Diagnosis of cracked teeth using cone-beam computed tomography: literature review and clinical experience

Prognostic factors associated with pulp status in patients with cracked teeth treated with occlusal veneer: A 6- through 24-month prospective clinical study

BACKGROUND

The authors evaluated the prognostic factors associated with pulp status in patients with cracked teeth (CT) treated with occlusal veneer.

METHODS

An analysis of 80 CT (71 patients) with 1 or more crack lines (CLs) and normal pulp vitality or reversible pulpitis was performed. All patients received occlusal veneer and their demographic and clinical data were recorded. Pulp status and clinical features were recorded at 1 week and posttreatment at 1, 2, 3, 6, 12, 18, and 24 months.

RESULTS

Maxillary first molars were commonly involved (30 [38%]). The number of CLs on the finish line ranged from 1 through 7 and most had 3 CLs (24 [30%]). The number of CLs through preparation on the finish line ranged from 0 through 4, and 2 CLs (42 [53%]) were the most prevalent. During follow-up, 5 of 80 CT progressed to pulp disease, resulting in a success rate of 93.8%. Results of the Cox model and Kaplan-Meier analysis showed that probing depth greater than 6 mm, widening periodontal ligament of apical area, more than 4 CLs on finish line, and more than 2 CLs through preparation on the finish line were risk factors associated with pulp status (P < .05).

CONCLUSIONS

Occlusal veneer can protect CT without preventive root canal therapy.

PRACTICAL IMPLICATIONS

The success rate and risk factors of pulp disease in CT restored with occlusal veneer are reported.

Development and validation of a 3D anthropomorphic phantom for dental CBCT imaging research

BACKGROUND

Optimization of dental cone beam computed tomography (CBCT) imaging is still in a preliminary stage and should be addressed using task-based methods. Dedicated models containing relevant clinical tasks for image quality studies have yet to be developed.

PURPOSE

To present a methodology to develop and validate a virtual adult anthropomorphic voxel phantom for use in task-based image quality optimization studies in dental CBCT imaging research, focusing on root fracture (RF) detection tasks in the presence of metal artefacts.

METHODS

The phantom was developed from a CBCT scan with an isotropic voxel size of 0.2 mm, from which the main dental structures, mandible and maxilla were segmented. The missing large anatomical structures, including the spine, skull and remaining soft tissues, were segmented from a lower resolution full skull scan. Anatomical abnormalities were absent in the areas of interest. Fine detailed dental structures, that could not be segmented due to the limited resolution and noise in the clinical data, were modelled using a-priori anatomical knowledge. Model resolution of the teeth was therefore increased to 0.05 mm. Models of RFs as well as dental restorations to create the artefacts, were developed, and could be inserted in the phantom in any desired configuration. Simulated CBCT images of the models were generated using a newly developed multi-resolution simulation framework that incorporated the geometry, beam quality, noise and spatial resolution characteristics of a real dental CBCT scanner. Ray-tracing and Monte Carlo techniques were used to create the projection images, which were reconstructed using the classical FDK algorithm. Validation of the models was assessed by measurements of different tooth lengths, the pulp volume and the mandible, and comparison with reference values. Additionally, the simulated images were used in a reader study in which two oral radiologists had to score the realism level of the model's normal anatomy, as well as the modelled RFs and restorations.

RESULTS

A model of an adult head, as well as models of RFs and different types of dental restorations were created. Anatomical measurements were consistent with ranges reported in literature. For the tooth length measurements, the deviations from the mean reference values were less than 20%. In 77% of all the measurements, the deviations were within 10.1%. The pulp volumes, and mandible measurements were within one standard deviation of the reference values. Regarding the normal anatomy, both readers considered the realism level of the dental structures to be good. Background structures received a lower realism score due to the lack of detailed enough trabecular bone structure, which was expected but not the focus of this study. All modelled RFs were scored at least adequate by at least one of the readers, both in appearance and position. The realism level of the modelled restorations was considered to be good.

CONCLUSIONS

A methodology was proposed to develop and validate an anthropomorphic voxel phantom for image quality optimization studies in dental CBCT imaging, with a main focus on RF detection tasks. The methodology can be extended further to create more models representative of the clinical population.

