Phantom Validation of Spectral Detector Computed Tomography-Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images

Purpose Spectral detector computed tomography (SDCT) is a new CT technology that uses a dual-layer detector to perform energy separation. We aim to assess 3 clinical concepts using a phantom model: noise profile across the virtual monoenergetic (VME) spectrum, accuracy of iodine quantification, and virtual noncontrast (VNC) reconstructions' ability to remove iodine contribution to attenuation. Methods Six vials containing varying concentrations of iodinated contrast (0-6 mg/mL) diluted in water were placed in a water bath and scanned on an SDCT scanner. Virtual monoenergetic (40-200 keV at 10-keV increments), iodine-no-water, and VNC reconstructions were created. Attenuation (in Hounsfield units [HU]), VME noise at each energy level, CT-derived iodine concentration, and VNC attenuation were recorded. Results Virtual monoenergetic noise was improved at all energies compared with conventional images (conventional, 9.8-11.2; VME, 7.5-9.5). Noise profile showed a slightly higher image noise at 40 keV, but was otherwise relatively flat across the energy spectrum. On iodine-no-water reconstructions, measured varied from actual iodine concentration by ±0.1 mg/mL (SD, 0.16-0.36). Virtual noncontrast attenuation was within 5 HU of water attenuation at all iodine concentrations. Conclusion Reconstructions of SDCT show lower VME image noise, accurate iodine quantification, and VNC attenuation values within 5 HU of expected in a phantom model.