Effectiveness of AI-driven remote monitoring technology in improving oral hygiene during orthodontic treatment

AI-Driven Advancements in Orthodontics for Precision and Patient Outcomes

Artificial Intelligence (AI) is rapidly transforming orthodontic care by providing personalized treatment plans that enhance precision and efficiency. This narrative review explores the current applications of AI in orthodontics, particularly its role in predicting tooth movement, fabricating custom aligners, optimizing treatment times, and offering real-time patient monitoring. AI's ability to analyze large datasets of dental records, X-rays, and 3D scans allows for highly individualized treatment plans, improving both clinical outcomes and patient satisfaction. AI-driven aligners and braces are designed to apply optimal forces to teeth, reducing treatment time and discomfort. Additionally, AI-powered remote monitoring tools enable patients to check their progress from home, decreasing the need for in-person visits and making orthodontic care more accessible. The review also highlights future prospects, such as the integration of AI with robotics for performing orthodontic procedures, predictive orthodontics for early intervention, and the use of 3D printing technologies to fabricate orthodontic devices in real-time. While AI offers tremendous potential, challenges remain in areas such as data privacy, algorithmic bias, and the cost of adopting AI technologies. However, as AI continues to evolve, its capacity to revolutionize orthodontic care will likely lead to more streamlined, patient-centered, and effective treatments. This review underscores the transformative role of AI in modern orthodontics and its promising future in advancing dental care.

Telemedicine and Digital Tools in Dentistry: Enhancing Diagnosis and Remote Patient Care

Teledentistry enhances access to oral healthcare by enabling remote consultations, diagnosis, and patient management. This paper explores its applications, benefits, challenges, and impact on modern dentistry. A comprehensive review of existing literature and case studies was conducted to examine the effectiveness of teledentistry. Key aspects analyzed include digital imaging, AI (artificial intelligence)-assisted diagnostics, and cloud-based patient records, which facilitate early disease detection, reduce wait times, and minimize unnecessary visits. The review also highlights how teledentistry improves collaboration among dental professionals for better treatment planning. Challenges include legal barriers, data security concerns, and limited digital infrastructure. Standardized protocols and professional training are essential for effective implementation. Future advancements in AI and telecommunication technologies will further integrate teledentistry into standard practice, improving accessibility and efficiency in oral healthcare.

Evaluation of the impact of AI-based chatbot on orthodontic patient education: a preliminary randomised controlled trial

OBJECTIVES

To evaluate the impact of AI-based chatbots on orthodontic patient education in terms of compliance with oral hygiene procedures and level of knowledge and understanding of the treatment recommendations received. Furthermore, to assess the patient's satisfaction with the information received.

MATERIALS AND METHODS

100 orthodontic patients were enrolled and randomly allocated to receive information leaflets (control group n = 50) or access to an AI-based chatbot created on the guidelines of the leading scientific societies in the field (n = 50). The plaque index (PI) and modified gingival index (MGI) were assessed at baseline (T0) and after 5 weeks of treatment (T1). A questionnaire with a Likert scale was used to evaluate patients' knowledge and satisfaction. Statistical investigations were conducted to perform intra- and inter-group evaluations and to compare the effects of orthodontic therapies on the independent variables analysed. The questionnaire' s reliability was assessed using Cronbach's α.

RESULTS

At T1, a statistically significant increase in MGI and PI was observed in both analyzed groups (P < 0,001). However, the increase in MGI in the chatbot group was statistically lower than in the control group (P < 0.001). The increase in MGI was significantly higher in the chatbot-fixed orthodontic treatment subgroup than in the chatbot-aligners subgroup (P < 0,001).

CONCLUSIONS

The use of AI-based chatbots, whose reliability of the information provided can be validated, positively influences orthodontic oral hygiene in orthodontic patients. Further studies with greater follow-up should be conducted to understand the real impact of AI-based chatbot on patient education and satisfaction.

AI driven monitoring of orthodontic tooth movement using automated image analysis

Artificial intelligence (AI) driven automated image analysis accurately tracks orthodontic tooth movement by reducing reliance on time-consuming manual assessments. AI achieved 92% precision with a 0.25 mm error margin and a strong correlation (r = 0.94, p < 0.001) to manual measurements in a study of 100 patients. AI analysis took 3 seconds per image set, significantly faster than the 7-minute manual process (p < 0.001). Orthodontists rated AI reliability at 4.7/5, with 86% preferring AI-assisted monitoring. Thus, AI enhances treatment efficiency, standardization, and clinical decision-making.

Assessment of virtual bracket removal by artificial intelligence and thermoplastic retainer fit

INTRODUCTION

Digital orthodontics is here to make our specialty more efficient, and the integration of artificial intelligence (AI) is no exception. This study aimed to compare the accuracy of a workflow involving virtual bracket removal (VBR) by AI to traditional bracket removal. A secondary objective was to compare the clinical fit of thermoplastic orthodontic retainers fabricated from 3-dimensional (3D) printed models created by each method.

