Rcadia Medical Imaging, 157 Yafo str, 35251, Haifa, Israel.
Int J Comput Assist Radiol Surg. 2012 Nov;7(6):819-27. doi: 10.1007/s11548-012-0684-7. Epub 2012 Apr 7.
Following a recent introduction of computer-aided simple triage (CAST) as a new subclass of computer-aided detection/diagnosis (CAD), we present a CAST software system for a fully automatic initial interpretation of coronary CT angiography (CCTA). We show how the system design and diagnostic performance make it CAST-compliant and suitable for chest pain patient triage in emergency room (ER).
The processing performed by the system consists of three major steps: segmentation of coronary artery tree, labeling of major coronary arteries, and detection of significant stenotic lesions (causing > 50% stenosis). In addition, the system performs an automatic image quality assessment to discards low-quality studies. For multiphase studies, the system automatically chooses the best phase for each coronary artery. Clinical evaluation results were collected in 14 independent trials that included more than 2000 CCTA studies. Automatic diagnosis results were compared with human interpretation of the CCTA and to cath lab results.
The presented system performs a fully automatic initial interpretation of CCTA without any human interaction and detects studies with significant coronary artery disease. The system demonstrated higher than 90% per patient sensitivity and 40-70% per patient specificity. For the chest pain, ER population, the specificity was 60-70%, yielding higher than 98% NPV.
The diagnostic performance of the presented CCTA CAD system meets the CAST requirements, thus enabling efficient, 24/7 utilization of CCTA for chest pain patient triage in ER. This is the first fully operational, clinically validated, CAST-compliant CAD system for a fully automatic analysis of CCTA and detection of significant stenosis.
近期引入计算机辅助简单分诊(CAST)作为计算机辅助检测/诊断(CAD)的新子类,我们提出了一种用于冠状动脉 CT 血管造影(CCTA)全自动初始解读的 CAST 软件系统。我们展示了系统设计和诊断性能如何使其符合 CAST 标准,并适合急诊科胸痛患者分诊。
系统执行的处理过程包括三个主要步骤:冠状动脉树的分割、主要冠状动脉的标记以及明显狭窄病变(导致 >50%狭窄)的检测。此外,该系统还进行自动图像质量评估,以丢弃低质量的研究。对于多期研究,系统会自动为每条冠状动脉选择最佳期相。临床评估结果是在 14 项独立试验中收集的,这些试验包括 2000 多项 CCTA 研究。自动诊断结果与 CCTA 的人工解读和导管实验室结果进行了比较。
所提出的系统无需任何人工交互即可对 CCTA 进行全自动初始解读,并可检测出存在明显冠状动脉疾病的研究。该系统的患者敏感性高于 90%,特异性为 40-70%。对于胸痛急诊人群,特异性为 60-70%,阳性预测值(NPV)高于 98%。
所提出的 CCTA CAD 系统的诊断性能符合 CAST 要求,从而能够在急诊科实现 CCTA 对胸痛患者分诊的高效、24/7 利用。这是首个用于 CCTA 全自动分析和检测明显狭窄的全操作、临床验证、符合 CAST 的 CAD 系统。