A Bayesian approach for 4D flow imaging of aortic valve in a single breath-hold.
A Bayesian approach for 4D flow imaging of aortic valve in a single breath-hold.
复制标题
单次屏气时主动脉瓣 4D 血流成像的贝叶斯方法。
DOI：
10.1002/mrm.27386
复制
发表时间：
2019
影响因子：
3.3
通讯作者：
Ahmad,Rizwan
中科院分区：
文献类型：
--
作者：
Rich,Adam;Potter,LeeC;Jin,Ning;Liu,Yingmin;Simonetti,OrlandoP;Ahmad,Rizwan
PurposeTo开发和验证一种数据处理技术，允许基于相位对比MRI的4D血流成像的主动脉瓣在一个单一的breath-hold.Theory和MethodsTo正则化不适定的逆问题，我们最近提出的2D相位对比MRI方法扩展到4D血流成像。采用经验贝叶斯方法，通过小波域中的稀疏性来利用空间和时间冗余，并且在条件混合先验中捕获跨编码的逐体素幅度和相位结构，该条件混合先验基于流的存在应用正则化约束。我们验证所提出的技术使用的数据从机械流幻影和五个健康volunteers.ResultsThe来自所提出的技术的流量参数是在很好的协议与来自参考数据集在体内和机械流实验在加速率高达asR= 27。此外，所提出的技术优于kt SPARSE-SENSE和一种利用时空稀疏性但不利用跨encoding.ConclusionsUsing信号结构的方法，该技术可以高度加速4D血流采集，从而在单次屏气内实现主动脉瓣成像。
PurposeTo develop and validate a data processing technique that allows phase‐contrast MRI‐based 4D flow imaging of the aortic valve in a single breath‐hold.Theory and MethodsTo regularize the ill‐posed inverse problem, we extend a recently proposed 2D phase‐contrast MRI method to 4D flow imaging. Adopting an empirical Bayes approach, spatial and temporal redundancies are exploited via sparsity in the wavelet domain, and the voxel‐wise magnitude and phase structure across encodings is captured in a conditional mixture prior that applies regularizing constraints based on the presence of flow. We validate the proposed technique using data from a mechanical flow phantom and five healthy volunteers.ResultsThe flow parameters derived from the proposed technique are in good agreement with those derived from reference datasets for both in vivo and mechanical flow experiments at accelerations rates as high asR= 27. Additionally, the proposed technique outperforms kt SPARSE‐SENSE and a method that exploits spatio‐temporal sparsity but does not utilize signal structure across encodings.ConclusionsUsing the proposed technique, it is feasible to highly accelerate 4D flow acquisition and thus enable aortic valve imaging within a single breath‐hold.