Teruel Jose R, Fjøsne Hans E, Østlie Agnes, Holland Dominic, Dale Anders M, Bathen Tone F, Goa Pål E
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
St. Olavs University Hospital, Trondheim, Norway.
Magn Reson Med. 2015 Oct;74(4):1138-44. doi: 10.1002/mrm.25489. Epub 2014 Oct 16.
To evaluate the performance of an advanced method for correction of inhomogeneous static magnetic field induced distortion in echo-planar imaging (EPI), applied to diffusion-weighted MRI (DWI) of the breast.
An algorithm for distortion correction based on the symmetry of the distortion induced by static field inhomogeneity when the phase encoding polarity is reversed was evaluated in 36 data sets of patients who received an MRI examination that included DWI (b = 0 and 700 s/mm(2) ) and an extra b = 0 s/mm(2) sequence with opposite phase encoding polarity. The decrease of the L2 -square norm after correction between opposed phase encoding b = 0 images was calculated. Mattes mutual information between b = 0 images and fat-suppressed T2 -weighted images was calculated before and after correction.
The L2 -square norm between different phase encoding polarities for b = 0 images was reduced 94.3% on average after distortion correction. Furthermore, Mattes mutual information between b = 0 images and fat-suppressed T2 -weighted images increased significantly after correction for all cases (P < 0.001).
Geometric distortion correction in DWI of the breast results in higher similarity of DWI to anatomical non-EPI T2 -weighted images and would potentially allow for a more reliable lesion segmentation mapping among different MRI modalities.
评估一种先进方法在回波平面成像(EPI)中校正不均匀静磁场诱导失真的性能,该方法应用于乳腺扩散加权磁共振成像(DWI)。
基于相位编码极性反转时静磁场不均匀性引起的失真对称性的失真校正算法,在36例接受包括DWI(b = 0和700 s/mm²)及额外一个具有相反相位编码极性的b = 0 s/mm²序列的MRI检查的患者数据集中进行评估。计算校正后相反相位编码b = 0图像之间L2范数的降低。计算校正前后b = 0图像与脂肪抑制T2加权图像之间的马泰斯互信息。
失真校正后,b = 0图像不同相位编码极性之间的L2范数平均降低了94.3%。此外,校正后所有病例中b = 0图像与脂肪抑制T2加权图像之间的马泰斯互信息均显著增加(P < 0.001)。
乳腺DWI中的几何失真校正使DWI与解剖学非EPI T2加权图像具有更高的相似性,并可能允许在不同MRI模态之间进行更可靠的病变分割映射。