A comparison of the horizontal and vertical bitewing images in detecting approximal caries and interdental bone loss in posterior teeth: A diagnostic accuracy randomized cross over clinical trial

Natto, Zuhair S.; Olwi, Anas; Abduljawad, Faisal

doi:10.1016/j.jds.2022.08.006

Cited by 3 publications

(3 citation statements)

References 16 publications

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“…Three studies used intraclass correlation coefficients to measure the reliability of digital intraoral radiography for a dental assessment. A photostimulable phosphor storage plate x-ray sensor had up to 98.1% agreement with clinical practice in detecting bone defects [ 60 ], and up to 51% of observers agreed with the potential of vertical bitewing radiographs in detecting caries when compared with horizontal bitewings [ 61 ], while specialists’ agreement on overall image quality superiority from a complementary metal-oxide-semiconductor (CMOS) sensor over a charge-coupled device (CCD) was 66% (95% CI 30% to 87%) [ 56 ]. Vertical bitewing images had agreement varying from 23.4 to 51% when compared to horizontal images and clinical observation in identifying caries and bone loss.…”

Section: Resultsmentioning

confidence: 99%

Performance of Oral Cavity Sensors: A Systematic Review

Bueno

Kwong

Bergmann

2023

Sensors

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Technological advancements are enabling new applications within biomedical engineering. As a connection point between the outer environment and the human system, the oral cavity offers unique opportunities for sensing technologies. This paper systematically reviews the performance of measurement systems tested in the human oral cavity. Performance was defined by metrics related to accuracy and agreement estimation. A comprehensive search identifying human studies that reported on the accuracy or agreement of intraoral sensors found 85 research papers. Most of the literature (62%) was in dentistry, followed by neurology (21%), and physical medicine and rehabilitation (12%). The remaining papers were on internal medicine, obstetrics, and aerospace medicine. Most of the studies applied force or pressure sensors (32%), while optical and image sensors were applied most widely across fields. The main challenges for future adoption include the lack of large human trials, the maturity of emerging technologies (e.g., biochemical sensors), and the absence of standardization of evaluation in specific fields. New research should aim to employ robust performance metrics to evaluate their systems and incorporate real-world evidence as part of the evaluation process. Oral cavity sensors offer the potential for applications in healthcare and wellbeing, but for many technologies, more research is needed.

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Section: Resultsmentioning

confidence: 99%

Performance of Oral Cavity Sensors: A Systematic Review

Bueno

Kwong

Bergmann

2023

Sensors

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“…This demonstrated the difficulty of defining the ground truth for an objective comparison. In other comparable (i.e., in vivo) studies, the reported inter-rater agreement on evaluating bitewing radiographs ranged between in [ 19 ] to in [ 20 ] and was even as low as [ 16 ]. (Please note that this study formulates the task as a detection, not classification, so the absence of caries is not explicitly labeled and cannot be calculated.)…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, three of the previous studies [ 13 – 15 ] verified the existence of caries clinically but that may have even been counterproductive, given the low sensitivity of proximal caries detection in posterior teeth [ 5 ]. The uncertainty led some researchers to use a 5-point scale: 1, caries definitely present; 2, caries probably present; 3, uncertain-unable to tell; 4, caries probably not present; and 5, caries definitely not present [ 10 , 11 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic caries detection in bitewing radiographs—Part II: experimental comparison

Tichý,

Kunt,

Nagyová

et al. 2024

Clin Oral Invest

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Objective The objective of this study was to compare the detection of caries in bitewing radiographs by multiple dentists with an automatic method and to evaluate the detection performance in the absence of a reliable ground truth. Materials and methods Four experts and three novices marked caries using bounding boxes in 100 bitewing radiographs. The same dataset was processed by an automatic object detection deep learning method. All annotators were compared in terms of the number of errors and intersection over union (IoU) using pairwise comparisons, with respect to the consensus standard, and with respect to the annotator of the training dataset of the automatic method. Results The number of lesions marked by experts in 100 images varied between 241 and 425. Pairwise comparisons showed that the automatic method outperformed all dentists except the original annotator in the mean number of errors, while being among the best in terms of IoU. With respect to a consensus standard, the performance of the automatic method was best in terms of the number of errors and slightly below average in terms of IoU. Compared with the original annotator, the automatic method had the highest IoU and only one expert made fewer errors. Conclusions The automatic method consistently outperformed novices and performed as well as highly experienced dentists. Clinical significance The consensus in caries detection between experts is low. An automatic method based on deep learning can improve both the accuracy and repeatability of caries detection, providing a useful second opinion even for very experienced dentists.

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CBCT Evaluation of Alveolar Bone Change and Root Resorption after Orthodontic Treatment: A Retrospective Study

Pop,

Cerghizan,

Mițariu

et al. 2024

Diagnostics

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Background: For years, there has been a long debate about the impact of orthodontic treatment on the periodontium of patients. Therefore, it is important to understand the effects of orthodontic forces on the periodontium. The objective of this study was to evaluate the height of the alveolar bone at the four surfaces of specific teeth and the root length of the central incisors before and after orthodontic treatment. Materials and Methods: CBCTs from a group of fifty patients were evaluated before (T0) and after orthodontic treatment (T1). Evaluations of the alveolar bone were performed by measuring the distance from the most apical point of the marginal portion to the CEJ at the buccal (B-ABL), lingual (L-ABL), mesial (M-ABL), and distal (D-ABL) surfaces of the central incisor (CI), first premolar (1st PM), and first molar (1st M). Meanwhile, root resorptions were evaluated by measuring the distance from the center of the tooth at the CEJ to the most apical point of the central incisor. Results: The reduction in the alveolar bone level was highest at the buccal segment (75%) and lowest at the distal (42%) segment, although the decrease was not statistically significant. Root resorption, in terms of reduction in the total length, was detected in the upper central incisor. Conclusions: Fixed orthodontic treatment can produce a significant reduction in root length, but not at the level of the alveolar bone.

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A comparison of the horizontal and vertical bitewing images in detecting approximal caries and interdental bone loss in posterior teeth: A diagnostic accuracy randomized cross over clinical trial

Cited by 3 publications

References 16 publications

Performance of Oral Cavity Sensors: A Systematic Review

Performance of Oral Cavity Sensors: A Systematic Review

Automatic caries detection in bitewing radiographs—Part II: experimental comparison

CBCT Evaluation of Alveolar Bone Change and Root Resorption after Orthodontic Treatment: A Retrospective Study

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