Valk, Anne; Willers, Corin; Shahim, Kamal; Pusterla, Orso; Bauman, Grzegorz; Sandkühler, Robin; Bieri, Oliver; Wyler, Florian; Latzin, Philipp (2021). Defect distribution index: A novel metric for functional lung MRI in cystic fibrosis. Magnetic resonance in medicine, 86(6), pp. 3224-3235. Wiley-Liss 10.1002/mrm.28947
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Defect_distribution_index_A_novel_metric_for_functional_lung_MRI_in_cystic_fibrosis.pdf - Published Version Available under License Creative Commons: Attribution-Noncommercial-No Derivative Works (CC-BY-NC-ND). Download (1MB) | Preview |
PURPOSE
Lung impairment from functional MRI is frequently assessed as defect percentage. The defect distribution, however, is currently not quantified. The purpose of this work was to develop a novel measure that quantifies how clustered or scattered defects in functional lung MRI appear, and to evaluate it in pediatric cystic fibrosis.
THEORY
The defect distribution index (DDI) calculates a score for each lung voxel categorized as defected. The index increases according to how densely and how far an expanding circle around a defect voxel contains more than 50% defect voxels.
METHODS
Fractional ventilation and perfusion maps of 53 children with cystic fibrosis were previously acquired with matrix pencil decomposition MRI. In this work, the DDI is compared to a visual score of 3 raters who evaluated how clustered the lung defects appear. Further, spearman correlations between DDI and lung function parameters were determined.
RESULTS
The DDI strongly correlates with the visual scoring (r = 0.90 for ventilation; r = 0.88 for perfusion; P < .0001). Although correlations between DDI and defect percentage are moderate to strong (r = 0.61 for ventilation; r = 0.75 for perfusion; P < .0001), the DDI distinguishes between patients with comparable defect percentage.
CONCLUSION
The DDI is a novel measure for functional lung MRI. It provides complementary information to the defect percentage because the DDI assesses defect distribution rather than defect size. The DDI is applicable to matrix pencil MRI data of cystic fibrosis patients and shows very good agreement with human perception of defect distributions.
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