Evidence map›Paper›PMID 41295553›Full record

ArticleTomography (Ann Arbor, Mich.)2025

Dose-Dependent Analysis of Image Quality in Pediatric Head CT Scans Across Different Scanners to Optimize Clinical Protocols Using Phantom-Based Assessment.

Hiroshi Kuwahara, Mitsuaki Ojima, Tsuneko Kawamura, Daisuke Saitou, Kazunari Andou, Eiji Ariga, Kotaro Hasegawa, Michiaki Kai

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hiroshi KuwaharaDoctoral Course of Health Science, Graduate School of Nursing, Oita University of Nursing and Health Sciences, 2944-9 Megusuno, Oita City 870-1201, Oita Prefecture, Japan.ORCID 0009-0003-7119-851X
Mitsuaki OjimaDepartment of Environmental Health Science, Oita University of Nursing and Health Sciences, 2944-9 Megusuno, Oita City 870-1201, Oita Prefecture, Japan.ORCID 0000-0003-3541-1195
Tsuneko KawamuraRadiology Department, Nakatsu Municipal Hospital, 173-1 Shimoikenaga, Nakatsu City 871-8511, Oita Prefecture, Japan.
Daisuke SaitouRadiology Department, Seichokai Social Medical Corporation Belland General Hospital, 500-3 Higashiyama, Naka Ward, Sakai City 599-8247, Osaka Prefecture, Japan.
Kazunari AndouDepartment of Radiology, Oita Children's Hospital, Fujimoto Ikuseikai Social Medical Corporation, 83-7 Katajima, Oita City 870-0943, Oita Prefecture, Japan.
Eiji ArigaDepartment of Radiology, Medical Technology Division, Nagoya Daini Red Cross Hospital, Japanese Red Cross Aichi Medical Center, 2-9 Myoken-cho, Showa-ku, Nagoya City 466-8650, Aichi Prefecture, Japan.
Kotaro HasegawaDepartment of Radiologic Technology, Kariya Toyota General Hospital, Toyota Medical Corporation, 5-15 Sumiyoshi-cho, Kariya City 448-8505, Aichi Prefecture, Japan.
Michiaki KaiDepartment of Health Science, School of Health Science, Nippon Bunri University, 1727 Ichiki, Oita City 870-0397, Oita Prefecture, Japan.

Funding

This research was funded by the Japan Society for the Promotion of Science and internal research funding from Oita University of Nursing and Health Sciences. 18K07765
6 · The paper itself

Abstract

BACKGROUND/

objectivesOptimization of pediatric head computed tomography (CT) protocols is essential to minimize radiation exposure while maintaining diagnostic image quality. Previous studies mainly relied on phantom-based measurements or visual assessments, and validation using clinical images remains limited. This study aimed to establish quantitative thresholds for noise and contrast-to-noise ratio (CNR) in pediatric head CT by integrating multicenter clinical data with phantom evaluations.

methodsA multicenter retrospective study was conducted using CT systems from eight hospitals, combined with Catphan phantom experiments and pediatric head CT data. Scan parameters, automatic exposure control settings, and reconstruction methods were collected. Image quality was quantified by the standard deviation (SD) of noise and CNR obtained from regions of interest in gray and white matter. Radiation dose was represented by CTDIvol. Relationships among CTDIvol, SD, and CNR were analyzed across scanners from three manufacturers (Canon, FUJI, and GE).

resultsConsistent dose-response trends were observed across institutions and manufacturers. Image noise decreased as CTDIvol increased, but reached a plateau at higher doses. CNR improved with dose escalation, then stabilized. Both phantom experiments and clinical analyses identified a target SD of 5 and CNR of 2 as optimal indicators for pediatric head CT.

conclusionsQuantitative thresholds were determined as practical indicators for balancing diagnostic image quality with dose reduction. Further reduction may be achieved through advanced reconstruction methods, such as deep learning-based algorithms. These findings may contribute to standardizing pediatric head CT protocols and supporting safer and more effective diagnostic imaging.

Indexed as

HeadTomography Scanners, X-Ray ComputedTomography, X-Ray ComputedChildChild, PreschoolDose-Response Relationship, RadiationFemaleHumansInfantMalePhantoms, ImagingRadiation DosageRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesSignal-To-Noise Ratioautomatic exposure controlCatphan phantomdeep learning image reconstructionpediatric head CTradiation dose

Identifiers

PMID41295553
PMCPMC12656656

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