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用于三维血管内超声中管腔和中膜-外膜边界检测的自动化系统的验证

Validation of an automated system for luminal and medial-adventitial border detection in three-dimensional intravascular ultrasound.

作者信息

Klingensmith Jon D, Tuzcu E Murat, Nissen Steven E, Vince D Geoffrey

机构信息

Department of Biomedical Engineering, Lerner Research Institute, The Cleveland Clinic Foundation, Cleveland, OH 44195, USA.

出版信息

Int J Cardiovasc Imaging. 2003 Apr;19(2):93-104. doi: 10.1023/a:1022843104297.

Abstract

The precise tomographic assessment of coronary artery disease by intravascular ultrasound (IVUS) is useful in quantitative studies. Such studies require identification of luminal and medial-adventitial (MA) borders in a sequence of IVUS images. We have developed a three-dimensional (3D) active-surface system for border detection that facilitates the analysis of many images with minimal user interaction. To assess the validity of the technique, luminal and MA borders in 529 end-diastolic images from nine coronary arterial segments (58.8 +/- 14.2 images per patient) were traced manually by four experienced observers. The computer-detected borders were compared with borders determined by the four observers using a modified Williams' index (WI), the ratio of inter-observer variability to computer-observer variability. While manual tracing required 49.2 +/- 12.1 min for analysis, the analysis system identified luminal (R2 = 0.92) and MA borders (R2 = 0.97) in 13.8 +/- 4.0 min, a decrease of 35.4 min (p < 0.000001). The computer minus observer differences in lumen area and MA area were -0.88 +/- 0.90 and -0.07 +/- 0.63 mm2. Therefore, the computer system underestimated both lumen and MA area, but this effect was very small in MA area. The WI values and 95% confidence intervals were 0.98 (0.89,1.06) for luminal border detection and 0.99 (0.95,1.04) for MA border detection. Plaque volume measurements, a common endpoint of clinical trials, also verified the accuracy of the technique (R2 = 0.98). The proposed 3D active-surface border detection system provides a faster and less-tedious alternative to manual tracing for assessment of coronary artery anatomy in vivo.

摘要

通过血管内超声(IVUS)对冠状动脉疾病进行精确的断层评估在定量研究中很有用。此类研究需要在一系列IVUS图像中识别管腔和中膜-外膜(MA)边界。我们开发了一种用于边界检测的三维(3D)活动表面系统,该系统以最少的用户交互促进了对许多图像的分析。为了评估该技术的有效性,由四名经验丰富的观察者手动追踪来自九个冠状动脉节段的529张舒张末期图像(每位患者58.8±14.2张图像)中的管腔和MA边界。使用改良的威廉姆斯指数(WI),即将观察者间变异性与计算机-观察者变异性的比率,将计算机检测到的边界与四名观察者确定的边界进行比较。虽然手动追踪分析需要49.2±12.1分钟,但分析系统在13.8±4.0分钟内识别出管腔(R2 = 0.92)和MA边界(R2 = 0.97),减少了35.4分钟(p < 0.000001)。计算机与观察者在管腔面积和MA面积上的差异分别为-0.88±0.90和-0.07±0.63 mm2。因此,计算机系统低估了管腔和MA面积,但这种影响在MA面积中非常小。管腔边界检测的WI值和95%置信区间为0.98(0.89,1.06),MA边界检测的WI值和95%置信区间为0.99(0.95,1.04)。斑块体积测量是临床试验的常见终点,也验证了该技术的准确性(R2 = 0.98)。所提出的3D活动表面边界检测系统为体内评估冠状动脉解剖结构提供了一种比手动追踪更快且更不繁琐的替代方法。

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