The value of dual-energy computed tomography angiography-based virtual monoenergetic imaging for evaluations after cerebral aneurysm clipping.

PURPOSE

This study aimed to research the optimal energy range of dual-energy computed tomography angiography (DECTA)-based virtual monoenergetic imaging (VMI) for evaluations after cerebral aneurysm clipping.

METHODS

Sixty patients who underwent DECTA after cerebral aneurysm clipping were analyzed retrospectively. Conventional computed tomography angiography (CTA) was compared with VMIs at 60, 70, 80, 90, and 100 keV. The mean attenuation and standard deviation values within the regions of interest placed in the brain parenchyma and arteries with the worst artifact were measured, respectively. The ΔCT and artifact index (AI) values were calculated to assess the artifact severity. The contrast-to-noise ratio (CNR) was calculated to assess vascular contrast. Two radiologists assessed brain parenchyma and cerebrovascular scores qualitatively using a five-point Likert scale.

RESULTS

Quantitative analysis showed that the artifacts of VMIs were significantly reduced compared with conventional CTA ( ≤ 0.014), except for the ΔCT and AI of 60 keV and the ΔCT of 70 keV. However, there was no significant difference in the vascular contrast on VMIs compared with conventional CTA, except for the CNR of 60 keV ( = 0.008). In qualitative analysis, the proportions of brain parenchyma scores and cerebrovascular scores ≥4 on the VMIs of 70 and 80 keV were higher than those of conventional CTA and other VMIs.

CONCLUSION

For the patients who underwent DECTA after cerebral aneurysm clipping, the 70-80 keV VMIs are expected to be the optimal energy range for balancing clip artifacts and visibility of adjacent vessels.

CLINICAL SIGNIFICANCE

Studying the optimal energy range of DECTA-based VMI for post-operative assessment of aneurysm clipping can reduce metal artifacts in images and increase vascular contrast. This facilitates the follow-up of patients after aneurysm clipping, offers timely and accurate detection of postoperative complications, provides assistance to clinicians in diagnosis and treatment, and improves patient prognosis.