Maximizing Iodine Contrast-to-Noise Ratios in Abdominal CT Imaging through Use of Energy Domain Noise Reduction and Virtual Monoenergetic Dual-Energy CT

Abstract

Purpose To determine the iodine contrast-to-noise ratio (CNR) for abdominal computed tomography (CT) when using energy domain noise reduction and virtual monoenergetic dual-energy (DE) CT images and to compare the CNR to that attained with single-energy CT at 80, 100, 120, and 140 kV. Materials and Methods This HIPAA-compliant study was approved by the institutional review board with waiver of informed consent. A syringe filled with diluted iodine contrast material was placed into 30-, 35-, and 45-cm-wide water phantoms and scanned with a dual-source CT scanner in both DE and single-energy modes with matched scanner output. Virtual monoenergetic images were generated, with energies ranging from 40 to 110 keV in 10-keV steps. A previously developed energy domain noise reduction algorithm was applied to reduce image noise by exploiting information redundancies in the energy domain. Image noise and iodine CNR were calculated. To show the potential clinical benefit of this technique, it was retrospectively applied to a clinical DE CT study of the liver in a 59-year-old male patient by using conventional and iterative reconstruction techniques. Image noise and CNR were compared for virtual monoenergetic images with and without energy domain noise reduction at each virtual monoenergetic energy (in kiloelectron volts) and phantom size by using a paired t test. CNR of virtual monoenergetic images was also compared with that of single-energy images acquired with 80, 100, 120, and 140 kV. Results Noise reduction of up to 59% (28.7/65.7) was achieved for DE virtual monoenergetic images by using an energy domain noise reduction technique. For the commercial virtual monoenergetic images, the maximum iodine CNR was achieved at 70 keV and was 18.6, 16.6, and 10.8 for the 30-, 35-, and 45-cm phantoms. After energy domain noise reduction, maximum iodine CNR was achieved at 40 keV and increased to 30.6, 25.4, and 16.5. These CNRs represented improvement of up to 64% (12.0/18.6) with the energy domain noise reduction technique. For single-energy CT at the optimal tube potential, iodine CNR was 29.1 (80 kV), 21.2 (80 kV), and 11.5 (100 kV). For patient images, 39% (24/61) noise reduction and 67% (0.74/1.10) CNR improvement were observed with the energy domain noise reduction technique when compared with standard filtered back-projection images. Conclusion Iodine CNR for adult abdominal CT may be maximized with energy domain noise reduction and virtual monoenergetic DE CT.

Optimal virtual monoenergetic image in “TwinBeam” dual‐energy CT for organs‐at‐risk delineation based on contrast‐noise‐ratio in head‐and‐neck radiotherapy

“…Figure demonstrated the noise level of monoenergetic images at different energies averaged among the ten patients. The noise level sharply decreased and then slowly increased to a stable value as energy increased, which is consistent with existing literatures . The minimum noise was achieved around 80 keV.…”

Technical Note: Improved CT number stability across patient size using dual-energy CT virtual monoenergetic imaging

“…The resulting image set is the one in which high atomic number materials are very bright (i.e., they maintain the characteristics of the low energy virtual monoenergetic image), but because of the frequency splitting, it contains less noise than the original low energy virtual monoenergetic image set. This approach is similar to the work previously described by Leng et al 12,13 Because mono+ primarily reduces noise relative to mono, differences in CT number accuracy and stability across object size are not expected.…”

An Image-Domain Contrast Material Extraction Method for Dual-Energy Computed Tomography

“…The high noise of the ratio map propagates to the final material specific images, and can be observed by the modest-sized error bars of Figures 4, 7 and 9. This is a well-known problem for dual-energy imaging (22), and while various noise reduction techniques have been proposed (32, 33), evaluation of those techniques were beyond the scope of our proof-of-concept work. A second disadvantage with DSCT is the slightly lower temporal resolution due to the 90° offset of the two sources (34).…”