Purpose: The accuracy of stopping power ratio (SPR), particularly for low density materials such as lung tissue, is a limiting factor in proton therapy plan robustness. We investigate the potential improvements associated with the use of dual-energy CT (DECT) for estimating SPR of lung tissue samples.
Methods: Single energy CT (SECT) and DECT scans of six sheep and one cow lung tissue samples were acquired on a Siemens SOMATOM Definition Edge CT. SPR images were created for each lung samples from the DECT generated relative electron densities (Ï?â‚‘) and effective atomic numbers (Z(eff)). To calculate water equivalent thickness (WET), the generated SPR and acquired SECT images were imported into Eclipse (v13.7, Varian Medical Systems, Palo Alto, CA) treatment planning system (TPS). The SPR-to-SPR (straight line with a slope 1) and clinical HU-to-SPR calibration curves were applied to the SPR and SECT image sets, respectively to calculate water equivalent thickness (WET) and SPR of each lung tissue sample. For each sample, the calculated SPR values estimated from SECT and DECT scans were compared with the measurement performed using a multilayer ionization chamber (MLIC).
Results: For all lung tissue samples, for SECT the TPS WET was less than the measured WET by 15% to 28% (average=21.0%). For DECT, the TPS calculated WET values were within Â±8% (average=3.1%) of the measurement. Similarly, DECT derived SPR values agreed with the measurements to within Â±8% (average=5.22%) for sheep and 0.54% for cow lung tissues, whereas SECT derived values (using HU-to-SPR calibration) deviated from measurement by as much as 38% (sheep: <38%, average=28.34% and cow =18.26%).
Conclusion: Our study suggests that using DECT can improve the accuracy of SPR and WET predictions for low density tissues such as lung.