METHODS

Thirty dental arches were scanned intraorally with the fixed labial orthodontic brackets in place, creating 30 standard tessellation language (STL) files which were labeled "pre-debond." For each patient, all brackets and residual adhesive were then clinically removed, and an additional intraoral scan was taken and labeled "post-debond." Each pre-debond scan was uploaded to the uDesign by uLab software (version 7.0; uLab Systems, Inc, Memphis, Tenn), which uses AI to virtually remove orthodontic brackets using 1-touch bracket identification. New STL files were created for each of the 30 arches and labeled VBR. Best fit superimpositions were performed using Geomagic Control X (3D Systems, Inc, Rock Hill, SC), and data were collected as both numerical values and color-coded deviation maps. Superimposition data were segmented for each arch (anterior, posterior right, and posterior left) to determine if the arch location was a relevant factor. All post-debond and VBR STL files were 3D printed. Thermoplastic retainers were fabricated on each 3D-printed model. Retainers were delivered to patients and clinically graded by 2 practitioners.

RESULTS

There was a statistically significant difference in standard deviation and out-of-tolerance percentage values when comparing traditional debonded arches and virtually debonded arches when using sextant locations as a factor (anterior, posterior right, and posterior left). Grading scores for both evaluators show a statistically significant difference for the evaluation of facial surface adaptation and snap-fit acceptability between retainer fabrication methods. However, there was no correlation between out-of-tolerance values and clinical retainer fit evaluation among any of the graded variables in either the maxillary or mandibular arches.

CONCLUSIONS

VBR by AI is considered accurate enough to be used for the fabrication of clinically acceptable thermoplastic orthodontic retainers.

Influence of elastomeric and steel ligatures on periodontal health during fixed appliance orthodontic treatment: a systematic review and meta-analysis

INTRODUCTION

Metallic and elastomeric ligatures are widely used in orthodontics to secure the archwire within the bracket slots, but elastomeric ligatures have traditionally been associated with increased microbial colonization, which could adversely affect periodontal health.

AIM

This systematic review compares the periodontal effects of elastomeric and steel ligatures used for orthodontic fixed appliances.

METHODS

Unrestricted literature search of 7 databases (MEDLINE, Scopus, Web of Science, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Virtual Health Library) up to July 2023 were performed for randomized / non-randomized clinical studies on humans comparing the two ligation methods during fixed-appliance therapy. After duplicate study selection, data extraction, and risk-of-bias assessment with the Risk of Bias (RoB) 2 or the Risk Of Bias In Non-randomized Studies - of Interventions (ROBINS-I) tool, random-effects meta-analyses of Mean Differences (MD) or Standardized Mean Differences (SMD) and their 95% confidence intervals (CIs) were carried out, followed by assessment of certainty of existing evidence with the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) approach.

RESULTS

A total of 11 studies (3 randomized / 8 non-randomized) with 354 patients (mean age 14.7 years and 42% male) were included. No statistically significant differences were seen for plaque index (5 studies; SMD = 0.48; 95% CI = -0.03 to 1.00; P = 0.07), gingival index (2 studies; MD = 0.01; 95% CI = -0.14 to 0.16; P = 0.89), probing pocket depth (2 studies; MD = 0; 95% CI = -0.17 to 0.16; P = 0.97), or Streptococcus mutans counts (4 studies; SMD = 0.40; 95% CI=-0.41 to 1.20; P = 0.21). Elastomeric ligatures were associated with moderately increased total bacterial load (3 studies; SMD = 0.43; 95% CI = 0.10 to 0.76; P = 0.03). Confidence in these estimates was low in all instances due to the inclusion of non-randomized studies with high risk of bias.

CONCLUSIONS

Existing low quality evidence indicates that ligature method does not seem to influence the periodontal health during fixed treatment, even if elastomeric ligatures are associated with a moderate increase of bacterial load.

REGISTRATION

PROSPERO (CRD42023444383).

Efficacy of Visual Oral Health Reinforcement in Reducing Plaque Accumulation and Gingival Bleeding: A Pilot Randomized Controlled Trial

AIM

To compare oral hygiene (OH) differences during verbal or video OH instructions with or without images displaying poor oral health consequences.

MATERIALS AND METHODS

Twenty-one healthy females (18-30 years) were randomly and equally divided into three intervention OH instruction groups: (1) verbal, (2) video-based, (3) video-based with image displaying the consequences of poor OH. Gingival bleeding on probing (BOP), gingival bleeding index (BI), and plaque score (PS) were assessed at baseline and after 4 weeks. Within- and between-group differences were assessed by non-parametric tests.

RESULTS

Plaque score only showed a statistical group difference after follow-up [H(2) = 9.214, p = 0.01]. The post hoc test revealed that group III showed a significantly lower PS than groups I and II (p = 0.04 and p = 0.017, respectively). No differences were observed in PS between groups I and II. Group I showed no follow-up reduction in PS, BI, and BOP, while group II showed a statistically significant reduction in BI only after follow-up (p = 0.028). However, group III showed a statistically significant reduction in BOP and PS (p = 0.023 and p = 0.045, respectively) but not BI.

CONCLUSIONS

Verbal and video-alone OH instructions similarly affect gingival health, while participants who were exposed to images displaying the severe OH consequences had lower PS than verbal or video-alone groups.

CLINICAL SIGNIFICANCE

The mode of OH instructions is not influential for optimum oral health. However, employing visuals highlighting the severe consequences of poor OH leads to short-term reduction of plaque accumulation. How to cite this article: Aleid AA, Alnowaiser A, AlSakakir A, et al. Efficacy of Visual Oral Health Reinforcement in Reducing Plaque Accumulation and Gingival Bleeding: A Pilot Randomized Controlled Trial. J Contemp Dent Pract 2024;25(2):186-190.