Yang Zi, Ren Lei, Yin Fang-Fang, Liang Xiao, Cai Jing
Medical Physics Graduate Program, Duke University, Durham, NC, USA.
Department of Radiadan Oncology, Duke University Medical Center, Durham, NC, USA.
Radiat Med Prot. 2020 Mar;1(1):41-47. doi: 10.1016/j.radmp.2020.01.003. Epub 2020 Mar 10.
Motion artifacts induced by breathing variations are common in 4D-MRI images. This study aims to reduce the motion artifacts by developing a novel, robust 4D-MRI sorting method based on anatomic feature matching and applicable in both cine and sequential acquisition.
The proposed method uses the diaphragm as the anatomic feature to guide the sorting of 4D-MRI images. Initially, both abdominal 2D sagittal cine MRI images and axial MRI images were acquired. The sagittal cine MRI images were divided into 10 phases as ground truth. Next, the phase of each axial MRI image is determined by matching its diaphragm position in the intersection plane to the ground truth cine MRI. Then, those matched phases axial images were sorted into 10-phase bins which were identical to the ground truth cine images. Finally, 10-phase 4D-MRI were reconstructed from these sorted axial images. The accuracy of reconstructed 4D-MRI data was evaluated by comparing with the ground truth using the 4D extended Cardiac Torso (XCAT) digital phantom. The effects of breathing signal, including both regular (cosine function) and irregular (patient data) in both axial cine and sequential scanning modes, on reconstruction accuracy were investigated by calculating total relative error (TRE) of the 4D volumes, Volume-Percent-Difference (VPD) and Center-of-Mass-Shift (COMS) of the estimated tumor volume, compared with the ground truth XCAT images.
In both scanning modes, reconstructed 4D-MRI images matched well with ground truth with minimal motion artifacts. The averaged TRE of the 4D volume, VPD and COMS of the EOE phase in both scanning modes are 0.32%/1.20%/±0.05 mm for regular breathing, and 1.13%/4.26%/±0.21 mm for patient irregular breathing.
The preliminary evaluation results illustrated the feasibility of the robust 4D-MRI sorting method based on anatomic feature matching. This method provides improved image quality with reduced motion artifacts for both cine and sequential scanning modes.
呼吸变化引起的运动伪影在4D-MRI图像中很常见。本研究旨在通过开发一种基于解剖特征匹配的新型、稳健的4D-MRI排序方法来减少运动伪影,该方法适用于电影成像和序列采集。
所提出的方法使用膈肌作为解剖特征来指导4D-MRI图像的排序。首先,采集腹部二维矢状位电影MRI图像和轴位MRI图像。矢状位电影MRI图像被划分为10个相位作为真值。接下来,通过将每个轴位MRI图像在相交平面中的膈肌位置与真值电影MRI进行匹配来确定其相位。然后,将那些匹配相位的轴位图像分类到与真值电影图像相同的10个相位区间中。最后,从这些分类后的轴位图像重建10相位的4D-MRI。使用4D扩展心脏躯干(XCAT)数字体模与真值进行比较,评估重建的4D-MRI数据的准确性。通过计算4D体积的总相对误差(TRE)、估计肿瘤体积的体积百分比差异(VPD)和质心偏移(COMS),与真值XCAT图像相比,研究了呼吸信号(包括轴位电影成像和序列扫描模式下的规则(余弦函数)和不规则(患者数据)信号)对重建准确性的影响。
在两种扫描模式下,重建的4D-MRI图像与真值匹配良好,运动伪影最小。两种扫描模式下EOE期4D体积的平均TRE、VPD和COMS,规则呼吸时分别为0.32%/1.20%/±0.05 mm,患者不规则呼吸时分别为1.13%/4.26%/±0.21 mm。
初步评估结果表明基于解剖特征匹配的稳健4D-MRI排序方法是可行的。该方法在电影成像和序列扫描模式下均能提供更高的图像质量,减少运动伪影。