Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands.
AJNR Am J Neuroradiol. 2013 Aug;34(8):1522-7. doi: 10.3174/ajnr.A3463. Epub 2013 Mar 7.
Cerebral infarct volume as observed in follow-up CT is an important radiologic outcome measure of the effectiveness of treatment of patients with acute ischemic stroke. However, manual measurement of CIV is time-consuming and operator-dependent. The purpose of this study was to develop and evaluate a robust automated measurement of the CIV.
The CIV in early follow-up CT images of 34 consecutive patients with acute ischemic stroke was segmented with an automated intensity-based region-growing algorithm, which includes partial volume effect correction near the skull, midline determination, and ventricle and hemorrhage exclusion. Two observers manually delineated the CIV. Interobserver variability of the manual assessments and the accuracy of the automated method were evaluated by using the Pearson correlation, Bland-Altman analysis, and Dice coefficients. The accuracy was defined as the correlation with the manual assessment as a reference standard.
The Pearson correlation for the automated method compared with the reference standard was similar to the manual correlation (R = 0.98). The accuracy of the automated method was excellent with a mean difference of 0.5 mL with limits of agreement of -38.0-39.1 mL, which were more consistent than the interobserver variability of the 2 observers (-40.9-44.1 mL). However, the Dice coefficients were higher for the manual delineation.
The automated method showed a strong correlation and accuracy with the manual reference measurement. This approach has the potential to become the standard in assessing the infarct volume as a secondary outcome measure for evaluating the effectiveness of treatment.
在随访 CT 中观察到的脑梗死体积是评估急性缺血性脑卒中患者治疗效果的重要影像学结局指标。然而,手动测量 CIV 既耗时又依赖操作者。本研究旨在开发和评估一种强大的 CIV 自动测量方法。
使用基于强度的自动区域生长算法对 34 例连续急性缺血性脑卒中患者的早期随访 CT 图像中的 CIV 进行分割,该算法包括颅骨附近的部分容积效应校正、中线确定以及排除脑室和出血。两名观察者手动勾画 CIV。通过 Pearson 相关分析、Bland-Altman 分析和 Dice 系数评估手动评估的观察者间变异性和自动方法的准确性。准确性定义为与手动评估的相关性作为参考标准。
与参考标准相比,自动方法与手动方法的 Pearson 相关性相似(R = 0.98)。自动方法的准确性极好,平均差异为 0.5 mL,一致性界限为-38.0-39.1 mL,与 2 名观察者的观察者间变异性(-40.9-44.1 mL)相比更一致。然而,手动勾画的 Dice 系数更高。
自动方法与手动参考测量具有很强的相关性和准确性。这种方法有可能成为评估梗死体积的标准,作为评估治疗效果的次要结局指标。