CT-derived radiomics predict the growth rate of renal tumours in von Hippel-Lindau syndrome

AIM

To predict renal tumour growth patterns in von Hippel-Lindau syndrome by utilising radiomic features to assist in developing personalised surveillance plans leading to better patient outcomes.

MATERIALS AND METHODS

The study evaluated 78 renal tumours in 55 patients with histopathologically-confirmed clear cell renal cell carcinomas (ccRCCs), which were segmented and radiomics were extracted. Volumetric doubling time (VDT) classified the tumours into fast-growing (VDT <365 days) or slow-growing (VDT ≥365 days). Volumetric and diametric growth analyses were compared between the groups. Multiple logistic regression and random forest classifiers were used to select the best features and models based on their correlation and predictability of VDT.

RESULTS

Fifty-five patients (mean age 42.2 ± 12.2 years, 27 men) with a mean time difference of 3.8 ± 2 years between the baseline and preoperative scans were studied. Twenty-five tumours were fast-growing (low VDT, i.e., <365 days), and 53 tumours were slow-growing (high VDT, i.e., ≥365 days). The median volumetric and diametric growth rates were 1.71 cm3/year and 0.31 cm/year. The best feature using univariate analysis was wavelet-HLL_glcm_ldmn (area under the receiver operating characteristic [ROC] curve [AUC] of 0.80, p<0.0001), and with the random forest classifier, it was log-sigma-0-5-mm-3D_glszm_ZonePercentage (AUC: 79). The AUC of the ROC curves using multiple logistic regression was 0.74, and with the random forest classifier was 0.73.

CONCLUSION

Radiomic features correlated with VDT and were able to predict the growth pattern of renal tumours in patients with VHL syndrome.

Artificial intelligence and smile design: An e-Delphi consensus statement of ethical challenges

PURPOSE

Smile design software increasingly relies on artificial intelligence (AI). However, using AI for smile design raises numerous technical and ethical concerns. This study aimed to evaluate these ethical issues.

METHODS

An international consortium of experts specialized in AI, dentistry, and smile design was engaged to emulate and assess the ethical challenges raised by the use of AI for smile design. An e-Delphi protocol was used to seek the agreement of the ITU-WHO group on well-established ethical principles regarding the use of AI (wellness, respect for autonomy, privacy protection, solidarity, governance, equity, diversity, expertise/prudence, accountability/responsibility, sustainability, and transparency). Each principle included examples of ethical challenges that users might encounter when using AI for smile design.

RESULTS

On the first round of the e-Delphi exercise, participants agreed that seven items should be considered in smile design (diversity, transparency, wellness, privacy protection, prudence, law and governance, and sustainable development), but the remaining four items (equity, accountability and responsibility, solidarity, and respect of autonomy) were rejected and had to be reformulated. After a second round, participants agreed to all items that should be considered while using AI for smile design.

CONCLUSIONS

AI development and deployment for smile design should abide by the ethical principles of wellness, respect for autonomy, privacy protection, solidarity, governance, equity, diversity, expertise/prudence, accountability/responsibility, sustainability, and transparency.

Navigating therapeutic strategies: HPV classification in head and neck cancer

The World Health Organisation recognised human papillomavirus (HPV) as the cause of multiple cancers, including head and neck cancers. HPV is a double-stranded DNA virus, and its viral gene expression can be controlled after infection by cellular and viral promoters. In cancer cells, the HPV genome is detected as either integrated into the host genome, episomal (extrachromosomal), or a mixture of integrated and episomal. Viral integration requires the breakage of both viral and host DNA, and the integration rate correlates with the level of DNA damage. Interestingly, patients with HPV-positive head and neck cancers generally have a good prognosis except for a group of patients with fully integrated HPV who show worst clinical outcomes. Those patients present with lowered expression of viral genes and limited infiltration of cytotoxic T cells. An impediment to effective therapy applications in the clinic is the sole testing for HPV positivity without considering the HPV integration status. This review will discuss HPV integration as a potential determinant of response to therapies in head and neck cancers and highlight to the field a novel therapeutic avenue that would reduce the cancer burden and improve patient survival.

Can predictive factors determine the time to treatment initiation for oral and oropharyngeal cancer? A classification and regression tree analysis

This ecological study aimed to identify the factors with the greatest power to discriminate the proportion of oral and oropharyngeal cancer (OOC) records with time to treatment initiation (TTI) within 30 days of diagnosis in Brazilian municipalities. A descriptive analysis was performed on the variables grouped into five dimensions related to patient characteristics, access to health services, support for cancer diagnosis, human resources, and socioeconomic characteristics of 3,218 Brazilian municipalities that registered at least one case of OOC in 2019. The Classification and Regression Trees (CART) technique was adopted to identify the explanatory variables with greater discriminatory power for the TTI response variable. There was a higher median percentage of records in the age group of 60 years or older. The median percentage of records with stage III and IV of the disease was 46.97%, and of records with chemotherapy, radiation, or both as the first treatment was 50%. The median percentage of people with private dental and health insurance was low. Up to 75% had no cancer diagnostic support services, and up to 50% of the municipalities had no specialist dentists. Most municipalities (49.4%) started treatment after more than 30 days. In the CART analysis, treatment with chemotherapy, radiotherapy, or both explained the highest TTI in all municipalities, and it was the most relevant for predicting TTI. The final model also included anatomical sites in the oral cavity and oropharynx and the number of computed tomography services per 100,000. There is a need to expand the availability of oncology services and human resources specialized in diagnosing and treating OOC in Brazilian municipalities for a timely TTI of OOC.

Artificial intelligence chatbots and large language models in dental education: Worldwide survey of educators

INTRODUCTION

Interest is growing in the potential of artificial intelligence (AI) chatbots and large language models like OpenAI's ChatGPT and Google's Gemini, particularly in dental education. To explore dental educators' perceptions of AI chatbots and large language models, specifically their potential benefits and challenges for dental education.

MATERIALS AND METHODS

A global cross-sectional survey was conducted in May-June 2023 using a 31-item online-questionnaire to assess dental educators' perceptions of AI chatbots like ChatGPT and their influence on dental education. Dental educators, representing diverse backgrounds, were asked about their use of AI, its perceived impact, barriers to using chatbots, and the future role of AI in this field.

RESULTS

428 dental educators (survey views = 1516; response rate = 28%) with a median [25/75th percentiles] age of 45 [37, 56] and 16 [8, 25] years of experience participated, with the majority from the Americas (54%), followed by Europe (26%) and Asia (10%). Thirty-one percent of respondents already use AI tools, with 64% recognising their potential in dental education. Perception of AI's potential impact on dental education varied by region, with Africa (4[4-5]), Asia (4[4-5]), and the Americas (4[3-5]) perceiving more potential than Europe (3[3-4]). Educators stated that AI chatbots could enhance knowledge acquisition (74.3%), research (68.5%), and clinical decision-making (63.6%) but expressed concern about AI's potential to reduce human interaction (53.9%). Dental educators' chief concerns centred around the absence of clear guidelines and training for using AI chatbots.

CONCLUSION

A positive yet cautious view towards AI chatbot integration in dental curricula is prevalent, underscoring the need for clear implementation guidelines.

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.

METHODS

The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.

FINDINGS

The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.

INTERPRETATION

Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.

FUNDING

Bill & Melinda Gates Foundation.

Associations among gene polymorphisms, crestal bone loss, and bone mineral density in patients receiving dental implants

Objectives

Interleukin 1 (IL-1) and interleukin 6 (IL-6) gene polymorphisms have been suggested to be responsible for diminished bone mineral density (BMD) and high crestal bone loss (CBL) in some individuals. However, the effects of systemic BMD on variations in peri-implant CBL are unclear. Hence, this study was aimed at investigating the association of IL-1 and IL-6 gene polymorphisms with systemic BMD and CBL around dental implants.

Methods

A total of 190 participants undergoing dental implantation in the mandibular posterior region were selected according to predetermined selection criteria and divided into a normal BMD group (NBD, 93 participants, T-score ≥ -1) and low BMD group (LBD, including both osteoporosis and osteopenia, 97 participants, T-score < -1 standard deviation) according to the BMD of the right femoral neck, measured with dual-energy X-ray absorptiometry. Dental implants were placed through the standard surgical protocol, and CBL was calculated after 6 months with cone beam computed tomography scans before second-stage surgery. Genotyping was performed on all participants for IL-1A-889 A/G, IL-1B-511G/A, IL-1B+3954, and IL-6-572 C/G gene polymorphisms.

Results

The demographic and clinical characteristics of the participants in both groups were compared with t-test and chi-square test (χ2). The associations of NBD and LBD with the different genotypes and CBL was determined with odds ratios, and p < 0.05 was considered statistically significant. The frequency of IL-1B-511AA and IL-6-572 GG genotypes was significantly higher in LBD than in NBD (p < 0.05). In LBD, the IL-1B-511 AA (AA vs GA + GG; p ≤ 0.001) and IL-6-572 GG (GG vs CC + GC; p = 0.001) genotypes were significantly associated with higher peri-implant CBL.

