Direct aperture optimization for IMRT using Monte Carlo generated beamlets

Journal Article · Sun Oct 15 04:00:00 EDT 2006 · Medical Physics

DOI:https://doi.org/10.1118/1.2336509· OSTI ID:20853587

Bergman, Alanah M; Bush, Karl; Milette, Marie-Pierre; Popescu, I Antoniu; Otto, Karl; Duzenli, Cheryl ^[1]

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1. Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia (Canada)

This work introduces an EGSnrc-based Monte Carlo (MC) beamlet does distribution matrix into a direct aperture optimization (DAO) algorithm for IMRT inverse planning. The technique is referred to as Monte Carlo-direct aperture optimization (MC-DAO). The goal is to assess if the combination of accurate Monte Carlo tissue inhomogeneity modeling and DAO inverse planning will improve the dose accuracy and treatment efficiency for treatment planning. Several authors have shown that the presence of small fields and/or inhomogeneous materials in IMRT treatment fields can cause dose calculation errors for algorithms that are unable to accurately model electronic disequilibrium. This issue may also affect the IMRT optimization process because the dose calculation algorithm may not properly model difficult geometries such as targets close to low-density regions (lung, air etc.). A clinical linear accelerator head is simulated using BEAMnrc (NRC, Canada). A novel in-house algorithm subdivides the resulting phase space into 2.5x5.0 mm{sup 2} beamlets. Each beamlet is projected onto a patient-specific phantom. The beamlet dose contribution to each voxel in a structure-of-interest is calculated using DOSXYZnrc. The multileaf collimator (MLC) leaf positions are linked to the location of the beamlet does distributions. The MLC shapes are optimized using direct aperture optimization (DAO). A final Monte Carlo calculation with MLC modeling is used to compute the final dose distribution. Monte Carlo simulation can generate accurate beamlet dose distributions for traditionally difficult-to-calculate geometries, particularly for small fields crossing regions of tissue inhomogeneity. The introduction of DAO results in an additional improvement by increasing the treatment delivery efficiency. For the examples presented in this paper the reduction in the total number of monitor units to deliver is {approx}33% compared to fluence-based optimization methods.

• OSTI ID: 20853587
• Journal Information: Medical Physics, Journal Name: Medical Physics Journal Issue: 10 Vol. 33; ISSN 0094-2405; ISSN MPHYA6
• Country of Publication: United States
• Language: English

Related Subjects

62 RADIOLOGY AND NUCLEAR MEDICINE
ACCURACY
ALGORITHMS
APERTURES
COLLIMATORS
COMPUTERIZED SIMULATION
DOSIMETRY
EFFICIENCY
LINEAR ACCELERATORS
LUNGS
MONTE CARLO METHOD
OPTIMIZATION
PATIENTS
PHANTOMS
PHASE SPACE
PLANNING
RADIATION DOSE DISTRIBUTIONS
RADIATION DOSES
RADIOTHERAPY