Work

Respiratory Motion‐Corrected Model‐Based 3D Water‐Fat MRA of the Thorax at 0.55 T

Year: 2026

Type: article

Abstract: PURPOSE: The goal of this study was to develop a 5-min 3D MRA acquisition at 0.55 T with predictable scan time, 100% data efficiency, and robust water-fat separation. METHODS: For full data efficiency, the proposed method combined self-gating with retrospective motion correction while ensuring a predictable 5-min scan time. Water-fat separation was implemented using a model-based Dixon reconstruction. Evaluation in 18 volunteers compared results to navigator-gated reference scans with nominal scan times of 5 and 10 min via a Likert scale blinded expert rating. Susceptibility to irregular breathing patterns was also analyzed. RESULTS: The expert rating for image quality was 4.22 for the proposed method, 3.89 for the 5-min navigator-gated scan and 4.43 for the 10-min navigator-gated scan. Ranking the three methods revealed moderate inter-rater reliability of 0.46, suggesting only minor differences. While navigator-gated acquisitions deviated from the expected scan time by -2.26 to 2.86 min and -3.91 to 4.54 min for the 5- and 10-min protocols respectively, the proposed method deviated only by -0.17 to 0.45 min. The self-gated method further avoided saturation artifacts from the cross-beam navigator, allowing better distinction of the right pulmonary veins. Image quality for the proposed method was also less susceptible to irregular breathing patterns. CONCLUSION: Whole-thorax MRA acquisitions with water-fat separation and predictable scan times were successfully acquired in 18 volunteers at 0.55 T. The proposed method demonstrated on average better image quality than navigator-gated acquisitions of the same nominal scan time while mitigating limitations of prospective navigator gating.

Source: Magnetic Resonance in Medicine

DOI: 10.1002/mrm.70285

Authors: Robert Stoll, Christoph Kolbitsch, Michaela Schmidt, Marcel Dominik Nickel, Tobias Schaeffter, Daniel Giese

Institutions: Siemens Healthineers (Germany), Technische Universität Berlin, Physikalisch-Technische Bundesanstalt, Einstein Center Digital Future

Language: English

Topic: Advanced MRI Techniques and Applications

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,680