Automatic Versus Semiautomatic Registration of Digital Dental Cast to Cone Beam Computed Tomography Image

Settings:

Participants will be randomly selected from patients who will come to Oral and Maxillofacial Radiology department, Faculty of Dentistry, Cairo University for CBCT imaging for implant treatment.

Radiographic imaging of the patients by CBCT machine will be done at Oral and Maxillofacial Radiology Department, Faculty of Dentistry, Cairo University. While the steps of impression taking followed by stone dental cast pouring, then surface laser optical scanning of the patients' stone cast will be done at the Removable Prosthodontics Department, Faculty of Dentistry, Cairo University.

Variables:

The outcome of this study is accuracy and reliability of non-explored new registration technique (automatic registration) versus commonly used registration method (point-based registration).

Variables involved in this study includes: the CBCT image resolution, the accuracy of the surface optical scanner, the software used, the number of points used for registration (in point-based registration), the skills of the investigator who will carry out the registration procedures. To cancel the effect of these variables, Investigators are going to standardize the CBCT resolution, the surface optical scanner used, the software used in both registration techniques, the number of points used for point-based registration while regarding the investigator factor more than one will carry out the same procedures to assure the reliability and validity of the results.

Data sources and management:

• CBCT scanning: Each patient will be scanned by CBCT machine (Planmeca Promax 3D Mid - Asentajankatu, Helsinki, Finland) with a field of view that covers the entire jaw. Image will be exported and stored in DICOM (digital imaging and communication in medicine) format.
• Cast scanning: Dental cast will be obtained by taking impressions using alginate impression material and filling the impressions with plaster. The plaster cast will then be scanned by a 3D laser scanner to obtain digital image of the dental arch that will be exported and stored as STL (standard tessellation language) file.
• Image registration:

DICOM file of CBCT image and STL file of digital dental model will be imported to a dental 3D planning software (Blue Sky Plan, Blueskybio). Image registration of digital cast to CBCT images will be performed for each patient by two methods:

1. Automatic registration After importing the STL (standard tessellation language) file of the digital model, direct registration function of the software will be used to automatically perform the registration process.
2. Point-based registration Using point registration function of the software, three points will be selected at the same areas on the image of dental cast and CBCT image. Then, registration of both images will be automatically processed to finalize the superimposition of digital dental model to maxillofacial model. potential sources of bias:

• Investigators are going to standardize the CBCT resolution, the surface optical scanner used, the software used in both registration techniques, the number of points used for point-based registration.
• Registration will be performed by two oral radiologists independently; blinded from the results of each other.
• One of the radiologists will perform the registration twice with two weeks interval.
• Intra-observer and inter-observer will be evaluated to assure the reliability and validity of the results.

Study size:

investigators are planning a study of a continuous response variable from independent control and experimental subjects with 1 control(s) per experimental subject. In a previous study by Sang-Hoon in 2014 the response within each subject group was normally distributed with standard deviation 0.04. If the true difference in the experimental and control means is 0.07, investigators will need to study 12 subjects to be able to reject the null hypothesis that the population means of the experimental and control groups are equal with probability (power) 0.8. The Type I error probability associated with this test of this null hypothesis is 0.05.

Quantitative variables:

Handling of quantitative variables in the analyses The study involves two main groups; one for automatic registration and one for point based registration. Assessment of deviation in both groups will be made using a third party software and will be expressed in form of mean ± standard deviation in mm.

Statistical methods:

Data will be analysed using IBM SPSS advanced statistics (Statistical Package for Social Sciences), version 26 (SPSS Inc., Chicago, IL). Continuous data will be described using mean and standard deviation. Comparison between continuous data will be performed using t-test and ANOVA will be used to test interaction of variables. A p-value less than or equal to 0.05 will be considered statistically significant and all tests will be two tailed. Statistical power of the study will be set at 80 % with 95 % confidence level.