Estimating pediatric lung volumetric parameters via rapid, limited‐slice, free‐breathing thoracic dynamic MRI

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BACKGROUND: Dynamic, separate lung volume assessment during breathing is critical for evaluating thoracic disorders like scoliosis, thoracic insufficiency syndrome (TIS), and pulmonary diseases, as well as for monitoring treatments. While traditional volumetric assessment relies on static 3D imaging during breath-holds, this is unfeasible for many pediatric patients or those with severe respiratory distress. Free-breathing 4D dynamic MRI (dMRI) is the ideal modality due to its lack of radiation, excellent soft-tissue contrast, and flexible imaging planes. However, its clinical use is hampered by long acquisition times, during which patients struggle to maintain stable, consistent breathing patterns or remain still. Consequently, methods to accelerate dMRI acquisition while maintaining volumetric accuracy are urgently needed to make free-breathing assessments clinically practical. PURPOSE: We present an observational study involving free-breathing short-scan-time dynamic MRI (dMRI) method that can be routinely used for computing dynamic lung volumes accurately. METHODS: (1) Full sampled free-breathing sagittal 2D dMRI scans are gathered from 45 normal children via bSSFP sequence. Sparse dMRI (s-dMRI) scans are simulated from these datasets by optimally subsampling in the spatio-temporal domains via a limited number of selected sagittal locations and time instances. (2) A 4D image is constructed from both scans. Lungs are segmented from 4D image, and their volumes from full and sparse dMRI scans are computed. (3) A regression model is developed to predict full-scan volumes from sparse-scan data on a training set. (4) The accuracy is analyzed on both synthesized sparse dMRI scans from a separate fully-sampled-scan test set and actual s-dMRI scans prospectively acquired from 10 normal children. RESULTS: With 5 slices per lung and 40 time points, the predicted volume showed a ∼2% deviation from the full-scan volume, with a total scan-time of ∼9 min (vs. 49.72 ± 5.01 min for the full scan with 15-22 slices per lung and 80 time points). When the spatial sampling was increased to full number of slices (15-22 per lung) but only 40 time points, these metrics become 0.4%, and 24.86 ± 2.5 min. CONCLUSIONS: s-dMRI is a practical approach for computing dynamic lung volumes that can be used routinely with no radiation concern, especially on patients who cannot tolerate long acquisition times.

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