TG 105 Flashcards
What is TG-105 on?
TPS commissioning of Monte-Carlo photon and electron EBRT
what dose differences are clinically detectable?
-on the order of 7%
-5%changes in dose can result in 10%−20% changes in tumor control probabilityTCPor up to 20–30%changes in normal tissue complica-tion probabilitiesNCTPif the prescribed dose falls along the steepest region of the dose-effect curves
4 main steps in analog simulation of particle transport
1Select the distance to the next interaction.
2Transport the particle to the interaction site taking into account geometry constraints.
3Select the interaction type.
4Simulate the selected interaction.
Steps 1–4 are repeated until the original particle and allsecondary particles leave the geometry or are locally ab-sorbed. A particle is considered to be locally absorbed whenits energy falls below a specified threshold energy.
condensed history simulation
electrons undergo many small energy changes as they scatter
-group these into condensed history steps
class I condensed history
all collisions are subject to grouping. The effect of secondary particle creation above specified threshold energies are taken into account after the facti.e., independently of the energy actually lost during the stepby setting up and transporting the appropriate number of secondary particles. In this way the correlation between large energy losses and secondary particle creation is lost
class II condensed history
interactions are divided into “hard”sometimes also referred to as “cata-strophic”and “soft” collisions. Soft collisions are subject to grouping as in a class I scheme; hard collisions are explicitly simulated in an analog manner
-subject to analog simulation- but it is harder because the paths are not straight lines like they are for photons
step-size artifacts
Dependencies of the calculated re-sults on the step size
advantage of using phase space
calculation of electron as it exits linac, strikes head components etc is already done, speeding up calculations
virtual source model
-method for getting phase space that doesn’t use MC
-One class of virtual source models is based on characterizing the results of a MC simulation of the accel-erator head and another class is based solely on measured beam data such as depth-dose curves, profiles and output ratios. In either case, the patient-dependent componentse.g.,the MLCare simulated using either explicit transport meth-ods or approximate transport methods before detailed trans-port in the patient.
variance reduction technique
Techniques which improve the efficiency by changing the variance for a given N while not biasing the resulti.e., not changing the expectation value which is the value expected in an infinitely long run
Variance reduction techniques often in-crease the time to simulate a single history and are only useful if the overall efficiency is improved. A given tech-nique may increase the efficiency for some quantities being scored and decrease it for others
other options to reduce calc time outside of variance reduction techniques
-make an approximation which may or may not affect the result in a significant way
bremsstrahlung splitting
-variance reduction technique
-In the various forms of bremsstrahlung split-ting, each time an electron is about to produce a bremsstrah-lung secondary, a large number of secondary photons with lower weights are set in motion, the number possibly de-pending on a variety of factors related to the likelihood of them being in the field. If the number of photons created is selected to minimize those that are not directed toward the patient plane, then there is a further saving in time.
roussian roulette
-variance reduction technique
- The lowinterest particles are eliminated with a given probability, butto ensure an unbiased result, the weights of the survivingparticles are increased by the inverse of that probability
photon forcing
-variance reduction technique
-the parent photon is forced to interact in a given geometric region and the weights of the resulting particles are adjusted accordingly to maintain an unbiased result
range rejection
In range rejection, an electron’s history is terminated whenever its residual range is so short that it can-not escape from the current region or reach the region of interest. In most implementations this ignores the possible creation of bremsstrahlung photons while the electron loses energy which means this is an approximate technique. When applied to electrons below a certain energy threshold, this form of range rejection produces the same results in a re-duced computing time. It is also possible to implement range rejection in a manner which properly accounts for bremsstrahlung production and thus make it an unbiased variance reduction technique
