Abstract
BACKGROUND AND PURPOSE: Radiation exposure in the CT diagnostic imaging process is a conspicuous concern in pediatric patients. This study aimed to evaluate whether 60-keV virtual monoenergetic images of the pediatric cranium in dual-layer CT can reduce the radiation dose while maintaining image quality compared with conventional images.
MATERIALS AND METHODS: One hundred six unenhanced pediatric head scans acquired by dual-layer CT were retrospectively assessed. The patients were assigned to 2 groups of 53 and scanned with 250 and 180 mAs, respectively. Dose-length product values were retrieved, and noise, SNR, and contrast-to-noise ratio were calculated for each case. Two radiologists blinded to the reconstruction technique used evaluated image quality on a 5-point Likert scale. Statistical assessment was performed with ANOVA and the Wilcoxon test, adjusted for multiple comparisons.
RESULTS: Mean dose-length product values were 717.47 (SD, 41.52) mGy×cm and 520.74 (SD, 42) mGy×cm for the 250- and 180-mAs groups, respectively. Irrespective of the radiation dose, noise was significantly lower, SNR and contrast-to-noise ratio were significantly higher, and subjective analysis revealed significant superiority of 60-keV virtual monoenergetic images compared with conventional images (all P < .001). SNR, contrast-to-noise ratio, and subjective evaluation in 60-keV virtual monoenergetic images were not significantly different between the 2 scan groups (P > .05). Radiation dose parameters were significantly lower in the 180-mAs group compared with the 250-mAs group (P < .001).
CONCLUSIONS: Dual-layer CT 60-keV virtual monoenergetic images allowed a radiation dose reduction of 28% without image-quality loss in pediatric cranial CT.
ABBREVIATIONS:
- CNR
- contrast-to-noise ratio
- CTDIvol
- volume CT dose index
- DECT
- dual-energy CT
- DLCT
- dual-layer CT
- DLP
- dose-length product
- GWMA
- assessment of GM-WM differentiation
- PFAA
- assessment of artifacts in posterior fossa
- SSA
- assessment of the subcalvarial space
- SAI
- subcalvarial artifact index
- VMI
- virtual monoenergetic image
- © 2023 by American Journal of Neuroradiology
Indicates open access to non-subscribers at www.ajnr.org