Ortuño Juan E, Vegas-Sánchez-Ferrero Gonzalo, Gómez-Valverde Juan J, Chen Marcus Y, Santos Andrés, McVeigh Elliot R, Ledesma-Carbayo María J
Biomedical Research Networking Centre on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain; Biomedical Image Technologies Lab, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain.
Applied Chest Imaging Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States; Biomedical Image Technologies Lab, ETSI Telecomunicación, Universidad Politécnica de Madrid, Madrid, Spain; Biomedical Research Networking Centre on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.
Med Image Anal. 2020 Oct;65:101748. doi: 10.1016/j.media.2020.101748. Epub 2020 Jun 6.
The location of the mitral and aortic valves in dynamic cardiac imaging is useful for extracting functional derived parameters such as ejection fraction, valve excursions, and global longitudinal strain, and when performing anatomical structures tracking using slice following or valve intervention's planning. Completely automatic segmentation methods are still challenging tasks because of their fast movements and the different positions that prevent good visibility of the leaflets along the full cardiac cycle. In this article, we propose a processing pipeline to track the displacement of the aortic and mitral valve annuli from high-resolution cardiac four-dimensional computed tomographic angiography (4D-CTA). The proposed method is based on the dynamic separation of left ventricle, left atrium and aorta using statistical shape modeling and an energy minimization algorithm based on graph-cuts and has been evaluated on a set of 15 electrocardiography-gated 4D-CTAs. We report a mean agreement distance between manual annotations and our proposed method of 2.52±1.06 mm for the mitral annulus and 2.00±0.69 mm for the aortic valve annulus based on valve locations detected from manual anatomical landmarks. In addition, we show the effect of detecting the valvular planes on derived functional parameters (ejection fraction, global longitudinal strain, and excursions of the mitral and aortic valves).
在动态心脏成像中,二尖瓣和主动脉瓣的位置对于提取诸如射血分数、瓣膜偏移和整体纵向应变等功能衍生参数很有用,并且在使用切片跟踪进行解剖结构追踪或进行瓣膜干预规划时也很有用。由于心脏快速运动以及不同位置会妨碍在整个心动周期中清晰看到瓣叶,因此完全自动分割方法仍然是具有挑战性的任务。在本文中,我们提出了一种处理流程,用于从高分辨率心脏四维计算机断层血管造影(4D-CTA)中跟踪主动脉瓣和二尖瓣环的位移。所提出的方法基于使用统计形状建模对左心室、左心房和主动脉进行动态分离,以及基于图割的能量最小化算法,并已在一组15例心电图门控的4D-CTA上进行了评估。基于从手动解剖标志检测到的瓣膜位置,我们报告二尖瓣环的手动标注与我们提出的方法之间的平均一致性距离为2.52±1.06毫米,主动脉瓣环为2.00±0.69毫米。此外,我们展示了检测瓣膜平面对衍生功能参数(射血分数、整体纵向应变以及二尖瓣和主动脉瓣的偏移)的影响。