Periodontal Treatment Planning Research Articles

Knowledge, confidence and clinical reasoning of dental students for diagnosing pediatric periodontal diseases

ObjectiveGiven the importance of diagnosing periodontal diseases in pediatric patients, the objective of this study was to examine knowledge, confidence, and clinical reasoning of third- and fourth-year dental students regarding periodontal diagnosis and treatment planning in pediatric patients. MethodsAn explanatory sequential mixed-method study was conducted in two phases. In the first phase, the survey questions were administered online to the third-and fourth-year dental students. Surveys tested for knowledge, confidence and clinical decision-making using questions and case-studies. Answers from periodontists and the pediatric dentists were used as the gold standard. For the next phase, individual interviews were recorded, transcribed, and coded followed by verbal analysis to assess their clinical reasoning for the specific diagnosis and treatment planning. ResultsWhile there was no overall difference in the knowledge and the confidence level between the students, they differed from the experts for some questions in confidence levels. As measured using the Script Concordance Test (SCT), no significant differences were observed between the participants in their clinical reasoning. The verbal analysis of the interview data showed that the students used three different patterns for searching through the problem space. Most of the students used the forward pattern of search and reported low confidence in diagnosing and treating pediatric periodontal diseases. ConclusionDue to low self-reported confidence in diagnosing periodontal disease in pediatric patients. Providing education solutions will improve the confidence of undergraduate dental students in diagnosing and treating periodontal disease.

MAPPNet: A Multi-Scale Attention Pyramid Pooling Network for Dental Calculus Segmentation

Dental diseases are among the most prevalent diseases globally, and accurate segmentation of dental calculus images plays a crucial role in periodontal disease diagnosis and treatment planning. However, the current methods are not stable and reliable enough due to the variable morphology of dental calculus and the blurring of the boundaries between the dental edges and the surrounding tissues; therefore, our hope is to propose an accurate and reliable calculus segmentation algorithm to improve the efficiency of clinical detection. We propose a multi-scale attention pyramid pooling network (MAPPNet) to enhance the performance of dental calculus segmentation. The network incorporates a multi-scale fusion strategy in both the encoder and decoder, forming a model with a dual-ended multi-scale structure. This design, in contrast to employing a multi-scale fusion scheme at a single end, enables more effective capturing of features from diverse scales. Furthermore, the attention pyramid pooling module (APPM) reconstructs the features on this map by leveraging a spatial-first and channel-second attention mechanism. APPM enables the network to adaptively adjust the weights of different locations and channels in the feature map, thereby enhancing the perception of important regions and key features. Experimental evaluation of our collected dental calculus segmentation dataset demonstrates the superior performance of MAPPNet, which achieves an intersection-over-union of 81.46% and an accuracy rate of 98.35%. Additionally, on two publicly available datasets, ISIC2018 (skin lesion dataset) and Kvasir-SEG (gastrointestinal polyp segmentation dataset), MAPPNet achieved an intersection-over-union of 76.48% and 91.38%, respectively. These results validate the effectiveness of our proposed network in accurately segmenting lesion regions and achieving high accuracy rates, surpassing many existing segmentation methods.

Bidirectional Association between Periodontitis and Thyroid Disease: A Scoping Review.

Periodontitis is a chronic inflammatory disease of the tissues surrounding and supporting the teeth. Due to the development of chronic inflammation, periodontitis can contribute to the development of several systemic diseases, including thyroid disease. Thyroid pathology includes benign, malignant, and autoimmune conditions leading to hypothyroidism, hyperthyroidism, or euthyroidism. Alterations in thyroid hormones, especially hypothyroidism, can reveal significant oral manifestations, including periodontitis. This scoping review aims to explore the probable causal relationship between periodontitis and thyroid disease, in terms of epidemiology, pathogenesis, and treatment. The search strategy follows the PRISMA-ScR guidelines. PubMed, Scopus, Web of Science, and Cochrane were searched from January 2014 to January 2024, entering the MESH terms "periodontitis" and "thyroid". Of 153 initial records, 20 articles were selected and discussed. There is a high prevalence of periodontitis among patients with thyroid disease, including thyroid cancer. The causes at the basis of this association are genetic factors, the oral microbiome, and proinflammatory cytokines. Periodontal treatment, specifically scaling and root planning, can ameliorate thyroid parameters. Although there are a few randomized controlled studies in the literature, this review lays the foundation for a bidirectional relationship between periodontitis and thyroid disease, the link to which is, once again, systemic inflammation.

