Publications by authors named "Mark Brooke"

3 Publications

  • Page 1 of 1

Incorporating oxygenation levels in analytical DNA-damage models-quantifying the oxygen fixation mechanism.

Phys Med Biol 2021 Jul 9;66(14). Epub 2021 Jul 9.

University of Oxford, Department of Oncology, Oxford, United Kingdom.

To develop a framework to include oxygenation effects in radiation therapy treatment planning which is valid for all modalities, energy spectra and oxygen levels. The framework is based on predicting the difference in DNA-damage resulting from ionising radiation at variable oxygenation levels.Oxygen fixation is treated as a statistical process in a simplified model of complex and simple damage. We show that a linear transformation of the microscopic oxygen fixation process allows to extend this to all energies and modalities, resulting in a relatively simple rational polynomial expression. The model is expanded such that it can be applied for polyenergetic beams. The methodology is validated using Microdosimetric Monte Carlo Damage Simulation code (MCDS). This serves as a bootstrap to determine relevant parameters in the analytical expression, as MCDS is shown to be extensively verified with published empirical data. Double-strand break induction as calculated by this methodology is compared to published proton experiments. Finally, an example is worked out where the oxygen enhancement ratio (OER) is calculated at different positions in a clinically relevant spread out Bragg peak (SOBP) dose deposition in water. This dose deposition is obtained using a general Monte Carlo code (FLUKA) to determine dose deposition and locate fluence spectra.For all modalities (electrons, protons), the damage categorised as complex could be parameterised to within 0.3% of the value calculated using microdosimetric Monte Carlo. The proton beam implementation showed some variation in OERs which differed slightly depending on where the assessment was made; before the SOBP, mid-SOBP or at the distal edge. Environment oxygenation was seen to be the more important variable.An analytic expression calculating complex damage depending on modality, energy spectrum, and oxygenation levels was shown to be effective and can be readily incorporated in treatment planning software, to take into account the impact of variable oxygenation, forming a first step to an optimised treatment based on biological factors.
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July 2021

An inhomogeneous most likely path formalism for proton computed tomography.

Phys Med 2020 Feb 7;70:184-195. Epub 2020 Feb 7.

Department of Physics, University of Adelaide, Adelaide, South Australia 5005, Australia; Department of Medical Physics, Royal Adelaide Hospital, Adelaide, South Australia 5000, Australia.

Purpose: Multiple Coulomb scattering (MCS) poses a challenge in proton CT (pCT) image reconstruction. The assumption of straight paths is replaced with Bayesian models of the most likely path (MLP). Current MLP-based pCT reconstruction approaches assume a water scattering environment. We propose an MLP formalism based on accurate determination of scattering moments in inhomogeneous media.

Methods: Scattering power relative to water (RScP) was calculated for a range of human tissues and investigated against relative stopping power (RStP). Monte Carlo simulation was used to compare the new inhomogeneous MLP formalism to the water approach in a slab geometry and a human head phantom. An MLP-Spline-Hybrid method was investigated for improved computational efficiency.

Results: A piecewise-linear correlation between RStP and RScP was shown, which may assist in iterative pCT reconstruction. The inhomogeneous formalism predicted Monte Carlo proton paths through a water cube with thick bone inserts to within 1.0 mm for beams ranging from 210 to 230 MeV incident energy. Improvement in accuracy over the conventional MLP ranged from 5% for a 230 MeV beam to 17% for 210 MeV. There was no noticeable gain in accuracy when predicting 200 MeV proton paths through a clinically relevant human head phantom. The MLP-Spline-Hybrid method reduced computation time by half while suffering negligible loss of accuracy.

Conclusions: We have presented an MLP formalism that accounts for material composition. In most clinical cases a water scattering environment can be assumed, however in certain cases of significant heterogeneity the proposed algorithm may improve proton path estimation.
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February 2020

Sparsity constrained split feasibility for dose-volume constraints in inverse planning of intensity-modulated photon or proton therapy.

Phys Med Biol 2017 05 5;62(9):3599-3618. Epub 2017 Apr 5.

Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA 5000, Australia. Department of Physics, University of Adelaide, Adelaide, SA 5005, Australia.

A split feasibility formulation for the inverse problem of intensity-modulated radiation therapy treatment planning with dose-volume constraints included in the planning algorithm is presented. It involves a new type of sparsity constraint that enables the inclusion of a percentage-violation constraint in the model problem and its handling by continuous (as opposed to integer) methods. We propose an iterative algorithmic framework for solving such a problem by applying the feasibility-seeking CQ-algorithm of Byrne combined with the automatic relaxation method that uses cyclic projections. Detailed implementation instructions are furnished. Functionality of the algorithm was demonstrated through the creation of an intensity-modulated proton therapy plan for a simple 2D C-shaped geometry and also for a realistic base-of-skull chordoma treatment site. Monte Carlo simulations of proton pencil beams of varying energy were conducted to obtain dose distributions for the 2D test case. A research release of the Pinnacle proton treatment planning system was used to extract pencil beam doses for a clinical base-of-skull chordoma case. In both cases the beamlet doses were calculated to satisfy dose-volume constraints according to our new algorithm. Examination of the dose-volume histograms following inverse planning with our algorithm demonstrated that it performed as intended. The application of our proposed algorithm to dose-volume constraint inverse planning was successfully demonstrated. Comparison with optimized dose distributions from the research release of the Pinnacle treatment planning system showed the algorithm could achieve equivalent or superior results.
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May 2017