Proton MRI of the Lung: How to Tame Scarce Protons and Fast Signal Decay.

Pulmonary proton MRI techniques offer the unique possibility of assessing lung function and structure without the requirement for hyperpolarization or dedicated hardware, which is mandatory for multinuclear acquisition. Five popular approaches are presented and discussed in this review: 1) oxygen enhanced (OE)-MRI; 2) arterial spin labeling (ASL); 3) Fourier decomposition (FD) MRI and other related methods including self-gated noncontrast-enhanced functional lung (SENCEFUL) MR and phase-resolved functional lung (PREFUL) imaging; 4) dynamic contrast-enhanced (DCE) MRI; and 5) ultrashort TE (UTE) MRI. While DCE MRI is the most established and well-studied perfusion measurement, FD MRI offers a free-breathing test without any contrast agent and is predestined for application in patients with renal failure or with low compliance. Additionally, FD MRI and related methods like PREFUL and SENCEFUL can act as an ionizing radiation-free V/Q scan, since ventilation and perfusion information is acquired simultaneously during one scan. For OE-MRI, different concentrations of oxygen are applied via a facemask to assess the regional change in T , which is caused by the paramagnetic property of oxygen. Since this change is governed by a combination of ventilation, diffusion, and perfusion, a compound functional measurement can be achieved with OE-MRI. The known problem of fast T * decay of the lung parenchyma leading to a low signal-to-noise ratio is bypassed by the UTE acquisition strategy. Computed tomography (CT)-like images allow the assessment of lung structure with high spatial resolution without ionizing radiation. Despite these different branches of proton MRI, common trends are evident among pulmonary proton MRI: 1) free-breathing acquisition with self-gating; 2) application of UTE to preserve a stronger parenchymal signal; and 3) transition from 2D to 3D acquisition. On that note, there is a visible convergence of the different methods and it is not difficult to imagine that future methods will combine different aspects of the presented methods.