Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:1702-1706. doi: 10.1109/EMBC48229.2022.9871327.
Cardiac magnetic resonance (CMR) imaging is the one of the gold standard imaging modalities for the diagnosis and characterization of cardiovascular diseases. The clinical cine protocol of the CMR typically generates high-resolution 2D images of heart tissues in a finite number of separated and independent 2D planes, which are appropriate for the 3D reconstruction of biventricular heart surfaces. However, they are usually inadequate for the whole-heart reconstruction, specifically for both atria. In this regard, the paper presents a novel approach for automated patient-specific 3D whole-heart mesh reconstruction from limited number of 2D cine CMR slices with the help of a statistical shape model (SSM). After extracting the heart contours from 2D cine slices, the SSM is first optimally fitted over the sparse heart contours in 3D space to provide the initial representation of the 3D whole-heart mesh, which is further deformed to minimize the distance from the heart contours for generating the final reconstructed mesh. The reconstruction performance of the proposed approach is evaluated on a cohort of 30 subjects randomly selected from the UK Biobank study, demonstrating the generation of high-quality 3D whole-heart meshes with average contours to surface distance less than the underlying image resolution and the clinical metrics within acceptable ranges reported in previous literature. Clinical Relevance- Automated patient-specific 3D whole-heart mesh reconstruction has numerous applications in car-diac diagnosis and multimodal visualization, including treatment planning, virtual surgery, and biomedical simulations.
心脏磁共振(CMR)成像是诊断和表征心血管疾病的金标准成像方式之一。CMR 的临床电影协议通常会在有限数量的分离且独立的 2D 平面中生成心脏组织的高分辨率 2D 图像,这些图像适用于双心室心脏表面的 3D 重建。然而,它们通常不足以进行全心重建,特别是对于两个心房。在这方面,本文提出了一种从有限数量的二维电影 CMR 切片中自动重建患者特定的三维全心网格的新方法,该方法借助统计形状模型(SSM)来实现。从二维电影切片中提取心脏轮廓后,首先在 3D 空间中对稀疏的心脏轮廓进行最佳拟合,以提供 3D 全心网格的初始表示,然后进一步变形以最小化与心脏轮廓的距离,从而生成最终的重建网格。该方法的重建性能在从英国生物库研究中随机选择的 30 个受试者队列上进行了评估,结果表明生成了高质量的 3D 全心网格,平均轮廓到表面的距离小于基础图像分辨率,并且临床指标在可接受范围内,与之前文献中的报道一致。临床相关性-自动患者特定的 3D 全心网格重建在心脏诊断和多模态可视化、包括治疗计划、虚拟手术和生物医学模拟等方面具有广泛的应用。