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. .
Liu et al. (Tue,) studied this question.