[Strategies for the use of cone beam tomography in teeth with suspected root fracture. Report of case series]

Root fractures are after caries and periodontal disease, the third cause of loss of dental units, being very common in posterior and endodontically treated teeth. The symptoms they produce are ambiguous and their diagnosis depends on the combination of multiple clinical and imaging factors. Among the diagnostic studies available to establish the origin of the symptoms is the cone beam computed tomography (CBCT). The objective of this case report is to describe the strategies used in the acquisition and interpretation of the CBCT in three patients with suspected root fractures. The use of a reduced field of view, with a voxel of 0.150 mm or less, accompanied by dynamic volume exploration made it possible to detect bone defects as an indirect sign for locating root fracture lines.

The "Dedicated" C.B.C.T. in Dentistry

This position statement represents a consensus of an expert committee composed by the Italian Academy of General Dentistry (Accademia Italiana Odontoiatria Generale COI-AIOG) and Italian Academy of Legal and Forensic Dentistry (Accademia Italiana di Odontoiatria Legale e Forense OL-F) on the appropriate use of cone beam computed tomography (C.B.C.T.) in dentistry. This paper analyzes the use of C.B.C.T. in light of the rapid evolution of volumetric technologies, with the new low- and ultra-low-dose exposure programs. These upgrades are determining an improvement in the precision and safety of this methodology; therefore, the need of a guideline revision of the use of C.B.C.T. for treatment planning is mandatory. It appears necessary to develop a new model of use, which, in compliance with the principle of justification and as low as reasonably achievable (ALARA) and as low as diagnostically acceptable (ALADA), can allow a functional "Dedicated C.B.C.T." exam optimized for the individuality of the patient.

Diagnosis of cracked tooth: Clinical status and research progress

Cracked tooth is a common dental hard tissue disease.The involvement of cracks directly affects the selection of treatment and restoration of the affected teeth.It is helpful to choose more appropriate treatment options and evaluate the prognosis of the affected tooth accurately to determine the actual involvement of the crack.However, it is often difficult to accurately and quantitatively assess the scope of cracks at present.So it is necessary to find a real method of early quantitative and non-destructive crack detection.This article reviews the current clinical detection methods and research progress of cracked tooth in order to provide a reference for finding a clinical detection method for cracked tooth.

Diagnosis of in vivo vertical root fracture using deep learning on cone-beam CT images

Objectives

Evaluating the diagnostic efficiency of deep learning models to diagnose vertical root fracture in vivo on cone-beam CT (CBCT) images.

Materials and methods

The CBCT images of 276 teeth (138 VRF teeth and 138 non-VRF teeth) were enrolled and analyzed retrospectively. The diagnostic results of these teeth were confirmed by two chief radiologists. There were two experimental groups: auto-selection group and manual selection group. A total of 552 regions of interest of teeth were cropped in manual selection group and 1118 regions of interest of teeth were cropped in auto-selection group. Three deep learning networks (ResNet50, VGG19 and DenseNet169) were used for diagnosis (3:1 for training and testing). The diagnostic efficiencies (accuracy, sensitivity, specificity, and area under the curve (AUC)) of three networks were calculated in two experiment groups. Meanwhile, 552 teeth images in manual selection group were diagnosed by a radiologist. The diagnostic efficiencies of the three deep learning network models in two experiment groups and the radiologist were calculated.

Results

In manual selection group, ResNet50 presented highest accuracy and sensitivity for diagnosing VRF teeth. The accuracy, sensitivity, specificity and AUC was 97.8%, 97.0%, 98.5%, and 0.99, the radiologist presented accuracy, sensitivity, and specificity as 95.3%, 96.4 and 94.2%. In auto-selection group, ResNet50 presented highest accuracy and sensitivity for diagnosing VRF teeth, the accuracy, sensitivity, specificity and AUC was 91.4%, 92.1%, 90.7% and 0.96.

Conclusion

In manual selection group, ResNet50 presented higher diagnostic efficiency in diagnosis of in vivo VRF teeth than VGG19, DensenNet169 and radiologist with 2 years of experience. In auto-selection group, Resnet50 also presented higher diagnostic efficiency in diagnosis of in vivo VRF teeth than VGG19 and DensenNet169. This makes it a promising auxiliary diagnostic technique to screen for VRF teeth.

