High-Quality Four-Dimensional Magnetic Resonance Fingerprinting Reconstruction for Liver Cancer Radiation therapy

To develop a high-quality 4-dimensional magnetic resonance fingerprinting (HQ-4DMRF) framework with temporal low-rank-constrained motion compensation for precise tumor motion management in liver radiation therapy.

HQ-4DMRF integrated 4 key innovations: (1) an automated internal respiratory navigator to track organ motion without external sensors; (2) a results-driven phase-sorting algorithm to dynamically redistribute magnetic resonance fingerprinting (MRF) dynamics across respiratory phases; (3) a novel temporal low-rank-constrained 4-dimensional (4D) registration algorithm to simultaneously compute all interphase deformation vector fields by leveraging low-rank respiratory motion properties and enforcing spatiotemporal regularization; and (4) an iterative motion-compensated optimization algorithm to reconstruct motion-resolved 4D tissue maps. HQ-4DMRF was validated in 24 patients with hepatocellular carcinoma. All patients underwent a free-breathing abdominal MRF scan using a multislice 2-dimensional fast acquisition with steady-state precession sequence. The motion measurement accuracy of HQ-4DMRF was assessed through interphase structural repeatability. Interphase structural repeatability quantified the structural consistency in tissue maps across motion phases using the structural similarity index, local cross-correlation, and textural feature intraclass correlation coefficient for tumors.

The HQ-4DMRF demonstrated superior precision in motion measurement versus conventional 4DMRF techniques (P < .001), with interphase structural repeatability-structural similarity index/-local cross-correlation/-textural feature intraclass correlation coefficient of 0.82 ± 0.06/0.36 ± 0.07/0.75 ± 0.20 for T1, 0.89 ± 0.05/0.29 ± 0.06/0.84 ± 0.24 for T2, and 0.80 ± 0.06/0.38 ± 0.06/0.91 ± 0.12 for proton density maps. Compared with using conventional pair-wised registration methods, the temporal low-rank-constrained 4D registration improved motion measurement accuracy by an average of 8.5% to 12.5% (structural similarity index), 9.1% to 36.2% (local cross-correlation), and 8.2% to 17.1% (textural feature intraclass correlation coefficient). The respiratory curve derived from automated internal respiratory navigator showed strong agreement with manual measurements (Pearson correlation coefficient = 0.90 ± 0.12) and demonstrated consistent performance across different anatomic regions (Pearson correlation coefficient = 0.83 ± 0.13). The result-driven phase sorting enhanced the 4DMRF performance by 7.2%.

The HQ-4DMRF framework presents a comprehensive solution to critical challenges in 4DMRF. Clinical validation in patients with hepatocellular carcinoma demonstrates significant improvements in liver tumor motion characterization. These advances not only enhance the precision of radiation therapy planning through more accurate motion modeling but also establish HQ-4DMRF as a promising platform for 4D quantitative magnetic resonance imaging in oncologic applications.