Drake Virginia E, Rizzi Christopher J, Greywoode Jewel D, Vakharia Kavita T, Vakharia Kalpesh T
Department of Otolaryngology - Head and Neck Surgery, University of Maryland, School of Medicine, Baltimore, Maryland.
Department of Plastic Surgery, Pennsylvania State University, Hershey, Pennsylvania.
Craniomaxillofac Trauma Reconstr. 2019 Mar;12(1):14-19. doi: 10.1055/s-0037-1608696. Epub 2017 Nov 29.
We introduce a novel computer-based method to digitally fixate midfacial fractures to facilitate more efficient intraoperative fixation. This article aims to describe a novel computer-based algorithm that can be utilized to model midface fracture reduction and fixation and to evaluate the algorithm's ability to produce images similar to true postoperative images. This is a retrospective review combined with cross-sectional survey from January 1, 2010, to December 31, 2015. This study was performed at a single tertiary care, level-I trauma center. Ten patients presenting with acute midfacial traumatic fractures were evaluated. Thirty-five physicians were surveyed regarding the accuracy of the images obtained using the algorithm. A computer algorithm utilizing AquariusNet (TeraRecon, Inc., Foster City, CA) and Adobe Photoshop (Adobe Systems Inc., San Jose, CA) was developed to model midface fracture repair. Preoperative three-dimensional computed tomographic (CT) images were processed using the algorithm. Fractures were virtually reduced and fixated to generate a virtual postoperative image. A survey comparing the virtual postoperative and the actual postoperative images was produced. A Likert-type scale rating system of 0 to 10 (0 being completely different and 10 being identical) was utilized. Survey participants evaluated the similarity of fracture reduction and fixation plate appearance. The algorithm's capacity for future clinical utility was also assessed. Survey response results from 35 physicians were collected and analyzed to determine the accuracy of the algorithm. Ten patients were evaluated. Fracture types included zygomaticomaxillary complex, LeFort, and naso-orbito-ethmoidal complex. Thirty-four images were assessed by a group of 35 physicians from the fields of otolaryngology, oral and maxillofacial surgery, and radiology. Mean response for fracture reduction similarity was 7.8 ± 2.5 and fixation plate similarity was 8.3 ± 1.9. All respondents reported interest in the tool for clinical use. This computer-based algorithm is able to produce virtual images that resemble actual postoperative images. It has the ability to model midface fracture repair and hardware placement.
我们介绍一种基于计算机的新型方法,用于数字化固定面中部骨折,以促进更高效的术中固定。本文旨在描述一种基于计算机的新型算法,该算法可用于模拟面中部骨折复位和固定,并评估该算法生成与真实术后图像相似图像的能力。这是一项回顾性研究,并结合了2010年1月1日至2015年12月31日的横断面调查。本研究在一家单一的三级医疗、一级创伤中心进行。对10例急性面中部创伤性骨折患者进行了评估。就使用该算法获得的图像的准确性对35名医生进行了调查。开发了一种利用AquariusNet(TeraRecon公司,加利福尼亚州福斯特城)和Adobe Photoshop(Adobe系统公司,加利福尼亚州圣何塞)的计算机算法来模拟面中部骨折修复。术前三维计算机断层扫描(CT)图像使用该算法进行处理。骨折被虚拟复位并固定,以生成虚拟术后图像。制作了一份比较虚拟术后图像和实际术后图像的调查问卷。采用0至10的李克特式量表评分系统(0表示完全不同,10表示完全相同)。调查参与者评估了骨折复位和固定钢板外观的相似性。还评估了该算法未来临床应用的能力。收集并分析了35名医生的调查回复结果,以确定该算法的准确性。对10例患者进行了评估。骨折类型包括颧上颌复合体、LeFort骨折和鼻眶筛复合体。一组来自耳鼻喉科、口腔颌面外科和放射科的35名医生对34张图像进行了评估。骨折复位相似性的平均回复为7.8±2.5,固定钢板相似性的平均回复为8.3±1.9。所有受访者均表示对该工具在临床中的应用感兴趣。这种基于计算机的算法能够生成类似于实际术后图像的虚拟图像。它有能力模拟面中部骨折修复和硬件放置。