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使用表面模型对头的各种骨骼结构进行三维叠加技术的评估。

Evaluation of 3-dimensional superimposition techniques on various skeletal structures of the head using surface models.

作者信息

Gkantidis Nikolaos, Schauseil Michael, Pazera Pawel, Zorkun Berna, Katsaros Christos, Ludwig Björn

机构信息

Department of Orthodontics and Dentofacial Orthopedics, University of Bern, Bern, Switzerland.

Department of Orthodontics, University of Marburg, Marburg, Germany.

出版信息

PLoS One. 2015 Feb 23;10(2):e0118810. doi: 10.1371/journal.pone.0118810. eCollection 2015.

Abstract

OBJECTIVES

To test the applicability, accuracy, precision, and reproducibility of various 3D superimposition techniques for radiographic data, transformed to triangulated surface data.

METHODS

Five superimposition techniques (3P: three-point registration; AC: anterior cranial base; AC + F: anterior cranial base + foramen magnum; BZ: both zygomatic arches; 1Z: one zygomatic arch) were tested using eight pairs of pre-existing CT data (pre- and post-treatment). These were obtained from non-growing orthodontic patients treated with rapid maxillary expansion. All datasets were superimposed by three operators independently, who repeated the whole procedure one month later. Accuracy was assessed by the distance (D) between superimposed datasets on three form-stable anatomical areas, located on the anterior cranial base and the foramen magnum. Precision and reproducibility were assessed using the distances between models at four specific landmarks. Non parametric multivariate models and Bland-Altman difference plots were used for analyses.

RESULTS

There was no difference among operators or between time points on the accuracy of each superimposition technique (p>0.05). The AC + F technique was the most accurate (D<0.17 mm), as expected, followed by AC and BZ superimpositions that presented similar level of accuracy (D<0.5 mm). 3P and 1Z were the least accurate superimpositions (0.79<D<1.76 mm, p<0.005). Although there was no difference among operators or between time points on the precision of each superimposition technique (p>0.05), the detected structural changes differed significantly between different techniques (p<0.05). Bland-Altman difference plots showed that BZ superimposition was comparable to AC, though it presented slightly higher random error.

CONCLUSIONS

Superimposition of 3D datasets using surface models created from voxel data can provide accurate, precise, and reproducible results, offering also high efficiency and increased post-processing capabilities. In the present study population, the BZ superimposition was comparable to AC, with the added advantage of being applicable to scans with a smaller field of view.

摘要

目的

测试各种三维叠加技术对转换为三角测量表面数据的放射影像数据的适用性、准确性、精密度和可重复性。

方法

使用八对已有的CT数据(治疗前和治疗后)测试五种叠加技术(3P:三点配准;AC:前颅底;AC + F:前颅底 + 枕骨大孔;BZ:双侧颧弓;1Z:单侧颧弓)。这些数据来自接受快速上颌扩弓治疗的非生长发育期正畸患者。所有数据集由三名操作人员独立进行叠加,并在一个月后重复整个操作过程。通过位于前颅底和枕骨大孔的三个形态稳定的解剖区域上叠加数据集之间的距离(D)评估准确性。使用四个特定标志点处模型之间的距离评估精密度和可重复性。采用非参数多变量模型和Bland-Altman差异图进行分析。

结果

各叠加技术的准确性在操作人员之间或时间点之间均无差异(p>0.05)。正如预期的那样,AC + F技术最准确(D<0.17 mm),其次是AC和BZ叠加,其准确性水平相似(D<0.5 mm)。3P和1Z是最不准确的叠加技术(0.79<D<1.76 mm,p<0.005)。虽然各叠加技术的精密度在操作人员之间或时间点之间均无差异(p>0.05),但不同技术之间检测到的结构变化存在显著差异(p<0.05)。Bland-Altman差异图显示,BZ叠加与AC相当,尽管其随机误差略高。

结论

使用从体素数据创建的表面模型对三维数据集进行叠加可提供准确、精密和可重复的结果,还具有高效率和增强的后处理能力。在本研究人群中,BZ叠加与AC相当,其额外优势是适用于视野较小的扫描。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/294e/4338241/73ad43e1e75e/pone.0118810.g001.jpg

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