Publications
2024
Cuenin, Kyle; Chen, James; Tai, Sandra Khong; Lee, David; Gerges, Geraldine; Oh, Heesoo
Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology Journal Article
In: American Journal of Orthodontics and Dentofacial Orthopedics, vol. 165, iss. 1, pp. 54-63, 2024.
Abstract | Links | BibTeX | Tags: Bitewing (BW), Caries Detection, iTero 5D, Pediatric patients
@article{Cuenin2024,
title = {Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology},
author = {Kyle Cuenin and James Chen and Sandra Khong Tai and David Lee and Geraldine Gerges and Heesoo Oh},
url = {https://doi.org/10.1016/j.ajodo.2023.06.026},
doi = {10.1016/j.ajodo.2023.06.026},
year = {2024},
date = {2024-01-16},
urldate = {2024-01-16},
journal = {American Journal of Orthodontics and Dentofacial Orthopedics},
volume = {165},
issue = {1},
pages = {54-63},
abstract = {Introduction: Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians’ abilities to detect and characterize caries in pediatric patients using this instrument. Methods: Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading. Results: The reliability of lesion characterization (i.e., grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial. Conclusions: When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly.},
keywords = {Bitewing (BW), Caries Detection, iTero 5D, Pediatric patients},
pubstate = {published},
tppubtype = {article}
}
Introduction: Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians’ abilities to detect and characterize caries in pediatric patients using this instrument. Methods: Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading. Results: The reliability of lesion characterization (i.e., grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial. Conclusions: When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly.
Cuenin, Kyle; Chen, James; Tai, Sandra Khong; Lee, David; Gerges, Geraldine; Oh, Heesoo
Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology Journal Article
In: American Journal of Orthodontics and Dentofacial Orthopedics, vol. 165, iss. 1, pp. 54-63, 2024.
@article{Cuenin2024,
title = {Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology},
author = {Kyle Cuenin and James Chen and Sandra Khong Tai and David Lee and Geraldine Gerges and Heesoo Oh},
url = {https://doi.org/10.1016/j.ajodo.2023.06.026},
doi = {10.1016/j.ajodo.2023.06.026},
year = {2024},
date = {2024-01-16},
urldate = {2024-01-16},
journal = {American Journal of Orthodontics and Dentofacial Orthopedics},
volume = {165},
issue = {1},
pages = {54-63},
abstract = {Introduction: Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians’ abilities to detect and characterize caries in pediatric patients using this instrument. Methods: Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading. Results: The reliability of lesion characterization (i.e., grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial. Conclusions: When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Introduction: Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians’ abilities to detect and characterize caries in pediatric patients using this instrument. Methods: Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading. Results: The reliability of lesion characterization (i.e., grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial. Conclusions: When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly.
2024 |
Cuenin, Kyle; Chen, James; Tai, Sandra Khong; Lee, David; Gerges, Geraldine; Oh, Heesoo: Caries detection and characterization in pediatric patients using iTero 5D near-infrared technology. In: American Journal of Orthodontics and Dentofacial Orthopedics, vol. 165, iss. 1, pp. 54-63, 2024. (Type: Journal Article | Abstract | Links | BibTeX | Tags: Bitewing (BW), Caries Detection, iTero 5D, Pediatric patients)@article{Cuenin2024,Introduction: Near-infrared imaging (NIRI) has been proposed as an alternative to radiographs and uses nonionizing radiation in the near-infrared spectrum to differentially scatter light off tooth surfaces and generate images allowing interproximal caries detection. The new iTero 5D Element Scanner (Align Technology, Santa Clara, Calif) has integrated NIRI capture and viewing technology but has not been specifically studied in a pediatric population. Therefore, this study aimed to assess clinicians’ abilities to detect and characterize caries in pediatric patients using this instrument. Methods: Bitewing (BW) radiographs and an intraoral scan were captured on 17 pediatric patients (344 surfaces were analyzed). Data were randomized and graded by 5 calibrated clinicians individually with 2 different rounds of grading. Results: The reliability of lesion characterization (i.e., grade) among examiners was poor to fair in both systems, whereas the reliability of caries detection was moderate. Both systems had a high specificity and low sensitivity. The reliability of the characterization of the combined dataset was moderate to substantial, whereas, for detection, it was substantial. Conclusions: When using either BW or NIRI analysis, reliability is relatively poor, and clinicians are more likely to correctly identify a healthy tooth surface when compared with a carious surface. There is a small difference in error rate between BW and NIRI systems that is not likely to be clinically significant. When NIRI and BW data are combined, clinician agreement for both lesion characterization and detection increases significantly. |