Accuracy of automated forensic dental age estimation lab (F-DentEst Lab) on large Malaysian dataset.

When a disaster occurs, the authority must prioritise two things. First, the search and rescue of lives, and second, the identification and management of deceased individuals. However, with thousands of dead bodies to be individually identified in mass disasters, forensic teams face challenges such as long working hours resulting in a delayed identification process and a public health concern caused by the decomposition of the body. Using dental panoramic imaging, teeth have been used in forensics as a physical marker to estimate the age of an individual. Traditionally, dental age estimation has been performed manually by experts. Although the procedure is fairly simple, the large number of victims and the limited amount of time available to complete the assessment during large-scale disasters make forensic work even more challenging. The emergence of artificial intelligence (AI) in the fields of medicine and dentistry has led to the suggestion of automating the current process as an alternative to the conventional method. This study aims to test the accuracy and performance of the developed deep convolutional neural network system for age estimation in large, out-of-sample Malaysian children dataset using digital dental panoramic imaging. Forensic Dental Estimation Lab (F-DentEst Lab) is a computer application developed to perform the dental age estimation digitally. The introduction of this system is to improve the conventional method of age estimation that significantly increase the efficiency of the age estimation process based on the AI approach. A total number of one-thousand-eight-hundred-and-ninety-two digital dental panoramic images were retrospectively collected to test the F-DentEst Lab. Data training, validation, and testing have been conducted in the early stage of the development of F-DentEst Lab, where the allocation involved 80 % training and the remaining 20 % for testing. The methodology was comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental imaging, segmentation, and classification of mandibular premolars using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. The suggested DCNN approach underestimated chronological age with a small ME of 0.03 and 0.05 for females and males, respectively.

A Soft-Tissue Driven Bone Remodeling Algorithm for Mandibular Residual Ridge Resorption Based on Patient CT Image Data.

The role of the biomechanical stimulation generated from soft tissue has not been well quantified or separated from the self-regulated hard tissue remodeling governed by Wolff's Law. Prosthodontic overdentures, commonly used to restore masticatory functions, can cause localized ischemia and inflammation as they often compress patients' oral mucosa and impede local circulation. This biomechanical stimulus in mucosa is found to accelerate the self-regulated residual ridge resorption (RRR), posing ongoing clinical challenges. Based on the dedicated long-term clinical datasets, this work develops an in-silico framework with a combination of techniques, including advanced image post-processing, patient-specific finite element models and unsupervised machine learning Self-Organizing map algorithm, to identify the soft tissue induced RRR and quantitatively elucidate the governing relationship between the RRR and hydrostatic pressure in mucosa. The proposed governing equation has not only enabled a predictive simulation for RRR as showcased in this study, providing a biomechanical basis for optimizing prosthodontic treatments, but also extended the understanding of the mechanobiological responses in the soft-hard tissue interfaces and the role in bone remodeling.

Screw-retrievable cement-retained implant restorations: A scoping review of fracture strength and clinical performance.

BACKGROUND: The screw-retrievable cement-retained (SRCR) design combines the benefits of both screwand cement-retained implant-supported restorations. This concept has sparked interest in implant dentistry. However, there is a lack of research on fracture behaviors and clinical performance of such restorations. OBJECTIVES: The aim of the present article was to review the current literature on the fracture loads and fracture modes of SRCR implant restorations - in vitro studies, and also studies demonstrating the clinical performance of such design. MATERIAL AND METHODS: A literature search was conducted from January 2000 to June 2022, using 6 databases to identify studies on fracture load and clinical performance that fulfilled the eligibility criteria. Thirty-eight studies met the inclusion criteria (22 in vitro and16 in vivo). The in vivo studies comprised case reports/series/letters (9), clinical techniques (2), retrospective/prospective studies (3), and randomized controlled trials (RCTs) (2). RESULTS: The reviewed articles reported the effects of the SRCR design on the fracture risk if screw access channels were filled or unfilled, with regard to their diameter, and the preparation before or after glazing. The effect of the type of material used in the construction on the fracture modes SRCR restorations was also reported. The long-term clinical data was mainly retrospective and referred to metal-ceramic constructions. Limited long-term clinical data was available for all-ceramic materials and high-performance polymers (HPPs). CONCLUSIONS: Screw-retrievable cement-retained implant restorations appear to have potential in the monolithic design. If the SRCR construction is metal-ceramic or made of a veneered material, special design and abutment selection should be considered. High-performance polymers may be recommended as a substitute for posterior implant restoration.

