Slomka Piotr J, Nishina Hidetaka, Berman Daniel S, Kang Xingping, Friedman John D, Hayes Sean W, Aladl Usaf E, Germano Guido
Department of Imaging, Cedars-Sinai Medical Center, A047 8700 Beverly Boulevard, Los Angeles, CA 90048, USA.
J Nucl Med. 2004 Feb;45(2):183-91.
In myocardial perfusion SPECT (MPS), ischemia is typically quantified as the difference between stress and rest defect sizes obtained by separate comparisons with stress and rest normal limits. Such an approach is not optimal because images are not compared directly with each other and a complex set of stress and rest normal limits is required.
We developed a fully automatic technique to quantify stress-rest change. We applied it to 204 patients whose SPECT images were acquired using a same-day dual-isotope (99m)Tc/(201)Tl protocol and on whom coronary angiography had been performed. A 10-parameter registration of rest and stress images was performed by an iterative search of best translational, rotational, scaling, and optimal stress-rest count normalization parameters. Identical stress-rest 3-dimensional left ventricle (LV) contours were automatically derived from stress images. Integrated deficit counts (normalized rest-stress) within the LV volume were derived from registered image pairs. A global measure of ischemia (ISCH) was calculated as the ratio of the total deficit stress LV counts to the total rest LV counts.
Registration and derivation of quantitative measures were fully automatic. The average processing time was <40 s on a 2-GHz processor. When compared for prediction of stenosis, the area under the receiver operating characteristic curve (0.88 +/- 0.03) was significantly better for ISCH than that obtained by existing quantitative approaches, which use reference databases (0.80-0.82 +/- 0.03). The normalized stress-rest change could be visualized and localized directly on raw patient images using overlay display.
Automatic stress-rest MPS image registration allows a direct estimation of ischemia from SPECT that does not require comparisons with normal limits.
在心肌灌注单光子发射计算机断层扫描(MPS)中,缺血通常通过分别与静息和负荷正常范围比较得出的负荷和静息缺损大小的差异来量化。这种方法并非最优,因为图像并非直接相互比较,而且需要一组复杂的负荷和静息正常范围。
我们开发了一种全自动技术来量化负荷 - 静息变化。我们将其应用于204例患者,这些患者使用同日双同位素(99m)Tc/(201)Tl方案进行了SPECT图像采集,并已接受冠状动脉造影。通过对最佳平移、旋转、缩放和最佳负荷 - 静息计数归一化参数的迭代搜索,对静息和负荷图像进行10参数配准。从负荷图像中自动得出相同的负荷 - 静息三维左心室(LV)轮廓。LV容积内的综合缺损计数(归一化静息 - 负荷)从配准的图像对中得出。缺血的总体测量值(ISCH)计算为负荷时LV总计数缺损与静息时LV总计数的比值。
定量测量的配准和推导是完全自动的。在2GHz处理器上,平均处理时间<40秒。在预测狭窄方面进行比较时,ISCH的受试者操作特征曲线下面积(0.88±0.03)明显优于使用参考数据库的现有定量方法(0.80 - 0.82±0.03)。使用叠加显示可以直接在原始患者图像上可视化和定位归一化的负荷 - 静息变化。
自动负荷 - 静息MPS图像配准允许从SPECT直接估计缺血,而无需与正常范围进行比较。