Abstract:
Background. Thoracoabdominal MRI is limited by respiratory motion, especially in populations who cannot perform breath-holds. One approach for reducing motion blurring in radially-acquired MRI is respiratory gating. Straightforward \'hard-gating\' uses only data from a specified respiratory window and suffers from reduced SNR. Proposed \'soft-gating\' reconstructions may improve scan efficiency but reduce motion correction by incorporating data with nonzero weight acquired outside the specified window. However, previous studies report conflicting benefits, and importantly the choice of soft-gated weighting algorithm and effect on image quality has not previously been explored. The purpose of this study is to map how variable soft-gated weighting functions and parameters affect signal and motion blurring in respiratory-gated reconstructions of radial lung MRI, using neonates as a model population.Methods. Ten neonatal inpatients with respiratory abnormalities were imaged using a 1.5 T neonatal-sized scanner and 3D radial ultrashort echo-time (UTE) sequence. Images were reconstructed using ungated, hard-gated, and several soft-gating weighting algorithms (exponential, sigmoid, inverse, and linear weighting decay outside the period of interest), with %Nprojrepresenting the relative amount of data included. The apparent SNR (aSNR) and motion blurring (measured by the maximum derivative of image intensity at the diaphragm, MDD) were compared between reconstructions.Results. Soft-gating functions produced higher aSNR and lower MDD than hard-gated images using equivalent %Nproj, as expected. aSNR was not identical between different gating schemes for given %Nproj. While aSNR was approximately linear with %Nprojfor each algorithm, MDD performance diverged between functions as %Nprojdecreased. Algorithm performance was relatively consistent between subjects, except in images with high noise.Conclusion. The algorithm selection for soft-gating has a notable effect on image quality of respiratory-gated MRI; the timing of included data across the respiratory phase, and not simply the amount of data, plays an important role in aSNR. The specific soft-gating function and parameters should be considered for a given imaging application\'s requirements of signal and sharpness.
摘要:
背景:胸腹MRI受到呼吸运动的限制,尤其是不能屏气的新生儿。为了减少运动模糊,可以从特定呼吸阶段采集的数据重建径向采集的MRI(“硬门控”),但这会降低图像SNR。已经提出了各种“软门控”重建方案,这些方案将在感兴趣的时期之外获取的数据合并到权重减小的重建中。然而,软门控加权算法和参数的选择,以及对图像信噪比和运动模糊的影响,以前没有被探索过。
方法:本研究的目的是绘制可变数据包含和加权如何影响新生儿放射状肺MRI的呼吸门控重建中的SNR和运动模糊,使用现有的和新颖的软门控加权函数。使用1.5T新生儿大小的扫描仪和3D径向超短回波时间(UTE)序列对来自新生儿重症监护病房的十名患有呼吸异常的新生儿受试者进行了成像。回顾性呼吸门控UTE-MRI的表观SNR和运动模糊在使用非门控重建的图像之间进行比较。硬门,以及几种软门控加权算法和参数(使用指数,乙状结肠,反向,和感兴趣期之外的线性加权衰减)。通过光圈处的图像强度的最大导数(MDD)来测量运动模糊。
结果:软门控函数产生比使用相等数量的投影(%Nproj)的硬门控图像更高的aSNR,但MDD较低。虽然每个算法的aSNR与%Nproj近似成线性关系,随着%Nproj的降低,MDD性能在函数之间出现差异。算法性能在受试者之间相对一致,除了在高噪声的图像中,功能性能不同的地方。
结论:欠采样的时间模式对图像质量有显着影响;对于相同的%Nproj,包含数据的更宽的时间分布产生更高的aSNR,较窄的时间分布会增加MDD。因此,欠采样方案的定时策略可以根据所需的应用在aSNR和MDD之间的折衷进行优化。
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