Porous NiTi Dental Implant Fabricated by a Metal Injection Molding: An in Vivo Biocompatibility Evaluation in an Animal Model.

This study assessed the corrosion resistance, intracutaneous reactivity, acute systemic toxicity, and in situ tissue effect of the implantation of porous NiTi fabricated by metal injection molding in animal models. For the intracutaneous reactivity study, five intracutaneous injections were administered per site with and without the tested extract in polar and nonpolar solutions. The extract was also delivered via intravenous and intraperitoneal routes for acute systemic toxicity. TiAl6 V4 (control) and porous NiTi were implanted in rabbit femora for a period of 13 weeks to evaluate the in situ tissue response. Corrosion was evaluated through open and cyclic polarization in PBS, while biocompatibility was investigated by assessing the general conditions, skin irritation score (edema and erythema), and histopathology. No active dissolution or hysteresis loop was observed in the corrosion study. None of the animals exhibited death, moribundity, impending death, severe pain, self-mutilation, or overgrooming. No edema was observed at injection sites. Only the positive control showed an erythematous reaction at 24, 48, and 72 h observations (p < 0.001). Porous NiTi showed a low in situ biological response for inflammation, neovascularization, and fibrosis in comparison to the control implant (p = 0.247, 0.005, and 0.011, respectively). Porous NiTi also demonstrated high pitting corrosion resistance while causing no acute hypersensitivity or acute systemic toxicity. The study concludes that porous NiTi implants were unlikely to cause local sensitization, acute systemic toxicity, or chronic inflammatory reactions in an animal model. Porous NiTi also exhibited osseointegration equivalent to Ti6AI4 V of known biocompatibility.

Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier: A scoping review.

Background: Forensic odontology may require a visual or clinical method during identification. Sometimes it may require forensic experts to refer to the existing technique to identify individuals, for example, by using the atlas to estimate the dental age. However, the existing technology can be a complicated procedure for a large-scale incident requiring a more significant number of forensic identifications, particularly during mass disasters. This has driven many experts to perform automation in their current practice to improve efficiency. Objective: This article aims to evaluate current artificial intelligence applications and discuss their performance concerning the algorithm architecture used in forensic odontology. Methods: This study summarizes the findings of 28 research papers published between 2010 and June 2022 using the Arksey and O'Malley framework, updated by the Joanna Briggs Institute Framework for Scoping Reviews methodology, highlighting the research trend of artificial intelligence technology in forensic odontology. In addition, a literature search was conducted on Web of Science (WoS), Scopus, Google Scholar, and PubMed, and the results were evaluated based on their content and significance. Results: The potential application of artificial intelligence technology in forensic odontology can be categorized into four: (1) human bite marks, (2) sex determination, (3) age estimation, and (4) dental comparison. This powerful tool can solve humanity's problems by giving an adequate number of datasets, the appropriate implementation of algorithm architecture, and the proper assignment of hyperparameters that enable the model to perform the prediction at a very high level of performance. Conclusion: The reviewed articles demonstrate that machine learning techniques are reliable for studies involving continuous features such as morphometric parameters. However, machine learning models do not strictly require large training datasets to produce promising results. In contrast, deep learning enables the processing of unstructured data, such as medical images, which require large volumes of data. Occasionally, transfer learning was used to overcome the limitation of data. In the meantime, this method's capacity to automatically learn task-specific feature representations has made it a significant success in forensic odontology.

The antibacterial effect of Plectranthus scutellarioides (L.) R.Br. leaves extract against bacteria associated with peri-implantitis.

Background and aim: The present study investigates Plectranthus scutellarioides (L.) R.Br. as potential antibacterial oral rinse against bacteria associated with peri-implantitis to prevent the initial infection as well as disease progression. Experimental procedure: Phytochemical screening was done on P. scutellarioides lyophilized extract to identify the presence of chemical constituent by using mass-based identification. The extract was screened for its antibacterial activity against 4 Gram-positive aerobes (early colonizer) and 5 Gram-negative facultative anaerobes as well as obligate anaerobes (late colonizer) using disc diffusion method. The extract was tested for minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), its cytotoxicity effects on human gingival fibroblast cell (HnGF) as well as bacteria morphological changes by scanning electron microscopy (SEM). Results and conclusion: Four flavonoid compounds were identified namely quercetin-3-glucoside, quercitrin, quercetin 3-(6″-acetylglucoside) and quercetin 3-O-acetyl-rhamnoside. The sensitivity test revealed that P. scutellarioides extract was effective against all the bacteria tested. MIC concentrations for the Gram-positive aerobes were in the range of 1.56-12.50 mg/mL, and the MBC concentrations were within 3.13-12.50 mg/mL. For Gram-negative obligate anaerobes, the MIC concentration were within 3.13-12.50 mg/mL and MBC within 6.25-200.00 mg/mL. The ethanolic extract did not have any cytotoxic effect on HnGF cells at the tested concentrations. SEM images showed bacterial cell wall disruption for all the bacteria tested. The results showed that P. scutellarioides extract exerts its antibacterial property by disrupting the cell wall of all the bacteria tested. Hence, P. scutellarioides may benefit from further investigations on its safety for oral use as an adjunctive treatment for peri-implantitis.

Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging.

BACKGROUND: This study aims to propose the combinations of image processing and machine learning model to segment the maturity development of the mandibular premolars using a Keras-based deep learning convolutional neural networks (DCNN) model. METHODS: A dataset consisting of 240 images (20 images per stage per sex) of retrospect digital dental panoramic imaging of patients between 5 and 14 years of age was retrieved. In image preprocessing, abounding box with a dimension of 250 × 250 pixels was assigned to the left mandibular first (P1) and second (P2) permanent premolars. The implementation of dynamic programming of active contour (DP-AC) and convolutions neural network on images that require the procedure of image filtration using Python TensorFlow and Keras libraries were performed in image segmentation and classification, respectively. RESULTS: Image segmentation using the DP-AC algorithm enhanced the visibility of the image features in the region of interest while suppressing the image's background noise. The proposed model has an accuracy of 97.74%, 96.63% and 78.13% on the training, validation, and testing set, respectively. In addition, moderate agreement (Kappa value = 0.58) between human observer and computer were identified. Nonetheless, a robust DCNN model was achieved as there is no sign of the model's over-or under-fitting upon the learning process. CONCLUSIONS: The application of digital imaging and deep learning techniques used by the DP-AC and convolutions neural network algorithms to segment and identify premolars provides promising results for semi-automated forensic dental staging in the future.

Stress, Anxiety and Depression among a Cohort of Health Sciences Undergraduate Students: The Prevalence and Risk Factors.

Stress, anxiety, and depression (SAD) have a negative impact on the learning and academic performance of university students. Hence, this study aimed to determine the prevalence, as well as the risk factors associated with SAD among a cohort of students pursuing undergraduate degree courses in health sciences. This is part of the strategy in building a healthy nation. A questionnaire containing socio-demographic factors and the short version of Depression, Anxiety, and Stress Scale-21 (DASS-21) was used to assess the likelihood of psychological distress. Logistic regression analysis was conducted to determine the risk factors of SAD. In total, 449 students completed the questionnaire (93.9% response rate). Of these, 65% had stress, 85.1% had anxiety and 51.4% had depression. Most cases of stress (74.6%) and depression (66.2%) were of normal-to-mild level, while 74.6% of them showed moderate-to-extremely severe anxiety. There was a statistically significant association between stress score and the year of study. In the regression analysis, poor sleep quality and fatigue were risk factors of anxiety and depression, whereas low-grade fever and frequent headaches were risk factors for stress and anxiety. Stress, anxiety, and depression scores were significantly higher among students studying medical imaging. A substantial proportion of health science students are suffering from SAD. This study recommends screening and close monitoring of the above-mentioned predictors and the formulation of comprehensive intervention strategies for students with SAD.

The Integration of a Dual-Wavelength Super Pulsed Diode Laser for Consistent Tissue Ablation in the Esthetic Zone: A Case Series.

INTRODUCTION: A diode laser is one of the universally compact accepted laser systems used fundamentally for soft tissue applications. Most diode laser devices have a single wavelength of either 810 nm for superior coagulation or 980 nm for tissue ablation. In these case series, the use of dual wavelengths (810 nm and 980 nm) in combination with super pulsing has provided a cleaner cut (no charring) with faster healing that eases the placement of the final restoration in the esthetic zone. Case Description. The present case series describe four cases in the esthetic zone that achieved hemostasis ablation without collateral damage to enhance gingival balance of definitive restoration. The gingivoplasty and gingivectomy modes are used to achieve efficient tissue ablation. Although there is no specific mode indicated in the FDA laser requirement for gingival depigmentation, the procedure could be safely performed with the dual-wavelength diode laser. RESULT: All four patients revealed a good esthetic outcome and reported no pain postoperatively. Healing was uneventful, and definitive restoration was delivered within two to four weeks postoperatively. CONCLUSION: Within the limitation of these case series, the dual-wavelength super pulsed diode laser has the capacity to deliver peak powers resulting in efficient cutting and less tissue charring and also as an alternative tool for removal of gingival pigmentation. Prospective clinical research with larger sample size is needed for conclusive results.

Effect of reconstruction parameters on cone beam CT trabecular bone microstructure quantification in sheep.

BACKGROUND: Cone Beam Computed Tomography (CBCT) is a reliable radiographic modality to assess trabecular bone microarchitecture. The aim of this study was to determine the effect of CBCT image reconstruction parameters, namely, the threshold value and reconstruction voxel size, on trabecular bone microstructure assessment. METHODS: Five sectioned maxilla of adult Dorper male sheep were scanned using a CBCT system with a resolution of 76 µm3 (Kodak 9000). The CBCT images were reconstructed using different reconstruction parameters and analysed. The effect of reconstruction voxel size (76, 100 and 200 µm3) and threshold values (±15% from the global threshold value) on trabecular bone microstructure measurement was assessed using image analysis software (CT analyser version 1.15). RESULTS: There was no significant difference in trabecular bone microstructure measurement between the reconstruction voxel sizes, but a significant difference (Tb.N = 0.03, Tb.Sp = 0.04, Tb.Th = 0.01, BV/TV = 0.00) was apparent when the global threshold value was decreased by 15%. CONCLUSIONS: Trabecular bone microstructure measurements are not compromised by changing the CBCT reconstruction voxel size. However, measurements can be affected when applying a threshold value of less than 15% of the recommended global value.

Effect of different implant configurations on biomechanical behavior of full-arch implant-supported mandibular monolithic zirconia fixed prostheses.

Mechanical failure of zirconia-based full-arch implant-supported fixed dental prostheses (FAFDPs) remains a critical issue in prosthetic dentistry. The option of full-arch implant treatment and the biomechanical behaviour within a sophisticated screw-retained prosthetic structure have stimulated considerable interest in fundamental and clinical research. This study aimed to analyse the biomechanical responses of zirconia-based FAFDPs with different implant configurations (numbers and distributions), thereby predicting the possible failure sites and the optimum configuration from biomechanical aspect by using finite element method (FEM). Five 3D finite element (FE) models were constructed with patient-specific heterogeneous material properties of mandibular bone. The results were reported using volume-averaged von-Mises stresses (σVMVA) to eliminate numerical singularities. It was found that wider placement of multi-unit copings was preferred as it reduces the cantilever effect on denture. Within the limited areas of implant insertion, the adoption of angled multi-unit abutments allowed the insertion of oblique implants in the bone and wider distribution of the multi-unit copings in the prosthesis, leading to lower stress concentration on both mandibular bone and prosthetic components. Increasing the number of supporting implants in a FAFDPs reduced loading on each implant, although it may not necessarily reduce the stress concentration in the most posterior locations significantly. Overall, the 6-implant configuration was a preferable configuration as it provided the most balanced mechanical performance in this patient-specific case.

Liquid Chromatography Mass Spectrometry (LC-MS) analysis in determining the saliva protein of orthodontic patients during retention phase.

BACKGROUND: The biological responses involved during retention phase have been studied for many years but little is known about the effect of saliva proteome during retention phase of post-orthodontic treatment. This study aims to identify the protein profiles during retention phase in relation to biological processes involved by Liquid Chromatography Mass Spectrometry (LC-MS) approach. MATERIAL AND METHODS: A total of 5 ml of unstimulated saliva was collected from each subject (10 non-orthodontic patients and 15 post-orthodontic patients with 6-months retention phase). Samples were then subjected to LC-MS analysis. The expressed proteins were identified and compared between groups. Incisor irregularity for both maxilla and mandible were determined with Little's Irregularity Index at 6-months retention phase. RESULTS: 146 proteins and 135 proteins were expressed in control and 6-months retention phase group respectively. 15 proteins were identified to be co-expressed between groups. Immune system process was only detected in 6-months retention phase group. Detected protein in immune system process was identified as Tyrosine-protein kinase Tec. Statistical significant of incisor irregularity was only found in mandible at 6-months retention phase. CONCLUSIONS: Our study suggests that immune system process protein which is Tyrosine-protein kinase Tec could be used as biomarker for prediction of stability during retention phase of post-orthodontic treatment. Key words:Orthodontics, proteomics, retention, LC-MS, saliva.

Blood Flow Alterations in the Anterior Maxillary Mucosa as Induced by Implant-Retained Overdenture.

PURPOSE: Blood flow disturbance from functional pressure may lead to ischemia and accumulation of metabolites leading to residual ridge resorption (RRR) underneath complete dentures. The purposes of this study were to determine the effect of mandibular complete denture (CD) and implant-retained overdenture (IRO) on blood flow disturbance in the opposing denture bearing-mucosa of maxillary CD and to compare the blood flow disturbance to RRR of the anterior maxilla. MATERIALS AND METHODS: The test group included 9 participants rehabilitated by maxillary CD opposing mandibular IRO, while the control group consisted of 4 participants with CDs. Blood flow was measured by laser Doppler flowmetry (LDF) after denture removal for 0, 30, 60, and 90 minutes. RRR was quantified as reduction in bone volume a year post-treatment. The measurement of blood flow was then compared to the quantification of RRR. RESULTS: The mean blood flow measure for the IRO group was significantly lower than CD after immediate denture removal and 30 minutes later. After 60 minutes, the mean difference was not significant between groups, and at 90 minutes, the mean blood flow of both groups equalized to reach a steady state of 377 BPU. The mandibular IRO had reduced the initial blood flow measure in the opposing anterior maxilla mucosa to almost a quarter (103 BPU) of the steady state value (377 BPU) compared to the CD, which reduced it to only about one half (183 BPU), suggesting greater blood flow disturbance in the IRO group. This result is in tandem with the greater reduction of bone volume observed in the IRO group, which was 7.3 ± 1.3% after a year, almost three times higher than CD group at 2.6 ± 1.7%. CONCLUSION: IRO may cause significantly higher blood flow disturbance than CD and may have contributed to greater RRR in the anterior maxilla.

Mandibular Implant-Retained Overdentures: Potential Accelerator of Bone Loss in the Anterior Maxilla?

PURPOSE: To compare the residual ridge resorption (RRR) of the anterior maxillary bone beneath complete dentures when opposed by mandibular complete dentures (CD) and implant-retained overdentures (IRO). MATERIALS AND METHODS: 18 patients were rehabilitated with maxillary CD opposing mandibular IRO, and 4 patients were prescribed with conventional CD. Cone beam computed tomography (CBCT) scans of the maxilla were acquired before and 1 year post-treatment and converted into 3D models using Mimics research software. RRR was quantified by measuring the changes in bone volume following superimpositioning and sectioning of these models at the anterior maxillary region. Subsequently, the sectioned 3D models of the anterior maxilla were exported to 3-Matic software to reveal the predominant region and depth of RRR. RESULTS: The mean reduction in bone volume of the anterior maxilla in the CD group was 2.60% (SD = 1.71%, range = -4.89 % to -0.92%, median = -2.30%), while the mean reduction in the IRO group was almost three times higher at 7.25% (SD = 3.16%, range = -13.25 to -1.50, median = -7.15%). The predominant areas of RRR were on the buccal and occlusal ridge of the anterior maxilla. CONCLUSION: Within the limits of this study, it may be concluded that an IRO caused significantly higher RRR of the anterior maxilla than a CD.

Premaxilla Stress Distribution and Bone Resorption Induced by Implant Overdenture and Conventional Denture.

