International Journal of Computerized Dentistry最新文献

Connective tissue grafting (CTG) remains the gold standard method for soft tissue augmentation in periodontal therapy. However, donor site morbidity is a challenge since patient discomfort is frequently reported due to prolonged healing time with pain, inflammation, bleeding and sometimes even infection. Current techniques try to avoid complications relying on collagen membranes, platelet-rich fibrin (PRF), and palatal stents. This report introduces a digital workflow to fabricate 3D printed palatal stents individualized on virtual patients using an implant planning software program. The 3D-printed palatal stent is suggested to be more comfortable and effective to achieve a better patient-reported outcome related to CTG postoperative comfort.

Aim: Adjustments to the vertical dimension of occlusion (VDO) are frequently required in full-mouth rehabilitations. This study evaluated the effect of increased VDO on soft tissue height using three-dimensional (3D) facial scanning.

Materials and methods: Sixteen participants (10 female, 6 male; 30.6 ± 9.1 years) underwent baseline 3D facial scans at maximum intercuspation (SB) and a second scan (S0) to assess reproducibility. VDO was increased by 3 mm and 5 mm at the right central incisor for additional scans (S3, S5). SB was superimposed with S0, S3 and S5 to create colorcoded 3D models (M0, M3 and M5). Sixteen facial regions were analyzed using 3D software and evaluated with a mixed-effects model. Comparisons were made between SB and each VDO increase, without comparison between S3 and S5.

Result: A total of 768 facial regions were analyzed. Reproducibility was confirmed except for the right temporal region. Soft tissue height changes, along with increased intra-subject variability, were observed in the pogonion, gnathion, labrale inferius, buccal regions, masseter muscles, and eyebrows. Vertical increases occurred in the gnathion, masseter muscles, and eyebrows, while decreases were found in the pogonion, buccal regions, and labrale inferius. Asymmetries were noted in the masseter muscles and eyebrows. No significant changes were observed in the labrale superius, temporal regions, lower orbital rims, or temporal muscles.

Conclusion: Increasing VDO by 3 mm and 5 mm resulted in measurable changes in facial soft tissue height. 3D facial scanning proved to be a reliable method for detecting these adaptations.

Hybrid abutment crowns (HACs) have gained increased attention due to the time and cost efficiency as well as their reliability for restoring single-tooth implants in the posterior region. This article presents a digital approach to restore single-tooth gaps with implantsupported HACs in combination with a simultaneous occlusal device therapy within four appointments combining implant surgery with prosthetic and functional therapy. 3D implant planning, guided surgery, PEEK customized healing abutments, intraoral scanning, and movement registration of the lower jaw function were applied together to achieve the predictable result.

The present article describes a dental implant planning workflow to solve the CBCT artifact problem. The technique uses a radiopaque 3D-printed tray to take impressions and complete data alignment of the dental arches where implants are planned. From the impressions, 3D Boolean inversion is performed to obtain the surface mesh of teeth and virtually remove the undercut of dentition mesh before an implant surgical guide is designed. The trueness and precision of 3D alignment are then compared with the original radiographic template alignment using the double-scan method. In the present study, the results showed that this method could improve alignment trueness and allow for the elimination of radiographic template making, reducing patient visits and making possible a same-day guided implant surgery.

Aim: The present study aimed to compare the responses and satisfaction reported by users with varying levels of experience regarding different types of CAD software programs to design crowns.

Materials and methods: A questionnaire was used to evaluate user responses to five domains (software visibility, 3D-scanned data preparation, crown design and adjustment, finish line registration, and overall experience) of various CAD software programs. The study included 50 undergraduate dental students (inexperienced group) and 50 dentists or dental technicians from two hospitals (experienced group). The participants used four different CAD software programs (Meshmixer, Exocad, BlueSkyPlan, and Dentbird) to design crowns, then recorded their responses on a questionnaire. Statistical analyses included one-way and two-way analysis of variance (ANOVA) to compare scores and verify the interaction between user response and experience.

