Evaluation of stopping-power prediction by dual- and single-energy computed tomography in an anthropomorphic ground-truth phantom

Publication date: Available online 17 September 2017
Source:International Journal of Radiation Oncology*Biology*Physics
Author(s): Patrick Wohlfahrt, Christian Möhler, Christian Richter, Steffen Greilich
PurposeTo determine the accuracy of particle range prediction for proton and heavier ion radiotherapy based on dual-energy computed tomography (DECT) in a realistic inhomogeneous geometry and to compare it to the state-of-the-art clinical approach.Methods and MaterialsA 3D ground-truth map of stopping-power ratios (SPRs) was created for an anthropomorphic head phantom by assigning measured SPR values to segmented structures in a high-resolution CT scan. This reference map was validated independently comparing proton transmission measurements to Monte Carlo transport simulations.Two DECT-based methods for direct SPR prediction via the Bethe formula (DirectSPR) and two established approaches based on Hounsfield look-up tables (HLUTs) were chosen for evaluation. SPR predictions from the four investigated methods were compared to the reference, employing material-specific voxel statistics and 2D gamma analysis. Furthermore, range deviations were analyzed in an exemplary proton treatment plan.ResultsThe established reference SPR map was successfully validated for the discrimination of SPR and range differences well below 0.3% and 1 mm respectively, even in complex inhomogeneous settings. For the phantom materials of larger volume (mainly brain, soft tissue), the investigated methods were overall able to predict SPR within 1% median deviation. The DirectSPR methods generally performed better than the HLUT approaches. For smaller phantom parts (such as cortical bone, air cavities), all methods were affected by image smoothing, leading to considerable SPR under- or overestimation. This effect was superimposed on the general SPR prediction accuracy in the exemplary treatment plan.ConclusionsDirectSPR predictions proved to be more robust with high accuracy in particular for larger volumes. In contrast, HLUT approaches exhibited a fortuitous component. The evaluation of accuracy in a realistic phantom with validated ground-truth SPR represents a crucial step towards possible clinical application of DECT-based SPR prediction methods.



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