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 5.561.16 to 6.990.22% 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 3-4h and 2-3min 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 center dot Geometric distortion varies according to MRI setting and patient positioning.p id=Par6 center dot Automated segmentation methods allow fast and accurate lung volume quantification. p id=Par7 center dot MRI is a valid radiation-free alternative to CT for quantitative data analysis.

Technical challenges of quantitative chest MRI data analysis in a large cohort pediatric study

Aliverti A.;Pennati F.;
2019-01-01

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 5.561.16 to 6.990.22% 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 3-4h and 2-3min 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 center dot Geometric distortion varies according to MRI setting and patient positioning.p id=Par6 center dot Automated segmentation methods allow fast and accurate lung volume quantification. p id=Par7 center dot MRI is a valid radiation-free alternative to CT for quantitative data analysis.
2019
Imaging; Lung; Lung volume measurements; Magnetic resonance imaging; Phantoms; Child; Cohort Studies; Female; Humans; Imaging, Three-Dimensional; Lung; Lung Volume Measurements; Magnetic Resonance Imaging; Male; Prospective Studies; ROC Curve; Reproducibility of Results; Phantoms, Imaging
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1121226
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