Ziwu Zhou1,2, Fei Han1,2, Takegawa Yoshida1, Kim-Lien Nguyen1,3, John Paul Finn1,4, Peng Hu5,6,7. 1. Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. 2. Department of Bioengineering, University of California, Los Angeles, CA, USA. 3. Division of Cardiology, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA. 4. Biomedical Physics Inter-Departmental Graduate Program, University of California, Los Angeles, CA, USA. 5. Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA. penghu@mednet.ucla.edu. 6. Biomedical Physics Inter-Departmental Graduate Program, University of California, Los Angeles, CA, USA. penghu@mednet.ucla.edu. 7. Department of Radiological Sciences, David Geffen School of Medicine, University of California, 300 UCLA Medical Plaza Suite B119, Los Angeles, CA, 90095, USA. penghu@mednet.ucla.edu.
Abstract
OBJECTIVE: Our aim was to develop and evaluate a motion-weighted reconstruction technique for improved cardiac function assessment in 4D magnetic resonance imaging (MRI). MATERIALS AND METHODS: A flat-topped, two-sided Gaussian kernel was used to weigh k-space data in each target cardiac phase and adjacent two temporal phases during the proposed phase-by-phase reconstruction algorithm. The proposed method (Strategy 3) was used to reconstruct 18 cardiac phases based on data acquired using a previously proposed technique [4D multiphase steady-state imaging with contrast enhancement (MUSIC) technique and its self-gated extension using rotating Cartesian k-space (ROCK-MUSIC) from 12 pediatric patients. As a comparison, the same data set was reconstructed into nine phases using a phase-by-phase method (Strategy 1), 18 phases using view sharing (Strategy 4), and 18 phases using a temporal regularized method (Strategy 2). Regional image sharpness and left ventricle volumetric measurements were used to compare the four reconstructions quantitatively. RESULTS: Strategies 1 and 4 generated significantly sharper images of static structures (P ≤ 0.018) than Strategies 2 and 3 but significantly more blurry (P ≤ 0.021) images of the heart. Left ventricular volumetric measurements from the nine-phase reconstruction (Strategy 1) correlated moderately (r < 0.8) with the 2D cine, whereas the remaining three techniques had a higher correlation (r > 0.9). The computational burden of Strategy 2 was six times that of Strategy 3. CONCLUSION: The proposed method of motion-weighted reconstruction improves temporal resolution in 4D cardiac imaging with a clinically practical workflow.
OBJECTIVE: Our aim was to develop and evaluate a motion-weighted reconstruction technique for improved cardiac function assessment in 4D magnetic resonance imaging (MRI). MATERIALS AND METHODS: A flat-topped, two-sided Gaussian kernel was used to weigh k-space data in each target cardiac phase and adjacent two temporal phases during the proposed phase-by-phase reconstruction algorithm. The proposed method (Strategy 3) was used to reconstruct 18 cardiac phases based on data acquired using a previously proposed technique [4D multiphase steady-state imaging with contrast enhancement (MUSIC) technique and its self-gated extension using rotating Cartesian k-space (ROCK-MUSIC) from 12 pediatric patients. As a comparison, the same data set was reconstructed into nine phases using a phase-by-phase method (Strategy 1), 18 phases using view sharing (Strategy 4), and 18 phases using a temporal regularized method (Strategy 2). Regional image sharpness and left ventricle volumetric measurements were used to compare the four reconstructions quantitatively. RESULTS: Strategies 1 and 4 generated significantly sharper images of static structures (P ≤ 0.018) than Strategies 2 and 3 but significantly more blurry (P ≤ 0.021) images of the heart. Left ventricular volumetric measurements from the nine-phase reconstruction (Strategy 1) correlated moderately (r < 0.8) with the 2D cine, whereas the remaining three techniques had a higher correlation (r > 0.9). The computational burden of Strategy 2 was six times that of Strategy 3. CONCLUSION: The proposed method of motion-weighted reconstruction improves temporal resolution in 4D cardiac imaging with a clinically practical workflow.
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