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Automatic segmentation and quantification of the cardiac structures from non-contrast-enhanced cardiac CT scans

机译:非对比增强心脏CT扫描的心脏结构的自动分割和量化

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Early structural changes to the heart, including the chambers and the coronary arteries, provide important information on pre-clinical heart disease like cardiac failure. Currently, contrast-enhanced cardiac computed tomography angiography (CCTA) is the preferred modality for the visualization of the cardiac chambers and the coronaries. In clinical practice not every patient undergoes a CCTA scan; many patients receive only a non-contrast-enhanced calcium scoring CT scan (CTCS), which has less radiation dose and does not require the administration of contrast agent. Quantifying cardiac structures in such images is challenging, as they lack the contrast present in CCTA scans. Such quantification would however be relevant, as it enables population based studies with only a CTCS scan. The purpose of this work is therefore to investigate the feasibility of automatic segmentation and quantification of cardiac structures viz whole heart, left atrium, left ventricle, right atrium, right ventricle and aortic root from CTCS scans. A fully automatic multi-atlas-based segmentation approach is used to segment the cardiac structures. Results show that the segmentation overlap between the automatic method and that of the reference standard have a Dice similarity coefficient of 0.91 on average for the cardiac chambers. The mean surface-to-surface distance error over all the cardiac structures is $1.4pm 1.7$ mm. The automatically obtained cardiac chamber volumes using the CTCS scans have an excellent correlation when compared to the volumes in corresponding CCTA scans, a Pearson correlation coefficient (R) of 0.95 is obtained. Our fully automatic method enables large-scale assessment of cardiac structures on non-contrast-enhanced CT scans.
机译:内心的早期结构变化,包括腔室和冠状动脉,提供了关于心衰竭等临床前心脏病的重要信息。目前,对比度增强的心脏计算机断层造影血管造影(CCTA)是心室和冠状冠状动脉的可视化的优选方式。在临床实践中,并非每只患者都会经历CCTA扫描;许多患者只接受非对比增强的钙分量CT扫描(CTC),其具有较少的辐射剂量,并且不需要给予造影剂。在这些图像中量化的心脏结构是具有挑战性的,因为它们缺乏CCTA扫描中存在的对比度。然而,这种量化将是相关的,因为它使基于CTCS扫描的人口的研究。因此,本作作品的目的是研究来自CTCS扫描的自动分割和全部心脏结构viz全心全食,左心房,左心室,右心房,右心室和主动脉根系的可行性。基于全自动的基于多纳拉斯的分割方法用于分割心脏结构。结果表明,基准标准的自动方法与参考标准之间的分割重叠的分割与心室平均为0.91的骰子相似系数。所有心脏结构的平均表面到表面距离误差为1.4 PM 1.7 $ mm。与相应的CCTA扫描中的体积相比,使用CTCS扫描的自动获得的心室体积具有出色的相关性,获得0.95的Pearson相关系数(R)。我们全自动方法可以实现对非对比度增强CT扫描上的心脏结构的大规模评估。

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