Dataset Information

Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload.

ABSTRACT:

Background

R2*-MRI is clinically used to noninvasively assess hepatic iron content (HIC) to guide potential iron chelation therapy. However, coexisting pathologies, such as fibrosis and steatosis, affect R2* measurements and may thus confound HIC estimations.

Purpose

To evaluate whether a multispectral auto regressive moving average (ARMA) model can be used in conjunction with quantitative susceptibility mapping (QSM) to measure magnetic susceptibility as a confounder-free predictor of HIC.

Study type

Phantom study and in vivo cohort.

Subjects

Nine iron phantoms covering clinically relevant R2* range (20-1200/second) and 48 patients (22 male, 26 female, median age 18 years).

Field strength/sequence

Three-dimensional (3D) and two-dimensional (2D) multi-echo gradient echo (GRE) at 1.5 T.

Assessment

ARMA-QSM modeling was performed on the complex 3D GRE signal to estimate R2*, fat fraction (FF), and susceptibility measurements. R2*-based dry clinical HIC values were calculated from the 2D GRE acquisition using a published R2*-HIC calibration curve as reference standard.

Statistical tests

Linear regression analysis was performed to compare ARMA R2* and susceptibility-based estimates to iron concentrations and dry clinical HIC values in phantoms and patients, respectively.

Results

In phantoms, the ARMA R2* and susceptibility values strongly correlated with iron concentrations (R² ≥ 0.9). In patients, the ARMA R2* values highly correlated (R² = 0.97) with clinical HIC values with slope = 0.026, and the susceptibility values showed good correlation (R² = 0.82) with clinical dry HIC values with slope = 3.3 and produced a dry-to-wet HIC ratio of 4.8.

Data conclusion

This study shows the feasibility that ARMA-QSM can simultaneously estimate susceptibility-based wet HIC, R2*-based dry HIC and FFs from a single multi-echo GRE acquisition. Our results demonstrate that both, R2* and susceptibility-based wet HIC values estimated with ARMA-QSM showed good association with clinical dry HIC values with slopes similar to published R2*-biopsy HIC calibration and dry-to-wet tissue weight ratio, respectively. Hence, our study shows that ARMA-QSM can provide potentially confounder-free assessment of hepatic iron overload.

Level of evidence

3 TECHNICAL EFFICACY: Stage 2.

SUBMITTER: Tipirneni-Sajja A

PROVIDER: S-EPMC9223690 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload.

Tipirneni-Sajja Aaryani A Loeffler Ralf B RB Hankins Jane S JS Morin Cara C Hillenbrand Claudia M CM

Journal of magnetic resonance imaging : JMRI 20210226 3

<h4>Background</h4>R2*-MRI is clinically used to noninvasively assess hepatic iron content (HIC) to guide potential iron chelation therapy. However, coexisting pathologies, such as fibrosis and steatosis, affect R2* measurements and may thus confound HIC estimations.<h4>Purpose</h4>To evaluate whether a multispectral auto regressive moving average (ARMA) model can be used in conjunction with quantitative susceptibility mapping (QSM) to measure magnetic susceptibility as a confounder-free predict ...[more]

PMID: 33634923

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Dataset Information

Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload.

Background

Purpose

Study type

Subjects

Field strength/sequence

Assessment

Statistical tests

Results

Data conclusion

Level of evidence

Publications

Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload.

Similar Datasets

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