Impact of dual-layer spectral CT-derived stopping power ratio on single-energy CT-based carbon-ion treatment planning for thoracic cancer.

Abstract

To evaluate the impact of stopping-power ratio (SPR) predictions derived from dual-layer detector-based spectral CT (DLCT) on conventional single-energy CT (SECT)-based carbon-ion treatment planning for thoracic cancer. Twenty patients with thoracic cancer who underwent non-contrast DLCT were retrospectively included. DLCT-based SPR images were generated from effective atomic number and relative electron density maps using the Bethe equation. SECT-based SPR was derived using a Hounsfield unit look-up table generated via stoichiometric calibration of a commercial electron density phantom. Using the same phantom, a phantom-based prediction assessment was performed by comparing SECT- and DLCT-based SPR predictions with theoretical SPR values for the inserts. For patient analysis, normal-tissue SPR values derived from SECT and DLCT were compared. Carbon-ion treatment plans were first generated based on SECT images and then recalculated using DLCT-derived SPR images. Range differences in the beam's-eye view and dose-volume histogram parameters for the planning target volume and organs at risk were evaluated. In the phantom-based assessment, the root-mean-square error relative to the theoretical SPR was 5.57% for SECT and 2.83% for DLCT. In patient images, mean SPR differences between SECT and DLCT were 3.62% for the lungs, 1.93% for the esophagus, 0.04% for the heart, 0.93% for the spinal cord, and 1.53% for the ribs. Across the patient cohort, the mean recalculated range difference was 0.71 ± 0.89 mm, corresponding to a relative difference of 0.60 ± 0.67%. No statistically significant differences were observed in target dose metrics, whereas selected organ-at-risk metrics showed statistically significant differences between SECT-based plans and DLCT-based recalculations. DLCT-derived SPR prediction showed better agreement with theoretical phantom SPR values in the phantom-based prediction assessment and produced tissue-dependent SPR differences in thoracic patient images compared with conventional SECT-based prediction. Recalculation on DLCT-derived SPR maps resulted in modest but systematic range differences and limited changes in selected dose metrics. These results may inform the implementation and future independent validation of patient-specific DLCT-based SPR workflows in carbon-ion treatment planning for thoracic cancer.