Virtual 3D reconstruction of complex congenital cardiac anatomy from 3D rotational angiography.

IF 3.2 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Ernesto Mejia, Shannon Sweeney, Jenny E Zablah
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引用次数: 0

Abstract

Background: Despite advancements in imaging technologies, including CT scans and MRI, these modalities may still fail to capture intricate details of congenital heart defects accurately. Virtual 3D models have revolutionized the field of pediatric interventional cardiology by providing clinicians with tangible representations of complex anatomical structures. We examined the feasibility and accuracy of utilizing an automated, Artificial Intelligence (AI) driven, cloud-based platform for virtual 3D visualization of complex congenital heart disease obtained from 3D rotational angiography DICOM images.

Methods: Five patients selected at random with 3DRA performed in the pediatric cardiac catheterization suite were selected. 3DRA's were performed following published institutional protocols and segmentations performed by primary operators. The 3DRA DICOM images were anonymized as per protocol and exported. Images when then processed by Axial3D Artificial Intelligence (AI) driven cloud-based platform for virtual segmentation. Two separate expert operators were selected to subjectively analyze the segmentations and compare them to the operator reconstructions for anatomic accuracy.

Results: Comparing results with local reconstructions by expert operators, five different patient anatomies were analyzed, showcasing Axial3D's ability to produce highly detailed reconstructions with improved visual appeal, including color-coded segments for implanted materials like stents. The reconstructions exhibited superior segmentation of different intrathoracic structures when compared to local models, offering valuable insights for medical professionals and patients.

Conclusions: The use of the AI driven, cloud-based platform for 3D visualization of complex congenital heart lesions presents a promising advancement in pediatric interventional cardiology, facilitating enhanced patient care, procedural planning, and educational opportunities for trainees and patients alike.

从三维旋转血管造影虚拟三维重建复杂的先天性心脏解剖结构。
背景:尽管包括CT扫描和MRI在内的成像技术取得了进步,但这些方式可能仍然无法准确地捕捉先天性心脏缺陷的复杂细节。虚拟3D模型通过为临床医生提供复杂解剖结构的有形表示,彻底改变了儿科介入心脏病学领域。我们研究了利用自动化的、人工智能(AI)驱动的、基于云的平台对复杂先天性心脏病进行虚拟3D可视化的可行性和准确性,该虚拟3D可视化是由3D旋转血管造影DICOM图像获得的。方法:随机选择5例在小儿心导管室行3DRA的患者。3DRA是根据公布的机构协议和主要运营商进行的分段进行的。3DRA DICOM图像按照协议匿名化并导出。图像处理后,由Axial3D人工智能(AI)驱动的云平台进行虚拟分割。选择两个独立的专家算子对分割结果进行主观分析,并将其与算子重建的解剖精度进行比较。结果:将结果与专家操作员的局部重建结果进行比较,分析了五种不同的患者解剖结构,展示了Axial3D能够产生高度详细的重建,并具有更好的视觉吸引力,包括用于植入材料(如支架)的彩色编码段。与局部模型相比,重建模型对不同胸内结构的分割效果更好,为医疗专业人员和患者提供了宝贵的见解。结论:使用人工智能驱动的云平台对复杂的先天性心脏病病变进行三维可视化,在儿科介入心脏病学中是一个有希望的进步,有助于加强患者护理,程序规划,并为学员和患者提供教育机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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