Artificial Intelligence in Periodontics: A Comprehensive Review.

Periodontal diseases are prevalent worldwide and pose a significant public health burden. With the advent of artificial intelligence (AI), there has been growing interest in leveraging AI technologies to improve diagnosis, treatment planning, and management of periodontal conditions. This review aims to provide a comprehensive overview of the applications of AI in periodontics, including its potential benefits, challenges, and future directions. Fifteen relevant studies were analyzed to explore the role of AI in periodontal disease detection, risk assessment, treatment planning, and patient management. The findings highlight the promising role of AI in enhancing the accuracy, efficiency, and personalized care delivery in periodontics.

Practical Periodontal Diagnosis and Treatment Planning, 2nd Edition

Practical Periodontal Diagnosis and Treatment Planning, 2nd Edition

Detection of periodontal bone loss patterns and furcation defects from panoramic radiographs using deep learning algorithm: a retrospective study

BackgroundThis retrospective study aimed to develop a deep learning algorithm for the interpretation of panoramic radiographs and to examine the performance of this algorithm in the detection of periodontal bone losses and bone loss patterns.MethodsA total of 1121 panoramic radiographs were used in this study. Bone losses in the maxilla and mandibula (total alveolar bone loss) (n = 2251), interdental bone losses (n = 25303), and furcation defects (n = 2815) were labeled using the segmentation method. In addition, interdental bone losses were divided into horizontal (n = 21839) and vertical (n = 3464) bone losses according to the defect patterns. A Convolutional Neural Network (CNN)-based artificial intelligence (AI) system was developed using U-Net architecture. The performance of the deep learning algorithm was statistically evaluated by the confusion matrix and ROC curve analysis.ResultsThe system showed the highest diagnostic performance in the detection of total alveolar bone losses (AUC = 0.951) and the lowest in the detection of vertical bone losses (AUC = 0.733). The sensitivity, precision, F1 score, accuracy, and AUC values were found as 1, 0.995, 0.997, 0.994, 0.951 for total alveolar bone loss; found as 0.947, 0.939, 0.943, 0.892, 0.910 for horizontal bone losses; found as 0.558, 0.846, 0.673, 0.506, 0.733 for vertical bone losses and found as 0.892, 0.933, 0.912, 0.837, 0.868 for furcation defects (respectively).ConclusionsAI systems offer promising results in determining periodontal bone loss patterns and furcation defects from dental radiographs. This suggests that CNN algorithms can also be used to provide more detailed information such as automatic determination of periodontal disease severity and treatment planning in various dental radiographs.

Advancements in Methods of Classification and Measurement Used to Assess Tooth Mobility: A Narrative Review.

Evaluating tooth mobility is clinically significant, not only for diagnosing periodontal tissues but also in determining the overall periodontal treatment plan. Numerous studies related to tooth mobility have been conducted over the years, including the proposal of various classifications as well as the development of electronic devices for objective measurement. However, there is still no consensus on the measurement methods and criteria for assessing tooth mobility. In this study, we provide a comprehensive review of past and current tooth mobility classification and measurement methods. In order to propose a new method to intuitively evaluate tooth mobility based on previous studies, a digital approach capable of recording tooth micromovements induced by dynamic load should be considered.

Evaluation of matrix metalloproteinase-1, -2, -3, -7, and -13 gene polymorphisms in patients with chronic periodontitis and healthy controls.

