ArticleAJNR. American journal of neuroradiology2023
Brain Parcellation Repeatability and Reproducibility Using Conventional and Quantitative 3D MR Imaging.
Article in AJNR. American journal of neuroradiology, 2023. 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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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.
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Who cites it
3 citing papers in PubMed.
- A computational model to describe multi-regional brain architecture during neurodegeneration in Alzheimer's disease.Scientific reports · 2026Article
- Intraoperative 3D quantitative magnetic resonance imaging in paediatric brain tumour surgery.PloS one · 2026Article
- Technical aspects and clinical applications of synthetic MRI: a scoping review.Diagnosis (Berlin, Germany) · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeAutomatic brain parcellation is typically performed on dedicated MR imaging sequences, which require valuable examination time. In this study, a 3D MR imaging quantification sequence to retrieve R MATERIALS AND
methodsTwelve subjects with a mean age of 54 years were scanned twice at 1.5T and 3T with 3D-QALAS and a conventionally acquired T1-weighted sequence. Using SyMRI, we converted the R
resultsA high correlation with medians of 0.97 for 1.5T and 0.92 for 3T was found. A high repeatability was shown with a median coefficient of variation of 1.2% for both T1-weighted and synthetic 3D-T1-weighted inversion recovery at 1.5T, and 1.5% for T1-weighted imaging and 4.4% for synthetic 3D-T1-weighted inversion recovery at 3T. However, significant biases were observed between the methods and field strengths.
conclusionsIt is possible to perform MR imaging quantification of R
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