Low-iodine-dose computed tomography coupled with an artificial intelligence-based contrast-boosting technique in children: a retrospective study on comparison with conventional-iodine-dose computed tomography
- PMID: 38839610
- PMCID: PMC11254996
- DOI: 10.1007/s00247-024-05953-1
Low-iodine-dose computed tomography coupled with an artificial intelligence-based contrast-boosting technique in children: a retrospective study on comparison with conventional-iodine-dose computed tomography
Erratum in
-
Correction to: Low‑iodine‑dose computed tomography coupled with an artificial intelligence‑based contrast‑boosting technique in children: a retrospective study on comparison with conventional‑iodine‑dose computed tomography.Pediatr Radiol. 2024 Jul;54(8):1412. doi: 10.1007/s00247-024-05996-4. Pediatr Radiol. 2024. PMID: 38963574 Free PMC article. No abstract available.
Abstract
Background: Low-iodine-dose computed tomography (CT) protocols have emerged to mitigate the risks associated with contrast injection, often resulting in decreased image quality.
Objective: To evaluate the image quality of low-iodine-dose CT combined with an artificial intelligence (AI)-based contrast-boosting technique in abdominal CT, compared to a standard-iodine-dose protocol in children.
Materials and methods: This single-center retrospective study included 35 pediatric patients (mean age 9.2 years, range 1-17 years) who underwent sequential abdominal CT scans-one with a standard-iodine-dose protocol (standard-dose group, Iobitridol 350 mgI/mL) and another with a low-iodine-dose protocol (low-dose group, Iohexol 240 mgI/mL)-within a 4-month interval from January 2022 to July 2022. The low-iodine CT protocol was reconstructed using an AI-based contrast-boosting technique (contrast-boosted group). Quantitative and qualitative parameters were measured in the three groups. For qualitative parameters, interobserver agreement was assessed using the intraclass correlation coefficient, and mean values were employed for subsequent analyses. For quantitative analysis of the three groups, repeated measures one-way analysis of variance with post hoc pairwise analysis was used. For qualitative analysis, the Friedman test followed by post hoc pairwise analysis was used. Paired t-tests were employed to compare radiation dose and iodine uptake between the standard- and low-dose groups.
Results: The standard-dose group exhibited higher attenuation, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) of organs and vessels compared to the low-dose group (all P-values < 0.05 except for liver SNR, P = 0.12). However, noise levels did not differ between the standard- and low-dose groups (P = 0.86). The contrast-boosted group had increased attenuation, CNR, and SNR of organs and vessels, and reduced noise compared with the low-dose group (all P < 0.05). The contrast-boosted group showed no differences in attenuation, CNR, and SNR of organs and vessels (all P > 0.05), and lower noise (P = 0.002), than the standard-dose group. In qualitative analysis, the contrast-boosted group did not differ regarding vessel enhancement and lesion conspicuity (P > 0.05) but had lower noise (P < 0.05) and higher organ enhancement and artifacts (all P < 0.05) than the standard-dose group. While iodine uptake was significantly reduced in low-iodine-dose CT (P < 0.001), there was no difference in radiation dose between standard- and low-iodine-dose CT (all P > 0.05).
Conclusion: Low-iodine-dose abdominal CT, combined with an AI-based contrast-boosting technique exhibited comparable organ and vessel enhancement, as well as lesion conspicuity compared to standard-iodine-dose CT in children. Moreover, image noise decreased in the contrast-boosted group, albeit with an increase in artifacts.
Keywords: Artificial intelligence; Computed tomography; Contrast enhancement; Image quality; Iodine; Pediatrics.
© 2024. The Author(s).
Conflict of interest statement
A condition of the funders of this project (Taejoon Pharmaceutical Co., Seoul, South Korea) was that the research team should use the company’s own contrast agent (Iobrix 240) in the conduct of the study.
Figures



Similar articles
-
Effect of low tube voltage and low iodine concentration abdominal CT on image quality and radiation dose in children: preliminary study.Abdom Radiol (NY). 2019 May;44(5):1928-1935. doi: 10.1007/s00261-019-01896-6. Abdom Radiol (NY). 2019. PMID: 30683980
-
Monochromatic Spectral Computed Tomography with Low Iodine Concentration Contrast Medium in a Rabbit VX2 Liver Model:: Investigation of Image Quality and Detection Rate.Acad Radiol. 2016 Apr;23(4):486-95. doi: 10.1016/j.acra.2015.12.001. Epub 2016 Jan 12. Acad Radiol. 2016. PMID: 26795435
-
Photon-counting CT yields superior abdominopelvic image quality at lower radiation and iodinated contrast doses.Pediatr Radiol. 2025 May;55(6):1202-1211. doi: 10.1007/s00247-025-06209-2. Epub 2025 Mar 20. Pediatr Radiol. 2025. PMID: 40111456
-
Complex Relationship Between Artificial Intelligence and CT Radiation Dose.Acad Radiol. 2022 Nov;29(11):1709-1719. doi: 10.1016/j.acra.2021.10.024. Epub 2021 Nov 24. Acad Radiol. 2022. PMID: 34836775 Review.
-
The use of deep learning towards dose optimization in low-dose computed tomography: A scoping review.Radiography (Lond). 2022 Feb;28(1):208-214. doi: 10.1016/j.radi.2021.07.010. Epub 2021 Jul 27. Radiography (Lond). 2022. PMID: 34325998
Cited by
-
Artificial intelligence: a primer for pediatric radiologists.Pediatr Radiol. 2024 Dec;54(13):2127-2142. doi: 10.1007/s00247-024-06098-x. Epub 2024 Nov 18. Pediatr Radiol. 2024. PMID: 39556194 Review.
-
From promise to practice: a scoping review of AI applications in abdominal radiology.Abdom Radiol (NY). 2025 Jul 28. doi: 10.1007/s00261-025-05144-y. Online ahead of print. Abdom Radiol (NY). 2025. PMID: 40719923 Review.
-
Image Quality and Lesion Detectability of Low-Concentration Iodine Contrast and Low Radiation Hepatic Multiphase CT Using a Deep-Learning-Based Contrast-Boosting Model in Chronic Liver Disease Patients.Diagnostics (Basel). 2024 Oct 17;14(20):2308. doi: 10.3390/diagnostics14202308. Diagnostics (Basel). 2024. PMID: 39451631 Free PMC article.
References
-
- Thomson KR, Varma DK. Safe use of radiographic contrast media. Aust Prescr. 2010;33:19–22. doi: 10.18773/austprescr.2010.006. - DOI
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical