Digital Remote Solutions For Clinical Orthodontic Image Collection

To investigate the clinical practices of the remote, digital MOOELI solution in orthodontic image collection. 27 patients who received orthodontic treatment using invisible aligners in Hospital of Stomatology, Xi’an Jiaotong University (March–June 2023) were enrolled. MOOELI and conventional way were used to collect intraoral images, which were then evaluated by orthodontists. The following clinical outcomes were analyzed using the paired McNemar chi-square test, including the status of the aligner, the occlusal state of the oral teeth, the condition of the periodontal tissue and the invisible aligner attachments. Images collected by MOOELI and conventional way showed the same result for majority of the clinical outcomes including whether the appliance was degloved or not in all areas, the calculus status of the anterior teeth and premolars, the midline, the overbite index of the anterior teeth, the horizontal occlusal relationship of the posterior teeth, the judgment of the gingival status and the invisible aligner attachments in all areas, without statistical difference in the analysis (all P>0.05). However, there were significant differences in the assessment of posterior teeth sagittal occlusion, as well as the status of dental calculus in the premolar and molar regions (P<0.05). The images collected by MOOELI system could meet the requirements in clinical practices, especially for patients with relatively few periodontal problems, which were consistent with the images taken by traditional way. These results suggest MOOELI system is worthy of application and promotion in orthodontics.

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Publication Details

Journal
International Dental Journal
Published
2025-10-01
DOI
https://doi.org/10.1016/j.identj.2025.105388
Primary Topic
Orthodontics and Dentofacial Orthopedics
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article
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article

Digital Remote Solutions For Clinical Orthodontic Image Collection

Hu Qiao, Wanting Wan, Bing Qi
International Dental Journal
Orthodontics and Dentofacial Orthopedics
article

Digital Remote Solutions For Clinical Orthodontic Image Collection

Hu Qiao, Wanting Wan, Bing Qi
article en

Abstract

To investigate the clinical practices of the remote, digital MOOELI solution in orthodontic image collection. 27 patients who received orthodontic treatment using invisible aligners in Hospital of Stomatology, Xi’an Jiaotong University (March–June 2023) were enrolled. MOOELI and conventional way were used to collect intraoral images, which were then evaluated by orthodontists. The following clinical outcomes were analyzed using the paired McNemar chi-square test, including the status of the aligner, the occlusal state of the oral teeth, the condition of the periodontal tissue and the invisible aligner attachments. Images collected by MOOELI and conventional way showed the same result for majority of the clinical outcomes including whether the appliance was degloved or not in all areas, the calculus status of the anterior teeth and premolars, the midline, the overbite index of the anterior teeth, the horizontal occlusal relationship of the posterior teeth, the judgment of the gingival status and the invisible aligner attachments in all areas, without statistical difference in the analysis (all P>0.05). However, there were significant differences in the assessment of posterior teeth sagittal occlusion, as well as the status of dental calculus in the premolar and molar regions (P<0.05). The images collected by MOOELI system could meet the requirements in clinical practices, especially for patients with relatively few periodontal problems, which were consistent with the images taken by traditional way. These results suggest MOOELI system is worthy of application and promotion in orthodontics.

International Dental JournalVol. 75
Xi'an Jiaotong University (CN)
Openalex Percentile: Top 65%
Orthodontics and Dentofacial Orthopedics
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Digital Remote Solutions For Clinical Orthodontic Image Collection — Hu Qiao, Wanting Wan, et al. · International Dental Journal (2025) | TGRS Research Map | TGRS