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Key Points Discusses the latest technologies in 3D imaging and printing that can be applied in dentistry. Suggests these technologies could be used in daily practice. 3D printing has been hailed as a disruptive technology which will change manufacturing. Used in aerospace, defence, art and design, 3D printing is becoming a subject of great interest in surgery. The technology has a particular resonance with dentistry, and with advances in 3D imaging and modelling technologies such as cone beam computed tomography and intraoral scanning, and with the relatively long history of the use of CAD CAM technologies in dentistry, it will become of increasing importance. Uses of 3D printing include the production of drill guides for dental implants, the production of physical models for prosthodontics, orthodontics and surgery, the manufacture of dental, craniomaxillofacial and orthopaedic implants, and the fabrication of copings and frameworks for implant and dental restorations. This paper reviews the types of 3D printing technologies available and their various applications in dentistry and in maxillofacial surgery.

Key Points Explores the effect of various dental implant surfaces on osseointegration. Explains different materials, designs and surface characteristics that are available for dental implants. Discusses the techniques that are used to modify dental implant surfaces to provide more predictable outcomes. Aim The aim of this literature review is to find current knowledge of dental implants focusing on materials, designs and surface modifications and to understand which implant surfaces have more predictable clinical outcomes. Research material and methods An electronic search using PubMed/Medline, Scopus and The Cochrane Library databases from 1950 onwards was conducted using keywords and terms. Published papers were then obtained online or from specialist libraries. References from individual published papers were also searched for relevant publications. Results Different designs, materials and methods to modify surfaces of implants have been discussed in this paper. Many laboratory studies using animal models reported improved biological outcomes with surface modification of implants at the microscopic level. Despite pure titanium being commercially the prime material of choice, ceramics have the potential to become the next generation of dental implants. Presently there is not sufficient scientific evidence for routine use of ceramic implants. Conclusions Pure titanium is the ideal material for implants. Rough implant surfaces are believed to deliver better osseointegration compared with smooth surfaces however, results from different studies vary. It is not clear which combination of different surface modifications provide a more predictable outcome. More standardised high quality prospective studies are required to prove which implant surfaces have the optimum properties for replacing missing teeth.

Few investigations have evaluated the 3-dimensional (3D) accuracy of digital implant scans. The aim of this study was to evaluate the performance of 10 intraoral scanners (IOSs) (CEREC Omnicam, CEREC Primescan, CS 3600, DWIO, i500, iTero Element, PlanScan, Trios 2, Trios 3, and True Definition) in obtaining the accurate positions of 6 cylinders simulating implant scan bodies. Digital scans of each IOS were compared with the reference dataset obtained by means of a coordinate measuring machine. Deviation from the actual positions of the 6 cylinders along the XYZ axes and the overall 3D deviation of the digital scan were calculated. The type of IOSs and position of simulated cylindrical scan bodies affected the magnitude and direction of deviations on trueness. The lowest amount of deviation was found at the cylinder next to the reference origin, while the highest deviation was evident at the contralateral side for all IOSs ( p  < 0.001). Among the tested IOSs, the CEREC Primescan and Trios 3 had the highest trueness followed by i500, Trios 2, and iTero Element, albeit not statistically significant ( p  > 0.05), and the DWIO and PlasScan had the lowest trueness in partially edentulous mandible digital implant scans ( p  < 0.001).

Graphene based materials (GBMs) have potentials for dental and medical applications. GBMs may cause changes in the levels of cytokine released in the body. This study aimed to study the corrosion resistance of graphene oxide (GO) and GO/silver (GO/Ag) nanocomposite coated nickel-titanium (NiTi) alloy by electrophoretic deposition and to access the viability of human pulp fibroblasts, and the interleukin (IL)-6 and IL-8 expression level. The bare and coated NiTi samples were characterized by scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), Raman spectroscopy, surface profilometry, and X-ray diffraction (XRD). The corrosion resistance of the bare NiTi and coated NiTi samples were investigated by potentiodynamic polarization and electrochemical impedance spectroscopy in 3.5% NaCl solution. The cell viability of human pulp fibroblasts was accessed by the treated culture medium of the bare NiTi and coated NiTi alloys containing 1% fetal bovine serum. IL-6 and IL-8 expression levels were studied by human enzyme-linked immunosorbent assay (ELISA). Data were analyzed using One-way ANOVA (α  =  0.05). Both the GO-coated NiTi and GO/Ag-coated NiTi alloys showed better corrosion resistance, a lower rate of corrosion, and higher protection efficiency than the bare NiTi alloy. The coated NiTi alloys were biocompatible to human pulp fibroblasts and showed upregulation of IL-6 and IL-8 levels.

This study aims to evaluate the potential enhancement in implant classification performance achieved by incorporating artificially generated images of commercially available products into a deep learning process of dental implant classification using panoramic X-ray images. To supplement an existing dataset of 7,946 in vivo dental implant images, a three-dimensional scanner was employed to create implant surface models. Subsequently, implant surface models were used to generate two-dimensional X-ray images, which were compiled along with original images to create a comprehensive dataset. Images of 10 types of implants were classified using ResNet50 into the following datasets: (A) images of implants captured in vivo, (B) artificial implant images generated without background adjustments, and (C) implant images derived from in vivo images and generated with background adjustments. The classification accuracy was 0.8888 for dataset A, 0.903 for dataset B, and 0.9146 for dataset C. Notably, dataset C demonstrated the highest performance and exhibited the optimal feature distribution. In the context of deep learning classifiers for dental implants using panoramic X-ray images, incorporating artificially generated X-ray images—designed to mirror the appearance of human body implants—proved to be the most beneficial in enhancing the performance of the classification model.

