Linear quantification correction for myocardial perfusion imaging from x-ray coronary angiography

Jingwu Yao, T. Sakaguchi, O. Yousuf, J. Trost, J. Lima, T. Ichihara, R. George
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引用次数: 4

Abstract

Myocardial perfusion imaging from x-ray coronary angiography is important with clinical benefits because online real-time assessment of myocardial blood flow can promote the clinical outcomes of interventional treatments for coronary artery disease. In this paper, we aim at the nonlinearity problem of contrast image measurements for the perfusion estimation, since x-ray nonlinear responses of iodinated contrast agent is always an important concern when lacking of x-ray depth information on 2D angiography. A new approach is developed to perform linear quantification correction to angiographic measurements in terms of iodine concentration for estimated body thickness. We recognize the causes of nonlinear measurements from three different sources, that is, image processing artifacts of background subtraction, x-ray physics causes of beam hardening, photon scattering and detector glare if image intensifier applied, as well as clinical application issue of residual contrast agents in myocardium during cardiac catheterization heart procedure. Correspondingly, the developed approach involves three countermeasures to handle the three nonlinear sources. In order to compensate the registration artifacts of background subtraction, the technique of layer image processing is applied to compensate the different cardiac and breathing motions. A prior phantom-based calibration is implemented to make a lookup table of correction models. A polynomial model selected from the table is used online to correct the nonlinear measurements due to x-ray physics causes. For the effect of residual contrast agent, a new workflow of triple background subtractions is proposed by introducing an initial background image. Finally, the proposed approach is validated with pre-clinical studies of porcine models.
x线冠状动脉造影心肌灌注成像的线性定量校正
x线冠状动脉造影的心肌灌注成像具有重要的临床价值,因为在线实时评估心肌血流可以提高冠状动脉疾病介入治疗的临床效果。在本文中,我们针对灌注估计的对比图像测量的非线性问题,因为在缺乏x射线深度信息的二维血管造影中,碘造影剂的x射线非线性响应一直是一个重要的问题。开发了一种新的方法来执行线性定量校正血管造影测量的碘浓度估计体厚。我们从三个不同的来源认识到非线性测量的原因,即图像处理伪影的背景减除,x射线物理原因的光束硬化,光子散射和探测器眩光如果图像增强器的应用,以及临床应用问题的对比剂残留在心导管心脏手术期间的心肌。相应地,所开发的方法涉及三种对策来处理三种非线性源。为了补偿背景减法的配准伪影,采用分层图像处理技术对不同的心脏和呼吸运动进行补偿。实现了基于先验幻象的校准以生成校正模型的查找表。利用从表中选择的多项式模型在线修正由于x射线物理原因引起的非线性测量。针对残余造影剂的影响,提出了一种引入初始背景图像的三重背景减影新流程。最后,通过猪模型的临床前研究验证了所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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