Solomon Lee, Niel Panchal, William Hoffman, Jason Pomerantz, Benjamin Laguna, Jesse Courtier
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Clinicians (n = 30) in specialties managing craniofacial trauma assessed a database of mandibular and maxillofacial complex fractures of varying severity using computed-tomography slices supplemented with either traditional 3D reformats (control) or the AR model (experimental), completed diagnostic and spatial characterization tasks, and were evaluated quantitatively and qualitatively on diagnostic accuracy, task cognitive load, and weighted preference for the traditional versus AR model. Most clinicians (83%) preferred the AR model overall. Control and experimental groups had equivalent diagnostic sensitivity and specificity. Less experienced clinicians found the AR model required less effort, was less frustrating, and was preferred for fracture displacement characterization. The AR model had no significant impact on more experienced clinicians. All clinicians found the AR model allowed more intuitive manipulation of the 3D object. Those with less experience preferred the AR model over traditional imaging for diagnostic and educational purposes, whereas more experienced clinicians found that the AR model did not significantly alter their established approach to fracture evaluation. Our mobile-based AR model may be preferable to traditional 3D formats for spatial assessment tasks and decreasing task cognitive load, most notably for less experienced clinicians for whom perioperative practices are less established.","PeriodicalId":508736,"journal":{"name":"FACE","volume":"40 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Augmented Reality Model for Evaluating Traumatic Craniofacial Fractures\",\"authors\":\"Solomon Lee, Niel Panchal, William Hoffman, Jason Pomerantz, Benjamin Laguna, Jesse Courtier\",\"doi\":\"10.1177/27325016241256671\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Accurate diagnosis and spatial characterization of craniofacial fractures is critical for treatment planning and precise fracture reduction. Since augmented reality (AR) has potential for better diagnostic evaluation than traditional three-dimensional (3D) reformats, we tested whether our accessible mobile-based AR model improves diagnostic accuracy, spatial understanding, and decreases task cognitive load when clinicians evaluate facial fractures. Clinicians (n = 30) in specialties managing craniofacial trauma assessed a database of mandibular and maxillofacial complex fractures of varying severity using computed-tomography slices supplemented with either traditional 3D reformats (control) or the AR model (experimental), completed diagnostic and spatial characterization tasks, and were evaluated quantitatively and qualitatively on diagnostic accuracy, task cognitive load, and weighted preference for the traditional versus AR model. Most clinicians (83%) preferred the AR model overall. Control and experimental groups had equivalent diagnostic sensitivity and specificity. Less experienced clinicians found the AR model required less effort, was less frustrating, and was preferred for fracture displacement characterization. The AR model had no significant impact on more experienced clinicians. All clinicians found the AR model allowed more intuitive manipulation of the 3D object. Those with less experience preferred the AR model over traditional imaging for diagnostic and educational purposes, whereas more experienced clinicians found that the AR model did not significantly alter their established approach to fracture evaluation. 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引用次数: 0
摘要
颅颌面骨折的准确诊断和空间特征描述对于治疗规划和精确骨折复位至关重要。由于增强现实技术(AR)比传统的三维(3D)重制技术具有更好的诊断评估潜力,我们测试了我们基于移动设备的可访问 AR 模型是否能提高诊断准确性、空间理解能力,并降低临床医生评估面部骨折时的任务认知负荷。颅颌面创伤专科的临床医生(n = 30)使用计算机断层扫描切片评估了不同严重程度的下颌骨和颌面部复杂骨折数据库,并辅以传统三维重建图(对照组)或 AR 模型(实验组),完成了诊断和空间特征描述任务,并对诊断准确性、任务认知负荷以及传统模型与 AR 模型的加权偏好进行了定量和定性评估。总体而言,大多数临床医生(83%)更倾向于 AR 模型。对照组和实验组的诊断灵敏度和特异性相当。经验较少的临床医生认为,AR 模型所需的工作量较少,不容易产生挫败感,在骨折位移特征描述方面更受青睐。AR 模型对经验丰富的临床医生没有明显影响。所有临床医生都认为 AR 模型可以更直观地操作三维物体。在诊断和教育方面,经验较少的临床医生更喜欢 AR 模型,而经验较多的临床医生则认为 AR 模型并没有明显改变他们既定的骨折评估方法。在空间评估任务和减少任务认知负荷方面,我们基于移动设备的 AR 模型可能优于传统的 3D 格式,尤其是对于围手术期实践经验较少的临床医生而言。
An Augmented Reality Model for Evaluating Traumatic Craniofacial Fractures
Accurate diagnosis and spatial characterization of craniofacial fractures is critical for treatment planning and precise fracture reduction. Since augmented reality (AR) has potential for better diagnostic evaluation than traditional three-dimensional (3D) reformats, we tested whether our accessible mobile-based AR model improves diagnostic accuracy, spatial understanding, and decreases task cognitive load when clinicians evaluate facial fractures. Clinicians (n = 30) in specialties managing craniofacial trauma assessed a database of mandibular and maxillofacial complex fractures of varying severity using computed-tomography slices supplemented with either traditional 3D reformats (control) or the AR model (experimental), completed diagnostic and spatial characterization tasks, and were evaluated quantitatively and qualitatively on diagnostic accuracy, task cognitive load, and weighted preference for the traditional versus AR model. Most clinicians (83%) preferred the AR model overall. Control and experimental groups had equivalent diagnostic sensitivity and specificity. Less experienced clinicians found the AR model required less effort, was less frustrating, and was preferred for fracture displacement characterization. The AR model had no significant impact on more experienced clinicians. All clinicians found the AR model allowed more intuitive manipulation of the 3D object. Those with less experience preferred the AR model over traditional imaging for diagnostic and educational purposes, whereas more experienced clinicians found that the AR model did not significantly alter their established approach to fracture evaluation. Our mobile-based AR model may be preferable to traditional 3D formats for spatial assessment tasks and decreasing task cognitive load, most notably for less experienced clinicians for whom perioperative practices are less established.