Phantom Validation of Spectral Detector Computed Tomography–Derived Virtual Monoenergetic, Virtual Noncontrast, and Iodine Quantification Images. Issue 6 (November 2018) - Ananthakrishnan, Lakshmi; Duan, Xinhui; Rajiah, Prabhakar; Soesbe, Todd C.; Lewis, Matthew A.; Xi, Yin; Fielding, Julia R.; Lenkinski, Robert E.; Leyendecker, John R.; Abbara, Suhny
Abstract : 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.