Marcus Jeffrey R, Domeshek Leahthan F, Das Rajesh, Marshall Sean, Nightingale Roger, Stokes Tracey H, Mukundan Srinivasan
Interdisciplinary Craniofacial Imaging Lab, Duke University, Durham, NC, USA.
Eplasty. 2008 Apr 9;8:e20.
The lack of adequate means to objectively characterize cranial shape contributes to ongoing controversies in the surgical management of craniosynostosis. Cranial shape analysis must address relevant clinical questions objectively and thoroughly and must be broadly applicable across the spectrum of normal and abnormal. Herein, we demonstrate and statistically validate an automated computed tomography (CT)-based application for 3-dimensional characterization of skull morphology. The technology is intended for application to diagnostic imaging, surgical planning, and outcomes assessment.
Three-dimensional vector analysis (3DVA) was applied to craniofacial CT data, generating three-dimensional cranial surface point clouds.
To assess accuracy, measurements derived from the 3DVA analysis of a CT scan of a skull phantom were compared to those made directly from the Digital Imaging and Communications in Medicine data on a Vitrea workstation. To assess reproducibility, 3 readers independently analyzed human head CT scans using 3DVA.
A normative database of 86 age-incremental pediatric patients was created. Preoperative craniosynostosis case datasets were analyzed using 3DVA and were compared with age-matched normative datasets.
Accuracy and reproducibility of less than 1% mean error and less than 0.5 mm standard error in all cases validated 3DVA-derived distances. Three-dimensional vector analysis point clouds provide qualitative and quantitative representations of morphology. Regional dysmorphology in craniosynostosis cases is demonstrated graphically.
Three-dimensional vector analysis generated accurate, reproducible, and comprehensive craniofacial morphometric data. 3DVA may be used for paired data analysis (eg, a single subject undergoing surgical correction), comparative group data analysis, and craniofacial data archiving. The technique can provide objective characterization of craniofacial morphology previously not possible.
缺乏客观描述颅骨形状的适当方法，这导致颅缝早闭手术治疗中持续存在争议。颅骨形状分析必须客观、全面地解决相关临床问题，并且必须广泛适用于正常和异常范围。在此，我们展示并通过统计学验证了一种基于计算机断层扫描（CT）的自动化应用程序，用于颅骨形态的三维表征。该技术旨在应用于诊断成像、手术规划和结果评估。
将三维矢量分析（3DVA）应用于颅面CT数据，生成三维颅骨表面点云。
为评估准确性，将从颅骨模型CT扫描的3DVA分析得出的测量结果与在Vitrea工作站上直接从医学数字成像和通信数据得出的测量结果进行比较。为评估可重复性，3名读者使用3DVA独立分析人头CT扫描。
创建了一个包含86例年龄递增的儿科患者的规范数据库。使用3DVA分析术前颅缝早闭病例数据集，并与年龄匹配的规范数据集进行比较。
在所有病例中，平均误差小于1%且标准误差小于0.5毫米的准确性和可重复性验证了3DVA得出的距离。三维矢量分析点云提供了形态的定性和定量表示。颅缝早闭病例中的区域畸形通过图形展示。
三维矢量分析生成了准确、可重复且全面的颅面形态测量数据。3DVA可用于配对数据分析（例如，接受手术矫正的单个受试者）、比较组数据分析和颅面数据存档。该技术可以提供以前无法实现的颅面形态的客观表征。
