An image registration framework to estimate 3D myocardial strains from cine cardiac MRI in mice.

Maziyar Keshavarzian, Elizabeth Fugate, Saurabh Chavan, Vy Chu, Mohammed Arif, Diana Lindquist, Sakthivel Sadayappan, Reza Avazmohammadi
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引用次数: 4

Abstract

Accurate and efficient quantification of cardiac motion offers promising biomarkers for non-invasive diagnosis and prognosis of structural heart diseases. Cine cardiac magnetic resonance imaging remains one of the most advanced imaging tools to provide image acquisitions needed to assess and quantify in-vivo heart kinematics. The majority of cardiac motion studies are focused on human data, and there remains a need to develop and implement an image-registration pipeline to quantify full three-dimensional (3D) cardiac motion in mice where ideal image acquisition is challenged by the subject size and heart rate and the possibility of traditional tagged imaging is hampered. In this study, we used diffeomorphic image registration to estimate strains in the left ventricular wall in two wild-type mice and one diabetic mouse. Our pipeline resulted in a continuous and fully 3D strain map over one cardiac cycle. The estimation of 3D regional and transmural variations of strains is a critical step towards identifying mechanistic biomarkers for improved diagnosis and phenotyping of structural left heart diseases including heart failure with reduced or preserved ejection fraction.

用图像配准框架估计小鼠电影心脏MRI的三维心肌株。
准确、有效地量化心脏运动为结构性心脏病的无创诊断和预后提供了有前途的生物标志物。心脏磁共振成像仍然是最先进的成像工具之一,可以提供评估和量化体内心脏运动学所需的图像采集。大多数心脏运动研究都集中在人类数据上,仍然需要开发和实施图像配准管道来量化小鼠的全三维(3D)心脏运动,其中理想的图像采集受到受试者尺寸和心率的挑战,传统标记成像的可能性受到阻碍。在这项研究中,我们使用差分图像配准来估计两只野生型小鼠和一只糖尿病小鼠左心室壁的菌株。我们的管道在一个心脏周期内产生了连续的全3D应变图。估计菌株的3D区域和跨壁变化是确定机械生物标志物的关键一步,用于改善结构性左心疾病(包括射血分数降低或保留的心力衰竭)的诊断和表型。
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