• Image quality comparison betwe...

*Result*: Image quality comparison between low-dose thin-slice deep-learning reconstruction and standard-dose thick-slice hybrid iterative reconstruction in pediatric abdominal CT.

Title:
Image quality comparison between low-dose thin-slice deep-learning reconstruction and standard-dose thick-slice hybrid iterative reconstruction in pediatric abdominal CT.
Authors:
Harai R; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Nagayama Y; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan. Electronic address: nagayama.yasunori@kuh.kumamoto-u.ac.jp., Ishiuchi S; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Yoshida R; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Inoue T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Osaki T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Shiraishi K; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Kidoh M; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Oda S; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Nakaura T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan., Hirai T; Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, 1-1-1, Honjo, Chuo-ku, Kumamoto 860-8556, Japan.
Source:
European journal of radiology [Eur J Radiol] 2026 Mar; Vol. 196, pp. 112703. Date of Electronic Publication: 2026 Jan 29.
Publication Type:
Journal Article; Comparative Study
Language:
English
Journal Info:
Publisher: Elsevier Science Ireland Ltd Country of Publication: Ireland NLM ID: 8106411 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7727 (Electronic) Linking ISSN: 0720048X NLM ISO Abbreviation: Eur J Radiol Subsets: MEDLINE
Imprint Name(s):
Publication: Limerick : Elsevier Science Ireland Ltd
Original Publication: Stuttgart ; New York : Thieme, [c1981-
MeSH Terms:
Tomography, X-Ray Computed*/methods , Radiographic Image Interpretation, Computer-Assisted*/methods , Radiography, Abdominal*/methods , Radiation Dosage* , Deep Learning*, Humans ; Male ; Female ; Child, Preschool ; Child ; Retrospective Studies ; Infant ; Contrast Media
Contributed Indexing:
Keywords: Deep learning; Image enhancement; Multidetector computed tomography; Pediatrics; Radiation exposure
Substance Nomenclature:
0 (Contrast Media)
Entry Date(s):
Date Created: 20260204 Date Completed: 20260221 Latest Revision: 20260221
Update Code:
20260222
DOI:
10.1016/j.ejrad.2026.112703
PMID:
41637843
Database:
MEDLINE

*Further Information*

*Objectives: To compare image quality between low-dose thin-slice deep-learning reconstruction (DLR) and standard-dose thick-slice hybrid iterative reconstruction (HIR) in pediatric abdominal CT.
Methods: 82 children (≤6 years) who underwent contrast-enhanced abdominal CT with standard-dose (STD, n = 41) or low-dose (LD, n = 41) protocol matched by age and weight were retrospectively identified. STD and LD images were reconstructed at 3.0-mm using HIR (STD-HIR/3.0 and LD-HIR/3.0, respectively). LD images were also reconstructed at 0.5-mm using HIR (LD-HIR/0.5) and DLR (LD-DLR/0.5). Size-specific dose estimate (SSDE) was compared between groups. Image noise and contrast-to-noise ratio (CNR) were quantified. Noise power spectrum (NPS) and edge-rise slope (ERS) were employed for noise texture and edge sharpness measures, respectively. For subjective evaluation, noise magnitude, noise texture, edge sharpness, delineation of small structures, and diagnostic confidence were rated on a 5-point scale (1 = undiagnostic, 5 = best).
Results: SSDE was on average 59.5% lower in LD than in STD group (1.7 ± 0.4 vs. 4.2 ± 0.8 mGy, p < 0.001). Image noise was lower in LD-DLR/0.5 compared to STD-HIR/3.0, LD-HIR/3.0, and LD-HIR/0.5 (8.7 ± 1.5, 9.6 ± 1.1, 11.7 ± 1.9, and 17.9 ± 2.3 HU, respectively, all p ≤ 0.017). LD-DLR/0.5 showed equivalent CNR (e.g., liver CNR: 7.1 ± 2.1 vs. 7.0 ± 2.8, p = 0.827) and higher ERS (64.3 ± 23.9 vs. 53.3 ± 10.6 HU/mm, p = 0.011) with similar average NPS frequency (0.281 ± 0.042 vs. 0.291 ± 0.027 mm<sup>-1</sup>, p = 0.177) compared to STD-HIR/3.0. Subjective scores for all criteria were higher in LD-DLR/0.5 than in STD-HIR/3.0 (e.g., diagnostic confidence score: 4.5 ± 0.5 vs. 3.4 ± 0.4, p < 0.001).
Conclusion: Low-dose thin-slice DLR improved edge sharpness, small structure visualization, and diagnostic confidence in pediatric abdominal CT without increasing noise compared to standard-dose thick-slice HIR.
(Copyright © 2026 The Authors. Published by Elsevier B.V. All rights reserved.)*

*Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Toshinori Hirai reports administrative support was provided by Canon Medical Systems Corporation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.*