Conclusions

Individuals with the IL-1B-511 AA or IL-6-572 GG genotype had elevated risk of osteoporosis/osteopenia and were more susceptible to CBL around dental implants.

A review of animal models for burning mouth syndrome: Mechanistic insights and knowledge gaps

OBJECTIVES

The underlying mechanisms of burning mouth syndrome (BMS) remain unclear leading to challenges and unsatisfactory management. Current treatments focus primarily on symptom relief, with few consistently achieving a 50% reduction in pain. This review aims to explore animal models of BMS to gain a better understanding of the underlying mechanisms and to discuss potential and existing knowledge gaps.

METHODS

A comprehensive review of PubMed® , Google Scholar, and Scopus was performed to assess advances and significant gaps of existing rodent models that mimic BMS-related symptoms.

RESULTS

Rodent models of BMS involve reproduction of dry-tongue, chorda tympani transection, or overexpression of artemin protein. Existing preclinical models tend to highlight one specific etiopathogenesis and often overlook sex- and hormone-specific factors.

CONCLUSION

Combining aspects from various BMS models could prove beneficial in developing comprehensive experimental designs and outcomes encompassing the multifaceted nature of BMS.

Global, regional, and national burden of neck pain, 1990-2020, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021

BACKGROUND

Neck pain is a highly prevalent condition that leads to considerable pain, disability, and economic cost. We present the most current estimates of neck pain prevalence and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) by age, sex, and location, with forecasted prevalence to 2050.

METHODS

Systematic reviews identified population-representative surveys used to estimate the prevalence of and YLDs from neck pain in 204 countries and territories, spanning from 1990 to 2020, with additional data from opportunistic review. Medical claims data from Taiwan (province of China) were also included. Input data were pooled using DisMod-MR 2.1, a Bayesian meta-regression tool. Prevalence was forecast to 2050 using a mixed-effects model using Socio-demographic Index as a predictor and multiplying by projected population estimates. We present 95% UIs for every metric based on the 2·5th and 97·5th percentiles of 100 draws of the posterior distribution.

FINDINGS

Globally, in 2020, neck pain affected 203 million (95% uncertainty interval [UI] 163-253) people. The global age-standardised prevalence rate of neck pain was estimated to be 2450 (1960-3040) per 100 000 population and global age-standardised YLD rate was estimated to be 244 (165-346) per 100 000. The age-standardised prevalence rate remained stable between 1990 and 2020 (percentage change 0·2% [-1·3 to 1·7]). Globally, females had a higher age-standardised prevalence rate (2890 [2330-3620] per 100 000) than males (2000 [1600-2480] per 100 000), with the prevalence peaking between 45 years and 74 years in male and female sexes. By 2050, the estimated global number of neck pain cases is projected to be 269 million (219-322), with an increase of 32·5% (23·9-42·3) from 2020 to 2050. Decomposition analysis of the projections showed population growth was the primary contributing factor, followed by population ageing.

INTERPRETATION

Although age-standardised rates of neck pain have remained stable over the past three decades, by 2050 the projected case numbers are expected to rise. With the highest prevalence in older adults (higher in females than males), a larger effect expected in low-income and middle-income countries, and a rapidly ageing global population, neck pain continues to pose a challenge in terms of disability burden worldwide. For future planning, it is essential we improve our mechanistic understanding of the different causes and risk factors for neck pain and prioritise the consistent collection of global neck pain data and increase the number of countries with data on neck pain.

FUNDING

Bill & Melinda Gates Foundation and Global Alliance for Musculoskeletal Health.

Deep-learning performance in identifying and classifying dental implant systems from dental imaging: a systematic review and meta-analysis

Deep learning (DL) offers promising performance in computer vision tasks and is highly suitable for dental image recognition and analysis. We evaluated the accuracy of DL algorithms in identifying and classifying dental implant systems (DISs) using dental imaging. In this systematic review and meta-analysis, we explored the MEDLINE/PubMed, Scopus, Embase, and Google Scholar databases and identified studies published between January 2011 and March 2022. Studies conducted on DL approaches for DIS identification or classification were included, and the accuracy of the DL models was evaluated using panoramic and periapical radiographic images. The quality of the selected studies was assessed using QUADAS-2. This review was registered with PROSPERO (CRDCRD42022309624). From 1,293 identified records, 9 studies were included in this systematic review and meta-analysis. The DL-based implant classification accuracy was no less than 70.75% (95% confidence interval [CI], 65.6%-75.9%) and no higher than 98.19 (95% CI, 97.8%-98.5%). The weighted accuracy was calculated, and the pooled sample size was 46,645, with an overall accuracy of 92.16% (95% CI, 90.8%-93.5%). The risk of bias and applicability concerns were judged as high for most studies, mainly regarding data selection and reference standards. DL models showed high accuracy in identifying and classifying DISs using panoramic and periapical radiographic images. Therefore, DL models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice.

Resorbable bilayer membrane made of L-lactide-ε-caprolactone in guided bone regeneration: an in vivo experimental study

PURPOSE

Guided bone regeneration (GBR) is an accepted method in dental practice that can successfully increase the bone volume of the host at sites chosen for implant placement; however, existing GBR membranes exhibit rapid absorption and lack of adequate space maintenance capabilities. We aimed to compare the effectiveness of a newly developed resorbable bilayer membrane composed of poly (L-lactic acid) and poly (-caprolactone) (PLACL) with that of a collagen membrane in a rat GBR model.

METHODS

The rat calvaria was used as an experimental model, in which a plastic cylinder was placed. We operated on 40 male Fisher rats and subsequently performed micro-computed tomography and histomorphometric analyses to assess bone regeneration.

RESULTS

Significant bone regeneration was observed, which was and similar across all the experimental groups. However, after 24 weeks, the PLACL membrane demonstrated significant resilience, and sporadic partial degradation. This extended preservation of the barrier effect has great potential to facilitate optimal bone regeneration.

CONCLUSIONS

The PLACL membrane is a promising alternative to GBR. By providing a durable barrier and supporting bone regeneration over an extended period, this resorbable bilayer membrane could address the limitations of the current membranes. Nevertheless, further studies and clinical trials are warranted to validate the efficacy and safety of The PLACL membrane in humans.

Deep learning for detection and 3D segmentation of maxillofacial bone lesions in cone beam CT

OBJECTIVES

To develop an automated deep-learning algorithm for detection and 3D segmentation of incidental bone lesions in maxillofacial CBCT scans.

METHODS

The dataset included 82 cone beam CT (CBCT) scans, 41 with histologically confirmed benign bone lesions (BL) and 41 control scans (without lesions), obtained using three CBCT devices with diverse imaging protocols. Lesions were marked in all axial slices by experienced maxillofacial radiologists. All cases were divided into sub-datasets: training (20,214 axial images), validation (4530 axial images), and testing (6795 axial images). A Mask-RCNN algorithm segmented the bone lesions in each axial slice. Analysis of sequential slices was used for improving the Mask-RCNN performance and classifying each CBCT scan as containing bone lesions or not. Finally, the algorithm generated 3D segmentations of the lesions and calculated their volumes.

RESULTS

The algorithm correctly classified all CBCT cases as containing bone lesions or not, with an accuracy of 100%. The algorithm detected the bone lesion in axial images with high sensitivity (95.9%) and high precision (98.9%) with an average dice coefficient of 83.5%.

CONCLUSIONS

The developed algorithm detected and segmented bone lesions in CBCT scans with high accuracy and may serve as a computerized tool for detecting incidental bone lesions in CBCT imaging.

CLINICAL RELEVANCE

Our novel deep-learning algorithm detects incidental hypodense bone lesions in cone beam CT scans, using various imaging devices and protocols. This algorithm may reduce patients' morbidity and mortality, particularly since currently, cone beam CT interpretation is not always preformed.

KEY POINTS

• A deep learning algorithm was developed for automatic detection and 3D segmentation of various maxillofacial bone lesions in CBCT scans, irrespective of the CBCT device or the scanning protocol. • The developed algorithm can detect incidental jaw lesions with high accuracy, generates a 3D segmentation of the lesion, and calculates the lesion volume.

The Global, Regional, and National Burden of Adult Lip, Oral, and Pharyngeal Cancer in 204 Countries and Territories: A Systematic Analysis for the Global Burden of Disease Study 2019

Importance

Lip, oral, and pharyngeal cancers are important contributors to cancer burden worldwide, and a comprehensive evaluation of their burden globally, regionally, and nationally is crucial for effective policy planning.

Objective

To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.

Evidence Review

The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.

Findings

In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.

Conclusions and Relevance

In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.

