MONACO

Question 1

What kind of TPS is Monaco

Answer 1

Voxel based
Meaning you can control voxels but not structures
If 50% of voxel is inside the contour, Monaco considers it to be a part of the structure

Question 2

Voxels

Answer 2

Extend from iso and are based of grid size
Finer the grid size, greater number of voxels

Question 3

Workflow of Monaco planning

Answer 3

1. Import the studyset(s) and assign the CT to ED.
2. Open the patient in the workspace.
3. Fuse multiple studysets.
4. Carefully contour all required targets and OARs. Create necessary margins.
5. Define and lock scan reference point.
6. Import applicable treatment devices.
7. Start a Monaco plan (load a plan template).
8. Verify/edit beam geometry, isocentre, machine and energy.
9. Verify/edit prescription.
10. Verify/edit electron densities and structure layering order.
11. Resolve any structure mismatches and edit the IMRT Constraints, Calculation
    Properties, IMRT Parameters, and Sequencing Parameters as necessary.
12. Run fluence optimization (Stage one).
13. Use plan analysis tools to evaluate your plan.
14. Adjust the parameters and prescription (constraints) as necessary.
15. Re-optimize the fluence and repeat evaluation until you have an acceptable
    optimized plan.
16. Run segment optimization (Stage two).
17. Use the plan analysis tools to evaluate your final plan
18. If the plan is not acceptable, make edits to the properties and/or prescription
    (constraints) as needed.
19. Verify plan meets all objectives.
20. Save and name plan.
21. Request proper plan approval.
22. DICOM export all necessary data.
23. Export plan PDF.
24. Create a QA plan.

Question 4

Arc increment

Answer 4

If you use an increment that is too large, Monaco creates fewer sectors.
• This can produce poor quality plans. When you use an increment that is too
small, Monaco gives you more sectors.
Use rule of 3 - add 3 to the number of static beams

Question 5

Partial arc sector

Answer 5

the system selects the closest
increment value that is uniformly divisible with the
posterior arc increment split into two.

Question 6

Sweep sequencer

Answer 6

Sweeping leaf sequencer is that the leaves move from
their start position to their end position in a continuous,
unidirectional manner
• The length they do this is determined by the sector
• Beginning with the first sector, the leaves move to the left
side of the BEV
• They then change direction and move to the right side of
the BEV
• The minimum width of these end segments is hard coded
at 5mm.

Question 7

Segment shape optimisation SSO

Answer 7

Segment Shape Optimization includes smoothing,
sequencing (clustering) and optimization of beam
weights and shapes.
• Range 1 to 20

Question 8

Fluency smoothing

Answer 8

Controlled im stage 1
Increase smoothing leads to decreased plan quality and control points
Option of off, low, medium and high

Question 9

Statistical uncertainty

Answer 9

the percent
(%) statistical uncertainty per voxel, on a per-segment
basis, that you are willing to accept for the final dose
calculation

Question 10

Optimisation approaches

Answer 10

Constrained and Pareto

Question 11

Constraint mode

Answer 11

set constraints on healthy tissue while it administers dose to
target volumes

Question 12

Pareto mode

Answer 12

prioritizes target underdoses on tumour volumes and relax
constraints on healthy tissue. This effectively reverses how Monaco normally
works.

Question 13

Cost functions

Answer 13

Target EUD
• Target Penalty
• Quadratic Overdose
• Parallel
• Serial
• Overdose DVH
• Underdose DVH
• Maximum dose
• Quadratic Underdose
• Conformality

Question 14

EUD

Answer 14

The dose that causes the same effect if applied homogeneously to the
entire organ volume or
• The EUD represents any two or more dose distributions that yield the
same radiobiological effect.

Question 15

Target EUD

Answer 15

Biological cost function
Default cell sensitivity of 0.5

Higher cell sensitivity = increased penalty paid for
cold spots
• high cell sensitivity = increase the pressure to deliver
dose to cold spots

Question 16

Quadratic overdose

Answer 16

Physical cost function =constraint
To limit high dose
Isoconstraint is the root mean square
Can be used to control conformity

Question 17

Parallel structure cost function

Answer 17

3 cost functions

The first parameter is the Reference Dose (Gy) whose
value is analogous to the dose that is only just
acceptable for the majority of the structure, and at which
a clear dose response begins to show

• The second parameter is the Isoconstraint, which is the
Mean Organ Damage (%) to the structure. The Mean
Organ Damage is the biological equivalent to the fraction
of the volume of the structure that can be sacrificed.

The third parameter is the Power Law Exponent (k). This
value changes the shape of the dose response curve and
determines how responsive the structure is to the Reference
Dose (Gy) and Mean Organ Damage (%) values entered.

Question 18

K value

Answer 18

For parallel ranges from 1-4

• A k value of 1 with the Parallel cost function, applies its greatest penalty to the region of low
dose and applies a penalty over most of the curve
• A Parallel cost function with a k value of 4 applies penalty in the region of the reference dose.

Question 19

Serial cost function

Answer 19

EUD
Biological equivalent of a max dose
Power law exponent
K=0.15*D50

Question 20

Overdose DVH

Answer 20

This physical cost function is the equivalent of a
DVH constraint for an OAR.

When you add more than one DVH constraint to a
structure, the values for dose and percent (%)
volume must be consecutive so that they create a
single continuous curv

Question 21

Underdose dvh

Answer 21

This physical cost function is the equivalent of a
DVH constraint for targets.
Should be cautious using this

Question 22

Conformality

Answer 22

Physical cost function that can be used with OARs
Shapes high dose volume around 1 or more target volumes
Works well for single or stereotactic volumes
Does not work well with head and neck
Start at 1, range 0-1

Question 23

Shrink margin

Answer 23

Instead of dose controlling ROIs

Question 24

Surface margin

Answer 24

Use for tumours on the surface

Question 25

Optimisation process

Answer 25

Stage 1: Produces the preliminary result “ideal” fluence distribution) so you can
evaluate how accurately the cost function(s) achieve the goals you set.
• Stage 2: The second stage performs the segmentation, which includes
optimizing the segment shapes and weights, so that deliverable fields are
obtained.
• Batch Optimisation -After stage 1 optimization and proceeds directly to stage 2
optimization

Question 26

Control point

Answer 26

Control points describe the movement of the MLC during treatment delivery
from the start to the end of each segment.