Treatment planning, software and algorithms 07/02 Flashcards
What does hand planning involve?
Manual manipulation of isodose charts
What does computerised treatment planning involve?
Plan optimisation
Why do we use CT for planning but not just MR?
For MR, there are no Hounsfield units so there is no electrical density in MR which means the dose is all based upon density and how the radiation interacts based on the structure it is going through. Due to this you cannot plan on MR.
Treatment Plans are produced – how the linac will deliver the RT - 3 main things in mind
Treats the TVs (Target Volume)
Reduces dose to OAR (Organs at risk)
Minimises dose to normal tissues
What do plans demonstrate?
The expected dose distribution in a patients tissue
Overall dose of radiation delivered will achieve the aim of the treatment, which is?
Radical – with intent to cure
Palliative - to relieve symptoms
Radical or palliative?
Consider dose per fraction (daily dose)
Total dose
Number of fractions (treatments)
Radical treatment features
Larger total doses given over a number of treatments (fractions #)
Daily Dose = Total Dose / No #
E.g., Typical Radical H&N 70Gy / 35# = 2Gy per #
Healthy cells have opportunity to recover during the course
Same dose over all fractions. Side effects not due to more intense dose over fractions but due to differences in DNA composition > intensity remains the same.
Palliative treatment features
Overall smaller total doses over fewer fractions
Daily dose = Total dose / No #
E.g., 20Gy / 5# = 4Gy per #
Individual dose greater than radical individual dose
Often role is to improve symptoms
Palliative Treatment Planning pathway
Simple plan arrangement Lower doses Emergency Oncology Little risk to healthy tissues GTV, CTV, & PTV generally not outlined Quick – treatment same day
Often called Virtual Simulation or V-S
Radical Treatment Planning pathway
Complex plans
Higher doses
Risk to healthy tissues can be calculated accurately
Target volumes outlined
Requires geometric verification – imaging e.g., KV, Cone beam CT
May require dosimetric verification
Time consuming – days-weeks
Treatment Planning Pathway
Patient has a RTP-CT in suitable & reproducible position
CT Data is imported into the TPS (Eclipse/Pinnacle/RayStation)
Contours of target volumes & OAR are delineated – by the clinician
+/- radiographer
A individualised treatment plan is produced & MU calculated using the treatment planning algorithm
Plans are reviewed by clinician
Plans are independently checked by ‘plan checker’
Plans are exported to the treatment machine
4 common UK RTP systems
Philips - pinnacle
Varian - eclipse
Nucletron
Research - ray station
What information does a treatment plan contain?
Total Dose / # Prescription Point Beam type – x-Ray, electrons, protons Machine information – treatment machine, beam energy, field size, beam modifications, technique Moves to isocentre Bolus Target Volumes Coverage of volumes & OAR information MU required to deliver each beam DRR’s / Verification images In-vivo dose measurements
What do algorithms allow us to do?
Algorithms allows us to demonstrate how we visualise dose in a medium. This allows use to predict with as much accuracy as possible the dose delivered to any point in the patient.
Uses CT data, beam direction and beam characteristics to calculate the dose at any point within the patient
Responsible for correct representation of dose in the patient
Clinical decisions can/may be taken from the resulted dose distribution
Dose calculations are linked to monitor unit (MU)
Dose calculation algorithms
Central axis models Semi-empirical models Pencil beam algorithms Convolution algorithms Monte Carlo simulation (increasing accuracy and decreasing speed)
Models are based upon
Models of electrons striking the target in the linac
Model propagation through the head of Linac
Models of interactions with the patient
Dose is computed by
Modelling the beam
Modelling the interactions in the patient model
Pencil beam algorithm
Assumes lots of forward facing ‘pencil’ beams called Kernals
Does not account for inhomogeneity’s well
Assumption that each pencil beam is the same energy
Fast and cheap
Widely used for optimisation of IMRT when using inverse planning or calculation of electrons
AAA algorithm
A convolution superposition algorithm
Based upon the Monte-Carlo simulated dose distribution
Correctly models the beam passing through the linac head and the patient
Calculates dose at bone/air/soft tissue interfaces better than P.B.
Fairly quick and mid-cost
Monte Carlo algorithm
Based upon probabilities
Random & ‘game-like’ behaviours of beams is similar to that of gambling
Used for quality assurance
Accurate ++ (better understanding of dose inhomogeneity’s)
Cost ++
Calculation time – (long)
