Comparison of intraoral radiography and cone-beam computed tomography for the detection of vertical root fractures: an in vitro study

Is cone-beam computed tomography more accurate than periapical radiography for detection of vertical root fractures? A systematic review and meta-analysis

BACKGROUND

This study aimed to conduct a systematic review and meta-analysis to summarize the available evidence comparing the diagnostic accuracy of periapical radiography (PA) and cone-beam computed tomography (CBCT) for detection of vertical root fractures (VRFs).

METHODS

A search was conducted in PubMed, Scopus, and Web of Science for articles published regarding all types of human teeth. Data were analyzed by Comprehensive Meta-Analysis statistical software V3 software program. The I2 statistic was applied to analyze heterogeneity among the studies.

RESULTS

Twenty-three articles met the criteria for inclusion in the systematic review and 16 for the meta-analysis. The sensitivity and specificity for detection of VRFs were calculated to be 0.51 and 0.87, respectively for PA radiography, and 0.70 and 0.84, respectively for CBCT.

CONCLUSIONS

The sensitivity of CBCT was higher than PA radiography; however, difference between the specificity of the two modalities was not statistically significant.

Vertical root fracture detection with cone-beam computed tomography in Biodentine™ filled teeth

PURPOSE

This study aimed to evaluate the accuracy of detecting vertical root fractures in Biodentine™-filled teeth using the Promax 3Dmax cone-beam computed tomography (CBCT) unit compared to periapical radiographs. It tested hypotheses regarding CBCT's diagnostic superiority in non-root-filled and Biodentine™-root-filled maxillary central incisors and assessed the impact of smaller field of view and lower intensity settings on detection accuracy.

MATERIALS AND METHODS

Extracted maxillary incisors were divided into groups based on fracture status and root filling material, then placed in a Thiel-embalmed skull to simulate clinical conditions. The teeth were imaged using periapical radiographs and the CBCT unit under different settings. Fracture thickness was measured with microcomputed tomography for accuracy benchmarking. Multiple observers assessed the images, and statistical analyses were conducted to evaluate diagnostic performance.

RESULTS

Intra-rater reliabilities of consensus scores ranged from good to very good. Specificities were generally higher than sensitivities across all imaging modalities, but sensitivities remained constantly low. None of the Area Under the Curve scores exceeded 0.6, indicating poor overall accuracy for all imaging modalities. Paired comparisons of the area differences under Receiver Operator Characteristic curves revealed no significant differences between the CBCT and periapical radiograph techniques for detecting vertical root fractures in either Biodentine™-filled or non-root-filled teeth.

CONCLUSIONS

There was no significant accuracy improvement of the current CBCT device (Promax 3Dmax, Planmeca, Finland) over periapical radiographs in detecting small vertical root fractures in both non-root-filled and Biodentine™-root-filled maxillary central incisors. A smaller field of view with lower intensity did not enhance detection accuracy. These results highlight the challenges in accurately detecting small VRFs, emphasizing the need for further research and technological advancements in this domain.

Evaluation of the Diagnostic and Prognostic Accuracy of Artificial Intelligence in Endodontic Dentistry: A Comprehensive Review of Literature

Aim

This comprehensive review is aimed at evaluating the diagnostic and prognostic accuracy of artificial intelligence in endodontic dentistry.

Introduction

Artificial intelligence (AI) is a relatively new technology that has widespread use in dentistry. The AI technologies have primarily been used in dentistry to diagnose dental diseases, plan treatment, make clinical decisions, and predict the prognosis. AI models like convolutional neural networks (CNN) and artificial neural networks (ANN) have been used in endodontics to study root canal system anatomy, determine working length measurements, detect periapical lesions and root fractures, predict the success of retreatment procedures, and predict the viability of dental pulp stem cells. Methodology. The literature was searched in electronic databases such as Google Scholar, Medline, PubMed, Embase, Web of Science, and Scopus, published over the last four decades (January 1980 to September 15, 2021) by using keywords such as artificial intelligence, machine learning, deep learning, application, endodontics, and dentistry.

