Department of Brain and Cognitive Engi-neering, Korea University, Seoul, South Korea.
Department of Radiology, Se-oul National University Hospital, College of Medicine, Seoul, South Korea.
Neurosurgery. 2018 Aug 1;83(2):226-236. doi: 10.1093/neuros/nyx379.
Intracerebral hemorrhage (ICH) is one of the most devastating subtypes of stroke. A rapid assessment of ICH severity involves the use of computed tomography (CT) and derivation of the hemorrhage volume, which is often estimated using the ABC/2 method. However, these estimates are highly inaccurate and may not be feasible for anticipating outcome favorability.
To predict patient outcomes via a quantitative, densitometric analysis of CT images, and to compare the predictive power of these densitometric parameters with the conventional ABC/2 volumetric parameter and segmented hemorrhage volumes.
Noncontrast CT images of 87 adult patients with ICH (favorable outcomes = 69, unfavorable outcomes = 12, and deceased = 6) were analyzed. In-house software was used to calculate the segmented hemorrhage volumes, ABC/2 and densitometric parameters, including the skewness and kurtosis of the density distribution, interquartile ranges, and proportions of specific pixels in sets of CT images. Nonparametric statistical analyses were conducted.
The densitometric parameter interquartile range exhibited greatest accuracy (82.7%) in predicting favorable outcomes. The combination of skewness and the interquartile range effectively predicted mortality (accuracy = 83.3%). The actual volume of the ICH exhibited good coherence with ABC/2 (R = 0.79). Both parameters predicted mortality with moderate accuracy (<78%) but were less effective in predicting unfavorable outcomes.
Hemorrhage volume was rapidly estimated and effectively predicted mortality in patients with ICH; however, this value may not be useful for predicting favorable outcomes. The densitometric analysis exhibited significantly higher power in predicting mortality and favorable outcomes in patients with ICH.
脑出血（ICH）是中风最具破坏性的亚型之一。ICH 严重程度的快速评估涉及到 CT 扫描的使用和出血量的计算，通常使用 ABC/2 方法进行估算。然而，这些估算的准确性较差，可能无法准确预测预后。
通过对 CT 图像进行定量、密度分析来预测患者的预后，并比较这些密度参数与传统的 ABC/2 体积参数和分割的血肿体积对预后的预测能力。
对 87 例成人 ICH 患者（预后良好=69 例，预后不良=12 例，死亡=6 例）的非增强 CT 图像进行分析。使用内部软件计算分割血肿体积、ABC/2 和密度参数，包括密度分布的偏度和峰度、四分位距和特定 CT 图像中像素的比例。进行了非参数统计分析。
密度参数四分位距在预测预后良好方面具有最高的准确性（82.7%）。偏度和四分位距的组合可以有效地预测死亡率（准确性=83.3%）。ICH 的实际体积与 ABC/2 具有很好的一致性（R=0.79）。这两个参数都能以中等准确性（<78%）预测死亡率，但在预测预后不良方面效果较差。
ICH 患者的出血量可以快速估算，并有效地预测死亡率；然而，该值可能对预测预后不良结果没有帮助。密度分析在预测 ICH 患者的死亡率和预后方面具有显著更高的能力。
