Cone-beam Computed Tomographic–based Assessment of Filled C-shaped Canals: Artifact Expression of Cone-beam Computed Tomography as Opposed to Micro–computed Tomography and Nano–computed Tomography

Mazzi‐Chaves, Jardel Francisco; Vasconcelos, Karla de Faria; Pauwels, Ruben; Jacobs, Reinhilde; Sousa‐Neto, Manoel Damião

doi:10.1016/j.joen.2020.07.010

Cited by 16 publications

(13 citation statements)

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“…Comparisons between micro-CT and CBCT images of filled root canals show a higher volumetric distortion and artefacts with CBCTs [65,66]. Using nano-CT as a reference, comparison of different CBCT machines and micro-CT demonstrated a significant distortion with all CBCT machines in filled root canals [57]. Micro-CT is considered as the gold standard in studies evaluating quality of root canal filling, root canal morphology, evaluation of canal preparation, and irrigation [65].…”

Section: Literature Reviewmentioning

confidence: 99%

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Complete Obturation—Cold Lateral Condensation vs. Thermoplastic Techniques: A Systematic Review of Micro-CT Studies

et al. 2021

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To prevent re-infection and provide a hermetic seal of the root canal system, an endodontist must aim to produce a void-free obturation. This review aimed to compare the completeness of root canal obturation between the two most prevalent methods—cold lateral condensation and warm gutta-percha techniques—using micro-CT (PROSPERO reg no. 249815). Materials and Methods: A search of Scopus, Embase, PubMed (Medline via PubMed), and Web of Science databases was done without any time restriction according to the PRISMA protocol. Articles that compared both techniques and were published in English were included. Data was extracted and the risk of bias was assessed using an adapted tool based on previous studies. Results: A total of 141 studies were identified by the search. Following the screening and selection of articles, 9 studies were included for review. Data was extracted manually and tabulated. Most studies had a moderate risk of bias. None determined operator skill in both methods before comparison. The data extracted from the included studies suggests that both techniques produce voids in the obturation. The thermoplasticized gutta-percha techniques may result in fewer voids compared to cold lateral condensation. Conclusion: Considering the limitations of the included studies, it was concluded that neither technique could completely obturate the root canal. Thermoplasticized gutta-percha techniques showed better outcomes despite a possible learning bias in favor of cold lateral condensation. Establishing operator skills before comparison may help reduce this bias.

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Section: Literature Reviewmentioning

confidence: 99%

“…This is done by using appropriate settings for scanning and a metal artifact reduction algorithm [55,56]. The expression of artefacts is variable among different CBCT machines [57]. MRI also suffers from similar problems in addition to high cost and long scan times [58,59].…”

Section: Literature Reviewmentioning

confidence: 99%

Complete Obturation—Cold Lateral Condensation vs. Thermoplastic Techniques: A Systematic Review of Micro-CT Studies

et al. 2021

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“…Micro-computed tomography (micro-CT) scanners are often used in laboratory research and have similar general characteristics to CBCT devices (e.g., beam shape and a flat panel detector), but micro-CT involves a smaller FOV, a higher radiation dose, a longer scanning time, and a critical hardware setup. 6 7 8 Although micro-CT scanners are not clinically applicable, several aspects regarding the use of CBCT have been developed and improved based on knowledge gained from micro-CT. For endodontics, the use of high-resolution 3D data has facilitated a better understanding of anatomical challenges, such as flattening, curvature, lateral and accessory canals, apical deltas, and isthmuses, as well as the cleaning, shaping and filling procedures of the root canal system (RCS), 5 8 9 offering better insights into anatomy, pathology, and anticipated endodontic strategies. 5 8 9 10 11 Among the anatomical variations of the root canal, studies have shown that in spite of development of new systems and protocols for cleaning and shaping, isthmuses in root canals continue to be areas that are inaccessible to instruments, resulting in debris accumulation and the maintenance of necrotic pulp tissue and microorganisms inside the RCS, affecting 3D filling and, consequently, clinical outcomes.…”

Section: Introductionmentioning

confidence: 99%

“…This has led to a deeper understanding of the potential, optimized use, and limitations of CBCT, allowing this modality to be used in a manner that facilitates diagnosis and endodontic planning. 6 12 13 14 15 …”

