Clinical and radiographics results at 3 years of RCT with split-mouth design of submerged vs. nonsubmerged single laser-microgrooved implants in posterior areas

TVGG Dental Implant Identification System

Identifying the right accessories for installing the dental implant is a vital element that impacts the sustainability and the reliability of the dental prosthesis when the medical case of a patient is not comprehensive. Dentists need to identify the implant manufacturer from the x-ray image to determine further treatment procedures. Identifying the manufacturer is a high-pressure task under the scaling volume of patients pending in the queue for treatment. To reduce the burden on the doctors, a dental implant identification system is built based on a new proposed thinner VGG model with an on-demand client-server structure. We propose a thinner version of VGG16 called TVGG by reducing the number of neurons in the dense layers to improve the system’s performance and gain advantages from the limited texture and patterns in the dental radiography images. The outcome of the proposed system is compared with the original pre-trained VGG16 to verify the usability of the proposed system.

Clinical, radiographic, and biochemical evaluation of two-piece versus one-piece single implants with a laser-microgrooved collar surface after 5 years of functional loading

AIM

To compare the clinical and radiographic conditions and the expression of pro-inflammatory cytokines in peri-implant crevicular fluid (PICF) at two-piece/bone level (TP/BL) versus one-piece/tissue level (OP/TL) single implants with a laser-microgrooved collar after at least 5 years of loading.

MATERIALS AND METHODS

In total, 20 single TP/BL implants and 20 contralateral OP/TL implants, both with a laser-microgrooved collar surface, in 20 systemically and periodontally healthy subjects (12 males and 8 females, between the age of 36 and 64 [mean age of 49.7 ± 12.3 years]), were examined. Levels of IL-1β, IL-1RA, IL-6, IL-8, IL-17, b-FGF, G-CSF, GM-CSF, IFN, MIP-1β, TNF-α, and VEGF were assessed in PICF using the Bio-Plex 200 Suspension Array System. Plaque index (PI), probing depth (PD), bleeding on probing (BOP), and gingival recession (REC) were recorded. Radiographic crestal bone levels (CBL) were assessed at the mesial and distal aspects of the implant sites.

RESULTS

The mean PI, PD, BOP, and REC values had no significant differences in either group. A higher mean value of CBL with statistical difference was detected for TP/BL compared with OP/TL implants. The levels of IL-1β, IL-6, IL-8, GM-CSF, and MIP-1β and TNF-α were higher at TP/BL implants than at OP/TL implants. However, only IL-1β, IL-6, and TNF-α values presented significant differences between the groups.

CONCLUSIONS

Although after 5 years of loading single TP/BL and OP/TL implants with a laser-microgrooved collar surface presented similar good clinical conditions, a higher proinflammatory state and higher crestal bone loss were detected for TP/BL implants.

Osseo-densification versus conventional surgical technique in low density jaw bone: A split mouth in vivo study

BACKGROUND: The success of dental implants depend on implant design, surgical technique, bone density, implant morphology and postoperative care. Initial stability is utmost importance and is of concern in low density bone. The osseo-densification strategy enhance primary stability by raising density of the osteotomy site walls by non-subtractive drilling, unlike conventional technique. OBJECTIVE: The aim of this in vivo study was to assess and compare the osseo-densification implant drilling technique with conventional implant drilling in terms of primary implant stability along with other factors, plaque index, bleeding on probe, pocket depth and radiographic assessment of bone density, marginal bone loss using CBCT. METHOD: A total of 20 patients aged between 40 and 59 years were included in this research. A split-mouth configuration of 40 implants was used. In the osseo-densification group, specialized (Densah) bur kit was used to insert 20 implants on one side. In the conventional group, standard bur kit was used to insert 20 implants on the opposite side of the jaw. For each patient, clinical and radiographic assessment was performed at regular intervals at the beginning (immediately after surgery), seven months, and a year following surgery. RESULTS: With the exception of bone density, which was statistically significant in favour of the osseo-densification group immediately after surgery, primary and secondary stability, plaque index, bleeding on probe, pocket depth and even marginal bone loss were not significantly different between the two groups in this investigation. CONCLUSION: Osseo-densification technique provided a better primary stability in the low density bone cases thus, can be consider as a trustworthy treatment for speeding up the healing process while also maintaining marginal bone integrity following loading. Use of specialized bur while drilling procedure improves the density around the implants.

Deep Neural Networks for Dental Implant System Classification

In this study, we used panoramic X-ray images to classify and clarify the accuracy of different dental implant brands via deep convolutional neural networks (CNNs) with transfer-learning strategies. For objective labeling, 8859 implant images of 11 implant systems were used from digital panoramic radiographs obtained from patients who underwent dental implant treatment at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2019. Five deep CNN models (specifically, a basic CNN with three convolutional layers, VGG16 and VGG19 transfer-learning models, and finely tuned VGG16 and VGG19) were evaluated for implant classification. Among the five models, the finely tuned VGG16 model exhibited the highest implant classification performance. The finely tuned VGG19 was second best, followed by the normal transfer-learning VGG16. We confirmed that the finely tuned VGG16 and VGG19 CNNs could accurately classify dental implant systems from 11 types of panoramic X-ray images.