Abstract
Introduction
The aim of this study was to evaluate the effect of advanced monoenergetic post-processing (MEI+) on the visualisation of spinal growth in contrast-enhanced dual-energy CT (DE-CT).
Methods
Twenty-six oncologic patients (age, 61 ± 17 years) with spinal tumorous growth were included. Patients underwent contrast-enhanced dual-energy CT on a third-generation dual-source CT scanner. Image acquisition was in dual-energy mode (100/Sn150kV), and scans were initiated 90 s after contrast agent administration. Virtual monoenergertic images (MEI+) were reconstructed at four different kiloelectron volts (keV) levels (40, 60, 80, 100) and compared to the standard blended portal venous computed tomography (CTpv). Image quality was assessed qualitatively (conspicuity, delineation, sharpness, noise, confidence; two independent readers; 5-point Likert scale; 5 = excellent) and quantitatively by calculating signal-to-noise (SNR) and contrast-to-noise-ratios (CNR). For a subgroup of 10 patients with MR imaging within 4 months of the DE-CT, we compared the monoenergetic images to the MRIs qualitatively.
Results
Highest contrast of spinal growth was observed in MEI+ at 40 keV, with significant differences to CTpv and all other keV reconstructions (60, 80, 100; p < 0.01). Highest conspicuity, delineation and sharpness were observed in MEI+ at 40 keV, with significant differences to CTpv (p < 0.001). Similarly, MEI+ at 40 keV yielded highest diagnostic confidence (4.6 ± 0.6), also with significant differences to CTpv (3.45 ± 0.9, p < 0.001) and to high keV reconstructions (80, 100; p ≤ 0.001). Similarly, CNR calculations revealed highest scores for MEI+ at 40 keV followed by 60 keV and CTpv, with significant differences to high keV MEI+ reconstructions. Qualitative analysis scores peaked for MR images followed by the MEI+ 40-keV reconstructions.
Conclusion
MEI+ at low keV levels can significantly improve image quality and delineation of spinal growth in patients with portal-venous phase CT scans due to increased CNR and limited image noise.
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