Dataset Information

Free-breathing fat and R₂ * quantification in the liver using a stack-of-stars multi-echo acquisition with respiratory-resolved model-based reconstruction.

ABSTRACT:

Purpose

To develop a free-breathing hepatic fat and R2∗ quantification method by extending a previously described stack-of-stars model-based fat-water separation technique with additional modeling of the transverse relaxation rate R2∗ .

Methods

The proposed technique combines motion-robust radial sampling using a stack-of-stars bipolar multi-echo 3D GRE acquisition with iterative model-based fat-water separation. Parallel-Imaging and Compressed-Sensing principles are incorporated through modeling of the coil-sensitivity profiles and enforcement of total-variation (TV) sparsity on estimated water, fat, and R2∗ parameter maps. Water and fat signals are used to estimate the confounder-corrected proton-density fat fraction (PDFF). Two strategies for handling respiratory motion are described: motion-averaged and motion-resolved reconstruction. Both techniques were evaluated in patients (n = 14) undergoing a hepatobiliary research protocol at 3T. PDFF and R2∗ parameter maps were compared to a breath-holding Cartesian reference approach.

Results

Linear regression analyses demonstrated strong (r > 0.96) and significant (P ≪ .01) correlations between radial and Cartesian PDFF measurements for both the motion-averaged reconstruction (slope: 0.90; intercept: 0.07%) and the motion-resolved reconstruction (slope: 0.90; intercept: 0.11%). The motion-averaged technique overestimated hepatic R2∗ values (slope: 0.35; intercept: 30.2 1/s) compared to the Cartesian reference. However, performing a respiratory-resolved reconstruction led to better R2∗ value consistency (slope: 0.77; intercept: 7.5 1/s).

Conclusions

The proposed techniques are promising alternatives to conventional Cartesian imaging for fat and R2∗ quantification in patients with limited breath-holding capabilities. For accurate R2∗ estimation, respiratory-resolved reconstruction should be used.

SUBMITTER: Schneider M

PROVIDER: S-EPMC7396291 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeTo evaluate workflow efficiency and diagnostic quality of a free-breathing 3D stack-of-stars gradient echo (Radial GRE) sequence compared to a breath-hold 3D Cartesian gradient echo (Cartesian GRE) sequence for needle position control in MR-guided liver interventions.Materials and methods12 MR-guided liver interventions were performed on a 1.5 T Siemens Aera and analyzed retrospectively. 15 series of the Radial GRE sequence were compared to 14 series of the Cartesian GRE sequence regarding the time interval between two consecutive live-scans for needle tracking (Tracking-2-Tracking-Time). The quality of both sequences was compared by the SNR within comparable slices in liver and tumor ROIs. The CNR was calculated by subtraction of the SNR values. Subjective image quality scores of three radiologists were assessed and inter-rater reliability was tested by Fleiss' kappa. Values are given as mean ± SD. P-values < 0.05 were considered as significant.ResultsThe median Tracking-2-Tracking-Time was significantly shorter for the Radial GRE sequence, 185 ± 42 s vs. 212 ± 142 s (p = 0.04) and the median SNR of the liver and tumor ROIs were significantly higher in the Radial GRE sequence, 249 ± 92 vs. 109 ± 67 (p = 0.03) and 165 ± 74 vs. 77 ± 43 (p = 0.02). CNR between tumor and liver ROIs showed a tendency to be higher for the Radial GRE sequence without significance, 68 ± 48 vs. 49 ± 32 (p = 0.28). Mean subjective image quality was 3.33 ± 1.08 vs. 2.62 ± 0.95 comparing Radial and Cartesian GRE with a Fleiss' kappa of 0.39 representing fair inter-rater reliability.ConclusionA free-breathing 3D stack-of-stars gradient echo sequence can simplify the workflow and reduce intervention time, while providing superior image quality. Under local anesthesia, it increases patient comfort and reduces potential risks for needle dislocations in MR-guided liver interventions by avoiding respiratory arrests for needle position control.

Dataset Information

Free-breathing fat and R₂ * quantification in the liver using a stack-of-stars multi-echo acquisition with respiratory-resolved model-based reconstruction.

Purpose

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Free-breathing fat and R2 * quantification in the liver using a stack-of-stars multi-echo acquisition with respiratory-resolved model-based reconstruction.

Purpose

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Free-breathing fat and R₂ * quantification in the liver using a stack-of-stars multi-echo acquisition with respiratory-resolved model-based reconstruction.