurate dose calculations and therefore failed portal dose verifications. Plus potentially more beam on time, more inter-leaf/intra-leaf/leaf end leakage, and more scatter dose reaching patient
59
what is base dose plan
can be specified when you want the optimizer to take into account another dose distribution while planning the current one. This is useful for e.g., TMI junction between POP used for lower limbs and VMAT used for upper body – to avoid hot/cold spots.
60
what us automatic feathering
can be used to reduce the effect of intra-fraction patient position inaccuracies in treatments with multiple isocentres.
61
what is aperture shape controller
favours apertures of minimal local curvature
62
what happens to optimized treatment plan?
PO algorithm generates a sequence of control points (corresponding to particular range of gantry angles) with MLC positions and MU weight for various gantry angles. This is the information that is transferred to the treatment machine. The machine control system then determines how dose rate and gantry speed need to be modulated to deliver the plan.
63
number of control points during optimization
the angle resolution of the segments gets more accurate (smaller range of angles for a given segment) as the optimization progresses from one level to the next. However, the number of control points remains the same during the whole optimization
For each segment, it is assumed that the control points contained within a given segment are delivered from a static gantry position in the middle of each sector. [leaf positions for only the central control point of a segment are modified as part of the optimization, but for the purpose of dose calculation, to improve accuracy of the calculated dose compared to if only the “active” control points are considered, all control points are accounted for. The non-optimized control point MLC patterns obtained by interpolating leaf positions between control points]
64
how do allowed discontinuities change with optimization?
-in earlier phases, more discontinuities are allowed
-at each step, sizes of discontinuities between segments are restricted as resolution increases
65
automatic intermediate dose option in Eclipse
• “Automatic intermediate dose”: if not checked off, then the dose from the previous optimization (calculated by AAA) is used as intermediate dose and the optimization proceeds from there at beginning of level 4 (although can rewind to an earlier level if you want). However, this should be checked off during the first optimization; in this case, the intermediate dose is calculated after level 3 using AAA (same as used in the final dose calculation).
o The option of using the dose from the previous optimization as intermediate dose for the current optimization is useful for speeding up the process, as well as for cases where the MRDC-calculated DVHs deviate from the AAA-calculated DVHs (AAA is more accurate than MRDC).
66
what is Multi-criteria optimization-based trade-off exploration
-instead of optimizing a single objective function, optimizes a vector of objective functions
There are a set of best compromise points which constitute the Pareto surface. If no trade-off objective can be improved without worsening some other trade-off, then these trade-offs are said to be balanced in an efficient manner, and make up the Pareto surface.
67
VMAT optimization per Mike's explanation
optimizer starts with a limited number of segments in the arc, and in successive stages break them up further into smaller segments.
You end up with 178 unique segments (control points) at the end.
This 178 number though remains the same for every step, it's just to start they are not unique. For example, 1-25 may have the same collimator settings in the initial step, and in successive steps these will be allowed to change...
Basically, every VMAT step has 178 control points, and as you step through you stop looking at batches of them and start looking at individual ones.
A segment's control point is the center one (ie if control points 1-25 are in a segment, 12 is the one being worked on)
For each segment, it is assumed that the control points contained within a given segment are delivered from a static gantry position in the middle of each sector. [leaf positions for only the central control point of a segment are modified as part of the optimization, but for the purpose of dose calculation, to improve accuracy of the calculated dose compared to if only the “active” control points are considered, all control points are accounted for. The non-optimized control point MLC patterns obtained by interpolating leaf positions between control points]
Go from 10-178 segments
68
modelled transmission through jaws
0
69
does PO account for MLC leakage?
No, just AAA
70
MLC leaf ends for Varian and Elekta vs Siemens
o On Varian and Elekta linacs, the leaf ends are rounded and the leaves move in a single plane
Siemens: flat ended leaves that move in a curved trajectory to match beam divergence
71
downside to rounded MLC leaves
increased transmission through closed leaves
close leaves under jaw
72
how is effect of tongue and groove design modelled in TPS?
extending the leaf slightly in direction perpendicular to leaf motion
73
what does tongue and groove design do?
reduce interleaf leakage
74
how does TPS model MLC leaves?
models leaves as simple rectangular prisms for simplicity and shifts the leaf positions so they are slightly open (according to dosimetric leaf gap, DLG) to account for rounded leaf ends and the fact that they don’t close perfectly.
75
how to measure DLG
plot dose against various gap widths. Extrapolate value of gap for dose of 0.
usually DLG is 1-2 mm
76
collimator rotation wrt ion chamber direction
• Choose collimator rotation such that MLC leaf motion is not parallel to ion chamber axis so that ion chamber is not e.g., always on leaf boundary – this would give a higher reading compared to if the ion chamber were slightly shifted so that it is under a particular leaf – want to avoid this issue.
77
operating limits for tru beam MLC, jaw, gantry
2.5 cm/s
6 deg/s
• Arcs must be between 30 and 359.8 degrees in length.
-max leaf length is 15 cm- in practise we allow 18 even though leaves may not be able to fully close at edge of the field
78
max dose rate for the plan
defined by user
79
difference between PRO and PO performance
• In general, PO is shown to produce better OAR sparing but higher MLC variability and require more MUs more complexity which can compromise clinical deliverability. Number of MUs required to deliver a specific dose is an indicator of treatment plan complexity. PO and PRO plans were comparable in terms of homogeneity and conformality
80
what is output of PO or PRO optimizer?
a sequence of MLC apertures and MU counts for each control point
81
are cost function terms calculated for voxels that don't violate the constraints?
No
82
what uses MRDC?
Both PO and PRO- for quicker estimate
83
what is gEUD
generalized equivalent uniform dose
• gEUD represents the dose that, if given uniformly, would give same TCP (for a target) or NTCP (for an OAR).
84
why is gEUD useful?
• gEUD is potentially useful because it may improve convexity of the cost function, thereby making it easier to find the global minimum and making it less likely to be stuck in a local minimum.
• Use of gEUD-based optimization generally results in the same tumour coverage, but lower normal tissue doses at the expense of more non-uniformity within the target (and hotter (global) hotspots within the target).
less objectives (only one per structure more simple; don’t have to worry about conflicting/ambiguous objectives).
GEUD optimization constraints may show less patient to patient variation, thereby potentially simplifying treatment planning
With gEUD don't have to crop opti structures when you have overlap
85
parameters in gEUD
• Negative alpha values: tumour; positive: normal tissues. Higher alpha values: serial organ; lower: parallel organ.
o Alpha represents where on the DVH the optimizer will focus efforts.
higher alpha = serial organ = optimizer focuses on the maximum dose; lower alpha = parallel organ =optimizer focuses on the entire DVH
86
downsides of gEUD
less for the user to control (user controls dose, priority, alpha value).
meaning of alpha is ambiguous (don’t know where exactly on the DVH the optimizer is focusing).
using gEUD constraints for the target was found to result in highly non-uniform dose distributions, so it is recommended to use dose-volume constraints for targets, and to just use gEUD for OARs.
Can use a combination of dose-volume and gEUD constraints.
• gEUD tends to be not as helpful for limiting low doses; is better for limiting the mean, and high doses.
87
NTO
normal tissue objective; limits dose to tissue outside of target (i.e. anything without lower objective)
-uer can adjust priority, distance from target border (to begin penalizing), start dose, end dose (i.e., exit dose) and fall off (parameter describing steepness of dose fall off)
• NTO function is normalized to the lowest dose upper objective of the target, or (if this doesn’t exist), then the highest dose lower objective times 1.05
88
reasonable NTO fall-off rate
10%/mm
89
example of an OAR that changes a lot in position and size
parotids tend to translate ~1 mm/week medially and undergo ~20% volume loss over Tx course
90
example of a deterministic method
gradient- based
can get stuck in local minima
91
does IMRT consider dose in normal tissue outside of OARs?
No, but VMAT does this with NTO
92
Is VMAT or IMRT faster?
VMAT faster to deliver but slower to plan
93
trick for bilateral disease
Use 85 degree collimator to help remove dose from in between the 2 lesions
94
how do you add flash in VMAT?
o Flash (typically 2 cm) is used in breast tangents to allow for small setup variations from one fraction to the next, tissue swelling and respiratory motion. In practice, tangents fields are chosen to extend beyond the body contour to achieve flash
o However, in VMAT, if the region is not contoured and specified as being a target, then the optimization algorithm will not put dose there. Furthermore, even if you did specify that the air above the breast is a target, the optimizer will struggle to put dose there because (1) air has very low density, (2) buildup must occur.
o In practice, for any PTV near or at the body surface, need to create a pseudocontour (artificial optimization structure) that is identical to the PTV but trimmed back from the body surface by 2-5 mm (i.e., excluding the buildup region).
o Can create flash by adding a synthetic bolus during planning which is 1-2 cm thick, and extending the PTV pseudocontour into the bolus (while still avoiding the region within 2-5 mm from air-body interface, where buildup occurs). Optimize with the bolus and then treat without the bolus.