The current study aimed to investigate the association of matrix metalloproteinase- (MMP-) 1, -2, -3, -7, and -13 gene polymorphisms with chronic periodontitis (CP) in an Iranian population. In this case-control study, 87 subjects with CP and 89 periodontally healthy subjects were allocated to case and control groups, respectively. Subjects' venous blood samples (5cc) were collected, and DNA extraction was performed. A spectrophotometer was utilized to assess the concentration of extracted DNAs. The desired gene polymorphisms were examined using restriction fragment length polymorphism polymerase chain reaction (RFLP-PCR) followed by electrophoresis. Statistical analyses were done using the Pearson Chi-Square test, odds ratio, and t-Test using SPSS Version 28. The MMP-1 (-1607 1G/2G) rs1799750, MMP-3 (-1171 5A/6A) rs3025058, and MMP-7 (-181 A/G) rs11568818 gene polymorphisms significantly differed between case and control groups (PV = 0.019, 0.007, and 0.028, respectively). In contrast, the gene polymorphisms of MMP-2 (-1306 C/T) rs243865 and MMP-13 (-77 A/G) rs2252070 did not make a significant difference. Regarding allele frequencies, the presence of the 2G allele in the MMP-1 (-1607) rs1799750 genotype increased the CP susceptibility significantly, while subjects with the 6A allele in their MMP-3 (-1171) rs3025058 genotype showed significantly lower susceptibility to CP (PV = 0.008 and < 0.001, respectively). In the studied population, gene polymorphisms in the DNA sequences of MMP-1 (-1607 1G/2G) rs1799750, MMP-3 (-1171 5A/6A) rs3025058, and MMP-7 (-181 A/G) rs11568818 may have impacts on CP incidence. Clinicians should be cautious about the association between MMP-1, MMP-3, and MMP-7 gene polymorphisms and the incidence of chronic periodontitis during periodontal treatment planning.

Deep Learning for Dental Diagnosis: A Novel Approach to Furcation Involvement Detection on Periapical Radiographs.

Furcation defects pose a significant challenge in the diagnosis and treatment planning of periodontal diseases. The accurate detection of furcation involvements (FI) on periapical radiographs (PAs) is crucial for the success of periodontal therapy. This research proposes a deep learning-based approach to furcation defect detection using convolutional neural networks (CNN) with an accuracy rate of 95%. This research has undergone a rigorous review by the Institutional Review Board (IRB) and has received accreditation under number 202002030B0C505. A dataset of 300 periapical radiographs of teeth with and without FI were collected and preprocessed to enhance the quality of the images. The efficient and innovative image masking technique used in this research better enhances the contrast between FI symptoms and other areas. Moreover, this technology highlights the region of interest (ROI) for the subsequent CNN models training with a combination of transfer learning and fine-tuning techniques. The proposed segmentation algorithm demonstrates exceptional performance with an overall accuracy up to 94.97%, surpassing other conventional methods. Moreover, in comparison with existing CNN technology for identifying dental problems, this research proposes an improved adaptive threshold preprocessing technique that produces clearer distinctions between teeth and interdental molars. The proposed model achieves impressive results in detecting FI with identification rates ranging from 92.96% to a remarkable 94.97%. These findings suggest that our deep learning approach holds significant potential for improving the accuracy and efficiency of dental diagnosis. Such AI-assisted dental diagnosis has the potential to improve periodontal diagnosis, treatment planning, and patient outcomes. This research demonstrates the feasibility and effectiveness of using deep learning algorithms for furcation defect detection on periapical radiographs and highlights the potential for AI-assisted dental diagnosis. With the improvement of dental abnormality detection, earlier intervention could be enabled and could ultimately lead to improved patient outcomes.

"A new orthodontic diagnosis based on the cupping depth of the alveolar bone "

Dentistry has made significant progress since the era when teeth were commonly extracted for dental pain, extensive dental caries, and endodontic disease. In this manuscript, we introduce the cupping depth of the alveolar bone and propose a new way to assess malalignment of teeth in orthodontics. Advancements in restorative dentistry and endodontic procedures have enabled the restoration of dental hard tissue using innovative techniques and advanced materials. However, despite these strides in restorative dentistry, a considerable gap persists in orthodontic diagnosis and practice. Fortunately, the universal application of Edward R. Angle's arbitrary treatment goal, irrespective of individual facial and developmental morphology, is finally waning due to advancements in orthodontic technologies. FASTBRACES® Technologies introduce technical advancements and a proper knowledge base for evaluating and treating the overlooked alveolar bone architecture of malaligned teeth. The axial ("horizontal") restoration of alveolar bone is promoted, which is analogous to the sagittal ("vertical") restoration of alveolar bone in periodontal treatment planning and therapy. This approach is biologically based and consistent with a patient's natural dentition and individual genetic morphologic appearance, rather than relying on subjective or arbitrary ideals. Moreover, this approach targets a highly pathogenic periodontal microbial flora associated with malaligned teeth and linked to systemic disease. Furthermore, restoring alveolar bone is not only important for suppressing this unique pathogenic microbial flora, but it also aligns with a comprehensive strategy of successful restoration of hard tissue that is emphasized in restorative dentistry and endodontics.

