Introduction: Near infrared imaging (NIRI) uses non-ionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces. This generates images that allow for interproximal caries detection, which have been proposed as an alternative to radiographic detection. The new iTero Element 5D intraoral scanner (Align Technology) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, the goal of this study was to assess clinicians’ abilities to detect and characterize caries in pediatric patients using this instrument. Methods: Bitewing (BW) radiographs and a NIRIenabled intraoral scan were captured on 17 pediatric patients, and a total of 344 surfaces were then analyzed. The data was randomized and graded by five calibrated clinicians individually. A follow up round of grading was also done in which NIRI and BW datasets were combined and provided for the same patient together. Results: The reliability of lesion characterization (i.e., grade) amongst examiners was generally poor to fair in both systems, while the reliability of caries detection was moderate for BW (κ=0.4774) and NIRI (κ=0.4001). NIRI had an overall accuracy of 87.79%, a high specificity of 96.07%, and low sensitivity of 23.98%. The overall reliability of characterization of the combined dataset was moderate (κ=0.4957), while for detection was substantial (κ=0.6463). Conclusions: When using either BW or NIRI analysis, reliability was relatively poor, and clinicians were more likely to correctly identify a healthy tooth surface when compared to a carious surface. There was a small difference in error rate between BW and NIRI systems that is unlikely to be clinically significant. When NIRI and BW data was combined, agreement among clinicians for both lesion characterization and detection increased significantly. Overall, NIRI appears to be relatively comparable to BW as a diagnostic test, although both tests have significant limitations that are important to recognize.
| Identifer | oai:union.ndltd.org:pacific.edu/oai:scholarlycommons.pacific.edu:dugoni_etd-1027 |
| Date | 30 September 2022 |
| Creators | Cuenin, Kyle, Chen, James |
| Publisher | Scholarly Commons |
| Source Sets | University of the Pacific |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Orthodontics and Endodontics Theses |
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