Must remove bolus and forward calculate the plan to assess the dose distribution in the absence of the bolus. The 1-2 cm thick bolus may perturb the dose distribution at depth (bolus adds additional 2-4 cm of separation!) such that the forward calculated plan is not acceptable (because optimization was done with the bolus there!)
95
typical penumbra prostate in VMAT
95-80 % - 4 mm
80- 50 % - 10 mm
50 - 20 % - 5 to 10 cm
96
typical breast penumbra in VMAT
95-80 % - 4 mm
80-50% - 4 cm in tissue, 7 mm if it goes into lung
50-20 % - 5 cm in tissue, 1 cm if it goes into lung
penumbra that go through lung then heart will go deeper into heart vs penumbra that don't pass through the heart first
shouldn't lung have bigger penumbra????
97
typical increase in MU for IMRT vs 3DCRT plan
2-3
98
what sites may not be candidates for IMRT?
-lots of motion (interplay effect)
-large tumours that are easily treated with 3DCRT
99
AAPM report for commissioning IMRT
TG 119
-Use phantom studies to verify that treatments can be planned, prepared for treatment, and delivered with sufficient accuracy. Gamma criteria of 3%/3 mm are used. It is common to only analyze pixels with doses > 10% of maximum dose. Typically require 95% pass rate (2 sigma confidence interval).
100
• Explain how to commission a new dose calculation algorithm (e.g., Acuros if you already have AAA)
o Can use same commissioning data that was used for original algorithm beam commissioning (there is no reason to remeasure the data).
o Comparison of results from the two algorithms: if new agrees with old and old agrees with measurements that were done originally, then new agrees with measurements (there is no reason to redo measurements)
o Use measurements (e.g., with film in anthropomorphic phantom) or Monte Carlo to investigate cases where they disagree
101
• Compare IMRT and VMAT with regard to efficiency and resources at all steps of the process.
o CT-simulation: Both methods are typically planned using a 3D image set hence there is likely no difference at this stage. However, for IMRT, some centres may use BEV images obtained in the chosen beam direction, to plan each step-and-shoot gantry angle individually. In contrast, VMAT requires a CT scan (since beams are coming in from all angles).
o Planning: IMRT may be forward planned, while VMAT uses inverse planning techniques. Time required to create a plan will depend on complexity of the situation, and skill (experience level) of the planner.
o Treatment delivery: in most cases, VMAT has been shown to take less time compared to IMRT since beam is on while gantry rotates around patient, as opposed to step and shoot technique.
o If the clinic only has IMRT implemented, then implementing VMAT will require significant resources
102
if asked to compare DVH for 3DCRT and VMAT, make sure to describe beam arrangement for 3DCRT and where you normalized it
3DCRT is sharper edge
also, if aiming for all of PTV to get 95 % of dose, 3DCRT DVH will be slightly shifted left from VMAT DVH since it has such a sharp fall-off
103
how is modulation done in IMRT vs VMAT
VMAT is aperture
IMRT is intensity (ie. one beam has intensity modulatio. In VMAT, this isn't the case)
104
how many beams in IMRT before you stop seeing improvement in conformity?
13
105
typical number of beams used in IMRT
7-9
106
what dose is higher in VMAT vs 3DCRT?
integral dose
107
how can a VMAT plan be verified?
dosimetry (portal, 2 D array, film + ion chamber), MC simulation, Rad Calc, comparing trajectory log file of delivered plan to treatment plan)
108
initial position of MLC leaves in VMAT
conform to the target
109
can you tell mean dose from DVH?
No, but if most of the dose is uniform, its likely the dose for 50% of the volume
110
when don't you use full VMAT arc?
avoiding entering through a structure or section
disease is only on one side
111
when would you use IMRT over VMAT?
trying to avoid entering through specific structures- want more control over beam entry points
112
why not just use target and NTO in cost function? Why put in OARs?
NTO is ring around target
would yield isotropic fall-off
include other OARs because sometimes we don't want isotropic fall off and instead want to spare critical structures