Section: Introductionmentioning

confidence: 99%

CBCT-based assessment of root canal treatment using micro-CT reference images

et al. 2022

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Purpose This study compared the root canal anatomy between cone-beam computed tomography (CBCT) and micro-computed tomography (micro-CT) images before and after biomechanical preparation and root canal filling. Materials and Methods Isthmus-containing mesial roots of mandibular molars (n=14) were scanned by micro-CT and 3 CBCT devices: 3D Accuitomo 170 (ACC), NewTom 5G (N5G) and NewTom VGi evo (NEVO). Two calibrated observers evaluated the images for 2-dimensional quantitative parameters, the presence of debris or root perforation, and filling quality in the root canal and isthmus. The kappa coefficient, analysis of variance, and the Tukey test were used for statistical analyses (α=5%). Results Substantial intra-observer agreement (κ=0.63) was found between micro-CT and ACC, N5G, and NEVO. Debris detection was difficult using ACC (42.9%), N5G (40.0%), and NEVO (40%), with no agreement between micro-CT and ACC, N5G, and NEVO (0.05<κ<0.12). After biomechanical preparation, 2.4%-4.8% of CBCT images showed root perforation that was absent on micro-CT. The 2D parameters showed satisfactory reproducibility between micro-CT and ACC, N5G, and NEVO (intraclass correlation coefficient: 0.60-0.73). Partially filled isthmuses were observed in 2.9% of the ACC images, 8.8% of the N5G and NEVO images, and 26.5% of the micro-CT images, with no agreement between micro-CT and ACC, and poor agreement between micro-CT and N5G and NEVO. Excellent agreement was found for area, perimeter, and the major and minor diameters, while the roundness measures were satisfactory. Conclusion CBCT images aided in isthmus detection and classification, but did not allow their classification after biomechanical preparation and root canal filling.

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“…5 Furthermore, the added dimension of CBCT may not improve the diagnosis of inflammation, 6 and the diagnostic value of CBCT can be severely affected by metal artefacts (e.g., from root canal fillings or adjacent implants). 7 Thus, IOR is expected to remain a frequently used imaging modality for routine periapical evaluation before, during, and after treatment. 5 Because of the limited diagnostic efficacy of IOR for periapical lesions, several previous studies have evaluated techniques to optimize lesion detection, including through image postprocessing.…”

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confidence: 99%

Artificial intelligence for detection of periapical lesions on intraoral radiographs: Comparison between convolutional neural networks and human observers

Pauwels

Brasil

Yamasaki

et al. 2021

Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology

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Objective. The aim of this study was to compare the diagnostic performance of convolutional neural networks (CNNs) with the performance of human observers for the detection of simulated periapical lesions on periapical radiographs. Study Design. Ten sockets were prepared in bovine ribs. Periapical defects of 3 sizes were sequentially created. Periapical radiographs were acquired of each socket with no lesion and with each lesion size with a photostimulable storage phosphor system. Radiographs were evaluated with no filter and with 6 image filter settings. A CNN architecture was set up using Keras-TensorFlow. Separate CNNs were evaluated for randomly sampled training/validation data and for data split up by socket (5-fold cross-validation) and filter (7-fold cross-validation). CNN performance on validation data was compared with that of 3 oral radiologists for sensitivity, specificity, and area under the receiver operating characteristic curve (ROC-AUC). Results. Using random sampling, the CNN showed perfect accuracy for the validation data. When data were split up by socket, the mean sensitivity, specificity, and ROC-AUC values were 0.79, 0.88, and 0.86, respectively; when split up by filter, they were 0.87, 0.98, and 0.93, respectively. For radiologists, the values were 0.58, 0.83, and 0.75, respectively. Conclusions. CNNs show promise in periapical lesion detection. The pretrained CNN model yielded in this study can be used for further training on larger samples and/or clinical radiographs. (Oral Surg Oral Med Oral Pathol Oral Radiol 2021;000:1À7) Statement of Clinical RelevanceConvolutional neural networks are used to develop artificial intelligence systems for diagnostic tasks in oral and maxillofacial radiology. This study indicates that convolutional neural networks can yield diagnostic performance comparable to or better than that of human observers for detection of periapical lesions.

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Cone-beam Computed Tomographic–based Assessment of Filled C-shaped Canals: Artifact Expression of Cone-beam Computed Tomography as Opposed to Micro–computed Tomography and Nano–computed Tomography

Cited by 16 publications

References 36 publications

Complete Obturation—Cold Lateral Condensation vs. Thermoplastic Techniques: A Systematic Review of Micro-CT Studies

Complete Obturation—Cold Lateral Condensation vs. Thermoplastic Techniques: A Systematic Review of Micro-CT Studies

CBCT-based assessment of root canal treatment using micro-CT reference images

Artificial intelligence for detection of periapical lesions on intraoral radiographs: Comparison between convolutional neural networks and human observers

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