Periodontal and Orthodontic Synergy in the Management of Stage IV Periodontitis: Challenges, Indications and Limits.

This retrospective study described the clinical and radiographic long-term outcomes of combined periodontal and orthodontic treatment (OT) with fixed appliances in patients with Stage IV periodontitis and pathologic tooth migration (PTM) in the anterior sextants. OT was performed in either one or both arches, using tooth-supported or skeletal anchorage, following completion of active periodontal treatment and accurate planning of tooth movement biomechanics. Twenty-nine patients were identified and retrospectively examined when presenting for a supportive periodontal care (SPC) appointment. The mean SPC duration was 8.9 years (range 5 to 12 years). All anterior-migrated teeth showed statistically significant periodontal improvement compared to baseline values and stable radiographic bone levels at the final follow-up. Residual probing depths were 2.9 ± 0.5 mm at the end of active periodontal treatment, and they remained stable at the completion of OT (2.9 ± 0.6 mm) and at the last follow-up visit (2.8 ± 0.5 mm). These findings suggest that OT is a safe and effective treatment in improving the long-term prognosis of teeth with PTM in Stage IV periodontitis provided that periodontal health has been re-established and maintained with individualized SPC sessions.

Periodontal diagnosis and treatment planning - An assessment of the understanding of the new classification system.

Substantial variations are seen among clinicians in the diagnosis and treatment planning of periodontal diseases. Accurate diagnosis and treatment planning are fundamental requirements for effective outcome-based patient care. The aim of this study was to evaluate the understanding of the American Academy of Periodontology and the European Federation of Periodontology 2017 periodontal disease classifications in diagnoses and treatment plans across four study groups. The study recruited at least 20 participants in each of the four study groups. These included 1) Periodontal faculty and residents at Indiana University School of Dentistry (IUSD-PF) 2) IUSD general practice faculty (IUSD-GPF), 3) private practice periodontists (PPP), and 4) general practitioners (GP). The participants were provided with 10 HIPPA de-identified case records and a link to a survey. The survey comprised five demographic questions and two questions on diagnosis and treatment plan for each case along with a fixed list of responses. The responses were then compared against gold standards that were determined by a group of three board-certified periodontists. Overall, for diagnostic questions, GP (69%) were correct significantly less often than IUSD-PF (86%, p<0.001), IUSD-GPF (79%, p=0.002), and PPP (80%, p=0.001). No significant differences (p>0.05) in the overall correct treatment plan responses were found among the four groups (IUSD-PF: 69%, IUSD-GPF: 62%, PPP: 68%, and GP: 60%). The multi-rater kappas for with-in-group agreement on overall diagnosis ranged from 0.36 (GP) to 0.55 (IUSD-PF) and on overall treatment plan ranged from 0.32 (IUSD-GPF) to 0.42 (IUSD-PF). Overall agreement for diagnosis and treatment plans among the four groups was relatively low and none of the groups were statistically different from each other (p>0.05). Regular participation in calibration sessions may lead to more accurate adoption of the 2017 periodontal classification and thereby help provide consistent diagnosis and treatment.

