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Assessing the accuracy of two posterior tooth-size discrepancy prediction methods based on virtual occlusal setups
Objective:
To assess accuracy of the Bolton and Johnson/Bailey (JB) analyses in identifying clinically significant posterior tooth-size discrepancies using virtually constructed occlusal setups.
Materials And Methods:
Virtual models and cone-beam computed tomography data sets from 30 patients were utilized to construct 60 (two per patient) virtual posterior occlusal setups. Observed discrepancies in cusp-embrasure relationships were compared to estimated posterior interarch tooth-size discrepancies (ITSDs) calculated via Bolton and JB posterior analyses. Clinical significance for discrepancies was established at >1 mm from ideal cusp-embrasure relationships in accordance with current American Board of Orthodontics methodology. Data within groups were normally distributed, thus comparisons were completed via paired t-tests. Paired nominal data were analyzed utilizing McNemar's test, and simple linear regression was used to model the relationship of predicted to observed discrepancies.
Results:
McNemar's test revealed significant differences (P ≤ .05) between the Bolton and JB groups' frequencies in matching the virtual setups correctly. JB predictions matched 100% (right) and 97% (left) setups; whereas, Bolton predictions matched only 23% (right and left) setups. A positive correlation was observed between JB predictions and cusp-embrasure discrepancies, demonstrating that average posterior discrepancy values increased 0.28 mm for every 1 mm predicted via the JB analysis.
Conclusions:
The JB analysis correctly characterized, but overestimated, the degree of posterior ITSDs corresponding to a clinically significant discrepancy in the virtual setups. Algebraically calculated posterior ITSDs based on the Overall and Anterior Bolton ratios were not accurate predictors of discrepancies observed in the virtual setups. Both Bolton and JB demonstrated weaknesses that limit precise identification of clinically significant ITSDs.
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