Abstract
Particle therapy treatment planning requires accurate volumetric maps of the relative stopping power, which can directly be acquired using proton computed tomography (pCT). With fluence-modulated pCT (FMpCT) imaging fluence is concentrated in a region-of-interest (ROI), which can be the vicinity of the treatment beam path, and imaging dose is reduced elsewhere. In this work we present a novel optimization algorithm for FMpCT which, for the first time, calculates modulated imaging fluences for joint imaging dose and image variance objectives. Thereby, image quality is maintained in the ROI to ensure accurate calculations of the treatment dose, and imaging dose is minimized outside the ROI with stronger minimization penalties given to imaging organs-at-risk. The optimization requires an initial scan at uniform fluence or a previous x-ray CT scan. We simulated and optimized FMpCT images for three pediatric patients with tumors in the head region. We verified that the target image variance inside the ROI was achieved and demonstrated imaging dose reductions outside of the ROI of 74% on average, reducing the imaging dose from 1.2 to 0.3 mGy. Such dose savings are expected to be relevant compared to the therapeutic dose outside of the treatment field. Treatment doses were re-calculated on the FMpCT images and compared to treatment doses re-recalculated on uniform fluence pCT scans using a 1% criterion. Passing rates were above 98.3% for all patients. Passing rates comparing FMpCT treatment doses to the ground truth treatment dose were above 88.5% for all patients. Evaluation of the proton range with a 1 mm criterion resulted in passing rates above 97.5% (FMpCT/pCT) and 95.3% (FMpCT/ground truth). Jointly optimized fluence-modulated pCT images can be used for proton dose calculation maintaining the full dosimetric accuracy of pCT but reducing the required imaging dose considerably by three quarters. This may allow for daily imaging during particle therapy ensuring a safe and accurate delivery of the therapeutic dose and avoiding excess dose from imaging.
Highlights
Particle therapy treatment planning for irradiation of tumors requires a precise knowledge of a patients anatomy (Engelsman et al 2013, Landry and Hua 2018), in particular of the stopping power relative to water relative stopping power (RSP)
In figures 2(d)–(f) the cost function of the pencil beam optimization averaged over all projections is shown
In this work we propose an algorithm with dose and variance objectives for fluence field optimization of proton computed tomography (CT) for particle therapy treatment planning
Summary
Particle therapy treatment planning for irradiation of tumors requires a precise knowledge of a patients anatomy (Engelsman et al 2013, Landry and Hua 2018), in particular of the stopping power relative to water relative stopping power (RSP). More frequent and ideally daily imaging could detect anatomical changes that inevitably occur during treatment Since this is currently not possible, additional margins have to be considered to cover such changes (Wedenberg et al 2018). An improvement of RSP accuracy and daily imaging in treatment position with low imaging dose may be possible using proton CT (pCT), which was proposed by Cormack (1963) and later realized by Hanson et al (1977). It directly uses the energy loss of protons for tomographic imaging of the RSP. This achieves a better dose efficiency than x-ray CT assuming ideal detectors (Schulte et al 2005) and a pre-clinical prototype scanner produced a comparable accuracy to state-of-the-art clinical dual-energy x-ray CT (Dedes et al 2019)
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