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Dose calculation

Monte Carlo treatment planning

In clinical practice, analytical models based on measured data are used to perform the calculation of the 3-dimensional delivered dose. Based on this dose calculation, the patient treatment is planned and optimized to avoid high dose in organs at risk and guarantee sufficient dose in the tumor. Unfortunately, in cases with pronounced tissue inhomogeneities - e.g. lung tumors – analytical models predict wrong dose values with relative errors of more than ten percent. As a result, the delivered dose to the patient can differ drastically from the planned dose distribution as indicated in figure 1.

Figure 1: a) Planned dose, calculated with an analytical pencil beam algorithm. b) Delivered dose calculated with a Monte Carlo algorithm, showing an under-dosage of the lung tumor.

One alternative to analytical methods are so called Monte Carlo algorithms, which simulate particles (photons or protons) and relevant interactions with the patient and memorize the energy depositions. The accuracy of Monte Carlo dose simulations is unbeaten and in fantastic agreement with measurements. However, in order to get statistically significant results, a large number of particles have to be simulated. Therefore, the calculation time of Monte Carlo algorithms is generally much longer than traditional methods. Thus, the goal of this work is a drastic reduction of the algorithmic runtime. Our approach is to find strategies to minimize the number of simulated particles while preserving the accuracy of the dose calculation and the treatment plan optimization simultaneously.

People involved

  • Martin Siggel, PhD student

Dose calculation for kV-imaging in radiotherapy

Image guided radiation therapy is increasingly being used in clinical practice. Due to the high image quality achieved at relatively low doses, kilovoltage- (kV-) imaging is a widely used option to position the patient and assess the tumor position. While daily imaging improves the treatment precision this also implies an additional radiation exposure to the patient [1].

Even though the dose applied during a single kV- cone beam CT might seem very low compared to the typical dose prescribed in a radiation treatment, the dose to organs at risk can reach a significant level due to the daily repetition of the imaging procedure [2]. In addition, unlike the dose due to treatment the imaging dose is not focused on the tumor, organs at risk often receive a higher dose than the tumor itself.

A dose calculation algorithm for kV-imaging offers the possibility to include the imaging dose in the treatment planning process or to adapt the imaging process itself to improve the combined dose distribution of imaging and treatment. Due to the different energy range and the hence occurring interaction processes, standard dose calculation algorithms used for the treatment dose calculation cannot be used in this case. We are aiming to develop a pencil beam algorithm which allows for a fast calculation of patient specific dose distributions due to kV-imaging.

People involved

  • Siri Jetter, PhD student
  • Stefan Bartzsch, MSc student

Dose Calculation in a Magnetic Field

With respect to soft-tissue contrast, magnetic resonance imaging (MRI) is superior to x-ray based techniques and no extra dose of ionizing radiation is associated with MRI. Approaches therefore exist to make this functionality available on-line, i.e. during the radiation treatment procedure. On-line availability of an MR system requires the permanent presence of the main magnetic field in the treatment room. Dose deposition will be affected by this magnetic field since the secondary electrons produced in the medium are subject to the Lorentz force. Other groups have observed that dose deposition is asymmetric in the presence of a magnetic field, and further modifications exist at the boundaries of anatomical cavities. [3,4,5]

Figure 2: Cut-away view of the MRI accelerator built at the UMC Utrecht, with kind permission. Find more details on their website.

Figure 3: Dose deposition of a monoenergetic photon beam (3MeV) in a cube of water without and in the presence of a magnetic field; dose in arbitrary units. The direction of incidence is from below.

We are investigating the effects in more detail with the use of Monte Carlo methods, which presently constitute the only means of dose calculation capable of including magnetic fields. Kernel-based dose calculation methods - which are generally faster than Monte Carlo techniques – have not yet been developed in this context. Appropriate kernels are therefore sought to be used in a fast and reliable method for dose calculation in the presence of a magnetic field. Such a dose calculation algorithm could then be used for on-line correction of the treatment plan in order to account for existing differences in patient anatomy and tumor position or size with respect to the images acquired beforehand and that the treatment planning was based on. [6]

People involved

  • Asja Pfaffenberger, PhD student

Selected publications

[1] Mohammad K. Islam, Hamideh Alasti, Douglas J. Moseley, and Michael B. Sharpe: Patient dose from kilovoltage cone beam computed tomography imaging in radiation therapy. 2006 Med. Phys. 33.

[2] Chow JC, Leung MK, Islam MK, Norrlinger BD, Jaffray DA.: Evaluation of the effect of patient dose from cone beam computed tomography on prostate IMRT using Monte Carlo simulation. 2008 Med Phys. 35.

[3] Raaijmakers et al. 2005: Integrating a MRI scanner with a 6 MV radiotherapy accelerator: dose increase at tissue–air interfaces in a lateral magnetic field due to returning electrons 2005 Phys. Med. Biol. 50 1363.

[4] Raaijmaker et al. 2008: Magnetic-field-induced dose effects in MR-guided radiotherapy systems: dependence on the magnetic field strength 2008 Phys. Med. Biol. 53 909.

[5] Kirkby et al. 2008: Dosimetry for hybrid MRI-radiotherapy systems Med. Phys. 35, 1019 (2008).

[6] Pfaffenberger A & Oelfke U 2011: A transformation approach for dose calculation in a magnetiv field.


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