Imaging of lung function using hyperpolarized helium‐3 magnetic resonance imaging: Review of current and emerging translational methods and applications

Abstract

During the past several years there has been extensive development and application of hyperpolarized helium-3 (HP 3 He) magnetic resonance imaging (MRI) in clinical respiratory indications such as asthma, chronic obstructive pulmonary disease, cystic fibrosis, radiation-induced lung injury, and transplantation. This review focuses on the state-of-the-art of HP 3 He MRI and its application to clinical pulmonary research. This is not an overview of the physics of the method, as this topic has been covered previously. We focus here on the potential of this imaging method and its challenges in demonstrating new types of information that has the potential to influence clinical research and decision making in pulmonary medicine. Particular attention is given to functional imaging approaches related to ventilation and diffusion-weighted imaging with applications in chronic obstructive pulmonary disease, cystic fibrosis, asthma, and radiationinduced lung injury. The strengths and challenges of the application of 3 He MRI in these indications are discussed along with a comparison to established and emerging imaging techniques.

Three‐dimensional oxygen‐enhanced MRI of the human lung at 1.5T with ultra‐fast balanced steady‐state free precession

“…Eq. [3]) to the observed volume-related average signal variations. A corresponding outline is shown in Figures 1a to 1c.…”

“…Imaging was performed with an ultrafast SSFP framework, as described elsewhere (15), yielding an echo time/repetition time (TE/TR) of 0.47 ms/1.19 ms using a nonselective radiofrequency pulse with a duration of 80 ms, a readout bandwidth of 1563 Hz/pixel, and a field of view of 400 Â 400 Â 250 mm 3 , yielding an isotropic resolution of 3.1 mm 3 (128 Â 128 Â 80 imaging matrix). A parallel imaging with generalized auto-calibrating partially parallel acquisition (GRAPPA) (23) factor 2 and 40% phase oversampling was used, yielding a total acquisition time of 16 seconds for an acquisition with two averages.…”

“…All datasets were subsequently median filtered (kernel size 5 Â 5 Â 5 voxels) and fitted voxel-wise to the linear sponge model (Eq. [3]) for each O 2 concentration using orthogonal regression (the lung volume was retrieved in the aforementioned segmentation process on the non-registered images). The local oxygen enhancement, OE local ð VÞ; was then calculated voxel-wise (Eq.…”

“…[4], unregistered images), using the sponge model (Eq. [3]). (d) The multi-volumetric datasets were ordered according to their volumes [using the information gained in (b)].…”

“…to 83 [a.u.] for corresponding lung volumes ranging from 2381 to 3075 cm 3 . This is in contrast to the liver SI, which remains constant (240 6 3 [a.u.])…”