Quantifying spatial and dynamic lung abnormalities with 3D PREFUL FLORET UTE imaging: A feasibility study.

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Tác giả: Abdullah S Bdaiwi, Zackary I Cleveland, Marcel Gutberlet, Filip Klimeš, Alexander M Matheson, Joseph W Plummer, Jens Vogel-Claussen, Andreas Voskrebenzev, Frank Wacker, Laura L Walkup, Marius M Wernz, Matthew M Willmering, Jason Woods

Ngôn ngữ: eng

Ký hiệu phân loại: 003.85 Dynamic systems

Thông tin xuất bản: United States : Magnetic resonance in medicine , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 689759

PURPOSE: Pulmonary MRI faces challenges due to low proton density, rapid transverse magnetization decay, and cardiac and respiratory motion. The fermat-looped orthogonally encoded trajectories (FLORET) sequence addresses these issues with high sampling efficiency, strong signal, and motion robustness, but has not yet been applied to phase-resolved functional lung (PREFUL) MRI-a contrast-free method for assessing pulmonary ventilation during free breathing. This study aims to develop a reconstruction pipeline for FLORET UTE, enhancing spatial resolution for three-dimensional (3D) PREFUL ventilation analysis. METHODS: The FLORET sequence was used to continuously acquire data over 7 ± 2 min in 36 participants, including healthy subjects (N = 7) and patients with various pulmonary conditions (N = 29). Data were reconstructed into respiratory images using motion-compensated low-rank reconstruction, and a 3D PREFUL algorithm was adapted to quantify static and dynamic ventilation surrogates. Image sharpness and signal-to-noise ratio were evaluated across different motion states. PREFUL ventilation metrics were compared with static RESULTS: Optimal image sharpness and accurate ventilation dynamics were achieved using 24 respiratory bins, leading to their use in the study. A strong correlation was found between 3D PREFUL FLORET UTE ventilation defect percentages (VDPs) and CONCLUSION: The proposed reconstruction pipeline for FLORET UTE MRI offers improved spatial resolution and strong correlation with
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