Lin Wei, Guo Junyu, Rosen Mark A, Song Hee Kwon
Department of Radiology, University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, USA.
Magn Reson Med. 2008 Nov;60(5):1135-46. doi: 10.1002/mrm.21740.
Dynamic contrast-enhanced (DCE)-MRI is becoming an increasingly important tool for evaluating tumor vascularity and assessing the effectiveness of emerging antiangiogenic and antivascular agents. In chest and abdominal regions, however, respiratory motion can seriously degrade the achievable image quality in DCE-MRI studies. The purpose of this work is to develop a respiratory motion-compensated DCE-MRI technique that combines the self-gating properties of radial imaging with the reconstruction flexibility afforded by the golden-angle view-order strategy. Following radial data acquisition, the signal at k-space center is first used to determine the respiratory cycle, and consecutive views during the expiratory phase of each respiratory period (34-55 views, depending on the breathing rate) are grouped into individual segments. Residual intrasegment translation of lesion is subsequently compensated for by an autofocusing technique that optimizes image entropy, while intersegment translation (among different respiratory cycles) is corrected using 3D image correlation. The resulting motion-compensated, undersampled dynamic image series is then processed to reduce image streaking and to enhance the signal-to-noise ratio (SNR) prior to perfusion analysis, using either the k-space-weighted image contrast (KWIC) radial filtering technique or principal component analysis (PCA). The proposed data acquisition scheme also allows for high frame-rate arterial input function (AIF) sampling and free-breathing baseline T(1) mapping. The performance of the proposed radial DCE-MRI technique is evaluated in subjects with lung and liver lesions, and results demonstrate that excellent pixelwise perfusion maps can be obtained with the proposed methodology.
动态对比增强(DCE)-MRI正成为评估肿瘤血管生成以及新兴抗血管生成和抗血管药物疗效的一种越来越重要的工具。然而,在胸部和腹部区域,呼吸运动会严重降低DCE-MRI研究中可达到的图像质量。本研究的目的是开发一种呼吸运动补偿DCE-MRI技术,该技术将径向成像的自门控特性与黄金角视图排序策略提供的重建灵活性相结合。在径向数据采集之后,首先使用k空间中心的信号来确定呼吸周期,并且将每个呼吸周期呼气阶段的连续视图(34 - 55个视图,取决于呼吸频率)分组为各个段。随后,通过优化图像熵的自动聚焦技术补偿病变在段内的残余平移,而使用三维图像相关性校正段间平移(在不同呼吸周期之间)。然后,在灌注分析之前,使用k空间加权图像对比度(KWIC)径向滤波技术或主成分分析(PCA),对得到的运动补偿、欠采样动态图像序列进行处理,以减少图像条纹并提高信噪比(SNR)。所提出的数据采集方案还允许高帧率动脉输入函数(AIF)采样和自由呼吸基线T(1)映射。在患有肺部和肝脏病变的受试者中评估了所提出的径向DCE-MRI技术的性能,结果表明,使用所提出的方法可以获得出色的逐像素灌注图。