Vasiliki Koretsi1, Constanze Kirschbauer2, Peter Proff2, Christian Kirschneck2. 1. Department of Orthodontics, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany. koretsi.vasiliki@gmail.com. 2. Department of Orthodontics, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
Abstract
OBJECTIVE: To investigate if orthodontic model analysis with a digital caliper can be interchangeably performed between plaster and printed dental models. MATERIALS AND METHODS: Forty-eight plaster models were digitized with orthoX®scan (DENTAURUM) and 48 counterparts were printed with Objet30 Dental Prime (Stratasys). One examiner performed five repeated orthodontic model analyses (41 outcomes) with a digital caliper in each plaster and the corresponding printed model and was externally validated by a second examiner. Inter- and intra-examiner reliability and error were evaluated with intraclass correlation coefficients (ICCs) and Dahlberg's formula, intra-examiner agreement with Bland-Altman analyses and Lin's correlation coefficients (CCCs), and changing bias with regression analyses. RESULTS: Inter- and intra-examiner ICCs and Dahlberg's error were ≥ 0.75 and ≤ 0.5 mm, respectively, for most outcomes in both plaster and printed models. Intra-examiner agreement (systematic bias) between plaster and printed models ranged from - 0.45 to 0.45 mm. Ranges of limits of agreement were wide for cumulative outcomes, such as crowding maxilla and mandible (2.69 mm and 3.07 mm around zero, respectively). Tooth widths were measured slightly larger in printed models. Lin's CCCs were ≥ 0.87 for all the outcomes between plaster and printed models, while no changing bias was detected. CONCLUSION: If orthodontic model analyses are consistently performed, plaster casts and their corresponding printed models obtained with orthoX®scan and Objet30 Dental Prime can be interchangeably used for clinical purposes in orthodontics. CLINICAL RELEVANCE: Orthodontic model analysis is important in treatment planning and printed dental models need to be validated regarding this diagnostic procedure.
OBJECTIVE: To investigate if orthodontic model analysis with a digital caliper can be interchangeably performed between plaster and printed dental models. MATERIALS AND METHODS: Forty-eight plaster models were digitized with orthoX®scan (DENTAURUM) and 48 counterparts were printed with Objet30 Dental Prime (Stratasys). One examiner performed five repeated orthodontic model analyses (41 outcomes) with a digital caliper in each plaster and the corresponding printed model and was externally validated by a second examiner. Inter- and intra-examiner reliability and error were evaluated with intraclass correlation coefficients (ICCs) and Dahlberg's formula, intra-examiner agreement with Bland-Altman analyses and Lin's correlation coefficients (CCCs), and changing bias with regression analyses. RESULTS: Inter- and intra-examiner ICCs and Dahlberg's error were ≥ 0.75 and ≤ 0.5 mm, respectively, for most outcomes in both plaster and printed models. Intra-examiner agreement (systematic bias) between plaster and printed models ranged from - 0.45 to 0.45 mm. Ranges of limits of agreement were wide for cumulative outcomes, such as crowding maxilla and mandible (2.69 mm and 3.07 mm around zero, respectively). Tooth widths were measured slightly larger in printed models. Lin's CCCs were ≥ 0.87 for all the outcomes between plaster and printed models, while no changing bias was detected. CONCLUSION: If orthodontic model analyses are consistently performed, plaster casts and their corresponding printed models obtained with orthoX®scan and Objet30 Dental Prime can be interchangeably used for clinical purposes in orthodontics. CLINICAL RELEVANCE: Orthodontic model analysis is important in treatment planning and printed dental models need to be validated regarding this diagnostic procedure.
Keywords:
3D printing; CAD-CAM workflow; Digitized plaster models; Measuring agreement; Orthodontic model analysis
Authors: Milagros Adobes Martin; Erica Lipani; Laura Bernes Martinez; Alfonso Alvarado Lorenzo; Riccardo Aiuto; Daniele Garcovich Journal: Int J Environ Res Public Health Date: 2022-03-17 Impact factor: 3.390