Choice of diagnostic and therapeutic imaging in periodontics and implantology

Swarna, Chakrapani; Sirisha, Kantheti; Srilalitha, Anumadi; Marmamula, Srinivas

doi:10.4103/0972-124x.124474

Cited by 17 publications

(5 citation statements)

References 62 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, bitewing radiographs differ from periapical radiographs in that they are usually limited to capturing the image of the 3–4 upper and lower teeth in one area of the mouth. A horizontal bitewing radiograph is primarily used to detect bone height measurements along the tooth root, while vertical bitewings are used to evaluate bone loss ( Figure 2 c) [ 91 ]. The change of intraoral radiograph is used as important evidence of periodontitis progression.…”

Section: Diagnosis With the Imaging Toolsmentioning

confidence: 99%

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future

Byrd

Kim

2021

Diagnostics

View full text Add to dashboard Cite

Periodontal diseases comprise a group of globally prevalent, chronic oral inflammatory conditions caused by microbial dysbiosis and the host immune response. These diseases specifically affect the tooth-supporting tissues (i.e., the periodontium) but are also known to contribute to systemic inflammation. If left untreated, periodontal diseases can ultimately progress to tooth loss, lead to compromised oral function, and negatively impact the overall quality of life. Therefore, it is important for the clinician to accurately diagnose these diseases both early and accurately chairside. Currently, the staging and grading of periodontal diseases are based on recording medical and dental histories, thorough oral examination, and multiple clinical and radiographic analyses of the periodontium. There have been numerous attempts to improve, automate, and digitize the collection of this information with varied success. Recent studies focused on the subgingival microbiome and the host immune response suggest there is an untapped potential for non-invasive oral sampling to assist clinicians in the chairside diagnosis and, potentially, prognosis. Here, we review the available toolkit available for diagnosing periodontal diseases, discuss commercially available options, and highlight the need for collaborative research initiatives and state-of-the-art technology development across disciplines to overcome the challenges of rapid periodontal disease diagnosis.

show abstract

Section: Diagnosis With the Imaging Toolsmentioning

confidence: 99%

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future

Byrd

Kim

2021

Diagnostics

View full text Add to dashboard Cite

show abstract

“…Complete radiographic workflow and indications and uses for each imaging modality in periodontal practice have extensively described elsewhere. 20,21 The recent updates to the classification system have increased the importance of radiographic evaluation, as crestal bone loss is now a significant factor in diagnosis. While guidelines for image acquisition TA B L E 2 Summary of the key points regarding safety protocols in periodontal practice.…”

Section: Periodontal Imagingmentioning

confidence: 99%

“…Radiographic evaluation is crucial for diagnosing periodontitis and assessing severity and local factors. Complete radiographic workflow and indications and uses for each imaging modality in periodontal practice have extensively described elsewhere 20,21 . The recent updates to the classification system have increased the importance of radiographic evaluation, as crestal bone loss is now a significant factor in diagnosis.…”

Section: Periodontal Imagingmentioning

confidence: 99%

Associated risks with periodontal x‐rays or CBCT scans: Are there any?

Pereira

Sabri

Pereira

et al. 2023

Clin Adv Periodontics

View full text Add to dashboard Cite

Periodontal and implant radiography, mainly including intra‐oral peri‐apical and cone beam computed tomography images, are crucial in the diagnosis and treatment planning process. However, radiation safety concerns have been a chronic concern over the years, leading to uncomfortable situations. It is therefore crucial to understand the actual radiation exposure to determine if the patients’ fear of necessary diagnostic exams is justified. In this perspective article, we aimed to provide concise information on dental imaging exposure, risks, and benefits, comparing them to that of absorbed radiation from daily life activities; and secondarily, to help periodontists choose the best option for each case and become more confident in addressing patients’ concerns and providing a summary of safety guidelines as a reference for them.

show abstract

“…X-ray investigations’ automatic interpretation may be successfully performed for periodontal disease diagnosis using convolutional neural networks (CNNs) [ 20 ]. The invasiveness generated by the ionizing radiation [ 21 ] and the soft tissue poor visualization [ 7 , 21 ] limit the usage of radiographs for monitoring the disease evolution or treatment results. Ultrasound imaging has a great potential to become a powerful tool for periodontal disease diagnostics [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic Segmentation of Periodontal Tissue Ultrasound Images with Artificial Intelligence: A Novel Method for Improving Dataset Quality

Chifor

Hotoleanu

Mariţa

et al. 2022

Sensors

View full text Add to dashboard Cite

This research aimed to evaluate Mask R-CNN and U-Net convolutional neural network models for pixel-level classification in order to perform the automatic segmentation of bi-dimensional images of US dental arches, identifying anatomical elements required for periodontal diagnosis. A secondary aim was to evaluate the efficiency of a correction method of the ground truth masks segmented by an operator, for improving the quality of the datasets used for training the neural network models, by 3D ultrasound reconstructions of the examined periodontal tissue. Methods: Ultrasound periodontal investigations were performed for 52 teeth of 11 patients using a 3D ultrasound scanner prototype. The original ultrasound images were segmented by a low experienced operator using region growing-based segmentation algorithms. Three-dimensional ultrasound reconstructions were used for the quality check and correction of the segmentation. Mask R-CNN and U-NET were trained and used for prediction of periodontal tissue’s elements identification. Results: The average Intersection over Union ranged between 10% for the periodontal pocket and 75.6% for gingiva. Even though the original dataset contained 3417 images from 11 patients, and the corrected dataset only 2135 images from 5 patients, the prediction’s accuracy is significantly better for the models trained with the corrected dataset. Conclusions: The proposed quality check and correction method by evaluating in the 3D space the operator’s ground truth segmentation had a positive impact on the quality of the datasets demonstrated through higher IoU after retraining the models using the corrected dataset.

show abstract

Choice of diagnostic and therapeutic imaging in periodontics and implantology

Cited by 17 publications

References 62 publications

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future

Associated risks with periodontal x‐rays or CBCT scans: Are there any?

Automatic Segmentation of Periodontal Tissue Ultrasound Images with Artificial Intelligence: A Novel Method for Improving Dataset Quality

Contact Info

Product

Resources

About