School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4000, Australia; Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia.
School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, Jiangsu, China.
J Biomech. 2024 Sep;174:112269. doi: 10.1016/j.jbiomech.2024.112269. Epub 2024 Aug 7.
Recent studies have suggested that irregular pulsation of intracranial aneurysm during the cardiac cycle may be potentially associated with aneurysm rupture risk. However, there is a lack of quantification method for irregular pulsations. This study aims to quantify irregular pulsations by the displacement and strain distribution of the intracranial aneurysm surface during the cardiac cycle using four-dimensional CT angiographic image data. Four-dimensional CT angiography was performed in 8 patients. The image data of a cardiac cycle was divided into approximately 20 phases, and irregular pulsations were detected in four intracranial aneurysms by visual observation, and then the displacement and strain of the intracranial aneurysm was quantified using coherent point drift and finite element method. The displacement and strain were compared between aneurysms with irregular and normal pulsations in two different ways (total and stepwise). The stepwise first principal strain was significantly higher in aneurysms with irregular than normal pulsations (0.20±0.01 vs 0.16±0.02, p=0.033). It was found that the irregular pulsations in intracranial aneurysms usually occur during the consecutive ascending or descending phase of volume changes during the cardiac cycle. In addition, no statistically significant difference was found in the aneurysm volume changes over the cardiac cycle between the two groups. Our method can successfully quantify the displacement and strain changes in the intracranial aneurysm during the cardiac cycle, which may be proven to be a useful tool to quantify intracranial aneurysm deformability and aid in aneurysm rupture risk assessment.
最近的研究表明,颅内动脉瘤在心动周期中的不规则脉动可能与动脉瘤破裂风险有关。然而,目前缺乏对不规则脉动的量化方法。本研究旨在使用四维 CT 血管造影图像数据,通过颅内动脉瘤表面在心动周期中的位移和应变分布来量化不规则脉动。对 8 例患者进行了四维 CT 血管造影检查。将心动周期的图像数据分为大约 20 个相位,通过视觉观察在四个颅内动脉瘤中检测到不规则脉动,然后使用相干点漂移和有限元方法量化颅内动脉瘤的位移和应变。通过两种方式(总应变和分步应变)比较了具有不规则和正常脉动的动脉瘤之间的位移和应变。具有不规则脉动的动脉瘤的分步第一主应变明显高于具有正常脉动的动脉瘤(0.20±0.01 比 0.16±0.02,p=0.033)。结果发现,颅内动脉瘤中的不规则脉动通常发生在心动周期中容积变化的连续上升或下降阶段。此外,两组之间动脉瘤在心动周期中的体积变化没有统计学差异。我们的方法可以成功地量化颅内动脉瘤在心动周期中的位移和应变变化,这可能被证明是量化颅内动脉瘤可变形性和辅助动脉瘤破裂风险评估的有用工具。