PURPOSE: To relate the principal stress, strain, and total deformation in the premaxilla region beneath a complete denture to the pattern of premaxilla bone resorption when opposed by a conventional complete denture (CD) or by a two-implant-retained overdenture (IOD) using finite element analysis (FEA). MATERIALS AND METHODS: Three-dimensional solid models of the maxilla, mucosa, and denture of a selected edentulous patient were created using Mimics and CATIA software. The FEA model was created and duplicated in ANSYS 16.0 to perform two simulations for the IOD and the CD models. The values of maximum stress and strain and total deformation were obtained and compared to the outcomes of premaxilla resorption from a parallel clinical study. RESULTS: The maximum principal stress in the premaxilla in the IOD model ranged from 0.019 to 0.336 MPa, while it ranged from 0.011 to 0.193 MPa in the CD model. The maximum principal strain in the IOD model was 1.75 times greater than that in the CD model. Total deformation was 1.8 times higher in the IOD model. Greater bone resorption was observed in regions of higher stress, which were on the occlusal and buccal sides of the premaxilla residual ridge. CONCLUSION: Stress, strain, and total deformation values present in the premaxilla area beneath a CD were approximately two times greater in a comparison between an opposing mandibular two-IOD and an opposing mandibular CD. The results were consistent with a parallel clinical study in which the rate of premaxilla bone resorption was almost three times greater in the IOD group.

The Relationship of Mandibular Morphology with Residual Ridge Resorption Associated with Implant-Retained Overdentures.

PURPOSE: The objective of this clinical study was to determine the relationship of mandibular morphology with residual ridge resorption (RRR) of implant-retained overdenture (IRO) patients. MATERIALS AND METHODS: RRR was quantified as change in bone volume over 1- and 2-year periods using cone beam computed tomography and a medical imaging program. Features of the mandibular morphology, namely the gonial angle, ramus length, ramus width, corpus length, and corpus height, were measured on three-dimensional models and correlated to the RRR. A total of 25 participants were treated with mandibular IROs opposing maxillary complete dentures. By the 2-year follow-up, radiographic data for 18 patients were complete for analysis. Of these 18 participants, half fall into the low gonial angle category and the other half into the high angle. RESULTS: The extent of RRR was highly variable among participants and ranged from -2 to +2 mm in depth over the 2-year period. The mean decrease in bone volume after the first year was 3.8 ± 4.5%. This rate decreased to 3.2 ± 4.1% after the second year. RRR occurs either by translation of the entire thickness of cortical layer apically or by thinning of the outer cortical layer. RRR was significantly correlated to gonial angle (r = .471; P = .048) and predominantly occurred in the molar region in low-angle participants and more anteriorly in high-angle participants. There was no association between RRR and ramus length (r = -.341; P = .166), ramus width (r = -.183; P =.468), corpus length (r = .057; P = .821), and corpus height (r = .097; P = .702). CONCLUSION: Within the limitations of this study, it may be concluded that gonial angle is significantly related to RRR associated with IROs.

Biomechanics of oral mucosa.

The prevalence of prosthodontic treatment has been well recognized, and the need is continuously increasing with the ageing population. While the oral mucosa plays a critical role in the treatment outcome, the associated biomechanics is not yet fully understood. Using the literature available, this paper provides a critical review on four aspects of mucosal biomechanics, including static, dynamic, volumetric and interactive responses, which are interpreted by its elasticity, viscosity/permeability, apparent Poisson's ratio and friction coefficient, respectively. Both empirical studies and numerical models are analysed and compared to gain anatomical and physiological insights. Furthermore, the clinical applications of such biomechanical knowledge on the mucosa are explored to address some critical concerns, including stimuli for tissue remodelling (interstitial hydrostatic pressure), pressure-pain thresholds, tissue displaceability and residual bone resorption. Through this review, the state of the art in mucosal biomechanics and their clinical implications are discussed for future research interests, including clinical applications, computational modelling, design optimization and prosthetic fabrication.

Shape Optimization for Additive Manufacturing of Removable Partial Dentures--A New Paradigm for Prosthetic CAD/CAM.

