Objective: To provide a new solution for the digital design of nasal prostheses, this study explores the three-dimensional (3D) facial morphology completion method for external nasal defects based on the non-rigid registration process of 3D face template. Methods: A total of 20 male patients with tooth defect and dentition defect who visited the Department of Prosthodontics, Peking University School and Hospital of Stomatology from June to December 2022 were selected, age 18-45 years old. The original 3D facial data of patients were collected, and the 3D facial data of the external nose defect was constructed in Geomagic Wrap 2021 software. Using the structured 3D face template data constructed in the previous research of the research group, the 3D face template was deformed and registered to the 3D facial data of external nose defect (based on the morphology of non-defective area) by non-rigid registration algorithm (MeshMonk program), and the personalized deformed data of the 3D face template was obtained, as the complemented facial 3D data. Based on the defect boundary of the 3D facial data of the external nose defect, the complemented external nose 3D data can be cut out from the complemented facial 3D data. Then the nasofacial angle and nasolabial angle of the complemented facial 3D data and the original 3D facial data was compared and analyzed, the ratio between the nose length and mid-face height, nose width and medial canthal distance of the complemented facial 3D data was measured, the edge fit between the edge curve of the complemented external nose 3D data and the defect edge curve of the 3D facial data of external nose defect was evaluated, and the morphological difference of the nose between the complemented external nose 3D data and the original 3D facial data was analyzed. Results: There was no significant statistically difference (t=-0.23, P=0.823; Z=-1.72, P=0.086) in the nasofacial angle (28.2°±2.9°, 28.4°±3.5° respectively) and nasolabial angle [95.4°(19.2°), 99.9°(9.5°) respectively] between the 20 original 3D facial data and the complemented facial 3D data. The value of the ratio of nose length to mid-face height in the complemented facial 3D data was 0.63±0.03, and the value of the ratio of nose width to medial canthal distance was 1.07±0.08. The curve deviation (root mean square value) between the edge curve of the complemented external nose 3D data and the defect edge curve of the 3D facial data of external nose defect was (0.37±0.09) mm, the maximum deviation was (1.14±0.32) mm, and the proportion of the curve deviation value within±1 mm was (97±3)%. The distance of corresponding nose landmarks between the complemented facial 3D data and the original 3D facial data were respectively, Nasion: [1.52(1.92)] mm; Pronasale: (3.27±1.21) mm; Subnasale: (1.99±1.09) mm; Right Alare: (2.64±1.34) mm; Left Alare: (2.42± 1.38) mm. Conclusions: The method of 3D facial morphology completion of external nose defect proposed in this study has good feasibility. The constructed complemented external nose 3D data has good facial coordination and edge fit, and the morphology is close to the nose morphology of the original 3D facial data.
目的: 基于三维人脸模板的非刚性配准过程探讨外鼻缺损三维形态补全方法,为鼻赝复体的数字化设计提供新的解决方案。 方法: 选取2022年6至12月于北京大学口腔医学院·口腔医院修复科就诊的牙体缺损或缺失男性患者20例,年龄18~45岁,采集患者原始三维颜面数据,用Geomagic Wrap 2021软件构建外鼻缺损三维颜面数据。使用课题组前期研究中构建的结构化三维人脸模板数据,基于非缺损区形态,通过MeshMonk程序(一种非刚性配准算法)将三维人脸模板变形配准至外鼻缺损三维颜面数据上,获得三维人脸模板个性化变形后的数据,即补全人脸三维数据。基于外鼻缺损三维颜面数据的缺损边界,在补全人脸三维数据上裁剪出补全外鼻三维数据。对比分析补全人脸三维数据与原始三维颜面数据的鼻面角和鼻唇角,测量补全人脸三维数据鼻长与中面高、鼻宽与内眦间距的比值,评价补全外鼻三维数据的边缘曲线与外鼻缺损三维颜面数据缺损边缘曲线的边缘密合度,并分析补全外鼻三维数据与原始三维颜面数据鼻部相同标志点间距离值。 结果: 20例原始三维颜面数据与补全人脸三维数据的鼻面角(分别为28.2°±2.9°、28.4°±3.5°)、鼻唇角[分别为95.4°(19.2°)、99.9°(9.5°)]差异均无统计学意义(t=-0.23,P=0.823;Z=-1.72,P=0.086)。补全人脸三维数据鼻长与中面高的比值为0.63±0.03,鼻宽与内眦间距的比值为1.07±0.08。补全外鼻三维数据的边缘曲线与外鼻缺损三维颜面数据缺损边缘曲线的曲线偏差(均方根值)为(0.37±0.09)mm、最大偏差为(1.14±0.32)mm,曲线偏差值位于±1 mm之内的占比为(97±3)%。补全人脸三维数据与原始三维颜面数据上对应鼻部标志点间距离分别为鼻根点[1.52(1.92)]mm,鼻尖点(3.27±1.21)mm,鼻下点(1.99±1.09)mm,右鼻翼点(2.64±1.34)mm,左鼻翼点(2.42±1.38)mm。 结论: 本项研究提出的外鼻缺损三维形态补全方法有较好的可行性,构建的补全外鼻三维数据的面部协调性和边缘密合度较好,形态与原始三维颜面数据的鼻部形态接近。.