Place of a new radiological index in predicting pulp exposure before intervention for deep carious lesions

Gasqui, Marie-Agnès; Pérard, Matthieu; Decup, Franck; Monsarrat, Paul; Turpin, Yann-Loïg; Villat, Cyril; Gueyffier, François; Maucort‐Boulch, Delphine; Roche, Laurent; Grosgogeat, Brigitte

doi:10.1007/s11282-021-00530-w

Cited by 5 publications

(4 citation statements)

References 32 publications

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“…Gender and type of treated tooth had no significant effect on dentine bridge thickness. This was in accordance with Gasqui et al, [ 17 ]; there was no association between type of tooth and radiographic measurement of RDT also with Al Jhany et al, [ 28 ] who reported absence of significant differences between premolars and molars as both have similar RDT ranges. All teeth cavity preparation was performed using a coarse grit carbide bur to decrease the influence of the smear layer which could be entrapped inside the dentinal tubules, as explained by Violich et al, [ 10 ] who found that the particle size of the smear layer influenced the accuracy of the Prepometer™ measurements.…”

Section: Discussionsupporting

confidence: 91%

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Comparative evaluation and patient satisfaction with an electrical impedance-based device versus digital radiography in the estimation of remaining dentin thickness in carious posterior permanent teeth: (Diagnostic accuracy study)

Abd ElAziz,

Ragab,

Elzayat

2024

BMC Oral Health

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Background Accurate assessment of remaining dentin thickness (RDT) is paramount for restorative decisions and treatment planning of vital teeth to avoid any pulpal injury. This diagnostic accuracy study compared the validity and patient satisfaction of an electrical impedance based device Prepometer™ (Hager & Werken, Duisburg, Germany) versus intraoral digital radiography for the estimation of remaining dentin thickness in carious posterior permanent teeth. Methods Seventy patients aged 12–25 years with carious occlusal or proximal permanent vital posterior teeth were recruited. Tooth preparation was performed to receive an adhesive restoration. Pre- and post-excavation RDT were measured radiographically by two calibrated raters using the paralleling periapical technique. Prepometer™ measurements were performed by the operator. Patients rated their satisfaction level with each tool on a 4-point Likert scale and 100 mm visual analog scale (VAS). Inter and intragroup comparisons were analyzed using signed rank test, while agreement between devices and observations was tested using weight kappa (WK) coefficient. Results the intergroup comparisons showed that, before and after excavation, there was a significant difference between measurements made by both techniques (p < 0.001). After excavation, there was a weak agreement between measurements (WK = 0.2, p < 0.001), whereas before excavation, the agreement was not statistically significant (p = 0.407). Patients were significantly more satisfied with Prepometer™ based on scales and VAS (p < 0.001). Conclusion Prepometer™ could be a viable clinical tool for determining RDT with high patient satisfaction, while radiographs tended to overestimate RDT in relation to the Prepometer™.

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Section: Discussionsupporting

confidence: 91%

“…The radiographic image and raters’ calibration processes were done on ten initial cases with the help of a dental radiologist. The measurement was executed by drawing a straight line from the deepest point of the carious tissue floor to the highest point of the pulp before and after ending of the tooth cavity preparation [ 17 ] Fig. 2 .…”

Section: Methodsmentioning

confidence: 99%

Comparative evaluation and patient satisfaction with an electrical impedance-based device versus digital radiography in the estimation of remaining dentin thickness in carious posterior permanent teeth: (Diagnostic accuracy study)

Abd ElAziz,

Ragab,

Elzayat

2024

BMC Oral Health

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“…Indeed, major differences have been noticed between raters in the detection of carious lesions, even using the same radiograph [3]. Factors such as X-ray quality, viewing conditions, the experience of dentists, and variability between examiners [4,5] lead to discrepancies in inter-rater agreement among observers.…”

Section: Introductionmentioning

confidence: 99%

Exploring the Methodological Approaches of Studies on Radiographic Databases Used in Cariology to Feed Artificial Intelligence: A Systematic Review

