Objectives: The primary objective of the present study was to find the gold-standard accuracy of voxel-based superimposition of cone-beam computed tomography (CBCT) datasets with a protocol developed for the Dolphin Imaging 3D software. The secondary objectives were to analyze reproducibility and efficiency of this protocol. Study Design: Twenty-five CBCT datasets of patients with dental implants present were selected. Each Base Volume dataset was duplicated to create a second volume. Subsequently, both volumes were superimposed with a voxel-based protocol consisting of 3 successive steps “Side-by-side Superimposition”; “Overlay Superimposition”; and “Export Orientation to 2nd Volume”. The protocol's accuracy was evaluated by measuring the mean distance between the apex of each dental implant on the Base Volume and second volume datasets. Efficiency was given by the mean time needed to complete all superimposition steps. Reproducibility was analyzed by calculating the intraclass correlation coefficients. Results: Mean time needed to complete the protocol was 198 seconds. The protocol had a rotational accuracy of 0.10° to 019° and a translational accuracy of 0.20 to 0.24 mm. Intra-observer and inter-observer reproducibility were 1 and 0.921 to 1, respectively. Conclusions: The protocol is accurate, precise, reproducible, and efficient. The validation of this method enables unbiased analysis of surgical outcomes based on a single, user-friendly software product that is widely available in academic and clinical settings.

The objective was to validate a semi-automated segmentation method for 3-dimensional (3D) reconstruction of the mandibular condyle from cone beam computed tomography (CBCT) data and illustrate its application in volumetric analysis of the condyle. Ten CBCT datasets were used to validate the proposed semi-automatic method for 3D rendering of mandibular condyles. First, a standardized orientation protocol of the skull was applied. After defining the volume of interest, a grey-scale cut-off value was selected to allow an automatic reconstruction of the condyle's surface. Subsequently, condylar contour was optimized manually. The whole process was repeated twice by 2 independent investigators. Volumetric measurements of the condyle were used as a measure of conformity between both investigators. The reproducibility of condylar volume reconstruction was excellent for intra-examiner measurements (CV = 3.65%, intraclass correlation coefficient = 0.97) and good for inter-examiner measurements (CV = 7.15%, ICC = 0.89). The overall mean time required for the segmentation process was 6.31 + 2.78 minutes. The proposed protocol provides an accurate and reproducible tool for 3D reconstruction of the mandibular condyle using CBCT data. Its implementation will enable adequate follow-up of morphological changes in bone tissue with a Hounsfield unit-based imaging segmentation method.

Statement of the problem: Most of the clinical documentation of implant success and survival published in the literature have been issued by either experienced teams from university settings involving strict patient selection criteria or from seasoned private practitioners. By contrast, studies focusing on implants placed and rehabilitated by inexperienced post-graduate students are scarce. Purpose: To record failure rates and identify the contributing factors to implant failure and marginal bone loss (MBL) of implants placed and rehabilitated by inexperienced post-graduate students at the one-year follow-up. Material and Methods: A prospective cohort study was conducted on study participants scheduled for implant therapy at the International University of Catalonia. An experienced mentor determined the treatment plan in accordance with the need of each participant who signed an informed consent. All surgeries and prosthetic rehabilitation were performed by the post-graduate students. Implant failure rate, contributors to implant failure, and MBL were investigated among 24 variables related to patient health, local site, and implant and prosthetic characteristics. The risk of implant failure was analyzed with a simple binary logistic regression model with generalized equation equations (GEE) models, obtaining unadjusted odds ratios (OR). The relationship between MBL and the other independent variables was studied by simple linear regression estimated with GEE models and the Wald chi² test. Results: One hundred and thirty dental implants have been placed and rehabilitated by post-graduate students. Five implants failed before loading and none after restoration delivery; survival and success rates were 96.15% and 94.62%, respectively. None of the investigated variables significantly affected the implant survival rate. At the one-year follow-up, the mean (SD) MBL was 0.53 (0.39) mm. The following independent variables significantly affected the MBL: Diabetes, implant depth placement. The width of keratinized tissue (KT) and probing depth (PD) above 3 mm were found to be good indicators of MBL, with each additional mm of probing depth resulting in 0.11 mm more MBL. Conclusion: The survival and success rates of dental implants placed and rehabilitated by inexperienced post-graduate students at the one-year follow-up were high. No contributing factor was identified regarding implant failure. However, several factors significantly affected MBL: Diabetes, implant depth placement, PD, and width of KT. Clinical Implications: Survival and success rates of dental implants placed and rehabilitated by inexperienced post-graduate students were high at the one-year follow-up, similar to experienced practitioners. No contributing factors were identified regarding implant failure; however, several factors significantly affected MBL: Diabetes, implant depth placement, PD, and KM.