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一种基于标准化X线片的不稳定骨盆骨折计算机辅助测量方法。

A computer aided measurement method for unstable pelvic fractures based on standardized radiographs.

作者信息

Zhao Jing-Xin, Zhao Zhe, Zhang Li-Cheng, Su Xiu-Yun, Du Hai-Long, Zhang Li-Ning, Zhang Li-Hai, Tang Pei-Fu

机构信息

Department of Orthopedics, Chinese PLA 82nd Hospital, No.100 East Jiankang Road, Qinghe District, Huai'an, Jiangsu Province, 223001, People's Republic of China.

Department of Orthopedics, Chinese PLA General Hospital, No.28 Fuxing Road, Beijing, Haidian District, 100853, People's Republic of China.

出版信息

BMC Med Imaging. 2015 Sep 30;15:41. doi: 10.1186/s12880-015-0084-x.

DOI:10.1186/s12880-015-0084-x
PMID:26423682
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4588254/
Abstract

BACKGROUND

To set up a method for measuring radiographic displacement of unstable pelvic ring fractures based on standardized X-ray images and then test its reliability and validity using a software-based measurement technique.

METHODS

Twenty-five patients that were diagnosed as AO/OTA type B or C pelvic fractures with unilateral pelvis fractured and dislocated were eligible for inclusion by a review of medical records in our clinical centre. Based on the input pelvic preoperative CT data, the standardized X-ray images, including inlet, outlet, and anterior-posterior (AP) radiographs, were simulated using Armira software (Visage Imaging GmbH, Berlin, Germany). After representative anatomic landmarks were marked on the standardized X-ray images, the 2-dimensional (2D) coordinates of these points could be revealed in Digimizer software (Model: Mitutoyo Corp., Tokyo, Japan). Subsequently, we developed a formula that indicated the translational and rotational displacement patterns of the injured hemipelvis. Five separate observers calculated the displacement outcomes using the established formula and determined the rotational patterns using a 3D-CT model based on their overall impression. We performed 3D reconstruction of all the fractured pelvises using Mimics (Materialise, Haasrode, Belgium) and determined the translational and rotational displacement using 3-matic suite. The interobserver reliability of the new method was assessed by comparing the continuous measure and categorical outcomes using intraclass correlation coefficient (ICC) and kappa statistic, respectively.

RESULT

The interobserver reliability of the new method for translational and rotational measurement was high, with both ICCs above 0.9. Rotational outcome assessed by the new method was the same as that concluded by 3-matic software. The agreement for rotational outcome among orthopaedic surgeons based on overall impression was poor (kappa statistic, 0.250 to 0.426). Compared with the 3D reconstruction outcome, the interobserver reliability of the formula method for translational and rotational measures was perfect with both ICCs more than 0.9.

CONCLUSIONS

The new method for measuring displacement using a formula was reliable, and could minimise the measurement errors and maximise the precision of pelvic fracture description. Furthermore, this study was useful for standardising the operative plan and establishing a theoretical basis for robot-assisted pelvic fracture surgery based on 2-D radiographs.

摘要

背景

建立一种基于标准化X线图像测量不稳定骨盆环骨折影像学移位的方法,并使用基于软件的测量技术测试其可靠性和有效性。

方法

通过回顾我们临床中心的病历,纳入25例被诊断为AO/OTA B型或C型骨盆骨折且单侧骨盆骨折并脱位的患者。基于输入的骨盆术前CT数据,使用Armira软件(德国柏林Visage Imaging GmbH公司)模拟标准化X线图像,包括入口位、出口位和前后位(AP)X线片。在标准化X线图像上标记代表性解剖标志后,这些点的二维(2D)坐标可在Digimizer软件(型号:日本东京三丰公司)中显示。随后,我们开发了一个公式来表示受伤半骨盆的平移和旋转移位模式。五名独立观察者使用既定公式计算移位结果,并根据他们的总体印象使用三维CT模型确定旋转模式。我们使用Mimics(比利时哈瑟罗德Materialise公司)对所有骨折骨盆进行三维重建,并使用3-matic套件确定平移和旋转移位。分别使用组内相关系数(ICC)和kappa统计量比较连续测量值和分类结果,评估新方法的观察者间可靠性。

结果

新方法在平移和旋转测量方面的观察者间可靠性较高,ICC均高于0.9。新方法评估的旋转结果与3-matic软件得出的结果相同。骨科医生基于总体印象对旋转结果的一致性较差(kappa统计量,0.250至0.426)。与三维重建结果相比,公式法在平移和旋转测量方面的观察者间可靠性极佳,ICC均大于0.9。

结论

使用公式测量移位的新方法可靠,可最大限度地减少测量误差并提高骨盆骨折描述的精度。此外,本研究有助于规范手术方案,并为基于二维X线片的机器人辅助骨盆骨折手术建立理论基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/f79cc1ff3227/12880_2015_84_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/9d5c3c40026e/12880_2015_84_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/c1094652a780/12880_2015_84_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/fc25d44f3ad6/12880_2015_84_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/df089a66921f/12880_2015_84_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/6da23296a820/12880_2015_84_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/4d821493c09a/12880_2015_84_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/eb5c24bea052/12880_2015_84_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/f79cc1ff3227/12880_2015_84_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/9d5c3c40026e/12880_2015_84_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/c1094652a780/12880_2015_84_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/fc25d44f3ad6/12880_2015_84_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/df089a66921f/12880_2015_84_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/6da23296a820/12880_2015_84_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/4d821493c09a/12880_2015_84_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/eb5c24bea052/12880_2015_84_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2305/4588254/f79cc1ff3227/12880_2015_84_Fig8_HTML.jpg

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