Ndiaye,

Gasqui,

Millioz

et al. 2024

Caries Res

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Introduction: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to those of certified dentists. This methodological systematic review aimed to evaluate the different methodological approaches used by studies focusing on machine learning and deep learning that have used radiographic databases to classify, detect, and segment dental caries. Methods: The protocol was registered in PROSPERO before data collection (CRD42022348097). Literature research was performed in MEDLINE, Embase, IEEE Xplore, and Web of Science until December 2022, without language restrictions. Studies and surveys using a dental radiographic database for the classification, detection, or segmentation of carious lesions were sought. Records deemed eligible were retrieved and further assessed for inclusion by two reviewers who resolved any discrepancies through consensus. A third reviewer was consulted when any disagreements or discrepancies persisted between the two reviewers. After data extraction, the same reviewers assessed the methodological quality using the CLAIM and QUADAS-AI checklists. Results: After screening 325 articles, 35 studies were eligible and included. The bitewing was the most commonly used radiograph (n = 17) at the time when detection (n = 15) was the most explored computer vision task. The sample sizes used ranged from 95 to 38,437, while the augmented training set ranged from 300 to 315,786. Convolutional neural network was the most commonly used model. The mean completeness of CLAIM items was 49% (SD ± 34%). The applicability of the CLAIM checklist items revealed several weaknesses in the methodology of the selected studies: most of the studies were monocentric, and only 9% of them used an external test set when evaluating the model’s performance. The QUADAS-AI tool revealed that only 43% of the studies included in this systematic review were at low risk of bias concerning the standard reference domain. Conclusion: This review demonstrates that the overall scientific quality of studies conducted to feed artificial intelligence algorithms is low. Some improvement in the design and validation of studies can be made with the development of a standardized guideline for the reproducibility and generalizability of results and, thus, their clinical applications.

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“…Moreover, I3M estimation requires and depends on the experience in dental radiograph interpretation, and therefore represents a potential source of inaccuracy, as illustrated by the I3M inter-intraclass correlation coefficient (ICC) values that are good or excellent, but never perfect [11][12][13]. This difficulty in dental radiograph analysis is not specific to I3M calculation, and must therefore be carefully managed, especially given the ethical and legal impact of the final decision [14][15][16]. This dependence on human interpretation strongly highlights the need for an accurate tool able to support and standardize I3M score estimation to assist less experienced forensic experts and reduce inaccuracies.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M

Bui

Iozzino

Richert

et al. 2023

IJERPH

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Expert determination of the third molar maturity index (I3M) constitutes one of the most common approaches for dental age estimation. This work aimed to investigate the technical feasibility of creating a decision-making tool based on I3M to support expert decision-making. Methods: The dataset consisted of 456 images from France and Uganda. Two deep learning approaches (Mask R-CNN, U-Net) were compared on mandibular radiographs, leading to a two-part instance segmentation (apical and coronal). Then, two topological data analysis approaches were compared on the inferred mask: one with a deep learning component (TDA-DL), one without (TDA). Regarding mask inference, U-Net had a better accuracy (mean intersection over union metric (mIoU)), 91.2% compared to 83.8% for Mask R-CNN. The combination of U-Net with TDA or TDA-DL to compute the I3M score revealed satisfying results in comparison with a dental forensic expert. The mean ± SD absolute error was 0.04 ± 0.03 for TDA, and 0.06 ± 0.04 for TDA-DL. The Pearson correlation coefficient of the I3M scores between the expert and a U-Net model was 0.93 when combined with TDA and 0.89 with TDA-DL. This pilot study illustrates the potential feasibility to automate an I3M solution combining a deep learning and a topological approach, with 95% accuracy in comparison with an expert.

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Place of a new radiological index in predicting pulp exposure before intervention for deep carious lesions

Cited by 5 publications

References 32 publications

Comparative evaluation and patient satisfaction with an electrical impedance-based device versus digital radiography in the estimation of remaining dentin thickness in carious posterior permanent teeth: (Diagnostic accuracy study)

Comparative evaluation and patient satisfaction with an electrical impedance-based device versus digital radiography in the estimation of remaining dentin thickness in carious posterior permanent teeth: (Diagnostic accuracy study)

Exploring the Methodological Approaches of Studies on Radiographic Databases Used in Cariology to Feed Artificial Intelligence: A Systematic Review

Artificial Intelligence as a Decision-Making Tool in Forensic Dentistry: A Pilot Study with I3M

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