ArticleEuropean radiology2019
Technical challenges of quantitative chest MRI data analysis in a large cohort pediatric study.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Acute Respiratory Failure in Children: A Clinical Update on Diagnosis.Children (Basel, Switzerland) · 2024Review
- Article
- Ultrashort echo time MRI of the lung in children and adolescents: comparison with non-enhanced computed tomography and standard post-contrast T1w MRI sequences.European radiology · 2022Article
- Practical protocol for lung magnetic resonance imaging and common clinical indications.Pediatric radiology · 2022Review
- The radiological diagnosis of bronchiectasis: what's in a name?European respiratory review : an official journal of the European Respiratory Society · 2020Review
- The current status and further prospects for lung magnetic resonance imaging in pediatric radiology.Pediatric radiology · 2020Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
objectivesThis study was conducted in order to evaluate the effect of geometric distortion (GD) on MRI lung volume quantification and evaluate available manual, semi-automated, and fully automated methods for lung segmentation.
methodsA phantom was scanned with MRI and CT. GD was quantified as the difference in phantom's volume between MRI and CT, with CT as gold standard. Dice scores were used to measure overlap in shapes. Furthermore, 11 subjects from a prospective population-based cohort study each underwent four chest MRI acquisitions. The resulting 44 MRI scans with 2D and 3D Gradwarp were used to test five segmentation methods. Intraclass correlation coefficient, Bland-Altman plots, Wilcoxon, Mann-Whitney U, and paired t tests were used for statistics.
resultsUsing phantoms, volume differences between CT and MRI varied according to MRI positions and 2D and 3D Gradwarp correction. With the phantom located at the isocenter, MRI overestimated the volume relative to CT by 5.56 ± 1.16 to 6.99 ± 0.22% with body and torso coils, respectively. Higher Dice scores and smaller intraobject differences were found for 3D Gradwarp MR images. In subjects, semi-automated and fully automated segmentation tools showed high agreement with manual segmentations (ICC = 0.971-0.993 for end-inspiratory scans; ICC = 0.992-0.995 for end-expiratory scans). Manual segmentation time per scan was approximately 3-4 h and 2-3 min for fully automated methods.
conclusionsVolume overestimation of MRI due to GD can be quantified. Semi-automated and fully automated segmentation methods allow accurate, reproducible, and fast lung volume quantification. Chest MRI can be a valid radiation-free imaging modality for lung segmentation and volume quantification in large cohort studies. KEY POINTS: • Geometric distortion varies according to MRI setting and patient positioning. • Automated segmentation methods allow fast and accurate lung volume quantification. • MRI is a valid radiation-free alternative to CT for quantitative data analysis.
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