Abstract
Fluence-modulated proton computed tomography (FMpCT) using pencil beam scanning aims at achieving task-specific image noise distributions by modulating the imaging proton fluence spot-by-spot based on an object-specific noise model. In this work, we present a method for fluence field optimization and investigate its performance in dose reduction for various phantoms and image variance targets. The proposed method uses Monte Carlo simulations of a proton CT (pCT) prototype scanner to estimate expected variance levels at uniform fluence. Using an iterative approach, we calculate a stack of target variance projections that are required to achieve the prescribed image variance, assuming a reconstruction using filtered backprojection. By fitting a pencil beam model to the ratio of uniform fluence variance and target variance, relative weights for each pencil beam can be calculated. The quality of the resulting fluence modulations is evaluated by scoring imaging doses and comparing them to those at uniform fluence, as well as evaluating conformity of the achieved variance with the prescription. For three different phantoms, we prescribed constant image variance as well as two regions-of-interest (ROI) imaging tasks with inhomogeneous image variance. The shape of the ROIs followed typical beam profiles for proton therapy. Prescription of constant image variance resulted in a dose reduction of 8.9% for a homogeneous water phantom compared to a uniform fluence scan at equal peak variance level. For a more heterogeneous head phantom, dose reduction increased to 16.0% for the same task. Prescribing two different ROIs resulted in dose reductions between 25.7% and 40.5% outside of the ROI at equal peak variance levels inside the ROI. Imaging doses inside the ROI were increased by 9.2% to 19.2% compared to the uniform fluence scan, but can be neglected assuming that the ROI agrees with the therapeutic dose region. Agreement of resulting variance maps with the prescriptions was satisfactory. We developed a method for fluence field optimization based on a noise model for a real scanner used in pCT. We demonstrated that it can achieve prescribed image variance targets. A uniform fluence field was shown not to be dose optimal and dose reductions achievable with the proposed method for FMpCT were considerable, opening an interesting perspective for image guidance and adaptive therapy.
Highlights
Cancer treatment using intensity–modulated proton and heavier ion therapy is effective, and comes at a low risk of side–effects for the patient compared to conventional treatment modalities using x–rays
The good tolerance is believed to be linked to the low dose to normal tissue when using protons for treatment. 1–4 At the same time, low–dose, frequent and accurate imaging, ideally at the treatment site, is required to ensure a safe delivery of the therapeutic doses. 5,6 Proton therapy treatment planning requires a spatial map of the relative stopping power (RSP), which in current clinical practice is acquired through a conversion from x–ray CT images. 7–9 X–ray CT images are typically not acquired in treatment position and not prior to every treatment fraction, in order to keep treatment time short and imaging dose low enough that they do not compromise the dose benefit of proton therapy
34 The problem of finding relative modulation factors for each pencil beam such that the summed fluence pattern results in a prescribed image variance map is a computationally expensive optimization problem which generally requires alternating between the reconstructed image domain and the projection domain
Summary
Cancer treatment using intensity–modulated proton and heavier ion therapy is effective, and comes at a low risk of side–effects for the patient compared to conventional treatment modalities using x–rays. 5,6 Proton therapy treatment planning requires a spatial map of the relative (to water) stopping power (RSP), which in current clinical practice is acquired through a conversion from x–ray CT images. 10 Direct imaging of RSP using proton computed tomography (pCT) 11–16 has been proposed to increase accuracy and to allow for a frequent, dose efficient acquisition in treatment position. Fluence–modulated pCT (FMpCT) has been proposed and its initial experimental feasibility using pencil beam scanning was investigated. The best achievable dose efficiency through fluence modulation or other techniques is a key requirement for x–ray CT and most likely will be for pCT as it moves closer to the clinics. 31 We verified that the resulting variance map approaches the target variance Both a constant variance target as well as two regions–of–interest (ROI) following typical treatment beam paths were investigated
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