Results: User evaluation scores in the domains of software visibility and 3D-scanned data preparation varied between software programs (P 0.001), with Exocad being favored by the experienced group. When evaluating crown design and finish line registration, Dentbird and Exocad scored significantly higher than the other software programs in both groups as they offered automation of the process using deep learning (P 0.001). Two-way ANOVA showed that prior experience of using CAD software significantly affected the users' responses to all questions (P 0.001).

Conclusions: User response and satisfaction varied with the type of CAD software program used to design dental prostheses, with prior experience of using such software playing a significant role. Automation of design functions can enhance user satisfaction with the software.

Aim: This article reports on a novel digital superimposition workflow that enables measuring the supracrestal peri-implant soft tissue dimensions at each stage of the implant treatment process and beyond.

Materials and methods: A preoperative CBCT scan and intraoral scans (IOSs) were successively taken before surgery, at the end of the healing period, at prosthesis delivery, and over time. The scans were digitally superposed using dedicated software. Then, the stereolithography (STL) files of the healing abutment, prosthetic abutment, and crown were successively merged into the superposition set of IOSs.

Results: The workflow protocol of successively merging the STL of each item into the superposition set of IOSs enabled capturing the dimensions of the height and width of the supracrestal soft tissue at every level of the healing abutment, prosthetic abutment, and crown. In addition, it allowed measuring the vertical distance at which the crown exerts pressure on the gingiva as well as the thickness of the papillae at every level of the abutment.

Conclusion: This novel digital superimposition workflow provides a straightforward method of measuring the vertical and horizontal dimensions of the supracrestal peri-implant soft tissue, including the papillae, at each stage of the implant treatment process and beyond. It allows investigating a certain number of soft tissue variables that were previously inaccessible to clinical research. The workflow should help to enhance our comprehension of peri-implant soft tissue dynamics.

Objective: The purpose of the present study was to assess the accuracy of full-coverage crowns produced by two manufacturing methods: additive 3D printing and subtractive milling utilizing three different predefined cement spaces.

Materials and methods: Nine groups were allocated based on the manufacturing method and the predefined cement space: printed wax with a 20-µm cement space (PW1); printed wax with a 50-µm cement space (PW2); printed wax with a 100-µm cement space (PW3); milled wax with a 20-µm cement space (MW1); milled wax with a 50-µm cement space (MW2); milled wax with a 100-µm cement space (MW3); milled zirconia coping with a 20-µm cement space (MZ1); milled zirconia coping with a 50-µm cement space (MZ2); milled zirconia coping with a 100-µm cement space (MZ3). All fabricated specimens were scanned using a Medit Identica Blue 3D scanner and saved as standard tessellation language (STL) files. A triple scan method was performed using Materialise 3-matic software to assess accuracy. The discrepancy values were recorded in micrometers (µm), and the analysis was conducted using one-way analysis of variance (ANOVA).

Results: The wax printing method, with a cement gap design of 100 μm, demonstrated a significant improvement in accuracy compared with the other methods (P 0.01). In contrast, the zirconia milling method exhibited significantly lower accuracy relative to the other techniques (P 0.01). Moreover, different cement spaces resulted in various accuracy levels, but the only statistically significant difference was observed for the 100-µm cement space in the printed wax group (PW3).

Conclusion: The additive 3D-printing method exhibited greater accuracy than the subtractive milling method. Furthermore, altering the cement gap was found to impact the accuracy of both techniques, albeit without statistical significance.

Aim: Malocclusion has emerged as a burgeoning global public health concern. Individuals with an anterior crossbite face an elevated risk of exhibiting characteristics such as a concave facial profile, negative overjet, and poor masticatory efficiency. In response to this issue, a convolutional neural network (CNN)-based model is proposed, designed for the automated detection and classification of intraoral images and videos.

Materials and methods: A total of 1865 intraoral images were included in the present study, 1493 (80%) of which were allocated for training, and 372 (20%) for testing the CNN. Additionally, the models on 10 videos were tested, spanning a cumulative duration of 124 s. To assess the performance of the present authors' predictions, metrics including accuracy, sensitivity, specificity, precision, F1 score, area under the precision-recall (AUPR) curve, and area under the receiver operating characteristic (ROC) curve(AUC) were employed.