A perspective on the diagnosis of cracked tooth: imaging modalities evolve to AI-based analysis

Despite numerous clinical trials and pre-clinical developments, the diagnosis of cracked tooth, especially in the early stages, remains a challenge. Cracked tooth syndrome is often accompanied by dramatic painful responses from occlusion and temperature stimulation, which has become one of the leading causes for tooth loss in adults. Current clinical diagnostical approaches for cracked tooth have been widely investigated based on X-rays, optical light, ultrasound wave, etc. Advances in artificial intelligence (AI) development have unlocked the possibility of detecting the crack in a more intellectual and automotive way. This may lead to the possibility of further enhancement of the diagnostic accuracy for cracked tooth disease. In this review, various medical imaging technologies for diagnosing cracked tooth are overviewed. In particular, the imaging modality, effect and the advantages of each diagnostic technique are discussed. What's more, AI-based crack detection and classification methods, especially the convolutional neural network (CNN)-based algorithms, including image classification (AlexNet), object detection (YOLO, Faster-RCNN), semantic segmentation (U-Net, Segnet) are comprehensively reviewed. Finally, the future perspectives and challenges in the diagnosis of the cracked tooth are lighted.

Cross-sectional study of posterior tooth root fractures in 2015 and 2019 in a Chinese population

OBJECTIVES

This study aimed to compare posterior tooth root fractures in endodontically treated teeth versus nonendodontically treated teeth in the Chinese population.

MATERIALS AND METHODS

We investigated 500 root fractured posterior teeth in 461 Chinese patients. The clinical information (age, sex of patients, tooth type) were recorded. The fractured teeth were divided into endodontically treated root fractured (ETRF) teeth and nonendodontically treated root fractured (NETRF) teeth. The morphology of the fractured root (circular, oval, other), the orientation of fracture lines (vertical and non-vertical), the restorations performed (crown, filling, non-filling), and the position of the teeth in the dental arch (normal, misaligned) were evaluated based on cone-beam computed tomography images. These data were compared between 2015 and 2019. ETRF% was calculated as ETRF/ETRF + NETRF. Vertical% was calculated as vertical/vertical + non-vertical.

RESULTS

There were 177 ETRF teeth and 323 NETRF teeth in this population. The total ETRF% was 29.3% in 2015 and 37.6% in 2019 (P = 0.087). The proportion of vertical root fracture in the ETRF group increased significantly in 2019 compared with that in 2015 (46.2% vs. 80.2%, P = 0.000). The ETRF% in female patients increased by 16.8%, but increased by only 1.2% in male patients in 2019 compared with that in 2015. The ETRF% of mandibular and maxillary premolars increased by 48.5% and 29.3%, respectively. The proportion of crown restoration increased by 2.4% in 2019 compared with that in 2015 in the ETRF group.

CONCLUSIONS

The proportion of NETRF teeth and non-vertical root fractures in posterior teeth is high in this Chinese population. The number of vertical root fractures in endodontically treated teeth increased significantly from 2015 to 2019.

CLINICAL RELEVANCE

More attention should be paid to endodontic treatment factors in the occurrence of root fractures, especially as female patients and premolars are more susceptible.

Effect of cone-beam computed tomography metal artefact reduction on incomplete subtle vertical root fractures

Purpose

This study compared the accuracy of detection of incomplete vertical root fractures (VRFs) in filled and unfilled teeth on cone-beam computed tomography images with and without a metal artefact reduction (MAR) algorithm.

Materials and Methods

Forty single-rooted maxillary premolars were selected and, after endodontic instrumentation, were categorized as unfilled teeth without fractures, filled teeth without fractures, unfilled teeth with fractures, or filled teeth with fractures. Each VRF was artificially created and confirmed by operative microscopy. The teeth were randomly arranged, and images were acquired with and without the MAR algorithm. The images were evaluated with OnDemand software (Cybermed Inc., Seoul, Korea). After training, 2 blinded observers each assessed the images for the presence and absence of VRFs 2 times separated by a 1-week interval. P-values<0.05 were considered to indicate significance.

Results

Of the 4 protocols, unfilled teeth analysed with the MAR algorithm had the highest accuracy of incomplete VRF diagnosis (0.65), while unfilled teeth reviewed without MAR were associated with the least accurate diagnosis (0.55). With MAR, an unfilled tooth with an incomplete VRF was 4 times more likely to be identified as having an incomplete VRF than an unfilled tooth without this condition, while without MAR, an unfilled tooth with an incomplete VRF was 2.28 times more likely to be identified as having an incomplete VRF than an unfilled tooth without this condition.

Conclusion

The use of the MAR algorithm increased the diagnostic accuracy in the detection of incomplete VRF on images of unfilled teeth.

"THE CORRELATION OF CRACK LINES AND DEFINITIVE RESTORATIONS WITH THE SURVIVAL AND SUCCESS RATES OF CRACKED TEETH: A LONG-TERM RETROSPECTIVE CLINICAL STUDY"

INTRODUCTION

Cracked teeth (CT) frequently require protective adhesive restorations. This long-term, longitudinal retrospective clinical study aimed to evaluate the factors influencing the success and survival rates of CT with crack lines (CLs) in different directions, when restored early with onlays or full-coverage crowns.

