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

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. Materials and Methods (i) Full-resolution free-breathing sagittally-acquired 2D dMRI scans are gathered from 45 normal children via True-FISP sequence. Sparse dMRI (s-dMRI) scans are simulated from these datasets by subsampling in the spatio-temporal domains via a limited number N SS of selected sagittal locations and T SS of time instances (respectively, N FS and T FS for full scan). (ii) A 4D image is constructed from both full and sparse scans. Lungs are segmented from 4D image, and their volumes from full ( VF ) and sparse dMRI ( VS ) scans are computed. (iii) A regression model is fit for VF as a function of VS on a training set, and the full-resolution volume VP predicted by the model is estimated from VS . (iv) The deviation of VP from VF is analyzed on both synthesized sparse dMRI scans from a separate full-resolution test set and actual s-dMRI scans prospectively acquired from 10 normal children. Results With N SS =5 (per lung) and T SS =40, the deviation of VP from VF was ∼2% with a total scan-time of ∼9 min (45-60 min for the full scan with N FS =15-22 (per lung) and T FS =80). These metrics become 0.4%, and <20 min for s-dMRI with N SS =15-22 (per lung) and T SS =40. Conclusion 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 scan times.