Assessment of knowledge and awareness among North Indian populations about oral precancerous lesions (OPL): A cross-sectional survey study

Background

A precancerous lesion is a morphologically altered tissue in which oral cancer is more likely to occur than its apparently normal counterpart. They are quite common in the Indian population due to the habitual habit of chewing tobacco. The aim of this study was to evaluate the awareness of oral precancerous lesions by a questionnaire-based survey among the study subjects having been diagnosed with it.

Methods

In this descriptive study, a structured questionnaire having 11 survey questions has been used to record the response from study subjects who have been diagnosed and reported for treatment for oral premalignant lesions in the Department of Oral Medicine and Radiology. A total of 1013 study subjects were assessed for awareness about OPL and its consequences.

Results

44.3% of the study population was addicted to smoking tobacco (cigarettes) while 57.9% of study subjects were addicted to non-smoking tobacco (Pan masala). The reason behind their addiction was reported to be stress (54.9%) and workload (25.3%). Most of the study subjects were diagnosed with oral sub-mucous fibrosis (53.4%). 78.6% of study subjects diagnosed with OPL were not aware of it and 94% were willing to quit the addiction.

Conclusion

The awareness about OPL among patients was found to be low. Although many wanted to quit their addiction to smoking and chewing tobacco but were unable to do so. So it is a need for time to develop a national policy on tobacco use and related diseases. This policy will definitely reduce the burden of oral premalignant lesions and oral cancer in Indian population.

Growth differentiation factor-15 and circulating biomarkers as predictors of periodontal treatment effects in patients with periodontitis: a randomized-controlled clinical trial

BACKGROUND

During the last decades, in patients with periodontitis, periodontal treatment has been shown to reduce the potential release of local and systemic biomarkers linked to an early risk of systemic inflammatory disorders. This study evaluated the efficacy of non-surgical-periodontal treatment (NSPT) on growth differentiation factor 15 (GDF-15) and related circulating biomarkers such as glutathione peroxidase 1 (GPx-1), c-reactive protein (hs-CRP), and surfactant protein D (SP-D) in periodontal patients and explored whether subjects who had high GDF-15 levels at baseline showed increased clinical benefits following NSPT at 6-months follow-up.

METHODS

For this two-arm, parallel randomized clinical trial, patients with periodontitis were randomly allocated to receive quadrant scaling and root-planing (Q-SRP, n = 23, median age 51 years old) or full-mouth disinfection (FMD, n = 23, median age 50 years old) treatment. Clinical and periodontal parameters were recorded in all enrolled patients. The primary outcome was to analyse serum concentrations changes of GDF-15 and of GPx-1, hs-CRP, and SP-D at baseline and at 30, 90, and 180-days follow-up after NSPT through enzyme-linked immunosorbent assay (ELISA) and nephelometric assay techniques.

RESULTS

In comparison with FMD, patients of the Q-SRP group showed a significant improvement in clinical periodontal parameters (p < 0.05) and a reduction in the mean levels of GDF-15 (p = 0.005), hs-CRP (p < 0.001), and SP-D (p = 0.042) and an increase of GPx-1 (p = 0.025) concentrations after 6 months of treatment. At 6 months of treatment, there was a significant association between several periodontal parameters and the mean concentrations of GDF-15, GPx-1, hs-CRP, and SP-D (p < 0.05 for all parameters). Finally, the ANOVA analysis revealed that, at 6 months after treatment, the Q-SRP treatment significantly impacted the reduction of GDF-15 (p = 0.015), SP-D (p = 0.026) and the upregulation of GPx-1 (p = 0.045).

CONCLUSION

The results evidenced that, after 6 months of treatment, both NSPT protocols improved the periodontal parameters and analyzed biomarkers, but Q-SRP was more efficacious than the FMD approach. Moreover, patients who presented high baseline GDF-15 and SP-D levels benefited more from NSPT at 6-month follow-up.

TRIAL REGISTRATION

NCT05720481.

Accuracy of digital and conventional systems in locating occlusal contacts: A clinical study

STATEMENT OF PROBLEM

The accuracy of methods used for locating occlusal contacts throughout the entire clinical procedure has been poorly studied.

PURPOSE

The purpose of this clinical study was to determine the reproducibility and criterion validity for different methods of locating occlusal contacts.

MATERIAL AND METHODS

Thirty-two adults with natural dentitions participated in this cross-sectional test-retest study. In total, occlusal contacts at maximum intercuspation were recorded by using 15 methods: silicone transillumination with Occlufast Rock (40, 50, 100, and 200 µm) and Occlufast CAD (40 and 50 µm); virtual occlusion (100, 200, 300, and 400 µm); articulating film (12-, 40-, 100-, and 200-µm-thick); and T-Scan III. Images of the occlusal records were scaled and calibrated spatially, and the occlusal contacts of the right posterior mandibular teeth were delimited by using the FIJI software program. Reproducibility was expressed as 95% confidence intervals (95% CI) of the percentage of agreement in the location of the occlusal contacts between images from the test sessions against retest sessions using the same method. Criterion validity was expressed as 95% CI of the percentage of agreement in the location of the occlusal contacts between images from the test sessions against images from Occlufast Rock (criterion standard).

RESULTS

Occlufast Rock achieved 85% to 95% agreement in the location of the occlusal contacts between the 2 sessions, whereas Occlufast CAD, 200-µm articulating film, and T-Scan offered 79% to 86%, 68% to 75%, and 65% to 75% agreement, respectively. The most valid method was Occlufast CAD (74% to 80%) followed by the 200-µm articulating film (57% to 63%), 400-µm virtual occlusion (53% to 62%), 100-µm articulating film (52% to 60%), and T-Scan (48% to 56%).

CONCLUSIONS

Conventional methods, such as 100- and 200-µm articulating film and digital methods, including 400 µm virtual occlusion and T-Scan, offer sufficient accuracy in locating the occlusal contacts. However, strategies are needed to improve accuracy.

A Systematic Review of the Use of mHealth in Oral Health Education among Older Adults

Oral diseases are largely preventable. However, as the number of older adults is expected to increase, along with the high cost and various barriers to seeking continuous professional care, a sustainable approach is needed to assist older adults in maintaining their oral health. Mobile health (mHealth) technologies may facilitate oral disease prevention and management through oral health education. This review aims to provide an overview of existing evidence on using mHealth to promote oral health through education among older adults. A literature search was performed across five electronic databases. A total of five studies were identified, which provided low to moderate evidence to support using mHealth among older adults. The selected studies showed that mHealth could improve oral health management, oral health behavior, and oral health knowledge among older adults. However, more quality studies regarding using mHealth technologies in oral health management, oral health behavior, and oral health knowledge among older adults are needed.

Federated vs Local vs Central Deep Learning of Tooth Segmentation on Panoramic Radiographs

OBJECTIVE

Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple data sources without directly sharing data. Due to the large amount of sensitive data in dentistry, FL may be particularly relevant for oral and dental research and applications. This study, for the first time, employed FL for a dental task, automated tooth segmentation on panoramic radiographs.

METHODS

We employed a dataset of 4,177 panoramic radiographs collected from nine different centers (n = 143 to n = 1881 per center) across the globe and used FL to train a machine learning model for tooth segmentation. FL performance was compared against Local Learning (LL), i.e., training models on isolated data from each center (assuming data sharing not to be an option). Further, the performance gap to Central Learning (CL), i.e., training on centrally pooled data (based on data sharing agreements) was quantified. Generalizability of models was evaluated on a pooled test dataset from all centers.

RESULTS

For 8 out of 9 centers, FL outperformed LL with statistical significance (p<0.05); only the center providing the largest amount of data FL did not have such an advantage. For generalizability, FL outperformed LL across all centers. CL surpassed both FL and LL for performance and generalizability.

CONCLUSION

If data pooling (for CL) is not feasible, FL is shown to be a useful alternative to train performant and, more importantly, generalizable deep learning models in dentistry, where data protection barriers are high.

CLINICAL SIGNIFICANCE

This study proves the validity and utility of FL in the field of dentistry, which encourages researchers to adopt this method to improve the generalizability of dental AI models and ease their transition to the clinical environment.

Ethical considerations on artificial intelligence in dentistry: A framework and checklist

OBJECTIVE

Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and intellectual human tasks. In dentistry, AI offers the potential to enhance diagnostic accuracy, improve patient outcomes and streamline workflows. The present study provides a framework and a checklist to evaluate AI applications in dentistry from this perspective.

METHODS

Lending from existing guidance documents, an initial draft of the checklist and an explanatory paper were derived and discussed among the groups members.

RESULTS

The checklist was consented to in an anonymous voting process by 29 Topic Group Dental Diagnostics and Digital Dentistry, ITU/WHO Focus Group AI on Health's members. Overall, 11 principles were identified (diversity, transparency, wellness, privacy protection, solidarity, equity, prudence, law and governance, sustainable development, accountability, and responsibility, respect of autonomy, decision-making).

