ArticleAJNR. American journal of neuroradiology2026
Deep-Learning Accelerated Vessel Wall Imaging Using T1-SPACE at Ultra-High-Field Strength MRI.
Article in AJNR. American journal of neuroradiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Integrated Deep Learning-Based Intracranial Vessel Wall Imaging with DANTE Preparation: Feasibility and Technical Performance.AJNR. American journal of neuroradiology · 2026Article
- Association of Glucagon-like Peptide-1 Receptor Agonist Use with Stroke and Mortality Outcomes in Asymptomatic Intracranial Atherosclerotic Disease: Propensity Score-Matched Real-World Analysis.Neurology international · 2026Article
- Deep learning-accelerated 3D flair for white matter lesion detection in multiple sclerosis: a feasibility study.Neuroradiology · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeCurrent literature on deep learning-accelerated intracranial vessel wall imaging has been largely limited to postprocessing-based approaches at 3T, with comparatively sparse data at 7T. The purpose of the present study was to evaluate the feasibility and technical performance of a postcontrast T1-SPACE sequence using deep learning-based image reconstruction (DLBIR) for intracranial vessel wall imaging (IC-VWI) at 7T, comparing image quality, artifacts, and acquisition time with the standard-of-care (SOC) T1-SPACE sequence. MATERIALS AND
methodsIn this retrospective single-center study, 36 patients (21 women; mean age, 53.3 ± 16.2 years) underwent IC-VWI at 7T using both SOC T1-SPACE and DLBIR-accelerated T1-SPACE sequences. Two independent neuroradiologists assessed overall image quality (noise, artifacts, sharpness, and overall quality) and wall and lumen visualization along the intracranial vessels using a 4-point Likert scale. A cumulative-logit mixed-effects model (CLMM) of segment ratings was used for intersequence comparison. Segments were also pooled into proximal versus distal vessels and quality was compared using the exact paired sign test. Overall image-quality metrics were compared using paired Wilcoxon tests and Bland-Altman plots. Interreader agreement was summarized using percent agreement.
resultsOn segment-level analysis, T1-SPACE
conclusionsContrast-enhanced T1-SPACE
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