Nowinski Wieslaw L, Gomolka Ryszard S, Qian Guoyu, Gupta Varsha, Ullman Natalie L, Hanley Daniel F
Biomedical Imaging Lab, Agency for Science Technology and Research; Singapore -
Biomedical Imaging Lab, Agency for Science Technology and Research; Singapore.
Neuroradiol J. 2014 Jun;27(3):299-315. doi: 10.15274/NRJ-2014-10042. Epub 2014 Jun 17.
Characterization of hematomas is essential in scan reading, manual delineation, and designing automatic segmentation algorithms. Our purpose is to characterize the distribution of intraventricular (IVH) and intracerebral hematomas (ICH) in NCCT scans, study their relationship to gray matter (GM), and to introduce a new tool for quantitative hematoma delineation. We used 289 serial retrospective scans of 51 patients. Hematomas were manually delineated in a two-stage process. Hematoma contours generated in the first stage were quantified and enhanced in the second stage. Delineation was based on new quantitative rules and hematoma profiling, and assisted by a dedicated tool superimposing quantitative information on scans with 3D hematoma display. The tool provides: density maps (40-85HU), contrast maps (8/15HU), mean horizontal/vertical contrasts for hematoma contours, and hematoma contours below a specified mean contrast (8HU). White matter (WM) and GM were segmented automatically. IVH/ICH on serial NCCT is characterized by 59.0HU mean, 60.0HU median, 11.6HU standard deviation, 23.9HU mean contrast, -0.99HU/day slope, and -0.24 skewness (changing over time from negative to positive). Its 0.1(st)-99.9(th) percentile range corresponds to 25-88HU range. WM and GM are highly correlated (R (2)=0.88; p<10(-10)) whereas the GM-GS correlation is weak (R (2)=0.14; p<10(-10)). The intersection point of mean GM-hematoma density distributions is at 55.6±5.8HU with the corresponding GM/hematoma percentiles of 88(th)/40(th). Objective characterization of IVH/ICH and stating the rules quantitatively will aid raters to delineate hematomas more robustly and facilitate designing algorithms for automatic hematoma segmentation. Our two-stage process is general and potentially applicable to delineate other pathologies on various modalities more robustly and quantitatively.
血肿的特征描述在扫描解读、手动勾勒以及设计自动分割算法中至关重要。我们的目的是在非增强计算机断层扫描(NCCT)中描述脑室内血肿(IVH)和脑内血肿(ICH)的分布,研究它们与灰质(GM)的关系,并引入一种用于血肿定量勾勒的新工具。我们使用了51例患者的289次连续回顾性扫描。血肿通过两阶段过程进行手动勾勒。在第一阶段生成的血肿轮廓在第二阶段进行量化和增强。勾勒基于新的定量规则和血肿轮廓分析,并借助一个专用工具将定量信息叠加在具有三维血肿显示的扫描图像上。该工具提供:密度图(40 - 85HU)、对比度图(8/15HU)、血肿轮廓的平均水平/垂直对比度,以及低于指定平均对比度(8HU)的血肿轮廓。白质(WM)和灰质自动分割。连续NCCT上的IVH/ICH的特征为平均59.0HU、中位数60.0HU、标准差为11.6HU、平均对比度为23.9HU、斜率为 - 0.99HU/天以及偏度为 - 0.24(随时间从负变为正)。其第0.1百分位数至第99.9百分位数范围对应于25 - 88HU范围。WM和GM高度相关(R² = 0.88;p < 10⁻¹⁰),而GM - GS相关性较弱(R² = 0.14;p < 10⁻¹⁰)。平均GM - 血肿密度分布的交点为55.6±5.8HU,相应的GM/血肿百分位数为第88/40百分位数。IVH/ICH的客观特征描述以及定量说明规则将有助于评估者更稳健地勾勒血肿,并便于设计自动血肿分割算法。我们的两阶段过程具有通用性,可能适用于更稳健、定量地勾勒各种模态下的其他病变。