Determining Target Margins

Margins account for residual uncertainties present during treatment. An appropriate margin accounts for systematic and random treatment errors while minimizing the treated volume to the degree possible.

 Systematic ErrorRandom Error
DefinitionSystematic errors are those errors which have a non-zero mean and accumulate linearly over the course of treatment. Random errors are those with a mean of zero and the amplitude of which varies from period to another.
Effect on Dose DistributionSystematic errors shift the dose distribution relative geometrically. They are much more important than random errors because they result can result in significant, localized under dosing.Random errors result in "blurring" of the dose distribution with maximal effect at volume margin.
Common Examples
  • Imaging geometric uncertainty
    • Image resolution
    • Non-linearity
  • Contour delineation
  • Patient position during sim
  • Patient positioning during treatment
    • Offsets in laser or treatment system imaging
  • Patient positioning error during treatment
  • Inter and intra-fraction organ motion

Quantifying Error Sources

Errors may be determined on the clinical scale evaluation of the error present in a few cases. See the below example in which 3 patients undergo the same simulation and treatment technique.

Mean Group (Treatment type) systematic error, M, is determined as the mean of each treatment’s error.

Standard Deviation (SD) of group systematic error, Σ, is determined as the standard deviation of the each patient’s mean error.

Mean of random error is taken to be zero by definition.

Standard deviation (SD) of random error, σ, is determined as the root mean square (RMS) of the standard deviation of each patients treatment error.

Example: Quantifying Error

 Patient 1 Setup ErrorPatient 2 Setup ErrorPatient 3 Setup Error 
Day 1212
Day 2101
Day 33-11




Group Systematic Error = Mean of means = 1.11
SD of Group Error = SD of means = 1.02
SD of Random Error = RMS of SDs = 0.88

Biological Factors Influencing Margins

Several biological factors influence TCP and probability of achieving prescription dose. Although technological limitations mean these factors are not routinely monitored, it is important to be aware of the effects. As biological imaging improves, these factors will become important in creating patient specific margins.

  • Probability of tumor cell presence outside gross tumor volume (in CTV)
  • Density of tumor cells
    • Greater tumor cell density requires a higher dose for control
  • Tumor cell radiosensitivity
    • Tumor cells with more oxygen are more radiosensitive
  • Proximity of normal tissue to target
    • A nearby radiosensitive normal structure may merit reduction to prevent unacceptable complications.

Margin Formulas

Several Authors have generated formulae (recipes) for establishing margins based on probability of achieving prescription or tumor control probability (TCP) change.​1​​2​​3​​4​ These generally weight the systematic error component, Σ, more heavily than the random error component, σ, because of their relative impacts on plan quality. Below is one representative margin recipe put forth by Van Herk et al. to assure a minimum dose to CTV is 95% for 90% of patients assuming a dose distribution with perfect conformation.


Main Page

Simulation, Imaging, and Controuring Table of Contents

Next Page

Treatment Planning
Table of Contents

Not a Premium Member?

Sign up today to get access to hundreds of ABR style practice questions.