Effective Management of Non-Surgical Periodontal Treatment in a Patient with Severe Gingival Enlargement and Periodontal Bone Loss: A Case Report

The immune-inflammatory response of periodontal tissue can be influenced by various systemic variables such as hormone disorders, hematologic diseases, nutrition, and medications. Inflammatory cytokines released by infected periodontal tissue are implicated in suppressing erythrocyte growth, differentiation, and erythropoiesis inhibition. We present a case of non-surgical periodontal treatment in a 31-year-old female patient with severe gingival enlargement associated with aggressive bone destruction combined with iron deficiency anemia (IDA). The periodontal treatment plan was achieved in collaboration with the hematologist, starting with oral hygiene instruction, scaling and root planning (SRP) by sextants with systemic antibiotic therapy combined with a chemical agent and low-level-laser-therapy (LLLT), and extraction of hopeless teeth. Effective non-surgical periodontal treatment with SRP and LLLT reduces inflammation and gingival enlargements and controls the recolonization of subgingival sites by periodontal pathogens as a crucial factor to proceed with periodontal surgery. Function, aesthetics, and the patient’s social communication are all improved.

Diagnosis and treatment planning using the 2017 classification of periodontal diseases among three dental schools.

The American Academy of Periodontology and the European Federation of Periodontology developed a new classification system for periodontal diseases in 2017. The next step in its widespread implementation involves training dental students to improve consistency in clinical decisions. This study conducted in 2020-2021 aimed to evaluate knowledge in periodontal diagnosis and treatment planning using the new classification, among first, second, third- and fourth-year dental students at Indiana University School of Dentistry (IUSD), University of Texas School of Dentistry at Houston (UTSD), and University of Louisville School of Dentistry (ULSD). A minimum of 20 dental students per class year from each of the three schools participated. Ten HIPPA de-identified case records and a questionnaire with a fixed list of answer options, comprising two demographic questions and two questions on diagnosis and treatment planning of each case, were presented to the participants. A group of three board-certified periodontists established the answers for all cases which were used to score the appropriateness of diagnosis and treatment planning among the participants. A total of 263 students participated. Overall, 22.6% of IUSD responses, 25.2% of UTSD, and 27.6% of ULSD responses were correct for diagnosis (no statistically significant differences). For the treatment plan, 64.9% of IUSD responses, 66.2% of UTSD, and 68.9% of ULSD responses were correct (no statistically significant differences). Based on the findings from our study, we suggest that additional training be considered to improve the understanding of the 2017 classification of periodontal and peri-implant diseases among dental students.

Detection of Natural and Simulated Periodontal Defects Using Cone-Beam Computed Tomography and Digital Intraoral Radiography

Objective: In this study, it was aimed to compare the diagnostic value of cone beam computed tomography (CBCT) and digital intraoral periapical imaging methods in the diagnosis of periodontal defects, and the comparison of observers practicing dentistry in the field of periodontology and 3 other observers specialized in various branches was evaluated. Methods: 7 dry mandible and 5 dry maxilla were used in this study. A total of 111 artificial and natural defects (dehiscence, furca, fenestration, vertical defects) on the anterior, premolar and molar region were imaged with digital imaging techniques using different exposure parameters and scanned with CBCT. Results: According to the results of this study, CBCT is a more reliable method in the evaluation of all periodontal defects compared to CCD and PSP. 60 and 70 kVp with 0.01 irradiation time in CCD and 70 kVp 0.25 irradiation time in PSP is not suitable for detecting defects owing to high contrast. In the evaluation of periodontal defects, there was no single observer who had good results, different imaging methods and varying results were obtained in different defects. Conclusion: This study showed that the CBCT method has some diagnostic value for detecting all natural and simulated periodontal defects but it should only be used in cases where clinical evaluation and conventional radiographic imaging do not provide the information necessary for an adequate diagnosis and proper periodontal treatment planning.

Cone-Beam Computed Tomography in Periodontal Diagnosis and Treatment Planning

AbstractDiagnosis of periodontal disease depends on conventional clinical parameters. In periodontitis with extensive bone defects, radiographs play a crucial role in arriving at a proper diagnosis. The emergence of cone-beam computed tomography (CBCT) became a boon in oral radiology. Limitations of conventional two-dimensional (2D) radiographs include inadequate visualization of bone defects, lamina dura, and furcation involvement. CBCT generates 3D images of anatomical structures necessary for the periodontal diagnosis of furcation involvement, intrabony defects, and implant placement. CBCT, thus, imparts various potential applications in the field of periodontics which serves to arrive at better diagnostic conclusions.

