Abstract
Objective: This study aims to develop a motion-robust magnetic resonance fingerprinting (MR-MRF) technique for liver cancer imaging to eliminate the need for breath-hold scanning.
Approach: To mitigate respiratory motion artifacts in free-breathing abdominal MRF, the MR-MRF technique comprising two core components. First, respiratory motion is modeled by applying an isotropic total variation (TV)-regularized registration algorithm between a target end-of-exhalation (EOE) phase and three motion phases. Second, motion-resolved tissue property maps are reconstructed using a low-rank total variation (LRTV) optimization framework, which incorporates the estimated inter-phase motion to align all acquired MRF dynamics to the EOE phase. MR-MRF is evaluated by 22 patients (mean age, 62 years ± 10 [SD]; 15 males and 7 females) with hepatocellular carcinoma. Radiologist’s blinded assessment and organ boundary sharpness measurements are performed to evaluate the image quality of MR-MRF-derived tissue maps. The test-retest tissue quantification repeatability is assessed by two consecutive MRF scans with distinct breathing patterns. Paired Student’s t-test is used for statistical significance analysis with a p-value threshold of 0.05.
Main results: MR-MRF achieved successful reconstruction of motion-resolved tissue maps at EOE phase, with blinded radiologist assessment yielding an average score of 3 (moderate quality - sufficient for diagnosis) for overall image impression. The FWHM of organ boundaries in MR-MRF-derived tissue maps is 3.1mm ± 1.7mm, significantly lower than motion-blurred tissue maps (9.9mm ± 3.4mm, p-value<0.0001). Test-retest analysis demonstrated good repeatability: liver coefficient of variation was 5.5% ± 7.1% (T1), 8.2% ± 4.4% (T2), and 5.0% ± 2.0% (PD), with excellent linear agreement (R² = 0.96, 0.80, and 0.85 for T1, T2, and PD, respectively).
Significance: This study establishes the technical foundation of MR-MRF to achieve repeatable and quantitative liver T1/T2/PD mapping under free-breathing conditions at 3T. The results validate the feasibility of addressing respiratory motion in abdominal multi-parametric quantitative MRI.
Approach: To mitigate respiratory motion artifacts in free-breathing abdominal MRF, the MR-MRF technique comprising two core components. First, respiratory motion is modeled by applying an isotropic total variation (TV)-regularized registration algorithm between a target end-of-exhalation (EOE) phase and three motion phases. Second, motion-resolved tissue property maps are reconstructed using a low-rank total variation (LRTV) optimization framework, which incorporates the estimated inter-phase motion to align all acquired MRF dynamics to the EOE phase. MR-MRF is evaluated by 22 patients (mean age, 62 years ± 10 [SD]; 15 males and 7 females) with hepatocellular carcinoma. Radiologist’s blinded assessment and organ boundary sharpness measurements are performed to evaluate the image quality of MR-MRF-derived tissue maps. The test-retest tissue quantification repeatability is assessed by two consecutive MRF scans with distinct breathing patterns. Paired Student’s t-test is used for statistical significance analysis with a p-value threshold of 0.05.
Main results: MR-MRF achieved successful reconstruction of motion-resolved tissue maps at EOE phase, with blinded radiologist assessment yielding an average score of 3 (moderate quality - sufficient for diagnosis) for overall image impression. The FWHM of organ boundaries in MR-MRF-derived tissue maps is 3.1mm ± 1.7mm, significantly lower than motion-blurred tissue maps (9.9mm ± 3.4mm, p-value<0.0001). Test-retest analysis demonstrated good repeatability: liver coefficient of variation was 5.5% ± 7.1% (T1), 8.2% ± 4.4% (T2), and 5.0% ± 2.0% (PD), with excellent linear agreement (R² = 0.96, 0.80, and 0.85 for T1, T2, and PD, respectively).
Significance: This study establishes the technical foundation of MR-MRF to achieve repeatable and quantitative liver T1/T2/PD mapping under free-breathing conditions at 3T. The results validate the feasibility of addressing respiratory motion in abdominal multi-parametric quantitative MRI.
| Original language | English |
|---|---|
| Journal | Physics in Medicine and Biology |
| DOIs | |
| Publication status | E-pub ahead of print - 20 Jan 2026 |
Funding
This research was partly supported by National Natural Science Foundation of China (NSFC) Young Scientist Fund (82202941), General Research Funds (GRF 15104323, GRF 15102219, GRF 15104822), Health and Medical Research Fund (HMRF 10211606), and the Innovation and Technology Support Programme (ITS/049/22FP).
Keywords
- Magnetic resonance imaging
- magnetic resonance fingerprinting
- liver cancer
- respiratory motion blurring
- motion robust
