A signal model for fat‐suppressed T<sub>1</sub>‐mapping and dynamic contrast‐enhanced MRI with interrupted spoiled gradient‐echo readout

The conventional gradient-echo steady-state signal model is the basis of various spoiled gradient-echo (SPGR) based quantitative MRI models, including variable flip angle (VFA) MRI and dynamic contrast-enhanced MRI (DCE). However, including preparation pulses, such as fat suppression or saturation bands, disrupts the steady-state and leads to a bias in T<sub>1</sub> and DCE parameter estimates. This work introduces a signal model that improves the accuracy of VFA T<sub>1</sub>-mapping and DCE for interrupted spoiled gradient-echo (I-SPGR) acquisitions. The proposed model was applied to a VFA T<sub>1</sub>-mapping I-SPGR sequence in the Gold Standard T<sub>1</sub>-phantom (3 T), in the brain of four healthy volunteers (3 T), and to an abdominal DCE examination (1.5 T). T<sub>1</sub>-values obtained with the proposed and conventional model were compared to reference T<sub>1</sub>-values. Bland-Altman analysis (phantom) and analysis of variance (in vivo) were used to test whether bias from both methods was significantly different (p = 0.05). The proposed model outperformed the conventional model by decreasing the bias in the phantom with respect to the phantom reference values (mean bias -2 vs. -35% at 3 T) and in vivo with respect to the conventional SPGR (-6 vs. -37% bias in T<sub>1</sub>, p < 0.01). The proposed signal model estimated approximately 48% (depending on baseline T<sub>1</sub>) higher contrast concentrations in vivo, which resulted in decreased DCE pharmacokinetic parameter estimates of up to 35%. The proposed signal model improves the accuracy of quantitative parameter estimation from disrupted steady-state I-SPGR sequences. It therefore provides a flexible method for applying fat suppression, saturation bands, and other preparation pulses in VFA T<sub>1</sub>-mapping and DCE.

Authors

Institutions

Publication Details

Journal
NMR in Biomedicine
Published
2024-11-21
DOI
https://doi.org/10.1002/nbm.5289
Citations
2
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A signal model for fat‐suppressed T1‐mapping and dynamic contrast‐enhanced MRI with interrupted spoiled gradient‐echo readout

Oliver J. Gurney‐Champion, Joost P.A. Kuijer, J. Tim Marcus, Leo Heunks et al.
2 citations
NMR in Biomedicine
Advanced MRI Techniques and Applications
0.81
article

A signal model for fat‐suppressed T1‐mapping and dynamic contrast‐enhanced MRI with interrupted spoiled gradient‐echo readout

Oliver J. Gurney‐Champion, Joost P.A. Kuijer, J. Tim Marcus, Leo Heunks, Gustav J. Strijkers, Bram F. Coolen, Aart J. Nederveen, Cristina Lavini, Myrte Wennen, Wilhelm Stehling
article en
2 citations

Abstract

The conventional gradient-echo steady-state signal model is the basis of various spoiled gradient-echo (SPGR) based quantitative MRI models, including variable flip angle (VFA) MRI and dynamic contrast-enhanced MRI (DCE). However, including preparation pulses, such as fat suppression or saturation bands, disrupts the steady-state and leads to a bias in T<sub>1</sub> and DCE parameter estimates. This work introduces a signal model that improves the accuracy of VFA T<sub>1</sub>-mapping and DCE for interrupted spoiled gradient-echo (I-SPGR) acquisitions. The proposed model was applied to a VFA T<sub>1</sub>-mapping I-SPGR sequence in the Gold Standard T<sub>1</sub>-phantom (3 T), in the brain of four healthy volunteers (3 T), and to an abdominal DCE examination (1.5 T). T<sub>1</sub>-values obtained with the proposed and conventional model were compared to reference T<sub>1</sub>-values. Bland-Altman analysis (phantom) and analysis of variance (in vivo) were used to test whether bias from both methods was significantly different (p = 0.05). The proposed model outperformed the conventional model by decreasing the bias in the phantom with respect to the phantom reference values (mean bias -2 vs. -35% at 3 T) and in vivo with respect to the conventional SPGR (-6 vs. -37% bias in T<sub>1</sub>, p < 0.01). The proposed signal model estimated approximately 48% (depending on baseline T<sub>1</sub>) higher contrast concentrations in vivo, which resulted in decreased DCE pharmacokinetic parameter estimates of up to 35%. The proposed signal model improves the accuracy of quantitative parameter estimation from disrupted steady-state I-SPGR sequences. It therefore provides a flexible method for applying fat suppression, saturation bands, and other preparation pulses in VFA T<sub>1</sub>-mapping and DCE.

NMR in BiomedicineVol. 38(1)
Radboud University Nijmegen (NL), Dutch Cancer Society (NL), Erasmus MC (NL), Radboud University Medical Center (NL), Amsterdam University Medical Centers (NL), Cancer Center Amsterdam (NL)
ZonMw
Openalex Percentile: Top 24%
Advanced MRI Techniques and Applications
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.