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This study aimed to evaluate the relationship between osteoarthritic bony alterations in the temporomandibular joint (TMJ) and general bone mineral density (BMD) in postmenopausal edentulous females. Cone beam computed tomography (CBCT) scans for both TMJs were acquired for 80 clinically asymptomatic patients (mean age 72 ± 8.8 y). Both lumbar spine and femoral neck measurements of BMD were performed using dual-energy X-ray absorptiometry (DXA). The most frequently observed bony alterations were flattening of the articular surface (47.5%), sclerosis (41.5%), subcortical cysts (10%), and erosions (5%). Osteophytes were not observed. No statistical differences were observed between those who had or did not have radiological signs of bony alterations according to age or DXA scores. The prevalence of radiological findings of degenerative TMJ bony alterations in clinically asymptomatic postmenopausal females did not confirm a connection with a generally low BMD. [ABSTRACT FROM AUTHOR]

Deproteinised bovine bone (DBB) is widely used as bone substitute in maxillary sinus floor augmentation (MSFA) surgery. No previous studies have shown the long-term volumetric changes in the augmented bone when using DBB. The selected patients had MFSA performed using a lateral window technique and a xenograft, alone or in combination with the patient's autologous bone from the mandible. Cone beam computed tomography (CBCT) images were used to compare the volumetric changes in the augmented bone for patients over a period of 6 or more years. No significant bone reduction was seen in the augmented bone region when comparing MSFA after 7 months and 6 or more years after dental implantation. [ABSTRACT FROM AUTHOR]

Background/Aim: This study aimed to develop a protocol that combines cone‐beam computed tomography (CBCT), software, and 3D printing to design 3D replicas for tooth autotransplantation. The goal was to evaluate the impact of this approach on the extraoral time of the donor teeth and the total surgical time, thereby enhancing surgical efficiency and outcomes. Materials and Methods: A non‐randomized trial (protocol 10.1186/ISRCTN13563091) was conducted at Riga Stradins University, enrolling 46 patients (13–22 years old) who required molar extraction and possessed a non‐erupted third molar. The patients were sequentially assigned to a 3D replica group (24 patients) or a control group (22 patients). The primary outcome measured was the extra‐alveolar time of the donor tooth, and the secondary outcome was the total duration of surgery. Both were assessed using a sample size capable of detecting a 10‐min difference. A generalized linear model adjusted for various factors was used to test for significant time differences (p <.05) between the groups. Results: Forty‐six patients were included in this analysis. The effect of using 3D replicas was not statistically significant and was associated with a decrease in the extraoral time of the donor tooth in seconds (β = −9.35, 95% CI [−40.86, 22.16]). For the total surgical time in minutes, the use of 3D replicas had a statistically significant impact, reducing the operation duration in minutes (β = −13.42, 95% CI [−24.50, −2.34]). No early complications were observed in either group, with all teeth present at 3–4 weeks post‐surgery. Conclusions: The integration of 3D printing technology can enhance the efficiency of autotransplantation surgeries, primarily by reducing surgical time. [ABSTRACT FROM AUTHOR]

Introduction: Periapical lesions of teeth are typically evaluated using periapical X-rays (PA) or cone-beam computer tomography (CBCT); however, ultrasound imaging (US) can also be used to detect bone defects. A comparative analysis is necessary to establish the diagnostic accuracy of US for the detection of periapical lesions in comparison with PA and CBCT. Objectives: This study aimed to evaluate and compare the measurement precision of US against PA and CBCT in detecting periapical lesions. Methods: This study included 43 maxillary and mandibular teeth with periapical lesions. All teeth were examined clinically, radiographically, and ultrasonographically. Observers evaluated and measured the periapical lesions on CBCT, PA, and US images. Results: The comparison of lesion size showed that it differs significantly between the different methods of examination. A statistically significant difference was found between CBCT and US (mean difference = 0.99 mm, 95% CI [0.43–1.55]), as well as between CBCT and PA (mean difference = 0.61 mm, 95% CI [0.17–1.05]). No difference was found between the US and PA methods (p = 0.193). Conclusion: US cannot replace PA radiography in detecting pathologies but it can accurately measure and characterize periapical lesions with minimal radiation exposure. CBCT is the most precise and radiation-intensive method so it should only be used for complex cases. [ABSTRACT FROM AUTHOR]