METHODS

The dental records of 71 patients with a total of 86 CT, with different pulpal and periapical diagnoses, and with follow-ups spanning over 1-11 years were included. Data regarding the demographics; clinical symptoms and signs; bruxism; occlusal interferences; eating habits; pulpal and periapical diagnoses; number, direction, location, and extent of crack lines; probing depth; and coronary condition before and after the placement of definitive restorations were collected. Univariate associations between tooth survival and explanatory variables were assessed. The long-term survival rate was estimated using the Kaplan-Meier analysis and the log-rank test. A multivariate analysis was performed using Cox regression analysis.

RESULTS

The overall success rate was 93.0%, and the overall survival estimates of CT restored early were 98.6%, 94.9% and 55.9% at the 1-, 5-, and 11-year follow-ups, respectively. The direction of the CLs did not influence the survival of the tooth. No significant association was observed between the type of tooth, probing depth, root canal treatment (RCT), and tooth loss (P>0.05). The multivariate analysis showed that previously treated CT (P<0.05), provision of onlay restorations (P<0.05), and placement of posts (P<0.05) had higher correlations with tooth loss. Additionally, placement of full-coverage crowns resulted in lower tooth loss compared with the placement of onlays (P<0.05).

CONCLUSION

Previous endodontic treatment in teeth that subsequently develop CLs has a negative impact on the survival rate of the teeth. Moreover, early placement of full-coverage crowns should be implemented for CT, regardless of the direction or number of CLs, since it is associated with a higher cracked tooth survival rate.

Dental Trauma on whole Body Trauma CT-An underreported finding

Background

The prevalence of dental injuries (DI) in polytrauma patients is unknown. The purpose of our study was to identify the frequency of dental injuries on whole body CTs acquired in a trauma setting and to estimate how often they are correctly reported by the radiologist.

Methods

In the time period between 2006 and 2018 the radiological database of one university hospital was screened for whole-body trauma CTs. A total of 994 CTs were identified and re-evaluated.

Results

Dental injuries were identified in 127 patients (12.8% of patients). There were 27 women (21.3%) and 100 men (78.7%) with a mean age of 51.0 ± 18.9 years (range 10–96 years). Regarding localization, most findings involved the molars (n = 107, 37.4%), followed by the incisors (n = 81, 28.3%), premolars (n = 59, 20.6%) and canines (n = 39, 13.7%). Most common findings were as follows: luxations (n = 49, 45.8%), followed by crown fractures (n = 46, 43%), root fractures (n = 10, 9.3%), extrusions (n = 1, 0.9%), and intrusions (n = 1, 0.9%). Only 15 findings (11.8% of all patients with dental injuries) were described in the original radiological reports.

Conclusion

DI had a high occurrence in polytrauma patients. A high frequency of underreported dental trauma findings was identified. Radiologists reporting whole-body trauma CT should be aware of possible dental trauma to report the findings adequately.

Detection of Dental Caries and Cracks with Quantitative Light-Induced Fluorescence in Comparison to Radiographic and Visual Examination: A Retrospective Case Study

The aim of this study was to present an optimal diagnostic protocol by comparing and analyzing a conventional examination and the quantitative light-induced fluorescence (QLF) technique. Selected were 297 teeth of 153 patients to take QLF images and bitewing radiographs. Occlusal dental caries, proximal dental caries and cracks were evaluated and scored using QLF, X-ray and/or visual criteria. The sensitivity, specificity, and area under the curve (AUC) of a receiver operating characteristic analysis were calculated. Two fluorescence parameters (|ΔFmax| and ΔRmax) were utilized to evaluate the fluorescence pattern according to the severity of lesions based on QLF or X-ray criteria. QLF showed higher scores for detecting occlusal dental caries and cracks than the conventional method. ΔRmax increased more clearly than ΔFmax did with occlusal dental caries. The |ΔFmax| values of occlusal dental caries, proximal dental caries and cracks showed good AUC levels (0.84, 0.81 and 0.83, respectively). The ΔRmax of occlusal dental caries showed the highest AUC (0.91) and the ΔRmax of proximal dental caries showed a fail level (0.59) compared to bitewing radiographs. The QLF image could visualize and estimate the degree of occlusal dental caries or cracks. Consequently, the QLF technique may be an adjunct tool to conventional methods for the detection of occlusal caries and peripheral cracks.