CONCLUSIONS

Providers, patients, researchers, industry, and other stakeholders should consider these principles when developing, implementing, or receiving AI applications in dentistry.

CLINICAL SIGNIFICANCE

While AI has become increasingly commonplace in dentistry, there are ethical concerns around its usage, and users (providers, patients, and other stakeholders), as well as the industry should consider these when developing, implementing, or receiving AI applications based on comprehensive framework to address the associated ethical challenges.

Advances in tissue engineering of cancer microenvironment-from three-dimensional culture to three-dimensional printing

Cancer treatment development is a complex process, with tumor heterogeneity and inter-patient variations limiting the success of therapeutic intervention. Traditional two-dimensional cell culture has been used to study cancer metabolism, but it fails to capture physiologically relevant cell-cell and cell-environment interactions required to mimic tumor-specific architecture. Over the past three decades, research efforts in the field of 3D cancer model fabrication using tissue engineering have addressed this unmet need. The self-organized and scaffold-based model has shown potential to study the cancer microenvironment and eventually bridge the gap between 2D cell culture and animal models. Recently, three-dimensional (3D) bioprinting has emerged as an exciting and novel biofabrication strategy aimed at developing a 3D compartmentalized hierarchical organization with the precise positioning of biomolecules, including living cells. In this review, we discuss the advancements in 3D culture techniques for the fabrication of cancer models, as well as their benefits and limitations. We also highlight future directions associated with technological advances, detailed applicative research, patient compliance, and regulatory challenges to achieve a successful bed-to-bench transition.

Deep convolutional neural network algorithm for the automatic segmentation of oral potentially malignant disorders and oral cancers

This study aimed to develop an algorithm to automatically segment the oral potentially malignant diseases (OPMDs) and oral cancers (OCs) of all oral subsites with various deep convolutional neural network applications. A total of 510 intraoral images of OPMDs and OCs were collected over 3 years (2006-2009). All images were confirmed both with patient records and histopathological reports. Following the labeling of the lesions the dataset was arbitrarily split, using random sampling in Python as the study dataset, validation dataset, and test dataset. Pixels were classified as the OPMDs and OCs with the OPMD/OC label and the rest as the background. U-Net architecture was used and the model with the best validation loss was chosen for the testing among the trained 500 epochs. Dice similarity coefficient (DSC) score was noted. The intra-observer ICC was found to be 0.994 while the inter-observer reliability was 0.989. The calculated DSC and validation accuracy across all clinical images were 0.697 and 0.805, respectively. Our algorithm did not maintain an excellent DSC due to multiple reasons for the detection of both OC and OPMDs in oral cavity sites. A better standardization for both 2D and 3D imaging (such as patient positioning) and a bigger dataset are required to improve the quality of such studies. This is the first study which aimed to segment OPMDs and OCs in all subsites of oral cavity which is crucial not only for the early diagnosis but also for higher survival rates.

Predictive profiling of gram-negative antibiotics in CagA oncoprotein inactivation: a molecular dynamics simulation approach

Gastric cancer (GC) is the fifth most prevalent form of cancer worldwide. CagA - positive Helicobacter pylori infects more than 60% of the human population. Moreover, chronic infection of CagA-positive H. pylori can directly affect GC incidence. In the current study, we have repurposed FDA-approved antibiotics that are viable alternatives to current regimens and can potentially be used as combination therapy against the CagA of H. pylori. The 100 FDA-approved gram negative antibiotics were screened against CagA protein using the AutoDock 4.2 tool. Further, top nine compounds were selected based on higher binding affinity with CagA. The trajectory analysis of MD simulations reflected that binding of these drugs with CagA stabilizes the system. Nonetheless, atomic density map and principal component analysis also support the notion of stable binding of antibiotics to the protein. The residues ASP96, GLN100, PRO184, and THR185 of compound cefpiramide, doxycycline, delafloxacin, metacycline, oxytetracycline, and ertapenem were involved in the binding with CagA protein. These residues are crucial for the CagA that aids in entry or pathogenesis of the bacterium. The screened FDA-approved antibiotics have a potential druggability to inhibit CagA and reduce the progression of H. pylori borne diseases.

Association of interleukin-1, interleukin-6, collagen type I alpha 1, and osteocalcin gene polymorphisms with early crestal bone loss around submerged dental implants: A nested case control study

STATEMENT OF PROBLEM

The reason for variations in peri-implant early crestal bone loss is unclear but may be due to genetic differences among individuals.

PURPOSE

The purpose of this nested case control study was to investigate the association of single-nucleotide polymorphisms of interleukin-1, interleukin-6, collagen type I alpha1, and osteocalcin genes to early crestal bone loss around submerged dental implants.

MATERIAL AND METHODS

Dental implants were placed in the mandibular posterior region (single edentulous space) of 135 participants selected according to predetermined selection criteria. Bone mineral density measurement by using dual energy X-ray absorptiometry, cone beam computed tomography scans at the baseline and after 6 months, and interleukin-1A-889 A/G (rs1800587), interleukin-1B-511 G/A (rs16944), interleukin-1B+3954 (rs1143634), interleukin-6-572 C/G (rs1800796), collagen type I alpha1 A/C (rs1800012), and osteocalcin C/T (rs1800247) genotyping were performed in all participants. Early crestal bone loss measured around dental implants was used to group participants into clinically significant bone loss (BL)>0.5 mm and clinically nonsignificant bone loss (NBL)≤0.5 mm. Early crestal bone loss was calculated as the mean of the difference of bone levels at the baseline and bone levels after 6 months as measured with cone beam computed tomography scans. The obtained data for basic characteristics, early crestal bone loss, and genotyping were tabulated and compared by using a statistical software program (α=.05).

RESULTS

AA genotype and the A allele frequency of interleukin-1B-511 and GG genotype and the G allele frequency of interleukin-6-572 were significantly higher in BL than in NBL (P<.05). Multiple logistic analysis suggested that interleukin-1B-511 AA/GG+AG and interleukin-6-572 GG/CC+CG genotype expression were significantly associated with early crestal bone loss (AA/GG+AG; P=.014, GG/CC+CG; P=.047) around dental implants. Other risk factors were not significantly different (P>.05).

CONCLUSIONS

Of the genes studied, individuals with interleukin-1B-511 AA (rs16944) or interleukin-6-572 GG (rs1800796) genotype had higher susceptibility to early crestal bone loss around dental implants.

PGPR: the treasure of multifarious beneficial microorganisms for nutrient mobilization, pest biocontrol and plant growth promotion in field crops

Plant growth-promoting rhizobacteria (PGPR) have multifarious beneficial activities for plant growth promotion; act as source of metabolites, enzymes, nutrient mobilization, biological control of pests, induction of disease resistance vis-a-vis bioremediation potentials by phytoextraction and detoxification of heavy metals, pollutants and pesticides. Agrochemicals and synthetic pesticides are currently being utilized widely in all major field crops, thereby adversely affecting human and animal health, and posing serious threats to the environments. Beneficial microorganisms like PGPR could potentially substitute and supplement the toxic chemicals and pesticides with promising application in organic farming leading to sustainable agriculture practices and bioremediation of heavy metal contaminated sites. Among field crops limited bio-formulations have been prepared till now by utilization of PGPR strains having plant growth promotion, metabolites, enzymes, nutrient mobilization and biocontrol activities. The present review contributes comprehensive description of PGPR applications in field crops including commercial, oilseeds, leguminous and cereal crops to further extend the utilization of these potent groups of beneficial microorganisms so that even higher level of crop productivity and quality produce of field crops could be achieved. PGPR and bacteria based commercialized bio-formulations available worldwide for its application in the field crops have been compiled in this review which can be a substitute for the harmful synthetic chemicals. The current knowledge gap and potential target areas for future research have also been projected.

Radiographic findings of space-occupying lesions in sialo-CBCT of the major salivary glands

OBJECTIVES

When performing CBCT sialography (sialo-CBCT), space-occupying lesions may be identified incidentally. The objective was to describe their radiologic-clinical-histopathologic correlations.

METHOD AND MATERIALS

The archive of sialo-CBCT scans was retrospectively searched for suspected space-occupying lesions. Based on the scan and clinical-histopathologic data, the cases were divided into "pathologic" vs "normal," "intra-parenchymal" vs "extra-parenchymal," and "benign" vs "malignant." Two precalibrated, blinded radiologists performed a survey of the radiographic features of each scan. Cohen kappa, chi-square, Kruskal-Wallis, and Mann-Whitney tests assessed inter-observer agreement and radiologic-clinical-histopathologic correlations.

