Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305-5105, USA.
J Digit Imaging. 2011 Dec;24(6):1078-86. doi: 10.1007/s10278-011-9373-2.
Aortoiliac and lower extremity arterial atherosclerotic plaque burden is a risk factor for the development of visceral and peripheral ischemic and aneurismal vascular disease. While prior research allows automated quantification of calcified plaque in these body regions using CT angiograms, no automated method exists to quantify soft plaque. We developed an automatic algorithm that defines the outer wall contour and wall thickness of vessels to quantify non-calcified plaque in CT angiograms of the chest, abdomen, pelvis, and lower extremities. The algorithm encodes the search space as a constrained graph and calculates the outer wall contour by deriving a minimum cost path through the graph, following the visible outer wall contour while minimizing path tortuosity. Our algorithm was statistically equivalent to a reference standard made by two reviewers. Absolute error was 1.9 ± 2.3% compared to the inter-observer variability of 3.9 ± 3.6%. Wall thickness in vessels with atherosclerosis was 3.4 ± 1.6 mm compared to 1.2 ± 0.4 mm in normal vessels. The algorithm shows promise as a tool for quantification of non-calcified plaque in CT angiography. When combined with previous research, our method has the potential to quantify both non-calcified and calcified plaque in all clinically significant systemic arteries, from the thoracic aorta to the arteries of the calf, over a wide range of diameters. This algorithm has the potential to enable risk stratification of patients and facilitate investigations into the relationships between asymptomatic atherosclerosis and a variety of behavioral, physiologic, pathologic, and genotypic conditions.
主动脉髂动脉和下肢动脉粥样硬化斑块负担是内脏和外周缺血性血管疾病及动脉瘤性血管疾病发展的一个风险因素。虽然先前的研究允许使用 CT 血管造影术自动量化这些身体部位的钙化斑块,但目前还没有自动量化软斑块的方法。我们开发了一种自动算法,用于定义血管的外壁轮廓和壁厚,以量化胸部、腹部、骨盆和下肢 CT 血管造影中的非钙化斑块。该算法将搜索空间编码为约束图,并通过在图中找到最小成本路径来计算外壁轮廓,在最小化路径曲折度的同时,遵循可见的外壁轮廓。我们的算法在统计学上与两位审阅者制定的参考标准相当。与观察者间变异性的 3.9±3.6%相比,绝对误差为 1.9±2.3%。动脉粥样硬化血管的壁厚为 3.4±1.6mm,而正常血管的壁厚为 1.2±0.4mm。该算法有望成为 CT 血管造影中非钙化斑块定量的工具。当与先前的研究相结合时,我们的方法有可能量化从胸主动脉到小腿动脉的所有具有临床意义的系统性动脉中的非钙化和钙化斑块,涵盖广泛的直径范围。这种算法有可能使患者的风险分层,并促进对无症状性动脉粥样硬化与各种行为、生理、病理和基因型状况之间的关系的研究。