Purpose: To improve the accuracy of a prototype proton computed tomography (pCT) scanner in imaging of the stopping power relative to water (RSP) used for particle therapy treatment planning, by reducing image artifacts using an empirical artifact correction method.
Methods: Inaccurate measurements of the water-equivalent pathlengths (WEPLs; RSP line integrals) degrade the performance of a prototype pCT scanner. An x-ray CT beam hardening correction was adapted to the requirements of pCT and used to calculate a correction function mapping distorted WEPLs to their corrected values. The function was optimized exploiting the linearity of the filtered backprojection operator and based on an experimental scan of a custom-built elliptical correction phantom with known RSP. The proposed method is simple and robust since it does not require knowledge of the correction phantom’s geometry. It was applied in subsequent scans of a water phantom, a sensitometry phantom and a pediatric head phantom.
Results: Application of the optimized correction function reduced an offset in the RSP maps and removed ring-shaped artifacts mainly stemming from protons stopping close to interfaces between segments of the energy detector. The scan of the water phantom was considerably more homogeneous. The mean absolute percentage RSP error reduced from 0.87% to 0.46%, which is an improvement by 47%. Artifacts visible in the head phantom were largely obviated.
Conclusion: With the proposed method, the amplitude of artifacts of a prototype pCT scanner could be almost halved. This is to date the best RSP accuracy reported for a pCT scanner. There may also be an improvement compared to state-of-the-art dual-energy x-ray CT, for which errors of 0.7% were reported. Using pCT together with the empirical artifact correction method may help to reduce range calculation uncertainties in image-guided particle therapy.
Funding Support, Disclosures, and Conflict of Interest: This work was supported by the German Research Foundation (DFG) project #388731804 and the DFG's Cluster of Excellence Munich-Centre for Advanced Photonics (MAP) and by the Bavaria-California Technology Center (BaCaTeC). Additional funding from the Zusatzfinanzierung 2019 fuer DFG-Sachbeihilfen from the Forschungsdekanat of the Faculty of Medicine of the LMU Munich.