Results: The trained model exhibited commendable classification performance, achieving an accuracy of 0.965 and an AUC of 0.986. Moreover, it demonstrated superior specificity (0.992 vs 0.978 and 0.956, P 0.05) in comparison with assessments by two orthodontists. Conversely, the CNN model displayed diminished sensitivity (0.89 vs 0.96 and 0.92, P 0.05) relative to the orthodontists. Notably, the CNN model accomplished a perfect classification rate, successfully identifying 100% of the videos in the test set.

Conclusion: The deep learning (DL) model exhibited remarkable classification accuracy in identifying anterior crossbite through both intraoral images and videos. This proficiency has the potential to expedite the detection of severe malocclusions, facilitating timely classification for appropriate treatment and, consequently, mitigating the risk of complications.

Aim: Condylar hyperplasia (CH) is a progressive and deforming disease that modifies the anatomy of the temporomandibular joint (TMJ) structures. The present study aims to correlate the metabolic bone activity of the condyle measured by single photon emission computed tomography (SPECT) with the volumetry anatomical information from the condyle, fossa, and joint space provided by CT images in patients with CH in the active and passive states.

Materials and methods: A cross-sectional comparative study was performed with a set of 116 images from healthy and diagnosed CH patients to compare volumetric measures of the TMJ. Images were acquired through a bone tissue mask using a 3D DICOM reconstruction for SPECT/CT and CBCT images and the threshold option for segmentation with standardized values for each tissue on the Hounsfield unit (HU) scale.

Results: Differences were found (P 0.01), with greater condylar volume on the affected side in patients with active compared with passive CH. The volume of the glenoid cavity showed no differences in either state of CH (P > 0.05); however, there were differences for the volume of the joint space on the affected right side of hemimandibular elongation (HE) in the active state. The volume of the mandibular condyle on the affected side in CH cases was larger in HE cases in both active and passive forms (P 0.01) compared with healthy patients (controls). Similar results were presented for the glenoid cavity and joint space.

Conclusions: Volumetric anatomical evaluation of TMJ structures as well as information on condylar metabolic activity can be obtained from SPECT/CT. The present study showed a greater condylar volume on the affected side of the CH compared with the contralateral side, but there were more significant differences in the active than in the passive state.

Aim: The aim of the present study was to evaluate the physical-mechanical behavior of occlusal veneers when subjected to thermomechanical cycling.

Materials and methods: Sixty specimens were divided into four groups (n = 15) according to different restorative materials and thicknesses: lithium disilicate (IPS e.max CAD) and nano-ceramic resin (Lava Ultimate) materials at thicknesses of 0.6 and 1.2 mm. The occlusal veneers were bonded over human freshly extracted flattened molars with dual-polymerizing luting agent (Variolink N and RelyX Ultimate) using the respective adhesive systems following the selective-etch technique (self-etch in dentin and total-etch in enamel). The resin cement was light cured for 40 s on each face using light-emitting diode (LED) light-cure equipment (Blue Star 2; 1100 mW/cm2). The response variables were veneer survival rates (crack formation, catastrophic cracks, and debonding) when subjected to thermal cycling from 5°C to 55°C and simultaneous mechanical cycling performed at load intensities of 100, 200, 300, 400, and 450 N for 20,000 cycles each.

Results: Data were submitted to the Kruskal-Wallis test and pairwise comparison, adopting a significance level of 5%. The occlusal veneers made of nano-ceramic resin presented a lower incidence of failures (P 0.05) than those made of lithium disilicate. According to the thickness factor, 1.2-mm-thick occlusal veneers withstood higher cycling loads.

Conclusion: The occlusal veneers made of nano-ceramic resin with a 1.2-mm thickness presented superior physical-mechanical behavior than those made of lithium disilicate with a 0.6-mm thickness. (Int J Comput Dent 2025;28(3):275-0; doi: 10.3290/j.ijcd.b5290647).