Generation and evaluation of 3D digital casts of maxillary defects based on multisource data registration: A pilot clinical study

• Published in: The Journal of prosthetic dentistry Vol. 118; no. 6; pp. 790 - 795
• Main Authors: Ye, Hongqiang, DDS, PhD, Ma, Qijun, BDS, Hou, Yuezhong, DDS, Li, Man, Zhou, Yongsheng, DDS, PhD
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-12-2017
• Subjects: Dentistry
• ISSN: 0022-3913; 1097-6841
• DOI: 10.1016/j.prosdent.2017.01.014

Abstract Statement of problem Digital techniques are not clinically applied for 1-piece maxillary prostheses containing an obturator and removable partial denture retained by the remaining teeth because of the difficulty in obtaining sufficiently accurate 3-dimensional (3D) images. Purpose The purpose of this pilot clinical study was to generate 3D digital casts of maxillary defects, including the defective region and the maxillary dentition, based on multisource data registration and to evaluate their effectiveness. Material and methods Twelve participants with maxillary defects were selected. The maxillofacial region was scanned with spiral computer tomography (CT), and the maxillary arch and palate were scanned using an intraoral optical scanner. The 3D images from the CT and intraoral scanner were registered and merged to form a 3D digital cast of the maxillary defect containing the anatomic structures needed for the maxillary prosthesis. This included the defect cavity, maxillary dentition, and palate. Traditional silicone impressions were also made, and stone casts were poured. The accuracy of the digital cast in comparison with that of the stone cast was evaluated by measuring the distance between 4 anatomic landmarks. Differences and consistencies were assessed using paired Student t tests and the intraclass correlation coefficient (ICC). In 3 participants, physical resin casts were produced by rapid prototyping from digital casts. Based on the resin casts, maxillary prostheses were fabricated by using conventional methods and then evaluated in the participants to assess the clinical applicability of the digital casts. Results Digital casts of the maxillary defects were generated and contained all the anatomic details needed for the maxillary prosthesis. Comparing the digital and stone casts, a paired Student t test indicated that differences in the linear distances between landmarks were not statistically significant ( P >.05). High ICC values (0.977 to 0.998) for the interlandmark distances further indicated the high degree of consistency between the digital and stone casts. The maxillary prostheses showed good clinical effectiveness, indicating that the corresponding digital casts met the requirements for clinical application. Conclusions Based on multisource data from spiral CT and the intraoral scanner, 3D digital casts of maxillary defects were generated using the registration technique. These casts were consistent with conventional stone casts in terms of accuracy and were suitable for clinical use.