Department of Clinical Physiology, Skåne University Hospital, Lund University, 221 85 Lund, Sweden.
J Nucl Cardiol. 2010 Oct;17(5):831-40. doi: 10.1007/s12350-010-9237-z. Epub 2010 May 4.
In order to determine myocardial salvage, accurate quantification of myocardium at risk (MaR) is necessary. We present a validated novel automatic segmentation algorithm for quantification of MaR by myocardial perfusion SPECT (MPS) in patients with acute coronary occlusion.
Twenty-nine patients with coronary occlusion were injected with a perfusion tracer before reperfusion, and underwent rest MPS within 4 hours. The MaR was quantified using the proposed algorithm (Segment software), the software Quantitative Perfusion SPECT (QPS) and by manual segmentation. The Segment MaR algorithm used a threshold of 55% of maximal counts and an a priori model based on normal coronary artery perfusion territories. The MaR was 30 ± 10% left ventricular mass (%LVM) by manual segmentation, 31 ± 12%LVM by Segment, and 36 ± 14%LVM by QPS. There was a good agreement between automatic and manual segmentation for both of the algorithms with a lower bias for Segment (.8 ± 4.0%LVM) than for QPS (5.8 ± 5.8%LVM) when compared to manual segmentation.
The Segment MaR algorithm can be used to correctly assess MaR from MPS images in patients with acute coronary occlusion without access to tracer-specific normal database. The MaR in relation to final infarct size enables determination of myocardial salvage.
为了确定心肌挽救程度,需要准确量化存在风险的心肌(MaR)。我们提出了一种经过验证的新型自动分割算法,用于定量分析急性冠状动脉闭塞患者的心肌灌注 SPECT(MPS)中的 MaR。
29 例冠状动脉闭塞患者在再灌注前注射灌注示踪剂,并在 4 小时内进行静息 MPS。MaR 使用所提出的算法(Segment 软件)、定量灌注 SPECT(QPS)软件和手动分割进行量化。Segment MaR 算法使用 55%最大计数的阈值和基于正常冠状动脉灌注区域的先验模型。手动分割的 MaR 为 30±10%左心室质量(%LVM),Segment 为 31±12%LVM,QPS 为 36±14%LVM。两种算法的自动分割与手动分割之间具有良好的一致性,与 QPS(5.8±5.8%LVM)相比,Segment 的偏差更小(.8±4.0%LVM)。
在无法获得示踪剂特异性正常数据库的情况下,Segment MaR 算法可用于正确评估急性冠状动脉闭塞患者的 MPS 图像中的 MaR。MaR 与最终梗死面积的关系可以确定心肌挽救程度。