Erschienen in:
12.04.2023 | Research Article
A low-rank deep image prior reconstruction for free-breathing ungated spiral functional CMR at 0.55 T and 1.5 T
verfasst von:
Jesse I. Hamilton, William Truesdell, Mauricio Galizia, Nicholas Burris, Prachi Agarwal, Nicole Seiberlich
Erschienen in:
Magnetic Resonance Materials in Physics, Biology and Medicine
|
Ausgabe 3/2023
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Abstract
Objective
This study combines a deep image prior with low-rank subspace modeling to enable real-time (free-breathing and ungated) functional cardiac imaging on a commercial 0.55 T scanner.
Materials and methods
The proposed low-rank deep image prior (LR-DIP) uses two u-nets to generate spatial and temporal basis functions that are combined to yield dynamic images, with no need for additional training data. Simulations and scans in 13 healthy subjects were performed at 0.55 T and 1.5 T using a golden angle spiral bSSFP sequence with images reconstructed using \({l}_{1}\)-ESPIRiT, low-rank plus sparse (L + S) matrix completion, and LR-DIP. Cartesian breath-held ECG-gated cine images were acquired for reference at 1.5 T. Two cardiothoracic radiologists rated images on a 1–5 scale for various categories, and LV function measurements were compared.
Results
LR-DIP yielded the lowest errors in simulations, especially at high acceleration factors (R \(\ge\) 8). LR-DIP ejection fraction measurements agreed with 1.5 T reference values (mean bias − 0.3% at 0.55 T and − 0.2% at 1.5 T). Compared to reference images, LR-DIP images received similar ratings at 1.5 T (all categories above 3.9) and slightly lower at 0.55 T (above 3.4).
Conclusion
Feasibility of real-time functional cardiac imaging using a low-rank deep image prior reconstruction was demonstrated in healthy subjects on a commercial 0.55 T scanner.