An Aristotelian View on MR-Based Attenuation Correction (ARISTOMRAC): Combining the Four Elements

Abstract

Magnetic resonance-based attenuation correction (MRAC) is important for accurate quantification of the uptake of PET tracers in combined PET/MR scanners. However, current techniques for MRAC usually require multiple acquisitions or complex post-processing to discriminate the different tissues. Inspired by the ancient Greeks, who believed that matter was made of the combination of four elements (earth, water, air, and fire), we formulated a multicomponent magnetic resonance (MR) fingerprinting framework, where every voxel was considered a weighted combination of four base elements: 1) bone; 2) water; 3) air; and 4) fat. We named our approach aristotelian MR-based attenuation correction (ARISTOMRAC). We used a 3-D radial acquisition scheme at 1.5T, acquiring a transient-state spoiled acquisition with variable flip angles and echo times (TE), with the shortest TEs being ultrashort echo times (UTEs). We simulated a multitissue MR signal model using the Bloch equations and used dictionary matching to extract tissue fraction maps for bone water and fat, while air fractions were obtained by thresholding the UTE parts of our acquisitions at higher spatial resolution. Compared to previous methods for MRAC, our approach used a full multicomponent signal model, including multiple tissues per voxel. For this reason, rather than reconstructing high resolutions images, MR data can be acquired more efficiently, directly at the resolution needed for PET attenuation maps. The ARISTOMRAC method allows to accurately estimate the air, water, bone, and fat fractions (concordance correlation coefficient = 0.81/0.91/0.98 for bone, water, and fat, respectively). Attenuation maps could be obtained in the head and neck with a single 1-min acquisition.