RESULTS

In total, 27 (1.5%) suspected space-occupying lesions were found in 1,758 reports. Full follow-up data were available for 15 cases: four were "malignant," six were "benign," and the remaining five were "normal." Kappa showed substantial inter-observer agreement (0.8 to 1.0). Constant swelling correlated with "pathologic" cases (P = .003). Lesion diameter was greater in "pathologic" than "normal" (P < .001) cases, with a cut-off of 12.6 mm. Clinical and radiographic features were similar in "benign" and "malignant" lesions. "Intra-parenchymal" and "extra-parenchymal" space-occupying lesions correlated with "no-fill-region" (P = .01) and "main-duct-displacement" (P = .002), respectively.

CONCLUSIONS

Suspected space-occupying lesions in sialo-CBCT with a diameter greater than 12.6 mm are likely to be "pathologic." No radiographic features were able to differentiate between "malignant" and "benign" space-occupying lesions.

Artificial intelligence for oral and dental healthcare: Core education curriculum

OBJECTIVES

Artificial intelligence (AI) is swiftly entering oral health services and dentistry, while most providers show limited knowledge and skills to appraise dental AI applications. We aimed to define a core curriculum for both undergraduate and postgraduate education, establishing a minimum set of outcomes learners should acquire when taught about oral and dental AI.

METHODS

Existing curricula and other documents focusing on literacy of medical professionals around AI were screened and relevant items extracted. Items were scoped and adapted using expert interviews with members of the IADR's e-oral health group, the ITU/WHO's Focus Group AI for Health and the Association for Dental Education in Europe. Learning outcome levels were defined and each item assigned to a level. Items were systematized into domains and a curricular structure defined. The resulting curriculum was consented using an online Delphi process.

RESULTS

Four domains of learning outcomes emerged, with most outcomes being on the "knowledge" level: (1) Basic definitions and terms, the reasoning behind AI and the principle of machine learning, the idea of training, validating and testing models, the definition of reference tests, the contrast between dynamic and static AI, and the problem of AI being a black box and requiring explainability should be known. (2) Use cases, the required types of AI to address them, and the typical setup of AI software for dental purposes should be taught. (3) Evaluation metrics, their interpretation, the relevant impact of AI on patient or societal health outcomes and associated examples should be considered. (4) Issues around generalizability and representativeness, explainability, autonomy and accountability and the need for governance should be highlighted.

CONCLUSION

Both educators and learners should consider this core curriculum during planning, conducting and evaluating oral and dental AI education.

CLINICAL SIGNIFICANCE

A core curriculum on oral and dental AI may help to increase oral and dental healthcare providers' literacy around AI, allowing them to critically appraise AI applications and to use them consciously and on an informed basis.

Global prevalence of edentulism and dental caries in middle-aged and elderly persons: A systematic review and meta-analysis

OBJECTIVE

The aim of the study was to analyze data collected from studies worldwide on the prevalence of edentulism and dental caries, in community-dwellers aged ≥ 45 years.

DATA

Inclusion criteria; participants aged ≥ 45 years, community-dwellers. Exclusion criteria; participants aged < 45 years, in nursing homes, data obtained from dental clinics or pre-2005. The quality assessment tool by The National Heart, Lung and Blood Institute for Observational Cohort and Cross-sectional studies was used. Meta-analysis using the random-effects model (95% confidence interval) was done with data on participants who were edentulous and/or had active dental caries and stratified by regions of the world, age and Gross National Income per capita. Limitations in the data arose from several factors such as design of the studies included differences in socioeconomic status and access to health care among different countries.

SOURCES

Embase, MEDLINE via Pubmed and Scopus, manual searches, from January 2016, restricted to English. Experts from different countries were contacted to identify National oral health surveys (NOHS) conducted from 2010 onwards.

STUDY SELECTION

Eighty-six papers and seventeen NOHS were selected for data extraction. Majority of the studies (n = 69) were cross-sectional and of fair quality. 1.1%-70%, 4.9% - 98% prevalence of edentulism and dental caries, respectively. 22%, 45% estimated random-effects pooled prevalence of edentulism and dental caries, respectively.

CONCLUSIONS

Within the limitations of this study, the findings indicate that untreated dental caries and tooth loss are prevalent on a global level with wide variations among different countries, age groups and socioeconomic status.

CLINICAL SIGNIFICANCE

The findings demonstrate the reality of the new cohort of older adults, with higher tooth retention implying more dental caries incidence and the need for different care strategies to ensure better oral health. Large variations and difficulty in making comparisons among different countries highlight the need for more standardized, regular research.

Artificial Intelligence for Caries Detection: Value of Data and Information

If increasing practitioners’ diagnostic accuracy, medical artificial intelligence (AI) may lead to better treatment decisions at lower costs, while uncertainty remains around the resulting cost-effectiveness. In the present study, we assessed how enlarging the data set used for training an AI for caries detection on bitewings affects cost-effectiveness and also determined the value of information by reducing the uncertainty around other input parameters (namely, the costs of AI and the population’s caries risk profile). We employed a convolutional neural network and trained it on 10%, 25%, 50%, or 100% of a labeled data set containing 29,011 teeth without and 19,760 teeth with caries lesions stemming from bitewing radiographs. We employed an established health economic modeling and analytical framework to quantify cost-effectiveness and value of information. We adopted a mixed public–private payer perspective in German health care; the health outcome was tooth retention years. A Markov model, allowing to follow posterior teeth over the lifetime of an initially 12-y-old individual, and Monte Carlo microsimulations were employed. With an increasing amount of data used to train the AI sensitivity and specificity increased nonlinearly, increasing the data set from 10% to 25% had the largest impact on accuracy and, consequently, cost-effectiveness. In the base-case scenario, AI was more effective (tooth retention for a mean [2.5%–97.5%] 62.8 [59.2–65.5] y) and less costly (378 [284–499] euros) than dentists without AI (60.4 [55.8–64.4] y; 419 [270–593] euros), with considerable uncertainty. The economic value of reducing the uncertainty around AI’s accuracy or costs was limited, while information on the population’s risk profile was more relevant. When developing dental AI, informed choices about the data set size may be recommended, and research toward individualized application of AI for caries detection seems warranted to optimize cost-effectiveness.

Emulating Clinical Diagnostic Reasoning for Jaw Cysts with Machine Learning

The detection and classification of cystic lesions of the jaw is of high clinical relevance and represents a topic of interest in medical artificial intelligence research. The human clinical diagnostic reasoning process uses contextual information, including the spatial relation of the detected lesion to other anatomical structures, to establish a preliminary classification. Here, we aimed to emulate clinical diagnostic reasoning step by step by using a combined object detection and image segmentation approach on panoramic radiographs (OPGs). We used a multicenter training dataset of 855 OPGs (all positives) and an evaluation set of 384 OPGs (240 negatives). We further compared our models to an international human control group of ten dental professionals from seven countries. The object detection model achieved an average precision of 0.42 (intersection over union (IoU): 0.50, maximal detections: 100) and an average recall of 0.394 (IoU: 0.50–0.95, maximal detections: 100). The classification model achieved a sensitivity of 0.84 for odontogenic cysts and 0.56 for non-odontogenic cysts as well as a specificity of 0.59 for odontogenic cysts and 0.84 for non-odontogenic cysts (IoU: 0.30). The human control group achieved a sensitivity of 0.70 for odontogenic cysts, 0.44 for non-odontogenic cysts, and 0.56 for OPGs without cysts as well as a specificity of 0.62 for odontogenic cysts, 0.95 for non-odontogenic cysts, and 0.76 for OPGs without cysts. Taken together, our results show that a combined object detection and image segmentation approach is feasible in emulating the human clinical diagnostic reasoning process in classifying cystic lesions of the jaw.

Population-level risks of alcohol consumption by amount, geography, age, sex, and year: a systematic analysis for the Global Burden of Disease Study 2020

BACKGROUND

The health risks associated with moderate alcohol consumption continue to be debated. Small amounts of alcohol might lower the risk of some health outcomes but increase the risk of others, suggesting that the overall risk depends, in part, on background disease rates, which vary by region, age, sex, and year.

METHODS

For this analysis, we constructed burden-weighted dose-response relative risk curves across 22 health outcomes to estimate the theoretical minimum risk exposure level (TMREL) and non-drinker equivalence (NDE), the consumption level at which the health risk is equivalent to that of a non-drinker, using disease rates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 for 21 regions, including 204 countries and territories, by 5-year age group, sex, and year for individuals aged 15-95 years and older from 1990 to 2020. Based on the NDE, we quantified the population consuming harmful amounts of alcohol.

