颅内动脉瘤的计算机辅助三维形态学评估
Computer-Assisted Three-Dimensional Morphology Evaluation of Intracranial Aneurysms.
作者信息
Rajabzadeh-Oghaz Hamidreza, Varble Nicole, Shallwani Hussain, Tutino Vincent M, Mowla Ashkan, Shakir Hakeem J, Vakharia Kunal, Atwal Gursant S, Siddiqui Adnan H, Davies Jason M, Meng Hui
机构信息
Canon Stroke and Vascular Research Center, University at Buffalo, Buffalo, New York, USA; Department of Mechanical and Aerospace Engineering, University at Buffalo, Buffalo, New York, USA.
Department of Neurosurgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, New York, USA; Department of Neurosurgery, Gates Vascular Institute, Kaleida Health, Buffalo, New York, USA.
出版信息
World Neurosurg. 2018 Nov;119:e541-e550. doi: 10.1016/j.wneu.2018.07.208. Epub 2018 Aug 1.
OBJECTIVE
Precise morphologic evaluation is important for intracranial aneurysm (IA) management. At present, clinicians manually measure the IA size and neck diameter on 2-dimensional (2D) digital subtraction angiographic (DSA) images and categorize the IA shape as regular or irregular on 3-dimensional (3D)-DSA images, which could result in inconsistency and bias. We investigated whether a computer-assisted 3D analytical approach could improve IA morphology assessment.
METHODS
Five neurointerventionists evaluated the size, neck diameter, and shape of 39 IAs using current and computer-assisted 3D approaches. In the computer-assisted 3D approach, the size, neck diameter, and undulation index (UI, a shape irregularity metric) were extracted using semiautomated reconstruction of aneurysm geometry using 3D-DSA, followed by IA neck identification and computerized geometry assessment.
RESULTS
The size and neck diameter measured using the manual 2D approach were smaller than computer-assisted 3D measurements by 2.01 mm (P < 0.001) and 1.85 mm (P < 0.001), respectively. Applying the definitions of small IAs (<7 mm) and narrow-necked IAs (<4 mm) from the reported data, interrater variation in manual 2D measurements resulted in inconsistent classification of the size of 14 IAs and the necks of 19 IAs. Visual inspection resulted in an inconsistent shape classification for 23 IAs among the raters. Greater consistency was achieved using the computer-assisted 3D approach for size (intraclass correlation coefficient [ICC], 1.00), neck measurements (ICC, 0.96), and shape quantification (UI; ICC, 0.94).
CONCLUSIONS
Computer-assisted 3D morphology analysis can improve accuracy and consistency in measurements compared with manual 2D measurements. It can also more reliably quantify shape irregularity using the UI. Future application of computer-assisted analysis tools could help clinicians standardize morphology evaluations, leading to more consistent IA evaluations.
目的
精确的形态学评估对于颅内动脉瘤（IA）的治疗至关重要。目前，临床医生在二维（2D）数字减影血管造影（DSA）图像上手动测量IA的大小和颈部直径，并在三维（3D）-DSA图像上对IA的形状进行规则或不规则分类，这可能导致不一致和偏差。我们研究了计算机辅助三维分析方法是否能改善IA形态学评估。
方法
5名神经介入医生使用当前方法和计算机辅助三维方法评估了39个IA的大小、颈部直径和形状。在计算机辅助三维方法中，使用三维DSA对动脉瘤几何形状进行半自动重建，提取大小、颈部直径和波动指数（UI，一种形状不规则度量），随后进行IA颈部识别和计算机化几何评估。
结果
使用手动二维方法测量的大小和颈部直径分别比计算机辅助三维测量小2.01 mm（P<0.001）和1.85 mm（P<0.001）。根据报告数据中对小IA（<7 mm）和窄颈IA（<4 mm）的定义，手动二维测量中的观察者间差异导致14个IA的大小和19个IA的颈部的分类不一致。视觉检查导致评估者之间对23个IA的形状分类不一致。使用计算机辅助三维方法在大小（组内相关系数[ICC]，1.00）、颈部测量（ICC，0.96）和形状量化（UI；ICC，0.94）方面取得了更高的一致性。
结论
与手动二维测量相比，计算机辅助三维形态学分析可以提高测量的准确性和一致性。它还可以使用UI更可靠地量化形状不规则性。计算机辅助分析工具的未来应用可以帮助临床医生规范形态学评估，从而使IA评估更加一致。
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