Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms
Semiautomatic vessel wall detection and quantification of wall thickness in computed tomography images of human abdominal aortic aneurysms
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DOI：
10.1118/1.3284976
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发表时间：
2010-02-01
期刊：
影响因子：
3.8
通讯作者：
Finol, Ender A.
中科院分区：
文献类型：
--
作者：
Shum, Judy;DiMartino, Elena S.;Finol, Ender A.
研究方法：作者描述了一种基于强度直方图和神经网络的AAA壁厚估计算法，该算法涉及对比增强腹部计算机断层扫描图像的分割。该算法被应用于10个破裂和10个未破裂的AAA图像数据集。两名血管外科医生手动分割每个数据集的管腔、内壁和外壁，并将参考标准定义为分割的平均值。通过比较参比标准品与由算法和市售软件包自动生成的管腔轮廓来确定重现性。通过比较两名外科医生使用该算法制作的管腔、外壁和内壁轮廓以及壁厚来评估可重复性。管腔面积的自动和手动测量值之间具有高度一致性（破裂和未破裂动脉瘤分别为r=0.978和r=0.996）和血管外科医生之间（破裂和未破裂动脉瘤分别为r=0.987和r=0.992）。与参考相比，作者的自动算法显示出更好的结果，平均流明误差为3.69%，小于市售应用Simpleware和参考之间误差（7.53%）的一半。血管外科医生之间的壁厚测量结果也显示出良好的一致性，平均变异系数为10.59%（破裂动脉瘤）和13.02%（未破裂动脉瘤）。破裂动脉瘤的壁厚（1.78 ± 0.39 mm）明显大于未破裂动脉瘤的壁厚（1.48 ± 0.22 mm），p= 0.044。结论：尽管需要进一步完善外壁分割算法以实现完全自动化，但这些初步结果表明该方法具有足够的重现性和较低的观察者间变异性。
Methods: The authors describe an algorithm for estimating wall thickness in AAAs based on intensity histograms and neural networks involving segmentation of contrast enhanced abdominal computed tomography images. The algorithm was applied to ten ruptured and ten unruptured AAA image data sets. Two vascular surgeons manually segmented the lumen, inner wall, and outer wall of each data set and a reference standard was defined as the average of their segmentations. Reproducibility was determined by comparing the reference standard to lumen contours generated automatically by the algorithm and a commercially available software package. Repeatability was assessed by comparing the lumen, outer wall, and inner wall contours, as well as wall thickness, made by the two surgeons using the algorithm.Results: There was high correspondence between automatic and manual measurements for the lumen area (r=0.978 and r=0.996 for ruptured and unruptured aneurysms, respectively) and between vascular surgeons (r=0.987 and r=0.992 for ruptured and unruptured aneurysms, respectively). The authors' automatic algorithm showed better results when compared to the reference with an average lumen error of 3.69%, which is less than half the error between the commercially available application Simpleware and the reference (7.53%). Wall thickness measurements also showed good agreement between vascular surgeons with average coefficients of variation of 10.59% (ruptured aneurysms) and 13.02% (unruptured aneurysms). Ruptured aneurysms exhibit significantly thicker walls (1.78 +/- 0.39 mm) than unruptured ones (1.48 +/- 0.22 mm), p=0.044.Conclusions: While further refinement is needed to fully automate the outer wall segmentation algorithm, these preliminary results demonstrate the method's adequate reproducibility and low interobserver variability.