FINDINGS

The burden-weighted relative risk curves for alcohol use varied by region and age. Among individuals aged 15-39 years in 2020, the TMREL varied between 0 (95% uncertainty interval 0-0) and 0·603 (0·400-1·00) standard drinks per day, and the NDE varied between 0·002 (0-0) and 1·75 (0·698-4·30) standard drinks per day. Among individuals aged 40 years and older, the burden-weighted relative risk curve was J-shaped for all regions, with a 2020 TMREL that ranged from 0·114 (0-0·403) to 1·87 (0·500-3·30) standard drinks per day and an NDE that ranged between 0·193 (0-0·900) and 6·94 (3·40-8·30) standard drinks per day. Among individuals consuming harmful amounts of alcohol in 2020, 59·1% (54·3-65·4) were aged 15-39 years and 76·9% (73·0-81·3) were male.

INTERPRETATION

There is strong evidence to support recommendations on alcohol consumption varying by age and location. Stronger interventions, particularly those tailored towards younger individuals, are needed to reduce the substantial global health loss attributable to alcohol.

FUNDING

Bill & Melinda Gates Foundation.

Impact of Laser Therapy on Periodontal and Peri-Implant Diseases

Objective: In the last few decades, lasers in dentistry have encompassed all branches in dentistry, with more focus in periodontology. In recent years, the use of lasers against periodontitis and peri-implantitis has undergone a decisive development that has involved various operational areas. The broadest applications were probably found in the clinical approach to soft tissues. Methods: Laser therapy is a novel technique that may provide further beneficial effects to conventional periodontal and peri-implant therapies. However, clinical evidence for the improvement of periodontal wound healing and tissue regeneration through laser treatment is still limited. Results: This review is aimed at assessing the advantages and disadvantages of the use of lasers in dental procedures and pathologies, focusing more on protocols for the management of periodontal and peri-implant diseases. Conclusions: The adjuvant action of laser therapy, in addition to conventional therapies for the management of periodontal and peri-implant disease, could induce benefits, but further investigation would be necessary to standardize better the protocols applied and to understand the actual tissue response to laser therapy.

Cost-effectiveness of AI for Caries Detection: Randomized Trial

OBJECTIVES

We assessed the cost-effectiveness of AI-supported detection of proximal caries in a randomized controlled clustered cross-over superiority trial.

METHODS

Twenty-three dentists were sampled to assess 20 bitewings; 10 were randomly evaluated supported by an AI-based software (dentalXrai Pro 1.0.4, dentalXrai Ltd, Berlin, Germany) and the other 10 without AI support. The reference test had been established by four independent experts and an additional review. We evaluated the proportion of true and false positive and negative detections and the treatment decisions assigned to each detection (non-invasive, micro-invasive, invasive). Cost-effectiveness was assessed using a mixed public-private-payer perspective in German healthcare. Using the accuracy and treatment decision data from the trial, a Markov simulation model was populated and posterior permanent teeth in initially 31-years old individuals followed over their lifetime. The model allowed extrapolation from the initial detection and therapy to treatment success, re-treatments and, eventually, tooth loss and replacement, capturing long-term effectiveness (tooth retention) and costs (cumulative in Euro). Costs were estimated using the German public and private fee catalogues. Monte-Carlo microsimulations were used and incremental cost-effectiveness at different willingness-to-pay ceiling thresholds assessed.

RESULTS

In the trial, AI-supported detection was significantly more sensitive than detection without AI. However, in the AI group, lesions were more often treated invasively. As a result, AI and no AI showed identical effectiveness (tooth retention for a mean (2.5-97.5%) 49 (48-51)) and nearly identical costs (AI: 330 (250-409) Euro, no AI: 330 (248-410) Euro). 41% simulations found AI and 43% no AI to be more cost-effective. The resulting cost-effectiveness remained uncertain regardless of a payer's willingness-to-pay.

CONCLUSIONS

Higher accuracy of AI did not lead to higher cost-effectiveness, as more invasive treatment approaches generated costs and diminished possible effectiveness advantages.

CLINICAL SIGNIFICANCE

The cost-effectiveness of AI could be improved by supporting not only caries detection, but also subsequent management.

The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

In estimating the global burden of cancer, adolescents and young adults with cancer are often overlooked, despite being a distinct subgroup with unique epidemiology, clinical care needs, and societal impact. Comprehensive estimates of the global cancer burden in adolescents and young adults (aged 15-39 years) are lacking. To address this gap, we analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, with a focus on the outcome of disability-adjusted life-years (DALYs), to inform global cancer control measures in adolescents and young adults.

METHODS

Using the GBD 2019 methodology, international mortality data were collected from vital registration systems, verbal autopsies, and population-based cancer registry inputs modelled with mortality-to-incidence ratios (MIRs). Incidence was computed with mortality estimates and corresponding MIRs. Prevalence estimates were calculated using modelled survival and multiplied by disability weights to obtain years lived with disability (YLDs). Years of life lost (YLLs) were calculated as age-specific cancer deaths multiplied by the standard life expectancy at the age of death. The main outcome was DALYs (the sum of YLLs and YLDs). Estimates were presented globally and by Socio-demographic Index (SDI) quintiles (countries ranked and divided into five equal SDI groups), and all estimates were presented with corresponding 95% uncertainty intervals (UIs). For this analysis, we used the age range of 15-39 years to define adolescents and young adults.

FINDINGS

There were 1·19 million (95% UI 1·11-1·28) incident cancer cases and 396 000 (370 000-425 000) deaths due to cancer among people aged 15-39 years worldwide in 2019. The highest age-standardised incidence rates occurred in high SDI (59·6 [54·5-65·7] per 100 000 person-years) and high-middle SDI countries (53·2 [48·8-57·9] per 100 000 person-years), while the highest age-standardised mortality rates were in low-middle SDI (14·2 [12·9-15·6] per 100 000 person-years) and middle SDI (13·6 [12·6-14·8] per 100 000 person-years) countries. In 2019, adolescent and young adult cancers contributed 23·5 million (21·9-25·2) DALYs to the global burden of disease, of which 2·7% (1·9-3·6) came from YLDs and 97·3% (96·4-98·1) from YLLs. Cancer was the fourth leading cause of death and tenth leading cause of DALYs in adolescents and young adults globally.

INTERPRETATION

Adolescent and young adult cancers contributed substantially to the overall adolescent and young adult disease burden globally in 2019. These results provide new insights into the distribution and magnitude of the adolescent and young adult cancer burden around the world. With notable differences observed across SDI settings, these estimates can inform global and country-level cancer control efforts.

FUNDING

Bill & Melinda Gates Foundation, American Lebanese Syrian Associated Charities, St Baldrick's Foundation, and the National Cancer Institute.

A randomized controlled trial for evaluation of bone density changes around immediate functionally and nonfunctionally loaded implants using three-dimensional cone-beam computed tomography

Aim

The aim of this study was to compare and assess bone density changes around immediate functionally and nonfunctionally loaded implants.

Settings and design

In vivo comparative study.

Materials and Methods

Sixty participants selected based on the predetermined inclusion and exclusion criteria received single tooth implants in mandible under two implant loading protocols: Immediate functionally loaded (IFL) and immediate nonfunctionally loaded (INFL). Randomization was done by computer-aided simple randomization procedure. Self-tapering, aggressive SLA implants were placed in the single tooth edentulous sites of mandible in both the groups. Three-dimensional cone-beam computed tomography (3D CBCT) was taken at baseline, 3 and 6 months postimplant placement. Quantitative analysis of the bone density was performed using 3D CBCT in three areas around the implants at crestal, middle, and apical regions of implants.

Statistical Analysis Used

Quantitative data were summarized as mean ± standard deviation. Statistical analyses were performed using the SPSS software version 21.0 (SPSS Inc., Chicago, IL, USA) by unpaired t-test.

Results

Bone density changes after implant placement in IFL group from baseline to 3 months were; crestal region (314.18 ± 71.69), middle (278.23 ± 70.17), apical (274.70 ± 59.79) and changes from 3 to 6 months were; crestal (-105.55 ± 39.60), middle (-114.80 ± 41.46), apical (-141.88 ± 69.58). Bone density changes after implant placement in INFL group from baseline to 3 months were crestal region (199.42 ± 47.97), middle (56.91 ± 10.39), apical (200.98 ± 67.43) and changes from 3 to 6 months were; crestal (-194.38 ± 75.30), middle (-204.40 ± 63.75), apical (-191.28 ± 62.33).

Conclusions

It was concluded that INFL implant group showed better bone density when compared to IFL implant group.

Effectiveness of mouthwash against viruses: 2020 perspective. A systematic review

INTRODUCTION

Antiseptic mouthwash is widely recommended to treat various oral diseases as well as to improve oral health. Most of the dental procedures lead to the generation of aerosols. These aerosols have a high potential to transmit disease. Preprocedural oral rinse with antimicrobial agents in the form of mouthwashes reduces the bacterial and viral load many folds. The purpose of this review was to summarize the effectiveness of mouthwash against viruses affecting human beings.

EVIDENCE ACQUISITION

Search engines like PubMed, Google Scholar, and others were used to search the electronic database. Articles were identified in which the effectiveness of antiseptic mouth rinse against the virus was tested. A comprehensive search strategy was designed to select the articles and then independently screened for eligibility.

