An Aristotelian view on MR-based attenuation correction (ARISTOMRAC): combining the four elements

TL;DR

This paper introduces ARISTOMRAC, a novel MR fingerprinting framework inspired by the four elements, enabling efficient and accurate multi-tissue attenuation correction in PET/MR imaging with a single quick acquisition.

Contribution

It presents a multi-component MR fingerprinting method that models tissues as combinations of four elements, improving efficiency and accuracy of attenuation correction in PET/MR scans.

Findings

Accurately estimates air, water, bone, and fat fractions with high concordance.

Achieves head and neck attenuation maps in 1 minute.

Uses a full multi-component signal model for better tissue discrimination.

Abstract

MR-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 multi-component Magnetic Resonance (MR) Fingerprinting framework, where every voxel was considered a weighted combination of four base elements: bone, water, air and fat. We named our approach Aristotelian MR based attenuation correction (ARISTOMRAC). We used a 3D 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 ultra-short echo times (UTE). We simulated a multi-tissue 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 MR-based Attenuation Correction (MRAC), our approach used a full multi-component 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-minute acquisition.