Background phase correction for quantitative cardiovascular MRI

项目摘要/摘要 血流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、门脉 由肝硬变、颅内动脉瘤和狭窄以及外周动脉疾病引起的高血压。阶段- 对比磁共振成像(PC-MRI)是一种非侵入性的成像技术，它可能提供全面的 血流动力学的评估，可以结合其他重要的磁共振成像信息 心血管解剖、功能和组织特征。然而，PC-MRI作为一种 背景相位带来的误差对定量工具提出了挑战。研究表明， 这一背景阶段可能会在流量的量化中引入重大误差。有一种方法一直是 建议对背景阶段进行量化和校正是使用静态扫描执行单独的扫描 幻影。这种方法虽然很健壮，但不切实际，因为需要大量额外的时间来 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 背景阶段基于对属于静态组织的像素执行多项式拟合。这个 这种方法的准确性在很大程度上依赖于在邻近脑区的静态组织的可用性。 兴趣--在对心脏或大血管进行成像时，这一要求往往得不到满足。 为了解决总是影响每个PC-MRI测量的背景阶段的问题，我们提出了一种 新的校正方案称为多切片采集和处理(MSAP)。在mSAP中，除了切片 值得注意的是，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 一个不同的桌子位置。通过联合处理来自多个切片的背景相位信息，mSAP 绕过了与现有方法相关的缺点，但代价是略微延长了获取时间。在……里面 具体目标1，我们将为mSAP开发一种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。联合 对多切片数据进行处理，开发并实现基于广义最小二乘的多项式回归 对多项式的系数施加ℓ1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，我们将使用以下工具验证mSAP 脉动的流动体模和健康的志愿者。通过仅使用一个额外的切片，我们预计mSAP将 将背景相位误差降低到流量误算减少到5%以下的水平。 我们的初步数据证明了mSAP中的主要假设的有效性，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 相信在这项工作中开发的方法可以很容易地在临床环境中使用，以提高 另一种强有力的成像工具。

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.