Durham, N.C. From the Interdisciplinary Craniofacial Imaging Laboratory, the Department of Radiology, and the Division of Plastic and Reconstructive Surgery, Department of Surgery, Duke University Medical Center, and the School of Medicine and the Department of Biomedical Engineering, Duke University.
Plast Reconstr Surg. 2009 Dec;124(6):2076-2084. doi: 10.1097/PRS.0b013e3181bf7e1b.
Surgical correction of cranial abnormalities, including craniosynostosis, requires knowledge of normal skull shape to appreciate dysmorphic variations. However, the inability of current anthropometric techniques to adequately characterize three-dimensional cranial shape severely limits morphologic study. The authors previously introduced three-dimensional vector analysis, a quantitative method that maps cranial form from computed tomography data. In this article, the authors report its role in the development and validation of a normative database of pediatric cranial morphology and in clinical analysis of craniosynostosis.
Normal pediatric craniofacial computed tomography data sets were acquired retrospectively from the Duke University Picture Archive and Communications System. Age increments ranging from 1 to 72 months were predetermined for scan acquisition. Three-dimensional vector analysis was performed on individual data sets, generating a set of point clouds. Averages and standard deviations for the age and gender bins of point clouds were used to create normative three-dimensional models. Anthropometric measurements from three-dimensional vector analysis models were compared with published matched data. Preoperative and postoperative morphologies of a sagittal synostosis case were analyzed using three-dimensional vector analysis and the normative database.
Three- and two-dimensional representations were created to define age-incremental normative models. Length and width dimensions agreed with previously published data. Detailed morphologic analysis is provided for a case of sagittal synostosis by applying age- and gender-matched data.
Three-dimensional vector analysis provides accurate, comprehensive description of cranial morphology with quantitative graphic output. The method enables development of an extensive pediatric normative craniofacial database. Future application of these data will facilitate analysis of cranial anomalies and assist with clinical assessment.
颅畸形的外科矫正，包括颅缝早闭，需要了解正常颅骨形状，以了解畸形的变化。然而，目前的人体测量技术无法充分描述三维颅骨形状，严重限制了形态学研究。作者先前介绍了三维向量分析，这是一种从计算机断层扫描数据中绘制颅骨形态的定量方法。本文作者报告了其在小儿颅形态正常数据库的开发和验证中的作用，以及在颅缝早闭的临床分析中的作用。
从杜克大学图片存档和通信系统中回顾性地获取正常小儿头面部计算机断层扫描数据集。预定了 1 至 72 个月的扫描采集年龄增量。对单个数据集进行三维向量分析，生成一组点云。点云的年龄和性别箱的平均值和标准差用于创建正常三维模型。从三维向量分析模型得出的人体测量值与已发表的匹配数据进行比较。使用三维向量分析和正常数据库分析矢状缝早闭病例的术前和术后形态。
创建了三维和二维表示，以定义年龄递增的正常模型。长度和宽度尺寸与之前发表的数据一致。通过应用年龄和性别匹配的数据，对头缝早闭的病例进行了详细的形态分析。
三维向量分析提供了颅骨形态的准确、全面的描述，并具有定量图形输出。该方法能够开发广泛的小儿正常颅面数据库。这些数据的未来应用将有助于分析颅面畸形，并协助临床评估。