EVIDENCE SYNTHESIS

A total of 9624 articles out of the 13 titles met the eligibility criteria. The selected papers were included in the present manuscript according to their relevance to the topic. Authors searched the most used chemicals as mouthwashes but records of three types of mouthwash tested against various types of viruses i.e. chlorhexidine gluconate, Povidone-iodine and essential oil containing mouthwash (Listerine) were found.

CONCLUSIONS

Povidone-iodine mouth rinse is effective in reducing viral load either in-vitro or in-vivo conditions. Chlorhexidine gluconate mouthwash and essential oils have shown its effectiveness in a few studies. Insufficient evidence is available to support the claim that oral antiseptics can reduce the risk of developing viral loads in humans or the rate of progression of diseases caused by viruses.

Oral cancer diagnostics: An overview

Cancer was first mentioned in medicine texts by Egyptians. Ancient Indians studied oral cancer in great detail under Susruta. Cancer has continued to be a challenge to physicians from ancient times to the present. Over the years, cancer underwent a shift in management from radical surgeries toward a more preventive approach. Early diagnosis is vital in reducing cancer-associated mortality especially with oral cancer. Even though the mainstay of oral cancer diagnosis still continues to be a trained clinician and histopathologic examination of malignant tissues. Translating innovation in technological advancements in diagnostic aids for oral cancer will require both improved decision-making and a commitment toward optimizing cost, skills, turnover time between capturing data and obtaining a useful result. The present review describes the conventional to most advanced diagnostic modalities used as oral cancer diagnostics. It also includes the new technologies available and the future trends in oral cancer diagnostics.

Gabapentin for cessation of smoking and non-smoking tobacco habits in Indian population

BACKGROUND

The effectiveness of gabapentin in tobacco dependence has been evaluated by many researchers. The randomized control trials, testing the efficacy of gabapentin in quitting the habit in smokers and users of smokeless tobacco, have not been published yet. We attempted to address this lacuna in knowledge in reducing dependence on tobacco use by gabapentin.

METHODS

Our study involves 150 study subjects, 75 of whom were identified as chronic users of tobacco and assigned randomly to one of the three groups consisting of 25 subjects each. Gabapentin in tablet form was prescribed thrice a day for 8 weeks wherein group 1 received a dose of 300mg, group 2 received 600 mg, and group 3 was prescribed 900 mg. An age and sex matched control group have received calcium tablets as placebo in three times daily dose for a period of 8 weeks.

RESULTS

Among the three doses of gabapentin, stoppage of habit was reported to be highest in the group-2 followed by group 1 and group 3 respectively. In our study, we found differences in response to quitting tobacco use between duration of habit prior to pharmacologic intervention amongst both smokers and the users of smokeless tobacco.

CONCLUSIONS

Gabapentin at dose of 600 mg TDS has optimum effect. Smokers having smoking for more than ten years showed notable benefit with gabapentin. Among smokeless tobacco users who quit tobacco dependence was better having history of habit less than 2 years.

Classification of Dental Radiographs Using Deep Learning

OBJECTIVES

To retrospectively assess radiographic data and to prospectively classify radiographs (namely, panoramic, bitewing, periapical, and cephalometric images), we compared three deep learning architectures for their classification performance.

METHODS

Our dataset consisted of 31,288 panoramic, 43,598 periapical, 14,326 bitewing, and 1176 cephalometric radiographs from two centers (Berlin/Germany; Lucknow/India). For a subset of images L (32,381 images), image classifications were available and manually validated by an expert. The remaining subset of images U was iteratively annotated using active learning, with ResNet-34 being trained on L, least confidence informative sampling being performed on U, and the most uncertain image classifications from U being reviewed by a human expert and iteratively used for re-training. We then employed a baseline convolutional neural networks (CNN), a residual network (another ResNet-34, pretrained on ImageNet), and a capsule network (CapsNet) for classification. Early stopping was used to prevent overfitting. Evaluation of the model performances followed stratified k-fold cross-validation. Gradient-weighted Class Activation Mapping (Grad-CAM) was used to provide visualizations of the weighted activations maps.

RESULTS

All three models showed high accuracy (>98%) with significantly higher accuracy, F1-score, precision, and sensitivity of ResNet than baseline CNN and CapsNet (p < 0.05). Specificity was not significantly different. ResNet achieved the best performance at small variance and fastest convergence. Misclassification was most common between bitewings and periapicals. For bitewings, model activation was most notable in the inter-arch space for periapicals interdentally, for panoramics on bony structures of maxilla and mandible, and for cephalometrics on the viscerocranium.

CONCLUSIONS

Regardless of the models, high classification accuracies were achieved. Image features considered for classification were consistent with expert reasoning.

Generalizability of deep learning models for dental image analysis

We assessed the generalizability of deep learning models and how to improve it. Our exemplary use-case was the detection of apical lesions on panoramic radiographs. We employed two datasets of panoramic radiographs from two centers, one in Germany (Charité, Berlin, n = 650) and one in India (KGMU, Lucknow, n = 650): First, U-Net type models were trained on images from Charité (n = 500) and assessed on test sets from Charité and KGMU (each n = 150). Second, the relevance of image characteristics was explored using pixel-value transformations, aligning the image characteristics in the datasets. Third, cross-center training effects on generalizability were evaluated by stepwise replacing Charite with KGMU images. Last, we assessed the impact of the dental status (presence of root-canal fillings or restorations). Models trained only on Charité images showed a (mean ± SD) F1-score of 54.1 ± 0.8% on Charité and 32.7 ± 0.8% on KGMU data (p < 0.001/t-test). Alignment of image data characteristics between the centers did not improve generalizability. However, by gradually increasing the fraction of KGMU images in the training set (from 0 to 100%) the F1-score on KGMU images improved (46.1 ± 0.9%) at a moderate decrease on Charité images (50.9 ± 0.9%, p < 0.01). Model performance was good on KGMU images showing root-canal fillings and/or restorations, but much lower on KGMU images without root-canal fillings and/or restorations. Our deep learning models were not generalizable across centers. Cross-center training improved generalizability. Noteworthy, the dental status, but not image characteristics were relevant. Understanding the reasons behind limits in generalizability helps to mitigate generalizability problems.

Artificial intelligence in dental research: Checklist for authors, reviewers, readers

OBJECTIVES

The number of studies employing artificial intelligence (AI), specifically machine and deep learning, is growing fast. The majority of studies suffer from limitations in planning, conduct and reporting, resulting in low robustness, reproducibility and applicability. We here present a consented checklist on planning, conducting and reporting of AI studies for authors, reviewers and readers in dental research.

METHODS

Lending from existing reviews, standards and other guidance documents, an initial draft of the checklist and an explanatory document were derived and discussed among the members of IADR's e-oral network and the ITU/WHO focus group "Artificial Intelligence for Health (AI4H)". The checklist was consented by 27 group members via an e-Delphi process.

RESULTS

Thirty-one items on planning, conducting and reporting of AI studies were agreed on. These involve items on the studies' wider goal, focus, design and specific aims, data sampling and reporting, sample estimation, reference test construction, model parameters, training and evaluation, uncertainty and explainability, performance metrics and data partitions.

CONCLUSION

Authors, reviewers and readers should consider this checklist when planning, conducting, reporting and evaluating studies on AI in dentistry.

CLINICAL SIGNIFICANCE

Current studies on AI in dentistry show considerable weaknesses, hampering their replication and application. This checklist may help to overcome this issue and advance AI research as well as facilitate a debate on standards in this fields.

Clinical outcomes of flap versus flapless immediately loaded single dental implants in the mandibular posterior region: One-year follow-up results from a randomized controlled trial

STATEMENT OF PROBLEM

Flapless implant placement with immediate functional loading has been reported in anterior locations. However, data on posterior locations are lacking.

PURPOSE

The purpose of this randomized controlled trial was to determine and compare clinical outcomes of flap versus flapless surgically placed single posterior mandibular dental implants subjected to immediate functional loading.

MATERIAL AND METHODS

Participants with missing mandibular first molar teeth were recruited and randomized into 2 groups (n=51): flapped and flapless. Dental implants were surgically placed and loaded immediately with interim restorations following implant protective occlusion. Outcome measures were implant failure, crestal bone loss, and periodontal parameters: modified plaque index, modified sulcus bleeding index, and pocket depths. Outcome data were recorded at baseline, 6-month, and 12-month follow-up visits. Cone beam computed tomography scans were used to calculate crestal bone loss, and periodontal outcomes were recorded by using a resin covered periodontal probe (α=.05).

