Abstract
Background: Computed tomography is the gold standard for lung aeration assessment, but exposure to ionizing radiation limits its application. We assessed the ability of magnetic resonance imaging (MRI) to detect changes in lung aeration in ex vivo isolated swine lung and the potential of translation of the findings to human MRI scans. Methods: We performed MRI scans in 11 isolated non-injured and injured swine lungs, as well as 6 patients both pre- and post-operatively. Images were obtained using a 1.5 T MRI scanner, with T(1) - weighted volumetric interpolated breath-hold examination (VIBE) and T(2) - weighted half-Fourier acquisition single-shot turbo spin-echo (HASTE) sequences. We scanned swine lungs, with reference samples of water and muscle, at different airway pressure levels: 0, 40, 10, 2 cmH(2)O. We investigated the relations between MRI signal intensity and both lung density and gas content fraction. We analyzed patients' images according to the findings of the ex vivo model. Results: In the ex vivo samples, the lung T(1) - VIBE signal intensity normalized to water or muscle reference signal correlated with lung density (r(2) = 0.98). Thresholds for poorly and non-aerated lung tissue, expressed as MRI intensity attenuation factor compared to the deflated lung, were estimated as 0.70 [95% CI: 0.65-0.74] and 0.28 [95% CI: 0.27-0.30], respectively. In patients, dorsal versus ventral regions had a higher MRI signal intensity both pre- and post-operatively (p = 0.031). Comparing post- versus pre-operative scans, lung volume decreased (p = 0.028), while the following increased: MRI signal intensity in ventral (p = 0.043) and dorsal (p < 0.0001) regions, and percentages of non-aerated (p = 0.028) and poorly aerated tissue volumes (p = 0.028). Conclusion: Magnetic resonance imaging signal intensity is a function of lung density, decreasing linearly with increasing gas content. Lung MRI might be useful for estimating lung aeration. Compared to CT, this technique is radiation-free but requires a longer acquisition time and has a lower spatial resolution.