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评估一种新的算法,用于使用腓骨瓣进行下颌骨重建中的虚拟手术规划自动化。

Evaluation of a novel algorithm for automating virtual surgical planning in mandibular reconstruction using fibula flaps.

机构信息

Department of Oral, Maxillofacial and Facial Plastic Surgery, RWTH Aachen University Hospital, Aachen, Germany.

Department of Oral, Maxillofacial and Facial Plastic Surgery, RWTH Aachen University Hospital, Aachen, Germany.

出版信息

J Craniomaxillofac Surg. 2019 Sep;47(9):1378-1386. doi: 10.1016/j.jcms.2019.06.013. Epub 2019 Jun 25.

Abstract

Virtual surgical planning plays an increasingly important role in jaw reconstruction. The aim of the present study was the evaluation of the clinical applicability of a novel algorithm for automating virtual mandibular reconstruction using fibula flaps. The software uses Computed-Tomography of the facial skeleton and the lower leg of 63 subjects, implemented in Python programming language. The developed algorithm is based on individual bone curvatures of the mandible and fibula. Ten different defects were generated for each mandible by virtually defined cutting planes. Three experienced surgeons reviewed all reconstruction proposals generated by the algorithm according to a visual analogue scale. The possible correlation between the ratings and the prioritization of the algorithm and the calculation time for the reconstructions were analyzed. Spearman analysis showed a strong correlation -0.613 (p < 0.001) between the deviation of the reconstruction result from the target line and the average assessment of the surgeons as well as a moderate correlation -0.448 (p = 0.013) between surgeons' assessments and the prioritization by the algorithm. The calculation time for twenty reconstructions per defect took between 4.99 s and 483.5 s depending on defect size and location. The evaluated algorithm automatically creates valid reconstruction results with acceptable computation time, which have received a high level of confirmation from experienced surgeons.

摘要

虚拟手术规划在颌骨重建中起着越来越重要的作用。本研究的目的是评估一种使用腓骨瓣自动进行虚拟下颌骨重建的新算法的临床适用性。该软件使用 63 名受试者的面部骨骼和小腿的计算机断层扫描数据,使用 Python 编程语言实现。所开发的算法基于下颌骨和腓骨的个体骨曲率。通过虚拟定义的切割平面,为每个下颌骨生成了十个不同的缺陷。三位经验丰富的外科医生根据视觉模拟量表对算法生成的所有重建方案进行了评估。分析了评分与算法优先级之间以及重建计算时间之间的可能相关性。Spearman 分析显示,重建结果与目标线的偏差与外科医生的平均评估之间存在很强的相关性-0.613(p<0.001),外科医生的评估与算法的优先级之间存在中度相关性-0.448(p=0.013)。每个缺陷的二十次重建的计算时间取决于缺陷的大小和位置,在 4.99 秒到 483.5 秒之间。评估的算法可以自动创建具有可接受计算时间的有效重建结果,并且已经得到了经验丰富的外科医生的高度认可。

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