The Suitability of Trabecular Patterns in the Assessment of Dental Implant Osseointegration Process through 2D Digital and 3D CBCT Radiographs.

OBJECTIVE: The research aims to determine the suitability of the trabecular pattern in the assessment of the dental implant osseointegration process through two-dimensional (2D) digital and three-dimensional (3D) cone-beam computed tomography (CBCT) radiographs. MATERIALS AND METHODS: This is a correlation description that explains the relationship between variables. The population consisted of 24 data points on 3D CBCT and 2D digital radiographs from the procedure after dental implants were inserted into the tibia of a New Zealand white rabbit (Oryctolagus cuniculus) on days 3, 14, and 28. The radiograph was selected based on the region of interest (ROI), which covers the peri-implant area with a width of 1 mm and length following the height of the implant. The ROI was analyzed for trabecular thickness (Tb.Th), separation (Tb.Sp), number (Tb.N), and fractal dimension. STATISTICAL ANALYSIS: The intraclass correlation coefficient (ICC) was used to statistically test the data to assess the consistency of intraobserver measurements and the r value (Pearson's correlation coefficient). This determines the correlation between trabecular patterns in both radiographic modalities and the Bland-Altman plot to observe the limits of acceptable discrepancies. RESULTS: The ICC test showed high intraobserver consistency in trabecular pattern measurements on 2D digital radiographs and 3D CBCT. The trabecular space pattern and number showed an r value of 0.88 with radiographic modalities of 0.72 mm and 0.018, respectively. Additionally, the trabecular thickness and fractal dimension had an insignificant correlation, with an r value of 0.22, and the mean of the 2D radiograph was lower than that of CBCT. CONCLUSION: The 2D radiograph and 3D CBCT showed correlations in the trabecular number and space results but had no correlation in the trabecular thickness and fractal dimension results. Based on intraclass correlation analysis, 3D CBCT appeared to be more reliable for measuring trabecular patterns (Tb.Th, Tb.Sp, Tb.N, and fractal dimension) than 2D radiograph.

Analysis of Bone Density and Bone Morphometry by Periapical Radiographs in Dental Implant Osseointegration Process.

Objective: This research aimed to analyze the differences in bone density and bone morphometry by periapical implant radiography in the dental implant osseointegration stages. Methods: This experimental research uses 12 periapical radiographs of tibial bones from a New Zealand white rabbit (Oryctolagus cuniculus). The analysis was performed on day 3, 14, and 28 of the osseointegration stages with density, trabecular thickness (Tb.Th.), trabecular separation (Tb.Sp.), and trabecular number (Tb.N.) as parameters. The implant used is a titanium alloy and coated by SA (sunblasted with alumina acid) of 4 mm in diameter and 7 mm in length. The radiographic assessment of the osseointegration process is obtained with the region of interest (ROI) segmentation results. Additionally, each ROI was analyzed for bone density and morphometry using the open-source ImageJ software with the BoneJ plugin. The significant difference was evaluated by analysis of variance (F-test) with p < 0.05 and nonparametric Kruskal-Wallis test with p < 0.05. Results: Analysis of the osseointegration images of dental implants at day 3, 14, and 28 with the periapical X-ray modality shows significant differences (p < 0.05) in the parameters measuring density and trabecular thickness (Tb.Th.). In the variables of trabecular separation (Tb.Sp.) and number (Tb.N.) (p > 0.05), there is no significant difference. Conclusion: Based on the results, density and trabecular thickness (Tb.Th.) showed a significant difference between healing times. However, trabecular separation (Tb.Sp.) and trabecular number (Tb.N.) showed no difference in healing time.

Micro Computed Tomography and Immunohistochemistry Analysis of Dental Implant Osseointegration in Animal Experimental Model: A Scoping Review.

Osseointegration is a complex process that involves the interaction of dental implants, bone, and the immune system. Preclinical testing was carried out to develop a better understanding of the mechanism. Micro-computed tomography (micro-CT) imaging techniques and immunohistochemistry are excellent tools for this objective as both enable quantitative assessment of bone microarchitecture and intercellular interaction. An extensive literature search was conducted using the databases PubMed, Science Direct, Wiley Online, Proquest and Ebscohost from January 2011 to January 2021. Among the publications retrieved, the rat model was the most frequently used experimental protocol, with the tibia being the most frequently implanted site. The region of interest demonstrates a high degree of homogeneity as measured by trabecula but varies in size and shape. The most frequently mentioned micro-CT bone parameter and immunohistochemistry bone markers were bone volume per total volume (BV/TV) and runt-related transcription factors (RUNX). Animal models, micro-CT analysis methods, and immunohistochemistry biomarkers yielded a variety of results in the studies. Understanding bone architecture and the remodeling process will aid in the selection of a viable model for a specific research topic.

Temporal Pattern of micro-CT Angiography Vascular Parameters and VEGF mRNA Expression in Fracture Healing: a Radiograph and Molecular Comparison.

