Rapid automated liver quantitative susceptibility mapping.

ABSTRACT:

Background

Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC.

Purpose

To develop a rapid, robust, and automated liver QSM for clinical practice.

Study type

Prospective.

Population

13 healthy subjects and 22 patients.

Field strength/sequences

1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence.

Assessment

Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T₂ *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22).

Statistical tests

IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R₂ *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC).

Results

Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T₂ *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97).

Data conclusion

Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications.

Level of evidence

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.

SUBMITTER: Jafari R 

PROVIDER: S-EPMC6929208 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature