Automated registration of sequential breath-hold dynamic contrast-enhanced MR images: a comparison of three techniques.
Automated registration of sequential breath-hold dynamic contrast-enhanced MR images: a comparison of three techniques.
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DOI：
10.1016/j.mri.2011.02.012
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发表时间：
2011-06
影响因子：
2.5
通讯作者：
Raghunand, Natarajan
中科院分区：
文献类型：
--
作者：
Rajaraman, Sivaramakrishnan;Rodriguez, Jeffrey J.;Graff, Christian;Altbach, Maria I.;Dragovich, Tomislav;Sirlin, Claude B.;Korn, Ronald L.;Raghunand, Natarajan
关键词：
动态对比增强MRI （DCE-MRI）越来越多地被用作癌症临床研究反应的研究性生物标志物。对不同时间点获得的图像进行适当的配准，对于从这些数据的定量药代动力学分析中获得诊断信息至关重要。由于对比度增强而存在时变强度的运动伪影使该配准问题具有挑战性。胸部和腹部病变的DCE-MRI通常在连续屏气期间进行，由于隔膜位置不一致而导致误配，并且也限制了-à-vis自由呼吸的时间分辨率。在这项工作中，我们使用计算机生成的DCE-MRI幻影来比较两种已发表的方法的性能，渐进式主成分配准和药代动力学模型驱动配准，使用已发表的通用弹性配准算法，顺序弹性配准（SER）来配准相邻的时间样本图像。在这三种方法中，采用一种具有互信息相似度度量的三维刚体配准方案作为预处理步骤。DCE-MRI幻影图像在数学上变形以模拟错配，并使用3种方案进行校正。所有3种方案在登记大感兴趣区域（roi）（如肌肉、肝脏和脾脏）方面都相当成功。SER在保留肿瘤体积和形状以及记录较小但重要的roi（如肿瘤核心和肿瘤边缘）方面具有优势。本文还介绍了SER在临床DCE-MRI数据集上的表现。
Dynamic Contrast-Enhanced MRI (DCE-MRI) is increasingly in use as an investigational biomarker of response in cancer clinical studies. Proper registration of images acquired at different time-points is essential for deriving diagnostic information from quantitative pharmacokinetic analysis of these data. Motion artifacts in the presence of time-varying intensity due to contrast-enhancement make this registration problem challenging. DCE-MRI of chest and abdominal lesions is typically performed during sequential breath-holds, which introduces misregistration due to inconsistent diaphragm positions, and also places constraints on temporal resolution vis-à-vis free-breathing. In this work, we have employed a computer-generated DCE-MRI phantom to compare the performance of two published methods, Progressive Principal Component Registration and Pharmacokinetic Model-Driven Registration, with Sequential Elastic Registration (SER) to register adjacent time-sample images using a published general-purpose elastic registration algorithm. In all 3 methods, a 3-D rigid-body registration scheme with a mutual information similarity measure was used as a pre-processing step. The DCE-MRI phantom images were mathematically deformed to simulate misregistration which was corrected using the 3 schemes. All 3 schemes were comparably successful in registering large regions of interest (ROIs) such as muscle, liver, and spleen. SER was superior in retaining tumor volume and shape, and in registering smaller but important ROIs such as tumor core and tumor rim. The performance of SER on clinical DCE-MRI datasets is also presented.
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影响因子：
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作者：
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