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CSB049 - Planning 2 > TPS Algorithms > Flashcards

TPS Algorithms Flashcards

1
Q

Different Types of Algorithms

A

• Segmentation
• Advanced margin
• Image Registration
• Inverse Plan Optimisation (specifically for IMRT or VMAT)
• Dose Calculation

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2
Q

Types of TPS and their corresponding Linac

A

• Monaco = Elekta TPS
• Eclipse = Varian TPS
• Pinnacle3 = Phillips

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3
Q

Values required for TPS Commissioning

A
  • Output Factors
  • Depth Dose Data
  • A large proportion of data is measured on the central axis
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4
Q

Two Components of Dose

A
  • Primary radiation (Dprim)
  • Scattered radiation (Dscat)
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5
Q

Does Penumbra alter the accuracy of the dose calculation algorithm?

A

Not all algorithms can calculate dose accurately in the penumbra region

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6
Q

Different Classes of Algorithms

A

Factor-Based Algorithms
Model-Based Algorithms

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7
Q

Factor Based Algorithms

A
  • Based on measured data
  • Example: Clarkson’s Technique
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8
Q

Model Based Algorithm (Parts and Examples)

A

Consists of two parts:

  1. a part of the algorithm that models the beam, and provides a representation of the fluence distribution before the beam enters the patient
  2. a part that models the patient, usually based on a tomographic representation of the patient tissues
  • Examples: Monte-Carlo, CCC, AAA, PB
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9
Q

What is the intent of algorithms?

A

To predict with as much accuracy as possible the dose delivered to any point in the patient

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10
Q

Speed and accuracy of most common algorithms

A
  • PB (Least accurate, Fastest)
  • Convolution (Intermediate)
  • Monte Carlo (Most accurate, Slowest)
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11
Q

Examples of Photon Algorithms

A

PB, Convolution, Superposition, Monte Carlo, AcurosXB

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12
Q

What is a Convolution?

A
  • Product of two functions to create a third
  • Dose at any point can be calculated from the convolution of TERMA and kernel
  • Dose is a product of TERMA and Kernel
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13
Q

Main Components of a Convolution

A
  1. energy imparted to the medium by the interactions of primary
    photons, called TERMA
  2. The energy deposited about a primary photon interaction site, the kernel.
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14
Q

Main Parts of a Kernel

A
  • The primary kernel calculates the primary dose
  • The scatter kernel calculates the first and multiple scatter doses.
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15
Q

What is a Scatter Kernel?

A

The summation of effects from scattering elements to calculate dose at a desired point

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16
Q

Scatter Kernel Shape

A

Tear-Drop Shape

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17
Q

What are some Variants of the Convolution Method?

A
  • Super position or Convolution Superposition Algorithms
  • Used by the TPS ‘CMS XiO’
  • Variant of the Superposition-Convolution Algorithm = CCC
18
Q

PB Algorithm

A
  • Still clinically used for IMRT/VMAT optimisation (not dose calculation)
  • Used in the first stage of IMRT/VMAT optimisation (finds initial set of control points)
  • Faster speed of PB is preferable to CCC or MC
19
Q

Pencil Beam Convolution Algorithms

A
  • anisotropic analytical algorithm (AAA) used by Eclipse TPS is based on PB-Convolution technique
  • AAA uses spatially variant convolution scatter kernels, from Monte Carlo simulation, to separate modelling for primary photons,
    scattered photons, and contaminant electrons.
  • AAA is attractive option for routine clinical use because of its relatively short computation time and accuracy comparted to Monte Carlo
20
Q

Electron Algorithms

A
  • Dose calculations are more complicated than photons
  • Side scattering of the electrons is more pronounced and has more influence on the dose distribution

Algorithm Examples
- Clarkson

21
Q

Clarkson Algorithm

A
  • Used on the CMS-XiO TPS
  • Measurement based method
  • Not accurate dose calculation
22
Q

Pencil Beam model for Electrons

A
  • Pinnacle3 uses PB for electron
  • Has problems in regions of inhomogeniety

-Tends to underestimate the effects of sharp discontinuities in density

23
Q

Monte-Carlo Dose Calculation Simulation Process

A

⇒ Start with an electron exiting from waveguide.
⇒ Follow it and its descendants through targets,
primary collimators, ion chambers etc.
⇒ Track it through patient-dependant structures (jaws,
MLC etc.).
⇒ Track it through the patient (as modelled from CT
data set).

24
Q

Monte Carlo Simulation

A
  • Is a stochastic integration method
  • Monte Carlo calculated quantities are subject to statistical uncertainties
  • One must simulate an infinite number of histories for a zero uncertainty
25
Q

What are histories in the Monte-Carlo Simulation

A

-the number of particles generated by the source model

26
Q

Statistical Uncertainty

A

Statistical Uncertainty (SU) is proportional to 1/√N

27
Q

What happens to the calculation time if you reduce the statistical uncertainty

A

Reducing the SU, calc time is increased

28
Q

Dose Distribution from Monte Carlo Simulation

A

⇒ Any MC-calculated dose distribution will be a noisy representation of the true dose distribution

28
Q

Dose Distribution from Monte Carlo Simulation

A

⇒ Any MC-calculated dose distribution will be a noisy representation of the true dose distribution

29
Q

What does the SU in MC Computed Dose affect in the treatment planning process?

A
  1. Isodose representations- appearance (noise)
  2. DVH accuracy diminishes
  3. Maximum and minimum dose in a volume affected
  4. Dose metrics such as TCP, NTCP, EUD are affected
  5. Cost functions used for treatment plan optimization are
    also affected.
30
Q

What would be the effect of increasing statistical uncertainty (SU) beyond 10% per calculation?

A

Further from 1, the isodose lines will display with more noise (increasing will change the visualisation of isodose line) (preferred is <2%)

31
Q

Benefits of PB

A

Fast
Accounts for scatter

32
Q

Limitations of PB

A

Doesn’t account for increased lateral scatter which occurs when the beam interacts with air.

Poor representation of inhomogeneity effects

-Assumes monoenergetic beams

-Struggle to deal with irregular contours

33
Q

Benefits of CONV/SUP-CONV

A

+ Accounts for inhomogeneities
+ Accounts for spectrum of energies
+ Accounts for beam modifiers

34
Q

Limitations of CONV/SUP-CONV

A

-Relatively Slow
-Difficult to commission

35
Q

Benefits of MC

A

+ Extremely accurate
+ Inherently accounts for patient and beam parameters

36
Q

Limitations of MC

A
  • Demanding of computing power
  • Slow compared to other Algorithms
  • Difficult to commission
37
Q

Acuros XB algorithm

A
  • advanced dose calc algorithm on Eclipse TPS
    Simulates an infinite number of particles, and systematic errors are introduced by discretisation in space, angle and energy
38
Q

What is SVD algorithm

A

The singular value decomposition
- used in pinnacle and raystation
Separates the lateral and depth direction of a pencil beam distribution in water therby saves memory and increases calc speed

39
Q

Model based algorithms use clinically

A

Eclipse - AAA, Acuros, EMC
Monaco - EMC, CC, PB
Pinnacle - CCC, SVD, PB
Raystation - CC, VMC, SVD
Oncentra MP - VMC, CCC
XiO - Superposition, clarkson, FFF

CSB049 - Planning 2 (8 decks)

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