ArticleInvestigative radiology2020
Inversion Recovery Susceptibility Weighted Imaging With Enhanced T2 Weighting at 3 T Improves Visualization of Subpial Cortical Multiple Sclerosis Lesions.
Article in Investigative radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- Imaging cortical multiple sclerosis lesions with ultra-high field MRI.NeuroImage. Clinical · 2021Pooled it
- Quantifying cortical lesions in multiple sclerosis MRI datasets using multi-contrast post-processing and deep learning.Communications medicine · 2026Article
- Whole-brain in situ postmortem MR imaging using a combination of sequences for cortical lesion detection in multiple sclerosis.La Radiologia medica · 2026Article
- Cortical Lesions Form Predominantly in Early Multiple Sclerosis.medRxiv : the preprint server for health sciences · 2026Article
- Enhancing precision in multiple sclerosis lesion segmentation: A U-net based machine learning approach with data augmentation.Neuroimage. Reports · 2025Article
- BrainAgeNeXt: Advancing brain age modeling for individuals with multiple sclerosis.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Imaging Outcomes for Phase 2 Trials Targeting Compartmentalized Inflammation.Multiple sclerosis (Houndmills, Basingstoke, England) · 2024Review
- New Imaging Markers in Multiple Sclerosis and Related Disorders: Smoldering Inflammation and the Central Vein Sign.Neuroimaging clinics of North America · 2024Review
- Decoding Gray Matter Involvement in Multiple Sclerosis via Imaging.Neuroimaging clinics of North America · 2024Review
- A novel imaging marker of cortical "cellularity" in multiple sclerosis patients.Scientific reports · 2024Article
- The use of 7T MRI in multiple sclerosis: review and consensus statement from the North American Imaging in Multiple Sclerosis Cooperative.Brain communications · 2024Review
- Toward Precision Phenotyping of Multiple Sclerosis.Neurology(R) neuroimmunology & neuroinflammation · 2022Review
- Linking lesions in sensorimotor cortex to contralateral hand function in multiple sclerosis: a 7 T MRI study.Brain : a journal of neurology · 2022Article
- Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.NMR in biomedicine · 2022Article
- Artificial double inversion recovery images can substitute conventionally acquired images: an MRI-histology study.Scientific reports · 2022Article
- Article
- Inversion Recovery Susceptibility Weighted Imaging With Enhanced T2 Weighting at 3 T Improves Visualization of Subpial Cortical Multiple Sclerosis Lesions.Investigative radiology · 2020Article
- Interrater reliability for the detection of cortical lesions on phase-sensitive inversion recovery magnetic resonance imaging in patients with multiple sclerosis.Radiologia brasileiraArticle
- TJournal of neuroimaging : official journal of the American Society of NeuroimagingArticle
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6 authors at 2 institutions in 2 countries.
Funding
Abstract
objectivesCortical demyelination is common in multiple sclerosis (MS) and can be extensive. Cortical lesions contribute to disability independently from white matter lesions and may form via a distinct mechanism. However, current magnetic resonance imaging methods at 3 T are insensitive to cortical, and especially subpial cortical, lesions. Subpial lesions are well seen on T2*-weighted imaging at 7 T, but T2*-weighted methods on 3 T scanners are limited by poor lesion-to-cortex and cerebrospinal fluid-to-lesion contrast. We aimed to develop and evaluate a cerebrospinal fluid-suppressed, T2*-weighted sequence optimized for subpial cortical lesion visualization. MATERIALS AND
methodsWe developed a new magnetic resonance imaging sequence, inversion recovery susceptibility weighted imaging with enhanced T2 weighting (IR-SWIET; 0.8 mm × 0.8 mm in plane, 0.64 mm slice thickness with whole brain coverage, acquisition time ~5 minutes). We compared cortical lesion visualization independently on IR-SWIET (median signal from 4 acquisitions), magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE), double inversion recovery (DIR), T2*-weighted segmented echo-planar imaging, and phase-sensitive inversion recovery images for 10 adults with MS. We also identified cortical lesions with a multicontrast reading of IR-SWIET (median of 2 acquisitions), MP2RAGE, and fluid-attenuated inversion recovery (FLAIR) images for each case. Lesions identified on 3 T images were verified on "gold standard" 7 T T2* and MP2RAGE images.
resultsCortical, and particularly subpial, lesions appeared much more conspicuous on IR-SWIET compared with other 3 T methods. A total of 101 true-positive subpial lesions were identified on IR-SWIET (average per-participant sensitivity vs 7 T, 29% ± 8%) versus 36 on MP2RAGE (5% ± 2%; comparison to IR-SWIET sensitivity, P = 0.07), 17 on FLAIR (2% ± 1%; P < 0.05), 28 on DIR (6% ± 2%; P < 0.05), 42 on T2*-weighted segmented echo-planar imaging (11% ± 5%; P < 0.05), and 13 on phase-sensitive inversion recovery (4% ± 2%; P < 0.05). When a combination of IR-SWIET, MP2RAGE, and FLAIR images was used, a total of 147 subpial lesions (30% ± 5%) were identified versus 83 (16% ± 3%, P < 0.01) on a combination of DIR, MP2RAGE, and FLAIR. More cases had at least 1 subpial lesion on IR-SWIET, and IR-SWIET improved cortical lesion subtyping accuracy and correlation with 7 T subpial lesion number.
conclusionsSubpial lesions are better visualized on IR-SWIET compared with other 3 T methods. A 3 T protocol combining IR-SWIET with MP2RAGE, in which leukocortical lesions are well seen, improves cortical lesion visualization over existing approaches. Therefore, IR-SWIET may enable improved MS diagnostic specificity and a better understanding of the clinical implications of cortical demyelination.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.