With ever-growing aging population and demand for denture treatments, pressure-induced mucosa lesion and residual ridge resorption remain main sources of clinical complications. Conventional denture design and fabrication are challenged for its labor and experience intensity, urgently necessitating an automatic procedure. This study aims to develop a fully automatic procedure enabling shape optimization and additive manufacturing of removable partial dentures (RPD), to maximize the uniformity of contact pressure distribution on the mucosa, thereby reducing associated clinical complications. A 3D heterogeneous finite element (FE) model was constructed from CT scan, and the critical tissue of mucosa was modeled as a hyperelastic material from in vivo clinical data. A contact shape optimization algorithm was developed based on the bi-directional evolutionary structural optimization (BESO) technique. Both initial and optimized dentures were prototyped by 3D printing technology and evaluated with in vitro tests. Through the optimization, the peak contact pressure was reduced by 70%, and the uniformity was improved by 63%. In vitro tests verified the effectiveness of this procedure, and the hydrostatic pressure induced in the mucosa is well below clinical pressure-pain thresholds (PPT), potentially lessening risk of residual ridge resorption. This proposed computational optimization and additive fabrication procedure provides a novel method for fast denture design and adjustment at low cost, with quantitative guidelines and computer aided design and manufacturing (CAD/CAM) for a specific patient. The integration of digitalized modeling, computational optimization, and free-form fabrication enables more efficient clinical adaptation. The customized optimal denture design is expected to minimize pain/discomfort and potentially reduce long-term residual ridge resorption.

Investigation of mucosa-induced residual ridge resorption under implant-retained overdentures and complete dentures in the mandible.

PURPOSE: This study aimed to investigate and compare the residual ridge resorption (RRR) induced by an implant-retained overdenture (IRO) and associative biomechanics and by a conventional complete denture (CD) without implants. MATERIALS AND METHODS: Cone beam computed tomography was used to quantify RRR in a three-dimensional (3D) manner before and after 1 year of treatment with either IROs or CDs. Twenty patients were treated with IROs, and nine patients were treated with CDs in the mandible. Their maximum bite forces were recorded. The same sets of high-resolution scan images were used to create patient-specific 3D finite element analysis models. The hydrostatic stresses, contact surface deformation, and strain energy absorption in soft tissue mucosa were correlated with the changes in RRR for patients with and without implants. RESULTS: With the IROs, contact surface deformation on the mucosa was two times greater than with CDs (0.32 ± 0.23 mm vs 0.16 ± 0.06 mm) and was in agreement with the amount of RRR measured, which was also two times higher for the IRO than the CD (-3.8% ± 4.5% vs -1.9% ± 0.4%). Taking into account the differences in bite forces with and without implants, which again were twice as high with IROs, the hydrostatic stress within the mucosa was found to correlate well to the RRR map measured over the 1-year interval of treatment. CONCLUSION: IROs resulted in at least twice the RRR as CDs. This could be caused by the higher hydrostatic stress and less effective energy absorption capabilities of the mucosa underneath the IRO. While implants associated with the IRO provide stronger bite force, they could potentially concentrate hydrostatic stress and cause greater RRR compared to a conventional CD.

A comparative study on complete and implant retained denture treatments: a biomechanics perspective.

Although implant-retained overdenture allows edentulous patients to take higher occlusal forces than the conventional complete dentures, the biomechanical influences have not been explored yet. Clinically, there is limited knowledge and means for predicting localized bone remodelling after denture treatment with and without implant support. By using finite element (FE) analysis, this article provides an in-silico approach to exploring the treatment effects on the oral mucosa and potential resorption of residual ridge under three different denture configurations in a patient-specific manner. Based on cone beam computerized tomography (CBCT) scans, a 3D heterogeneous FE model was created; and the supportive tissue, mucosa, was characterized as a hyperelastic material. A measured occlusal load (63N) was applied onto three virtual models, namely complete denture, two and four implant-retained overdentures. Clinically, the bone resorption was measured after one year in the two implant-retained overdenture treatment. Despite the improved stability and enhanced masticatory function, the implant-retained overdentures demonstrated higher hydrostatic stress in mucosa (43.6kPa and 39.9kPa for two and four implants) at the posterior ends of the mandible due to the cantilever effect, than the complete denture (33.4kPa). Hydrostatic pressure in the mucosa signifies a critical indicator and can be correlated with clinically measured bone resorption, pointing to severer mandibular ridge resorption posteriorly with implant-retained overdentures. This study provides a biomechanical basis for denture treatment planning to improve long-term outcomes with minimal residual ridge resorption.