RESULTS

After 12 months, similar implant failure rates (P>.05) were found between the groups. Crestal bone loss in the flapped group was statistically higher than in the flapless group at 6 months (0.83 ±0.21 mm versus 0.75 ±0.23 mm) and at 12 months (1.04 ±0.27 mm versus 0.90 ±0.24 mm) from the baseline. The modified plaque index, modified sulcus bleeding index, and peri-implant probing depths (PDs) in both groups increased from the baseline to 6-month follow-ups (Baseline modified plaque index: 0.82 ±0.54 versus 0.79 ±0.21; Baseline modified sulcus bleeding index: 0.74 ±0.21 versus 0.70 ±0.43; Baseline PD: 1.25 ±0.37 mm versus 1.20 ±0.22 mm; 6 months modified plaque index: 1.54 ±0.70 versus 1.21 ±0.45; 6 months modified sulcus bleeding index: 1.93 ±0.54 versus 1.51 ±0.61; 6 months PD: 3.20 ±0.73 mm versus 2.80 ±0.43 mm). At 12-month follow-ups after repeated oral hygiene reinforcements, periodontal parameters had improved (decreased) significantly.

CONCLUSIONS

Flapless implant insertion with immediate functional loading could be considered as an appropriate treatment option for providing functional restorations on the day of implant placement with minimal surgical intervention, reducing crestal bone loss, and periodontal complications.

Cost-effectiveness of Artificial Intelligence for Proximal Caries Detection

Artificial intelligence (AI) can assist dentists in image assessment, for example, caries detection. The wider health and cost impact of employing AI for dental diagnostics has not yet been evaluated. We compared the cost-effectiveness of proximal caries detection on bitewing radiographs with versus without AI. U-Net, a fully convolutional neural network, had been trained, validated, and tested on 3,293, 252, and 141 bitewing radiographs, respectively, on which 4 experienced dentists had marked carious lesions (reference test). Lesions were stratified for initial lesions (E1/E2/D1, presumed noncavitated, receiving caries infiltration if detected) and advanced lesions (D2/D3, presumed cavitated, receiving restorative care if detected). A Markov model was used to simulate the consequences of true- and false-positive and true- and false-negative detections, as well as the subsequent decisions over the lifetime of patients. A German mixed-payers perspective was adopted. Our health outcome was tooth retention years. Costs were measured in 2020 euro. Monte-Carlo microsimulations and univariate and probabilistic sensitivity analyses were conducted. The incremental cost-effectiveness ratio (ICER) and the cost-effectiveness acceptability at different willingness-to-pay thresholds were quantified. AI showed an accuracy of 0.80; dentists’ mean accuracy was significantly lower at 0.71 (minimum–maximum: 0.61–0.78, P < 0.05). AI was significantly more sensitive than dentists (0.75 vs. 0.36 [0.19–0.65]; P = 0.006), while its specificity was not significantly lower (0.83 vs. 0.91 [0.69–0.98]; P > 0.05). In the base-case scenario, AI was more effective (tooth retention for a mean 64 [2.5%–97.5%: 61–65] y) and less costly (298 [244–367] euro) than assessment without AI (62 [59–64] y; 322 [257–394] euro). The ICER was −13.9 euro/y (i.e., AI saved money at higher effectiveness). In the majority (>77%) of all cases, AI was less costly and more effective. Applying AI for caries detection is likely to be cost-effective, mainly as fewer lesions remain undetected. Notably, this cost-effectiveness requires dentists to manage detected early lesions nonrestoratively.

Gabapentin for cessation of smoking and non-smoking tobacco habits in Indian population

BACKGROUND

The effectiveness of gabapentin in tobacco dependence has been evaluated by many researchers. The randomized control trials, testing the efficacy of gabapentin in quitting the habit in smokers and users of smokeless tobacco, have not been published yet. We attempted to address this lacuna in knowledge in reducing dependence on tobacco use by gabapentin.

METHODS

Our study involves 150 study subjects, 75 of whom were identified as chronic users of tobacco and assigned randomly to one of the three groups consisting of 25 subjects each. Gabapentin in tablet form was prescribed thrice a day for 8 weeks wherein group 1 received a dose of 300mg, group 2 received 600 mg, and group 3 was prescribed 900 mg. An age and sex matched control group have received calcium tablets as placebo in three times daily dose for a period of 8 weeks.

RESULTS

Among the three doses of gabapentin, stoppage of habit was reported to be highest in the group-2 followed by group 1 and group 3 respectively. In our study, we found differences in response to quitting tobacco use between duration of habit prior to pharmacologic intervention amongst both smokers and the users of smokeless tobacco.

CONCLUSIONS

Gabapentin at dose of 600 mg TDS has optimum effect. Smokers having smoking for more than ten years showed notable benefit with gabapentin. Among smokeless tobacco users who quit tobacco dependence was better having history of habit less than 2 years.

Temporomandibular disorders in North Indian population visiting a tertiary care dental hospital

Background:

The terminology “temporomandibular disorders” (TMDs) encompasses a wide spectrum of conditions. Several hypothesized causes are occlusal disharmony, muscle hyperactivity, central pain mechanisms, psychological distress, and trauma. In day-to-day practice, TMDs had become more prevalent in Indian population due to changed dietary pattern and food habits, excessive stress of modern life, and other environmental causes. This study is an attempt to find the prevalence of TMDs in North Indian population.

Aims:

The present study is taken into account to determine the prevalence of TMDs on the basis of signs and symptoms based on the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD).

Materials and Methods:

The present cross-sectional study was conducted in the Department of Oral Medicine and Radiology. A total of 1009 patients aged between 6 and 80 years with a mean age of 42.04 ± 16.8 years seeking dental treatment from January 2016 to June 2017 were included in the study. All the patients were screened for TMD sign and symptoms. The demographic data and the signs and symptoms of TMDs were recorded in designed structured questionnaires which were based on the RDC/TMD criteria.

Results:

The study population consisted of 1009 patients aged between 6 and 80 years. In the present study population, based on RDC/TMD criteria, the incidence of clicking sound (42.5%) was highest in TMD joint followed by deviation of mandible on mouth opening (40.8%), internal derangement (36.8%), myofacial pain dysfunction syndrome (33.7%), osteoarthritis (29.5%), crepitus (25.8%), joint tenderness (5.8%), and pain on mouth opening (4.8%).

Conclusion:

Clicking sound was the most common sign of TMD disorders in Indian population.

Prevalence of trigeminal neuralgia in Indian population visiting a higher dental care center in North India

Objectives:

The present study aims to determine the incidence and prevalence of trigeminal neuralgia (TN) in study population and difference in prevalence of TN in urban and rural population.

Materials and Methods:

This retrospective study includes 1215 study participants with typical idiopathic TN. Data regarding the age of onset, gender, site of involvement, and clinical presentations were retrieved from clinical records of patients reported from January 2011 to January 2018.

Results:

The study population consists of 1215 study participants aged between 21 and 87 years, with a mean age of 50.62 ± 15.872 years. The mandibular nerve is involved in most of the cases (56.9%), followed by maxillary nerve (42%). The right side of the face (57.1%) is more involved than the left side (38.8%). TN was more prevalent (52.4%) in rural population than urban population (47.6%).

Conclusion:

TN is more common in females than males, the right side of the face is more involved than the left side, and it is more commonly found in rural population than urban population.

Comparative Evaluation of role of Lysyl oxidase gene (LOXG473A) expression in pathogenesis and malignant transformation of Oral Submucous Fibrosis

Background

Identification and comparison of gene expression of Lysyl oxidase (LOX) in oral submucous fibrosis and controls and to determine its role in Pathogenesis of Oral submucous fibrosis.

Material and Methods

Of total sample size (n=127), the whole blood sample were collected from case and control group in citrate vial. It is centrifused and stored at -800C. We collected and isolated RNA from blood of case group (n=127) and age and sex matched control group (n=127) recruited on the basis of inclusion criteria. The cDNA was prepared for 127 samples which were processed for gene expression of Lysyl oxidase (LOX) in relation to housekeeping genes (Beta actin and 18srRNA) and its role in pathogenesis of Oral submucous fibrosis.

Results

In relative expression (Normalized ratio),relatively 11 cases shown down-regulation of lysyl oxidase gene while 27 cases shows up-regulation of lysyl oxidase gene while in 89 cases there were no regulation i.e expression of lysyl oxidase gene in case group was of same degree of control. In non-relative expression results (Non-normalized ratio), the 38 cases shown down regulation of LOX gene while in 53 cases, it was up-regulated however in remaining 36 cases there was neither up-regulation nor down-regulation of Lysyl oxidase gene i.e the expression of LOX gene is null.

Conclusions

In oral submucous fibrosis, the expression of Lysyl oxidase gene is mixed type i.e either it will down regulate/upregulate or there will be no expression at all comparatively. However in majority of cases the upregulation of lysyl oxidase is relatively more common than down-regulation or non expression of Lysyl oxidase gene.

Key words:Oral submucous fibrosis, lysyl oxidase, betel nut, premalignant disorders.