There are various techniques to measure accuracy of dental implant surgery, but limited data validating the techniques used to analyze accuracy. Scan-body-assisted surface-based registration (SB-SBR) is deemed theoretically accurate, but with challenges in testing accuracy. The purpose of the study was to analyze the accuracy of SB-SBR for conventional (CVI) and zygomatic implants (ZI) using 2 complementary techniques. An in-vitro study was designed using a 3D-printed model of an edentulous maxilla with CVI and ZI digitally planned and placed. SB-SBR was performed on the physical model and on a model-free virtual setting, and the implant position was compared with those of the planned implants 10 times. Outcome variables were angular and linear errors (AE and LE), with thresholds of 1° and 1 mm. Paired t-test and Wilcoxson signed-ranked test were used. Results showed greater AE for ZI versus CVI (mean difference, MD 0.42°). Apical LE was greater for ZI (MD 0.68 mm), while CVI exhibited greater platform LE (MD 0.69 mm). Overall AE remained under 1°, but the apical LE of ZI exceeded 1 mm, which could potentially lead to violation of critical structures when combined with surgical error, highlighting the need for caution when interpreting data derived from SB-SBR especially for ZI.

Accurate segmentation of oral surgery-related tissues from cone beam computed tomography (CBCT) images can significantly accelerate treatment planning and improve surgical accuracy. In this paper, we propose a fully automated tissue segmentation system for dental implant surgery. Specifically, we propose an image preprocessing method based on data distribution histograms, which can adaptively process CBCT images with different parameters. Based on this, we use the bone segmentation network to obtain the segmentation results of alveolar bone, teeth, and maxillary sinus. We use the tooth and mandibular regions as the ROI regions of tooth segmentation and mandibular nerve tube segmentation to achieve the corresponding tasks. The tooth segmentation results can obtain the order information of the dentition. The corresponding experimental results show that our method can achieve higher segmentation accuracy and efficiency compared to existing methods. Its average Dice scores on the tooth, alveolar bone, maxillary sinus, and mandibular canal segmentation tasks were 96.5%, 95.4%, 93.6%, and 94.8%, respectively. These results demonstrate that it can accelerate the development of digital dentistry.

This study aimed to investigate the effects of crown seating speed, crown seating force, quantity of cement used, and type of implant cement on the amount of remnant cement in the subgingival region (RCS) after cementation. Cement-retained implant crowns were cemented to titanium abutments using the following methods: four types of implant cement (TBN: TEMP BOND NE, NR: NEXUS RMGI, ME: MAXCEM ELITE, and U200: RELYX U200), three quantities of cement (0.02 ml, 0.04 ml, and 0.06 ml), three crown seating speeds (5 mm/s, 10 mm/s, and 15 mm/s), and two crown seating forces (25 N, 50 N). The surface area and length of the RCS were measured using a 3D intraoral scanner. The total RCS weight was measured using an analytical balance. The RCS increased significantly as the seating speed increased, the seating force increased, and the quantity of cement increased ( p  < 0.05). The RCS values were the highest for TBN, followed by U200, NR, and ME ( p  < 0.05). The lower seating speed, smaller quantity of cement used, and smaller seating force applied in cement-retained implant restorations minimized the RCS in cement-retained prostheses. The type of cement is a factor that determines the aspects of the RCS.

In this in vitro study, the use of a 445 nm diode laser was investigated for the decontamination of titanium dental implants. Different irradiation protocols and the effect of repetitive laser irradiation on temperature increase and decontamination efficacy were evaluated on titanium implant models. An automated setup was developed to realize a scanning procedure for a full surface irradiation to recapitulate a clinical treatment. Three irradiation parameter sets A (continuous wave, power 0.8 W, duty cycle (DC) 100%, and 5 s), B (pulsed mode, DC 50%, power 1.0 W, and 10 s), and C (pulsed mode, DC 10%, power 3.0 W, and 20 s) were used to treat the rods for up to ten consecutive scans. The resulting temperature increase was measured by a thermal imaging camera and the decontamination efficacy of the procedures was evaluated against Escherichia coli and Staphylococcus aureus, and correlated with the applied laser fluence. An implant’s temperature increase of 10 °C was set as the limit accepted in literature to avoid thermal damage to the surrounding tissue in vivo. Repeated irradiation of the specimens resulted in a steady increase in temperature. Parameter sets A and B caused a temperature increase of 11.27 ± 0.81 °C and 9.90 ± 0.37 °C after five consecutive laser scans, respectively, while parameter set C resulted in a temperature increase of only 8.20 ± 0.53 °C after ten surface scans. The microbiological study showed that all irradiation parameter sets achieved a complete bacterial reduction (99.9999% or 6-log 10 ) after ten consecutive scans, however only parameter set C did not exceed the temperature threshold. A 445 nm diode laser can be used to decontaminate dental titanium rods, and repeated laser irradiation of the contaminated areas increases the antimicrobial effect of the treatment; however, the correct choice of parameters is needed to provide adequate laser fluence while preventing an implant’s temperature increase that could cause damage to the surrounding tissue.