Angiogenesis plays an important role in fracture healing with vascular endothelial growth factor (VEGF) as the main protein involved. Micro-computed tomography (CT) angiography may be used to analyze this revascularization with several parameters such as number of branches, total volume, and diameter. This systematic review is aimed to assess available studies on the temporal pattern of vascular imaging on micro-CT angiographs, especially in terms of the number of branches, total volume, and diameter as well as the temporal pattern of VEGF mRNA expression as the molecular comparison during bone fracture healing. This review was conducted according to the PRISMA guidelines. Electronic database searches were performed using PubMed, ProQuest, ScienceDirect, EBSCOhost, Taylor & Francis Online, and hand searching. The search strategy and keywords were adjusted to each database using the Boolean operators and other available limit functions to identify most relevant articles based on our inclusion and exclusion criteria. Screening and filtration were done in several stages by removing the duplicates and analyzing each title, abstract, and full-text in all included entries. Data extraction was done for syntheses to summarize the temporal pattern of each parameter. A total of 28 articles were eligible and met all criteria, 11 articles were synthesized in its angiograph's analysis, 16 articles were synthesized in its VEGF mRNA expression analysis, and 1 article had both parameters analyzed. The overall temporal pattern of both three micro-CT angiographic parameters and VEGF mRNA expression was in line qualitatively. The number of branches, total volume, and diameter of the blood vessels in micro-CT angiography showed an exponential rise at week 2 and decline at week 3 of fracture healing, with the VEGF mRNA expression concurrently showing a consistent pattern in the phase.

Enhancement of conformational B-cell epitope prediction using CluSMOTE.

BACKGROUND: A conformational B-cell epitope is one of the main components of vaccine design. It contains separate segments in its sequence, which are spatially close in the antigen chain. The availability of Ag-Ab complex data on the Protein Data Bank allows for the development predictive methods. Several epitope prediction models also have been developed, including learning-based methods. However, the performance of the model is still not optimum. The main problem in learning-based prediction models is class imbalance. METHODS: This study proposes CluSMOTE, which is a combination of a cluster-based undersampling method and Synthetic Minority Oversampling Technique. The approach is used to generate other sample data to ensure that the dataset of the conformational epitope is balanced. The Hierarchical DBSCAN algorithm is performed to identify the cluster in the majority class. Some of the randomly selected data is taken from each cluster, considering the oversampling degree, and combined with the minority class data. The balance data is utilized as the training dataset to develop a conformational epitope prediction. Furthermore, two binary classification methods, Support Vector Machine and Decision Tree, are separately used to develop model prediction and to evaluate the performance of CluSMOTE in predicting conformational B-cell epitope. The experiment is focused on determining the best parameter for optimal CluSMOTE. Two independent datasets are used to compare the proposed prediction model with state of the art methods. The first and the second datasets represent the general protein and the glycoprotein antigens respectively. RESULT: The experimental result shows that CluSMOTE Decision Tree outperformed the Support Vector Machine in terms of AUC and Gmean as performance measurements. The mean AUC of CluSMOTE Decision Tree in the Kringelum and the SEPPA 3 test sets are 0.83 and 0.766, respectively. This shows that CluSMOTE Decision Tree is better than other methods in the general protein antigen, though comparable with SEPPA 3 in the glycoprotein antigen.

Image quality assessment of pre-processed and post-processed digital panoramic radiographs in paediatric patients with mixed dentition.

PURPOSE: To determine the impact of an image processing technique on diagnostic accuracy of digital panoramic radiographs for the assessment of anatomical structures in paediatric patients with mixed dentition. MATERIALS AND METHODS: The study consisted of 50 digital panoramic radiographs of children aged from 6 to 12 years, which were later on processed using a dedicated image processing method. A modified clinical image quality evaluation chart was used to evaluate the diagnostic accuracy of anatomical structures in maxillary and mandibular anterior and maxillary premolar region of processed images. RESULTS: A statistically significant difference was observed between pre and post-processed evaluation of anatomical structures (P<0.05) in the maxillary and mandibular anterior region. The anterior region was found to be more accurate in post-processed images. No significant difference was observed in the maxillary premolar region (P>0.05). The Inter-observer and intra-observer reliability of both pre and post processed images were excellent (>0.82) for anterior region and good (>0.63) for premolar region. CONCLUSION: The application of image processing technique in digital panoramic radiography can be considered a reliable method for improving the quality of anatomical structures in paediatric patients with mixed dentition.

Image quality assessment of pre-processed and post-processed digital panoramic radiographs in paediatric patients with mixed dentition

PURPOSE: To determine the impact of an image processing technique on diagnostic accuracy of digital panoramic radiographs for the assessment of anatomical structures in paediatric patients with mixed dentition. MATERIALS AND METHODS: The study consisted of 50 digital panoramic radiographs of children aged from 6 to 12 years, which were later on processed using a dedicated image processing method. A modified clinical image quality evaluation chart was used to evaluate the diagnostic accuracy of anatomical structures in maxillary and mandibular anterior and maxillary premolar region of processed images. RESULTS: A statistically significant difference was observed between pre and post-processed evaluation of anatomical structures (P 0.05). The Inter-observer and intra-observer reliability of both pre and post processed images were excellent (>0.82) for anterior region and good (>0.63) for premolar region. CONCLUSION: The application of image processing technique in digital panoramic radiography can be considered a reliable method for improving the quality of anatomical structures in paediatric patients with mixed dentition.