ArticlePediatric radiology2026
Deep learning-enhanced zero echo time silent brain magnetic resonance imaging in infants without sedation.
Article in Pediatric radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Prompting the future: artificial intelligence in pediatric radiology.Pediatric radiology · 2026Article
- Perspectives on the future of artificial intelligence in paediatric radiology.Pediatric radiology · 2026Article
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7 authors.
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Abstract
backgroundReducing acoustic noise is essential in infant brain magnetic resonance imaging (MRI) to minimize the need for sedation. Deep learning (DL)-based MRI reconstruction may enhance the image quality of the zero echo time (ZTE) silent sequence.
objectiveTo evaluate the effect of DL-based reconstruction on the image quality of ZTE infant brain MRI using the feed-and-wrap technique, compared to conventional MRI with sedation. MATERIALS AND
methodsThis retrospective study included 78 infants (postmenstrual age ≤16 months) who underwent brain MRI between January 2022 and December 2024. The control group underwent sedated 3-dimensional T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) imaging. The experimental group underwent unsedated inversion recovery-prepared ZTE imaging with and without DL-based reconstruction (ZTE-DL and ZTE, respectively), using the feed-and-wrap technique. Three radiologists independently rated five image quality metrics using a 5-point Likert scale. Signal uniformity was assessed by the coefficient of variation across eight brain regions. Differences among sequences were analyzed using the Mann-Whitney U test with Bonferroni correction. Interrater agreement was assessed using Cohen's kappa coefficient.
resultsZTE-DL had the highest scores for noisiness, gray-white matter differentiation, artifacts, and overall image quality. ZTE-DL showed no significant differences from MPRAGE except for reduced noisiness, while significantly outperforming ZTE across all metrics (all P<0.017). Lesion conspicuity did not differ significantly among the groups. Interrater agreement was substantial (κ>0.6) for most metrics. Signal uniformity was greatest in ZTE-DL for gray and white matter (all P<0.001); no difference was observed between ZTE-DL and ZTE for cerebrospinal fluid (P=0.721).
conclusionDL-based MRI reconstruction improved ZTE image quality and provided comparable image quality to MPRAGE, potentially reducing the need for sedation in infant brain MRI.
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