ArticleAbdominal radiology (New York)2021
Comparison of compressed SENSE and SENSE for quantitative liver MRI in children and young adults.
Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Prospective study of quantitative liver MRI in cystic fibrosis: feasibility and comparison to PUSH cohort ultrasound.Pediatric radiology · 2023Trial
- Highly Reproducible, Vendor-Agnostic, Motion-Insensitive Liver PDFF Mapping at 0.55T, 1.5T, and 3T.Magnetic resonance in medicine · 2026Article
- State-of-the-Art Quantification of Liver Iron With MRI-Vendor Implementation and Available Tools.Journal of magnetic resonance imaging : JMRI · 2025Review
- Compressed Sensitivity Encoding Artificial Intelligence Accelerates Brain Metastasis Imaging by Optimizing Image Quality and Reducing Scan Time.AJNR. American journal of neuroradiology · 2024Article
- Magnetic resonance elastography of the liver: everything you need to know to get started.Abdominal radiology (New York) · 2022Review
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveCompressed SENSE (C-SENSE) allows more rapid MRI acquisition through incoherent, pseudorandom k-space undersampling. The purpose of our study was to compare conventional sensitivity encoded imaging (SENSE) quantitative MR images to those obtained using C-SENSE for measurement of liver proton density fat fraction (PDFF), T2*, and stiffness. METHODS AND MATERIALS: Clinical liver MRI examinations that included SENSE and C-SENSE quantitative MRI sequences were retrospectively identified. Patient age, gender, liver PDFF (%), T2* (ms), and stiffness (kPa) were recorded. Spearman's rank-order correlation (r) was used to evaluate association between methods, and Bland-Altman analysis was used to determine the mean bias and 95% limits of agreement.
resultsClinical liver MRI examinations that included SENSE and C-SENSE quantitative MRI sequences were retrospectively identified. Patient age, gender, liver PDFF (%), T2* (ms), and stiffness (kPa) were recorded. Spearman's rank-order correlation (r) was used to evaluate association between methods, and Bland-Altman analysis was used to determine the mean bias and 95% limits of agreement. Thirty-six examinations met the inclusion criteria. Mean patient age was 15.7 ± 7.7 years; twelve exams (33%) were in female patients. Liver PDFF showed very strong positive correlation (r = 0.98) between sequences, with a mean bias of 0.28% (95% LOA: -0.85, 1.41%). T2* showed moderate positive correlation (r = 0.53), with a mean bias of - 3.0 ms (95% LOA: - 12.0, 6.0 ms). Stiffness showed very strong positive correlation (r = 0.97), with a mean bias of 0.13 kPa (95% LOA: - 0.37, 0.63 kPa) that increased with increasing liver stiffness.
conclusionThere were strong positive correlations between SENSE and C-SENSE MRI measurements of liver PDFF and stiffness, with no to minimal bias. However, there was moderate correlation and greater negative mean bias between T2* measurements. Our results demonstrate the potential of compressed sensing to reliably measure PDFF and stiffness in the clinic.
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