PDF(Pubmed)
Abstract：
UNASSIGNED: This study aims to evaluate deep learning (DL) denoising reconstructions for image quality improvement of Doppler ultrasound (DUS)-gated fetal cardiac MRI in congenital heart disease (CHD).
UNASSIGNED: Twenty-five fetuses with CHD (mean gestational age: 35 ± 1 weeks) underwent fetal cardiac MRI at 3T. Cine imaging was acquired using a balanced steady-state free precession (bSSFP) sequence with Doppler ultrasound gating. Images were reconstructed using both compressed sensing (bSSFP CS) and a pre-trained convolutional neural network trained for DL denoising (bSSFP DL). Images were compared qualitatively based on a 5-point Likert scale (from 1 = non-diagnostic to 5 = excellent) and quantitatively by calculating the apparent signal-to-noise ratio (aSNR) and contrast-to-noise ratio (aCNR). Diagnostic confidence was assessed for the atria, ventricles, foramen ovale, valves, great vessels, aortic arch, and pulmonary veins.
UNASSIGNED: Fetal cardiac cine MRI was successful in 23 fetuses (92%), with two studies excluded due to extensive fetal motion. The image quality of bSSFP DL cine reconstructions was rated superior to standard bSSFP CS cine images in terms of contrast [3 (interquartile range: 2-4) vs. 5 (4-5), P < 0.001] and endocardial edge definition [3 (2-4) vs. 4 (4-5), P < 0.001], while the extent of artifacts was found to be comparable [4 (3-4.75) vs. 4 (3-4), P = 0.40]. bSSFP DL images had higher aSNR and aCNR compared with the bSSFP CS images (aSNR: 13.4 ± 6.9 vs. 8.3 ± 3.6, P < 0.001; aCNR: 26.6 ± 15.8 vs. 14.4 ± 6.8, P < 0.001). Diagnostic confidence of the bSSFP DL images was superior for the evaluation of cardiovascular structures (e.g., atria and ventricles: P = 0.003).
UNASSIGNED: DL image denoising provides superior quality for DUS-gated fetal cardiac cine imaging of CHD compared to standard CS image reconstruction.
UNASSIGNED: Twenty-five fetuses with CHD (mean gestational age: 35 ± 1 weeks) underwent fetal cardiac MRI at 3T. Cine imaging was acquired using a balanced steady-state free precession (bSSFP) sequence with Doppler ultrasound gating. Images were reconstructed using both compressed sensing (bSSFP CS) and a pre-trained convolutional neural network trained for DL denoising (bSSFP DL). Images were compared qualitatively based on a 5-point Likert scale (from 1 = non-diagnostic to 5 = excellent) and quantitatively by calculating the apparent signal-to-noise ratio (aSNR) and contrast-to-noise ratio (aCNR). Diagnostic confidence was assessed for the atria, ventricles, foramen ovale, valves, great vessels, aortic arch, and pulmonary veins.
UNASSIGNED: Fetal cardiac cine MRI was successful in 23 fetuses (92%), with two studies excluded due to extensive fetal motion. The image quality of bSSFP DL cine reconstructions was rated superior to standard bSSFP CS cine images in terms of contrast [3 (interquartile range: 2-4) vs. 5 (4-5), P < 0.001] and endocardial edge definition [3 (2-4) vs. 4 (4-5), P < 0.001], while the extent of artifacts was found to be comparable [4 (3-4.75) vs. 4 (3-4), P = 0.40]. bSSFP DL images had higher aSNR and aCNR compared with the bSSFP CS images (aSNR: 13.4 ± 6.9 vs. 8.3 ± 3.6, P < 0.001; aCNR: 26.6 ± 15.8 vs. 14.4 ± 6.8, P < 0.001). Diagnostic confidence of the bSSFP DL images was superior for the evaluation of cardiovascular structures (e.g., atria and ventricles: P = 0.003).
UNASSIGNED: DL image denoising provides superior quality for DUS-gated fetal cardiac cine imaging of CHD compared to standard CS image reconstruction.
摘要：
■本研究旨在评估深度学习（DL）去噪重建，以改善先天性心脏病（CHD）中多普勒超声（DUS）门控胎儿心脏MRI的图像质量。
■25例CHD胎儿（平均胎龄：35±1周）在3T时接受胎儿心脏MRI检查。使用带有多普勒超声门控的平衡稳态自由进动（bSSFP）序列获取电影成像。使用压缩感知（bSSFPCS）和经过DL去噪训练的预训练卷积神经网络（bSSFPDL）重建图像。根据5点Likert量表（从1=非诊断性到5=出色）定性比较图像，并通过计算表观信噪比（aSNR）和对比噪声比（aCNR）进行定量比较。评估心房的诊断信心，心室,卵圆孔,阀门,伟大的船只，主动脉弓,还有肺静脉.
■胎儿心脏电影MRI在23个胎儿（92％）中成功，由于广泛的胎儿活动而排除了两项研究。在对比度方面，bSSFPDL电影重建的图像质量被评为优于标准bSSFPCS电影图像[3（四分位数间距：2-4）与5（4-5）P<0.001和心内膜边缘定义[3(2-4)vs.4（4-5）P<0.001],而发现伪影的程度相当[4（3-4.75）与4（3-4）P=0.40]。与bSSFPCS图像相比，bSSFPDL图像具有更高的aSNR和aCNR（aSNR：13.4±6.9vs.8.3±3.6，P<0.001；aCNR：26.6±15.8vs.14.4±6.8，P<0.001）。bSSFPDL图像的诊断置信度优于心血管结构的评估(例如，心房和心室：P=0.003）。
■与标准CS图像重建相比，DL图像去噪为CHD的DUS门控胎儿心脏电影成像提供了卓越的质量。
■25例CHD胎儿（平均胎龄：35±1周）在3T时接受胎儿心脏MRI检查。使用带有多普勒超声门控的平衡稳态自由进动（bSSFP）序列获取电影成像。使用压缩感知（bSSFPCS）和经过DL去噪训练的预训练卷积神经网络（bSSFPDL）重建图像。根据5点Likert量表（从1=非诊断性到5=出色）定性比较图像，并通过计算表观信噪比（aSNR）和对比噪声比（aCNR）进行定量比较。评估心房的诊断信心，心室,卵圆孔,阀门,伟大的船只，主动脉弓,还有肺静脉.
■胎儿心脏电影MRI在23个胎儿（92％）中成功，由于广泛的胎儿活动而排除了两项研究。在对比度方面，bSSFPDL电影重建的图像质量被评为优于标准bSSFPCS电影图像[3（四分位数间距：2-4）与5（4-5）P<0.001和心内膜边缘定义[3(2-4)vs.4（4-5）P<0.001],而发现伪影的程度相当[4（3-4.75）与4（3-4）P=0.40]。与bSSFPCS图像相比，bSSFPDL图像具有更高的aSNR和aCNR（aSNR：13.4±6.9vs.8.3±3.6，P<0.001；aCNR：26.6±15.8vs.14.4±6.8，P<0.001）。bSSFPDL图像的诊断置信度优于心血管结构的评估(例如，心房和心室：P=0.003）。
■与标准CS图像重建相比，DL图像去噪为CHD的DUS门控胎儿心脏电影成像提供了卓越的质量。
