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• W4295249469 abstract "To develop and validate a deep learning-based reconstruction framework for highly accelerated two-dimensional (2D) phase contrast (PC-MRI) data with accurate and precise quantitative measurements.We propose a modified DL-ESPIRiT reconstruction framework for 2D PC-MRI, comprised of an unrolled neural network architecture with a Complex Difference estimation (CD-DL). CD-DL was trained on 155 fully sampled 2D PC-MRI pediatric clinical datasets. The fully sampled data ( n=29$$ n=29 $$ ) was retrospectively undersampled (6-11 ×$$ times $$ ) and reconstructed using CD-DL and a parallel imaging and compressed sensing method (PICS). Measurements of peak velocity and total flow were compared to determine the highest acceleration rate that provided accuracy and precision within ±5%$$ pm 5% $$ . Feasibility of CD-DL was demonstrated on prospectively undersampled datasets acquired in pediatric clinical patients ( n=5$$ n=5 $$ ) and compared to traditional parallel imaging (PI) and PICS.The retrospective evaluation showed that 9 ×$$ times $$ accelerated 2D PC-MRI images reconstructed with CD-DL provided accuracy and precision (bias, [95 %$$ % $$ confidence intervals]) within ±5%$$ pm 5% $$ . CD-DL showed higher accuracy and precision compared to PICS for measurements of peak velocity (2.8 %$$ % $$ [ -2.9$$ -2.9 $$ , 4.5] vs. 3.9 %$$ % $$ [ -11.0$$ -11.0 $$ , 4.9]) and total flow (1.8 %$$ % $$ [ -3.9$$ -3.9 $$ , 3.4] vs. 2.9 %$$ % $$ [ -7.1$$ -7.1 $$ , 6.9]). The prospective feasibility study showed that CD-DL provided higher accuracy and precision than PICS for measurements of peak velocity and total flow.In a retrospective evaluation, CD-DL produced quantitative measurements of 2D PC-MRI peak velocity and total flow with ≤5%$$ le 5% $$ error in both accuracy and precision for up to 9 ×$$ times $$ acceleration. Clinical feasibility was demonstrated using a prospective clinical deployment of our 8 ×$$ times $$ undersampled acquisition and CD-DL reconstruction in a cohort of pediatric patients." @default.
• W4295249469 created "2022-09-12" @default.
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• W4295249469 date "2022-09-12" @default.
• W4295249469 modified "2023-10-16" @default.
• W4295249469 title "Accelerated two‐dimensional phase‐contrast for cardiovascular MRI using deep learning‐based reconstruction with complex difference estimation" @default.
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• W4295249469 doi "https://doi.org/10.1002/mrm.29441" @default.
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