PURPOSE: An efficient Yarnball ultrashort-TE k-space trajectory, in combination with an optimized pulse sequence design and automated image-processing approach, is proposed for fast and quantitative imaging of water density in the lung parenchyma. METHODS: Three-dimensional Yarnball k-space trajectories (TE = 0.07 ms) were designed at 3 T for breath-hold and free-breathing navigator acquisitions targeting the lung parenchyma (full torso spatial coverage) with minimal T1 and T 2 ∗ weighting. A composite of all solid tissues surrounding the lungs (muscle, liver, heart, blood pool) was used for user-independent lung water density signal referencing and B1 -inhomogeneity correction needed for the calculation of relative lung water density images. Sponge phantom experiments were used to validate absolute water density quantification, and relative lung water density was evaluated in 10 healthy volunteers. RESULTS: Phantom experiments showed excellent agreement between sponge wet weight and imaging-derived water density. Breath-hold (13 seconds) and free-breathing (~2 minutes) Yarnball acquisitions in volunteers (2.5-mm isotropic resolution) had negligible artifacts and good lung parenchyma SNR (>10). Whole-lung average relative lung water density values with fully automated analysis were 28.2 ± 1.9% and 28.6 ± 1.8% for breath-hold and free-breathing acquisitions, respectively, with good test-retest reproducibility (intraclass correlation coefficient = 0.86 and 0.95, respectively). CONCLUSIONS: Quantitative lung water density imaging with an optimized Yarnball k-space acquisition approach is possible in a breath-hold or short free-breathing study with automated signal referencing and segmentation.
PURPOSE: An efficient Yarnball ultrashort-TE k-space trajectory, in combination with an optimized pulse sequence design and automated image-processing approach, is proposed for fast and quantitative imaging of water density in the lung parenchyma. METHODS: Three-dimensional Yarnball k-space trajectories (TE = 0.07 ms) were designed at 3 T for breath-hold and free-breathing navigator acquisitions targeting the lung parenchyma (full torso spatial coverage) with minimal T1 and T 2 ∗ weighting. A composite of all solid tissues surrounding the lungs (muscle, liver, heart, blood pool) was used for user-independent lung water density signal referencing and B1 -inhomogeneity correction needed for the calculation of relative lung water density images. Sponge phantom experiments were used to validate absolute water density quantification, and relative lung water density was evaluated in 10 healthy volunteers. RESULTS: Phantom experiments showed excellent agreement between sponge wet weight and imaging-derived water density. Breath-hold (13 seconds) and free-breathing (~2 minutes) Yarnball acquisitions in volunteers (2.5-mm isotropic resolution) had negligible artifacts and good lung parenchyma SNR (>10). Whole-lung average relative lung water density values with fully automated analysis were 28.2 ± 1.9% and 28.6 ± 1.8% for breath-hold and free-breathing acquisitions, respectively, with good test-retest reproducibility (intraclass correlation coefficient = 0.86 and 0.95, respectively). CONCLUSIONS: Quantitative lung water density imaging with an optimized Yarnball k-space acquisition approach is possible in a breath-hold or short free-breathing study with automated signal referencing and segmentation.