Abstract Objective :Accurate radiotherapy dose calculation critically depends on reliable conversion of Hounsfield units (HU) to density, traditionally achieved through scanner‑specific calibration using dedicated simulation computed tomography (CT) systems. This study aimed to derive and validate proposed HU-to-density calibration curves (PCT) from multi-vendor diagnostic CT (dCT) data, independent of scanner and acquisition parameters. Approach :Both HU-to-relative electron density (RED) and mass density (MD) calibration curves were generated using the CIRS-062M phantom scanned on eight multi-vendor CT systems at 80–140 kilovoltage-peak (kV p ), including dual-energy modes. PCT (PCT-RED, PCT-MD) were derived by piecewise regression across the multi-kV p dataset. 20 palliative 6 MV flattening-filter-free (FFF) volumetric modulated arc therapy (VMAT) and intensity-modulated radiotherapy (IMRT) plans were recalculated in Eclipse v18 using all these curves with Acuros XB (dose-to-medium, MD-based) and Anisotropic Analytical Algorithm (AAA, RED-based). Dosimetric comparisons assessed: (1) PCT validation versus scanner-kV p -specific calibrations; (2) intra-scanner effects of varying kV p (versus reference 120/110 kV p per scanner). Evaluation included dose–volume histogram (DVH) metrics—planning target volume (PTV), organs at risk (OARs), body maximum dose, conformity index—and 3D γ analysis (2%/2mm, 1%/1mm) between calculated dose distributions. Statistical differences were assessed using the Wilcoxon signed-rank test (α=0.05) with effect sizes. Main results :Differences between plan dose distributions obtained with PCT and those from scanner-specific curves were minimal. Although several DVH metrics were statistically different (p 99% (1%/1mm), confirming robustness. Significance : We propose a CT calibration model based on dCT for radiotherapy. This multi-vendor approach provides default curves when scanner-specific calibration is impractical, facilitating resource-efficient, simulation-free radiotherapy workflows via dCT-based treatment planning, while maintaining dosimetric accuracy across the evaluated dataset.
Albaladejo et al. (Mon,) studied this question.