Background The reliability of contrast-enhanced CT (CHCT) as a reference image for MR-based dose calculation in lung stereotactic body radiation therapy (SBRT) with MR-Linac remains uncertain due to contrast-induced electron density (ED) discrepancy. Whether CHCT can be used as a reference image for dose calculation for patients with lung tumors treated with MR-Linac still needs to be explored. Methods This retrospective study included 30 patients with lung metastases treated with SBRT (50 Gy in 5 fractions) on a 1.5 T MR-Linac. Non-contrast CT (pCT) and corresponding CHCT acquired in the same respiratory phase were used to extract mean electron density for targets and organs at risk (OARs). The treatment plans (TP csCT and TP psCT ) based on synthetic CT (sCT) generated by assigning mean ED derived from pCT and CHCT were recalculated without altering parameters. Dosimetric discrepancies were evaluated using dose-volume histogram metrics, conformity indices, gradient indices and gamma analysis. Results Significant differences in mean ED between pCT and CHCT were observed for several structures, most notably the lungs (mean differences > 12%), heart, aorta, and bronchial tree ( p < 0.05), whereas minimal changes were found in bone and spinal cord. Despite these ED variations, dosimetric differences in target coverage were modest, with average discrepancy of 2.21% and 2.31% for TP csCT and TP psCT , respectively. Differences in the other dosimetric parameters (D max , D 2% , D 95% , D 98% , D mean , CI and GI) for the target were generally below 3%. Although statistically significant differences were detected in some OARs dose metrics, all values remained well within clinical tolerance limits (3%). Conclusion Despite significant contrast-induced variations in ED, the use of CHCT as a reference image resulted in only minor dosimetric differences in lung SBRT. When clinical risks are appropriately managed, CHCT has the potential to serve as a reference image for lung tumor SBRT on MR-Linac to optimize imaging utilization and enhance clinical workflow efficiency.
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Zhao et al. (2026) studied this question.
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