Background phase correction for quantitative cardiovascular MRI

项目总结/摘要 血液动力学的改变与广泛的心脏和血管疾病有关，包括 先天性心脏病、瓣膜异常、主动脉粥样硬化和动脉瘤、肾狭窄、门静脉 肝硬化引起的高血压、颅内动脉瘤和狭窄以及外周动脉疾病。阶段- 对比MRI（PC-MRI）是一种非侵入性成像技术，可以提供全面的 血流动力学的评价，这可以与其他重要的MRI衍生信息相结合， 心血管解剖、功能和组织表征。然而，PC-MRI作为 定量工具受到背景相位引入的不准确性的挑战。研究表明 该背景相位可在流量的量化中引入显著的误差。一种方法， 所提出的量化和校正背景相位的方法是使用静态扫描来执行单独的扫描。 鬼魅尽管该方法是稳健的，但由于需要显著的额外时间来 对所执行的每个临床序列执行体模成像。另一种被广泛报道的纠正方法是 背景相位基于对属于静态组织的像素执行多项式拟合。的 该方法的准确性严重依赖于在邻近的区域中的静态组织的可用性。 兴趣-当对心脏或大血管进行成像时经常不能满足的要求。 为了解决总是影响每个PC-MRI测量的背景相位的问题，我们提出了一个 新的校正方案称为多切片采集和处理（mSAP）。在mSAP中，除了切片 在感兴趣的情况下，使用相同的切片方向和梯度波形收集至少一个额外的切片，但是 不同的桌子位置。通过联合处理来自多个切片的背景相位信息，mSAP 以稍微延长采集时间为代价避免了与现有方法相关的缺点。在 具体目标1，我们将开发一种用于mSAP的数据采集和处理方法。我们将修改和 简化我们当前的PC-MRI采集协议，以最大限度地减少与mSAP相关的开销。共同 处理多切片数据，我们将开发和实现基于广义最小的多项式回归 对多项式的系数施加了1-范数惩罚的平方。这种拟合方法是 完全自动化，不需要调整参数。在具体目标2中，我们将使用以下方法验证mSAP： 脉动流体模和健康志愿者。通过仅使用一个额外的切片，我们预计mSAP 将背景相位误差降低到流量的误计算降低到5%以下的水平。 我们的初步数据证明了mSAP中主要假设的有效性，即，背景 使用相同的梯度波形但不同的工作台位置收集的相位图是相同的。我们 我相信，这项工作中开发的方法可以很容易地用于临床环境，以提高准确性， 一个其他方面都很有效的成像工具。

Project Summary/Abstract Alterations in hemodynamics have been linked to wide-ranging cardiac and vascular conditions, including congenital heart disease, valvular abnormalities, aortic atherosclerosis and aneurysm, renal stenosis, portal hypertension due to liver cirrhosis, intracranial aneurysm and stenosis, and peripheral arterial disease. Phase- contrast MRI (PC-MRI) is a noninvasive imaging technique that can potentially provide a comprehensive evaluation of hemodynamics, which can be coupled with other important MRI-derived information on cardiovascular anatomy, function, and tissue characterization. However, the credibility of PC-MRI as a quantitative tool is challenged by the inaccuracies introduced by background phase. Studies have shown that this background phase can introduce significant errors in the quantification of flow. One method that has been proposed to quantify and correct for the background phase is to perform a separate scan using a static phantom. This method, despite being robust, is impractical because of the significant extra time required to perform phantom imaging for each clinical sequence performed. Another widely reported method to correct background phase is based on performing polynomial fitting to the pixels that belong to the static tissue. The accuracy of this method heavily relies on the availability of static tissue in the close vicinity of the region of interest–a requirement that is often not met when imaging the heart or great vessels. To address the issue of background phase that invariably impacts every PC-MRI measurement, we propose a new correction scheme called multi-slice acquisition and processing (mSAP). In mSAP, in addition to the slice of interest, at least one extra slice is collected using the same slice orientation and gradient waveforms but with a different table position. By jointly processing the background phase information from multiple slices, mSAP circumvents the shortcomings associated with existing methods at the cost of slightly prolonged acquisition. In Specific Aim 1, we will develop a data acquisition and processing method for mSAP. We will modify and streamline our current PC-MRI acquisition protocol to minimize the overhead associated with mSAP. To jointly process the multi-slice data, we will develop and implement polynomial regression based on generalized least squares with an ℓ1-norm penalty imposed on the coefficients of the polynomial. This fitting method is completely automated and does not require tuning parameters. In Specific Aim 2, we will validate mSAP using a pulsatile flow phantom and healthy volunteers. By using just one additional slice, we anticipate mSAP to reduce the background phase errors to the level where miscalculation of flow volume is reduced to below 5%. Our preliminary data demonstrate the validity of the primary assumption made in mSAP, i.e., background phase maps collected using the same gradient waveforms but different table positions are identical. We believe the methods developed in this work can be readily utilized in clinical settings to improve the accuracy of an otherwise potent imaging tool.