Gradual bone loss around the implants is an ongoing concern. Mucosal tissue thickness is considered as a contributing factor that influences bone remodelling after implantation. It has been suggested that tissue thickness thinner than 2.5 mm may contribute to more peri-implant bone loss, eventually affecting implant bone stability. Measuring mucosal thickness prior to surgery may be a predictor of the bone changes and could modify the surgical methods. In this study mucosal tissue thickness was measured retrospectively on radiographs before implant insertion, one year and at least three years after implantation. Within the limits of this study, no influence of initial mucosal tissue thickness on long term peri-implant bone stability was found. [ABSTRACT FROM AUTHOR]

In this technical note, we examine the capabilities of deep convolutional neural networks (DCNNs) for diagnosing osteoporosis through cone-beam computed tomography (CBCT) scans of the mandible. The evaluation was conducted using 188 patients' mandibular CBCT images utilizing DCNN models built on the ResNet-101 framework. We adopted a segmented three-phase method to assess osteoporosis. Stage 1 focused on mandibular bone slice identification, Stage 2 pinpointed the coordinates for mandibular bone cross-sectional views, and Stage 3 computed the mandibular bone's thickness, highlighting osteoporotic variances. The procedure, built using ResNet-101 networks, showcased efficacy in osteoporosis detection using CBCT scans: Stage 1 achieved a remarkable 98.85% training accuracy, Stage 2 minimized L1 loss to a mere 1.02 pixels, and the last stage's bone thickness computation algorithm reported a mean squared error of 0.8377. These findings underline the significant potential of AI in osteoporosis identification and its promise for enhanced medical care. The compartmentalized method endorses a sturdier DCNN training and heightened model transparency. Moreover, the outcomes illustrate the efficacy of a modular transfer learning method for osteoporosis detection, even when relying on limited mandibular CBCT datasets. The methodology given is accompanied by the source code available on GitLab. [ABSTRACT FROM AUTHOR]

Deep neural networks are widely used in computer vision for image classification, segmentation and generation. They are also often criticised as "black boxes" because their decisionmaking process is often not interpretable by humans. However, learning explainable representations that explicitly disentangle the underlying mechanisms that structure observational data is still a challenge. To further explore the latent space and achieve generic processing, we propose a pipeline for discovering the explainable directions in the latent space of generative models. Since the latent space contains semantically meaningful directions and can be explained, we propose a pipeline to fully resolve the representation of the latent space. It consists of a Dirichlet encoder, conditional deterministic diffusion, a group-swap and a latent traversal module. We believe that this study provides an insight into the advancement of research explaining the disentanglement of neural networks in the community. [ABSTRACT FROM AUTHOR]

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Bone density of the femur body of rabbit was determined in vivo. Experimental osteoporosis was induced by ovariectomy and subsequent injections of methylprednisolone. In the greater trochanter region of right femur, defects were created and filled with granules of hydroxyapatite and tricalcium phosphate (HAP/TCP 70/30) or HAP/TCP 70/30 together with 5% strontium. After three months, the animals were euthanized. The bone mass density of the right and left body of femur was measured by cone beam computed tomography (CT) scan. The results of the study showed that the right femur of the rabbit, where biomaterials had been implanted, and the left femur, where no biomaterial implantation occurred, became denser after filling the defect with HAP/TCP 70/30 ceramic granules or 5% Sr modified HAP/TCP ceramic granules. There was no difference between operated and non-operated legs and HAP/TCP and HAP/TCP with 5% strontium groups. [ABSTRACT FROM AUTHOR]

Biphasic calcium phosphate ceramic granules (0.5–1.0 mm) with a hydroxyapatite and β-tricalcium phosphate ratio of 90/10 were used. Biphasic calcium phosphate ceramic granules produced in the Riga Technical University, Riga Rudolph Cimdins Biomaterials Innovation and Development Centre, were used for filling the bone loss on 18 patients with peri-implantitis. After 5 years at the minimum, clinical and 3D cone-beam computed tomography control was done. Clinical situation confirmed good stability of implants without any signs of inflammation around. Radiodensity of the previous gap and alveolar bone horizontally from middle point of dental implants showed similar radiodensity as in normal alveolar bone. This trial is registered with ISRCTN13514478. [ABSTRACT FROM AUTHOR]