Image Quality of Virtual Monochromatic Reconstructions of Noncontrast CT on a Dual-Source CT Scanner in Adult Patients

Rationale and Objectives: To evaluate the image quality of virtual monochromatic images (VMI) reconstructed from dual-energy dual source noncontrast head CT with different reconstruction kernels. Materials and Methods: Twenty-five consecutive adult patients underwent noncontrast dual-energy CT. VMI were retrospectively reconstructed at 5-keV increments from 40 to 140 keV using quantitative and head kernels. CT-number, noise levels (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in the gray and white matter and artifacts using the posterior fossa artifact index (PFAI) were evaluated. Results: CT-number increased with decreasing VMI energy levels, and SD was lowest at 85 keV. SNR was maximized at 80 keV and 85 keV for the head and quantitative kernels, respectively. CNR was maximum at 40 keV; PFAI was lowest at 90 (head kernel) and 100 (quantitative kernel) keV. Optimal VMI image quality was significantly better than conventional CT. Conclusion: Optimal image quality of VMI energies can improve brain parenchymal image quality compared to conventional CT but are reconstruction kernel dependent and depend on indication for performing noncontrast CT. (c) 2020 The Association of University Radiologists. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Automated summary

Evaluation of virtual monochromatic images (VMI) from dual-energy dual source noncontrast head CT with different reconstruction kernels showed that optimal image quality can improve brain parenchymal image quality compared to conventional CT, depending on the reconstruction kernel used and the specific indication for performing noncontrast CT.