Results

The preliminary search yielded 2560 articles relevant enough to the paper's purpose. A total of 88 articles met the eligibility criteria. The majority of research on AI application in endodontics has concentrated on tracing apical foramen, verifying the working length, projection of periapical pathologies, root morphologies, and retreatment predictions and discovering the vertical root fractures.

Conclusion

In endodontics, AI displayed accuracy in terms of diagnostic and prognostic evaluations. The use of AI can help enhance the treatment plan, which in turn can lead to an increase in the success rate of endodontic treatment outcomes. The AI is used extensively in endodontics and could help in clinical applications, such as detecting root fractures, periapical pathologies, determining working length, tracing apical foramen, the morphology of root, and disease prediction.

Clinical guidelines for dental cone-beam computed tomography

Dental cone-beam computed tomography (CBCT) received regulatory approval in Japan in 2000 and has been widely used since being approved for coverage by the National Health Insurance system in 2012. This imaging technique allows dental practitioners to observe and diagnose lesions in the dental hard tissue in three dimensions (3D). When performing routine radiography, the examination must be justified, and optimal protection should be provided according to the ALARA (as low as reasonably achievable) principles laid down by the International Commission on Radiological Protection. Dental CBCT should be performed in such a way that the radiation exposure is minimized and the benefits to the patient are maximized. There is a growing demand for widespread access to cutting-edge health care through Japan's universal health insurance system. However, at the same time, people want our limited human, material, and financial resources to be used efficiently while providing safe health care at the least possible cost to society. Japan's aging population is expected to reach a peak in 2025, when most of the baby boomer generation will be aged 75 years or older. Comprehensive health care networks are needed to overcome these challenges. Against this background, we hope that this text will contribute to the nation's oral health by encouraging efficient use of dental CBCT.

Influence of voxel size and scan field of view on fracture-like artifacts from gutta-percha obturated endodontically treated teeth on cone-beam computed tomography images

OBJECTIVE

To determine the optimal scan settings (scan mode and position of field of view [FOV]) for cone beam computed tomography to reduce root fracture-like artifacts that are often observed in teeth filled with gutta-percha cones (GPCs).

STUDY DESIGN

Fracture-like artifacts that appeared on cone beam computed tomography images of 9 extracted human mandibular premolars filled with GPCs were analyzed using I-mode (FOV, 102 mm; voxel size, 0.2 mm) and D-mode (FOV, 51 mm; voxel size, 0.1 mm) settings.

RESULTS

The artificial lines were more obvious in I-mode than in D-mode. Increased distance between the center of the FOV and the GPCs produced stronger artificial lines in both I-mode and D-mode.

CONCLUSION

To reduce fracture-like artifacts, it is critical to use a mode with small voxel size and to place the target tooth in the center of the FOV.

Root canal filling materials spread pattern mimicking root fractures in dental CBCT images

OBJECTIVE

To clarify the cause of artificial tooth-root fracture lines in cone beam computed tomography (CBCT) images caused by root canal filling materials and to enhance the diagnostic performance of CBCT.

STUDY DESIGN

We analyzed the CBCT images of 18 extracted human teeth (9 upper central incisors and 9 lower premolars) that were filled with a size 50 gutta-percha cone and inserted into tooth sockets in a human skull.

RESULTS

The CBCT images of the incisors displayed artificial lines in the oblique directions, notably the mesiobuccal, distolingual, distobuccal and mesiolingual directions, but only rarely in the cross-directions (buccal, lingual, mesial, and distal). In the premolars, the reverse was true, with lines mainly in the cross-directions, mesial and distal directions particularly. The lines were predominantly at the cervical slice.

CONCLUSIONS

Artifacts resulting from root filling material appear along the long axis of the alveolar bones, and resemble root fractures.