In vivo imaging of the spectral line broadening of the human lung in a single breathhold

Purpose To present a technique, which allows for the in vivo quantification of the spectral line broadening of the human lung in a single breathhold. The line broadening is an interesting parameter of the lung because it can provide information about important lung properties, namely: inflation and oxygen uptake. The proposed technique integrates the asymmetric spin-echo (ASE) approach, which is commonly used to quantify the line broadening, with a single shot turbo spin-echo pulse sequence with half-Fourier acquisition (HASTE), to reduce the acquisition times. Materials and Methods Imaging experiments were performed at 1.5 Tesla on 14 healthy volunteers, using a ASE-prepared HASTE sequence. The line broadening was quantified using a two-points method. Data were acquired at different breathing states: functional residual capacity (FRC) and total lung capacity (TLC), and with different breathing gases: room-air and pure-oxygen. Image acquisition was accomplished within a single breathhold of approximately 15 s duration. The violation of the Carr-Purcell-Meiboom-Gill conditions, deriving from inhomogeneities of the static magnetic field, was overcome by means of radiofrequency-phase cycling and generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstruction. Results Significant increase of the line broadening was observed with both lung inflation and oxygen concentration (P < 0.0001). Values of the line broadening obtained within the lung parenchyma at different breathing states (1.48 ± 0.29 ppm at FRC and 1.95 ± 0.43 ppm at TLC) are in agreement with previous reports and show excellent reproducibility, with a coefficient of variation <0.03. The mean relative difference observed with oxygen-enhancement was approximately 14%. Conclusion The presented technique offers a robust way to quantify the spectral line broadening of the human lung in vivo. Image acquisition can be accomplished in a single breathhold, which could be suitable for clinical applications on patients with lung diseases. J. Magn. Reson. Imaging 2016;44:745–757.