Medical Accelerator F. Foppiano, M.G. Pia, M. Piergentili

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Presentation transcript:

Medical Accelerator F. Foppiano, M.G. Pia, M. Piergentili M. Piergentili Genoa 8 March 2004

Problem Statement build a simulation tool which determines the dose distributions given in a phantom by the head of a linear accelerator used for IMRT. Many algorithms were developed to estimate dose distributions, but the most sophisticated ones resort to some approximations too. These approximations might affect the outcome of dose calculation, especially in a complex treatment planning as IMRT. The goal of this project is to build a simulation tool which determines the dose distributions given in a phantom by the head of a linear accelerator used for IMRT. We consider the step and shoot technics, in which the MLC stands still while the beam is on. In medical applications, dose distributions are useful because they are indicative of the quantity of radiation absorbed by tissues. Many algorithms were developed to estimate dose distributions, but the most sophisticated ones resort to some approximations too. These approximations might affect the outcome of dose calculation, especially in a complex treatment planning as IMRT. Treatment planning that implement such algorithms are expensive and not very accurate but quick and could be therefore used to have a on-line dose evaluation. step and shoot

User Descriptions Oncology is the main  utilization field of radiotherapy. The goal of radiotherapy is delivering the required therapeutic dose to the tumor area with high precision, while preserving the surrounding healthy tissue Accurate dosimetry is at the basis of radiotherapy treatment planning Tipical user of this product is a medical physicist who have to make a treatment planning and needs to verify the distribution dose released by the beam.  usually a cancer or the tissue near a tumour surgically removed, have to be irradiated with gamma rays in order to reduce the tumour dimension or to sterilize the zone. During the treatment  we have to spare the healthy tissues as much as possible. Therefore we have to know the dose of radiation given to every zone of the patient.

Phases of Treatment planning to acquire patient's data to position and to immobilize the patient to acquire the anatomy of the target to set the beam to calculate the distribution dose and the length (of time) of the treatment This simulation is used in the last part of treatment planning (dose verification). is composed of various phases:

Varian Clinac 2100 Flattening filter serves to homogenize the photon beam Each pair of jaws can be rotated through an axis that is perpendicular to the beam axis Details regarding the exact composition and shape of all these objects are still incomplete (they will arrive soon) The electrons impinge on the target where bremstrahlung-photons arise.

Intensity Modulated Radiation Therapy IMRT generates tightly conforming dose distributions. This microscopic control allows IMRT to produce dose distribution patterns that are much closer to the desired patterns than possible previously Dose distributions within the planning target volume (PTV) can be made more homogeneous and , if so desired, a much sharper fall-off of dose at PTV boundary can be achieved. This in turns means that volume of normal tissues exposed of high doses can be reduced significantly. ( but that exposed to low doses is increased) To treat concave surfaces: delivery of intentionally inhomogeneous dose distribution

User Requirements Rigorous software process OO Design Geometry Modeling Select physics processes Dosimetric analysis User Interface Rigorous software engineering is important in the medical physics domain to be maintainable over a large time scale to be extensible, to accommodate new user requirements (thanks to the OO technology)

Specific User Requirements 1.Geometry UR 1.1 The phantom will correspond to an available's one on the market UR 1.2 The user shall be able to change the position of the collimators jaws x and y UR 1.3 The user shall be able to change the configuration of the MLC (selecting the distances of the leaves from the central axis source-isocentre)  3. Primary particles UR 3.1 The user shall be able to define the mean energy and standard deviation of the electrons delivered by the head; 4. Physical processes UR 4.1 The user shall be able to define the physical processes involved for e-, e+, gamma 5. Detector UR 5.1 The Phantom is the detector; UR 5.2 The information is the energy deposit due to primary and secondary particles.

Specific User Requirements 6. Events UR 6.1 The user shall be able to retrieve information about  the energy deposit due to the primary particle delivered by the gantry and all the secondary particles generated. 7. Visualization UR 7.1 The user shall be able to visualize: the experimental set-up the tracks of the particles. the isodose plots. the PDD (Percent Depth Dose) the flatness 8. GUI UR 8.1 There will be a section in which the user can be able to select the phantom's characteristics.    UR 8.3 There will be a section in which the user can be able to select the beam's characteristics.    UR 8.4 There will be a section in which the user can be able to select the configurations of the collimators  PPD: Percent Depth Dose (distribution dose along the central axis of the beam) defined as percentage ratio betweeen the dose at some depth and the absorbed dose at the depth of  maximum dose. Flatness: distribution dose along a trasverse axis to the central axis of the beam Isodose lines are lines of constant dose and are expressed as a percentage of the maximum dose on the central axis within the phantom. It's conventional to plot the isodose distribution for planes which contain the axis of the beam.

Specific User Requirements 9. Analysis UR 9.1 The user shall be able to store the information about the primary particles energy. UR 9.2 The user shall be able to store the information about the energy deposit in the phantom.   UR 9.3 The user shall be able to calculate the isodoses. UR 9.4 The user shall be able to calculate the PDD.  UR 9.5 The user shall be able to calculate the flatness. Specific requirements: constraint requirements UR A.1 The system should work on the following platforms: Linux; Windows.

What has been done? The user can choose the energy and standard deviation of the primary particles energy distribution (Gaussian) The primary particles (e-) leave from a point source with random direction (0˚< θ < 3˚) The head components modeled include: the target, primary and secondary collimators, the flattening filter, the mirror and the air The flattening filter is modeled as a cone E and standard deviation have to be adjusted such that a reasonable match between calculation and measurement is obtained. (We know only the value of accelerating potential and two identical machines may have different effective accelerating potentials) The Initial energy of primary particles is stored in a 1D histogram

Physical processes: What has been done? Multiple scattering Bremsstrahlung Ionisation Annihilation Photoelectric effect Compton scattering Rayleigh effect gamma conversion Depth and transverse dose distributions are measured in a water phantom LowEnergyPhotoElectric    LowEnergyCompton    LowEnergyGammaConversion    LowEnergyRayleigh    MultipleScattering    LowEnergyIonisation    LowEnergyBremsstrahlung    eIonisation    eBremsstrahlung    eplusAnnihilation default cut 0.1 mm

What’s Next Real shape and dimensions of the components Monitor chamber Multi Leaf Collimator tests Comparison with experimental results (exp measurements will be taken at IST)

Possible improvements To simulate the ionisation chamber inside the water phantom Reduce Calculation time Graphical user interface Treatment planning: CT interface (to insert the geometry of the patient inside the simulation) Inverse planning (we state our clinical objectives mathematically and let the IMRT optimisation process determine the beam parameters that will lead to the desired solution, these objectives should not be unrealistic) 100% dose to the target and zero outside (they, or a good approximation of them, must be achievable and clinically optimum at the same time)