RESUMO
Objective.Compact ion imaging systems based on thin detectors are a promising prospect for the clinical environment since they are easily integrated into the clinical workflow. Their measurement principle is based on energy deposition instead of the conventionally measured residual energy or range. Therefore, thin detectors are limited in the water-equivalent thickness range they can image with high precision. This article presents ourenergy paintingmethod, which has been developed to render high precision imaging with thin detectors feasible even for objects with larger, clinically relevant water-equivalent thickness (WET) ranges.Approach.A detection system exclusively based on pixelated silicon Timepix detectors was used at the Heidelberg ion-beam therapy center to track single helium ions and measure their energy deposition behind the imaged object. Calibration curves were established for five initial beam energies to relate the measured energy deposition to WET. They were evaluated regarding their accuracy, precision and temporal stability. Furthermore, a 60 mm × 12 mm region of a wedge phantom was imaged quantitatively exploiting the calibrated energies and five different mono-energetic images. These mono-energetic images were combined in a pixel-by-pixel manner by averaging the WET-data weighted according to their single-ion WET precision (SIWP) and the number of contributing ions.Main result.A quantitative helium-beam radiograph of the wedge phantom with an average SIWP of 1.82(5) % over the entire WET interval from 150 mm to 220 mm was obtained. Compared to the previously used methodology, the SIWP improved by a factor of 2.49 ± 0.16. The relative stopping power value of the wedge derived from the energy-painted image matches the result from range pullback measurements with a relative deviation of only 0.4 %.Significance.The proposed method overcomes the insufficient precision for wide WET ranges when employing detection systems with thin detectors. Applying this method is an important prerequisite for imaging of patients. Hence, it advances detection systems based on energy deposition measurements towards clinical implementation.
