Purpose: In orthognathic surgery, the repeatability of 3-dimensional (3D) measurements is limited by the need for manual reidentification of reference points, which can incorporate errors greater than 1 mm for every 4 repeated measurements. This report describes a semiautomatic approach to decrease the manual reidentification error. This study evaluated the repeatability of surgical outcome measurements using the semiautomatic approach. Furthermore, a step-by-step guide is provided to enable researchers and clinicians to perform the 3D analysis by themselves.
Materials And Methods: Evaluating surgical outcome consists of 2 parts. First, the scans are aligned at the anterior cranial base. Second, a semiautomatic approach is used to place 3 dental reference points at exactly the same sites of the pre- and postoperative maxilla. Because the maxilla is repositioned during surgery but otherwise unaltered, the reference points should be identical if the pre- and postoperative scans are aligned at the maxilla. Therefore, the authors propose the insertion of reference points on the preoperative scan and then repositioning a copy of the preoperative reference points relative to the postoperative scan. To align the reference points on the postoperative scan, the hard palate is used as a mutual maxillary reference structure. A reproducibility test was performed in 10 participants by analyzing the difference between repeated measurements.
Results: Repeated linear measurements differed by less than 0.1 mm along all 3 axes (standard deviations, <0.1 mm). The 2 largest differences between repeated measurements were 0.33 mm along the superoinferior axis and 0.29 along the anteroposterior axis. Repeated rotational measurements differed by less than 0.1° around all 3 axes (standard deviations, ≤0.1°).
Conclusion: The semiautomatic approach showed excellent linear and angular repeatability. The algorithm can be implemented in the clinical evaluation of orthognathic surgical outcome and postoperative relapse.
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http://dx.doi.org/10.1016/j.joms.2017.11.010 | DOI Listing |
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