Evaluation of virtual monoenergetic imaging algorithms for dual-energy carotid and intracerebral CT angiography: Effects on image quality, artefacts and diagnostic performance for the detection of stenosis.
To investigate the impact of traditional (VMI) and noise-optimized virtual monoenergetic imaging (VMI+) algorithms on quantitative and qualitative image quality, and the assessment of stenosis in carotid and intracranial dual-energy CTA (DE-CTA).
MATERIALS AND METHODS:
DE-CTA studies of 40 patients performed on a third-generation 192-slice dual-source CT scanner were included in this retrospective study. 120-kVp image-equivalent linearly-blended, VMI and VMI+ series were reconstructed. Quantitative analysis included evaluation of contrast-to-noise ratios (CNR) of the aorta, common carotid artery, internal carotid artery, middle cerebral artery, and basilar artery. VMI and VMI+ with highest CNR, and linearly-blended series were rated qualitatively. Three radiologists assessed artefacts and suitability for evaluation at shoulder height, carotid bifurcation, siphon, and intracranial using 5-point Likert scales. Detection and grading of stenosis were performed at carotid bifurcation and siphon.
Highest CNR values were observed for 40-keV VMI+ compared to 65-keV VMI and linearly-blended images (P < 0.001). Artefacts were low in all qualitatively assessed series with excellent suitability for supraaortic artery evaluation at shoulder and bifurcation height. Suitability was significantly higher in VMI+ and VMI compared to linearly-blended images for intracranial and ICA assessment (P < 0.002). VMI and VMI+ showed excellent accordance for detection and grading of stenosis at carotid bifurcation and siphon with no differences in diagnostic performance.
40-keV VMI+ showed improved quantitative image quality compared to 65-keV VMI and linearly-blended series in supraaortic DE-CTA. VMI and VMI+ provided increased suitability for carotid and intracranial artery evaluation with excellent assessment of stenosis, but did not translate into increased diagnostic performance.