Nakano Hiroyuki, Suzuki Kei, Inoue Kazuya, Nakajima Yoichiro, Mishima Katsuaki, Ueno Takaaki, Demura Noboru
Department of Oral and Maxillofacial Surgery, Kanazawa Medical University, Kahoku 920-0293, Ishikawa, Japan.
Department of Oral Surgery, Osaka Medical and Pharmaceutical University, Takatsuki 569-8686, Osaka, Japan.
J Pers Med. 2022 Nov 3;12(11):1831. doi: 10.3390/jpm12111831.
In the field of oral and maxillofacial surgery, establishment of a new method for predicting morphology is desirable. Therefore, the purpose of the present study was to establish a new method for predicting the original shape of a mandibular defect site using the homologous modeling technique. This study used data from 44 patients who underwent computed tomography in the Department of Oral Surgery at Osaka Medical College. Two types of homologous models were constructed: total mandible (TM) and half mandible (HM). Principal component analysis (PCA) was performed using point cloud data of the homologous model M and homologous model HM, and a multiple regression equation was created using the PC value of TM as the object variable and PC value of HM as the explanatory variable. The predicted PC (M) was created from PC (HM) using a regression formula, back-calculated from point cloud data from PC (M), to create the predicted mandible model. Finally, the original image (TC-M) and estimated mandible were superposed and examined. The mean absolute error between the predicted mandible and actual mandible was 1.04 ± 1.35 mm. We believe that this method will be applicable in actual clinical practice.
在口腔颌面外科领域，建立一种新的形态预测方法是很有必要的。因此，本研究的目的是利用同源建模技术建立一种预测下颌骨缺损部位原始形状的新方法。本研究使用了大阪医科大学口腔外科接受计算机断层扫描的44例患者的数据。构建了两种类型的同源模型：全下颌骨（TM）和半下颌骨（HM）。使用同源模型M和同源模型HM的点云数据进行主成分分析（PCA），并以TM的PC值为目标变量、HM的PC值为解释变量创建多元回归方程。使用回归公式从PC（HM）创建预测PC（M），从PC（M）的点云数据进行反算，以创建预测下颌骨模型。最后，将原始图像（TC-M）和估计的下颌骨进行叠加并检查。预测下颌骨与实际下颌骨之间的平均绝对误差为1.04±1.35毫米。我们认为该方法将适用于实际临床实践。