Splinting: The prosthodontist way: Case report

Dental splinting involves joining the crowns of two or more teeth by more or less rigid means: so that their relative movement is restricted and the forces applied to one of the splinted teeth are transmitted to the root system of all the linked teeth. Splinting has been used as a form of dental treatment for centuries. It remained a popular treatment for mobility until twentieth century, and was used as an integral part of periodontal treatment planning by many clinicians.

Treatment planning considerations in the older adult with periodontal disease.

Periodontal health in the elderly is influenced by numerous factors, including systemic conditions, patient compliance, age-associated changes, and restorative procedures. The numerous comorbidities seen in the elderly necessitate individualized approaches for treatment planning. In this paper, we review how age, comorbidities, oral hygiene, and restorative dental procedures collectively influence the treatment and management of the periodontium in the elderly. The elderly population is predicted to double in 30years, which will have an economic impact the dental profession needs to plan for. Preventative and noninvasive treatment, supportive periodontal therapy, and patient-specific maintenance plans are imperative to maintaining oral health in the older population. Multiple coexisting changes, including xerostomia, altered wound healing, altered bone physiology, altered microbiome, and diminished plaque control, can add complexity to periodontal management. Considerations of the patient's general health, the selected periodontal treatment plan, and the selected completed restorative procedures need to be considered. The influence of caries, fixed prosthodontics, partial dentures, shortened dental arch, and implant therapy can have unintended impacts on periodontal health in the elderly. Adverse periodontal outcomes in the elderly can be minimized by carefully assessing the patient's medical history, impact of medications, functional needs, properly finishing and contouring restorations to avoid plaque accumulation, and designing restorations to allow access for hygiene. Partial dentures can be a source of plaque accumulation leading to periodontal disease, caries, and recession around abutment teeth. A shortened dental arch should be considered as a functional and cost-effective alternative to partial dentures. With dental implants, the patient's tissue phenotype, keratinized tissue quantity, risk of peri-implantitis, and patient access for maintaining adequate oral hygiene are all important to consider. Implant risk-assessment tools show promise by providing a systematic approach for early diagnosis to avoid future complications.

A questionnaire-based crossover study on the association of microbiological testing with prescription of systemic antibiotics following initial periodontal therapy.

(1) To assess prescription of systemic antibiotics following initial periodontal therapy with and without the availability of microbiological information; (2) To identify factors associated with prescription of systemic antibiotics following initial periodontal therapy. Twenty-four clinicians were invited to complete a questionnaire on 20 patient records with respect to periodontal treatment planning, once with microbiological information available and once without. Randomization determined when the microbiological information was provided, and a 3-month washout period was respected between scoring sessions. Regression analysis was performed to identify factors associated with prescription of systemic antibiotics. Twenty-one clinicians completed both scoring sessions. Clinicians prescribed systemic antibiotics in on average 56% (95% Confidence Interval (CI) [0.51; 0.61]) of the cases having microbiological information, and in 52% (95% CI [0.47; 0.57]) of the same cases not having that information (p=0.094). The odds for prescribing systemic antibiotics were 3.34 (95% CI [2.06; 5.42]) times higher when the clinician had at least 3years of experience, 2.55 (95% CI [1.40; 4.66]) times higher for patients diagnosed with periodontitis stage IV when compared to stage III, 1.08 (95% CI [1.04; 1.11]) times higher for younger patients, 2.78 times (95% CI [1.37; 5.56]) times higher for non-smokers and 2.22 (95% CI [1.27; 3.85]) times higher when less than three teeth would require extraction. No significant associations with the prescription of systemic antibiotics were found for detection of A.actinomycetemcomitans (p=0.287), grade of periodontitis (p=0.499) and gender of the patient (p=0.067). Based on a limited number of cases and clinicians, several patient and clinician related factors were associated with prescription of systemic antibiotics following initial periodontal therapy. However, microbiological testing was not.

Periodontal treatment planning in case of a generalized severe chronic periodontitis

Periodontal treatment planning in case of a generalized severe chronic periodontitis