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Treatment length comparison between DIBS AI digital indirect bonding and traditional direct bonding: a preliminary assessment

Abstract:

Objective: A study was conducted to evaluate the time required for full orthodontic treatment using DIBS AI digital indirect bonding methodology provided by OrthoSelect, LLC compared to traditional direct bonding of orthodontic brackets. The study sought to evaluate both overall length of treatment and the number of appointments required to complete treatment to determine if there is a meaningful difference in the time required for treatment between the two clinical approaches.


Methodology: The study harvested existing data from two unrelated orthodontic practices that provide both direct and DIBS AI digital indirect bonding modalities for their patients. Data from a total of 182 completed cases were collected, segmented and analyzed to determine what, if any, statistically significant differences might exist between the two sample sets in terms of length of treatment and total number of treatments required.


Results: Based on the statistical analysis, the DIBS AI treatment protocol resulted in an average treatment time across practices of 18.3 months compared to 24.9 months for traditional directbonding—a 26.5% reduction in time required for treatment across the entire sample. Additionally, the mean number of visits required using DIBS AI came in at 13.1 compared to an average of 16.3 visits for direct bonding—a 19.6% reduction in the number of office visits.


Conclusion: Based on the data from this study, the DIBS AI platform allows for significantly fewer office visits and an overall shorter treatment time compared to treatment using direct bonding.


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Introduction:


Direct bonding to enamel has been the traditional method of placing brackets in orthodontic treatment since the 1960s. As indirect bonding methodologies have appeared on the market, controversy has arisen over the preferability of either direct or indirect bonding techniques.


Various approaches to indirect bonding have been developed, with varying levels of effectiveness and accuracy. While many practitioners who have used indirect bonding to treat their patients find that it shortens the time required for the initial bonding appointment, the question remains as to whether indirect bonding can actually shorten the overall length of treatment. The purpose of this study is to assess DIBS AI indirect bonding technique provided by OrthoSelect and compare treatment times among similar patients treated using direct bonding to determine if there are differences in treatment times and number of office visits required, and, if so, the extent of those differences.


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Methodology:


For this study, patients treated at two different orthodontic practices (Practice 1 located in Ft. Collins, CO and Practice 2 located in Orlando, FL) were selected post hoc, anonymized and then segmented into two groups: those who received bracket placement via direct bonding and those who had brackets placed via DIBS AI indirect bonding. Treatments fell under either Dental Procedure Code D8080 (comprehensive orthodontic treatment of the adolescent dentition) or D8090 (comprehensive orthodontic treatment of the adult dentition). A total of 182 completed cases were selected for this study (120 direct bonding cases and 62 indirect bonding cases). All cases but one treated both maxillary and mandibular arches. Selected patients constituted a mix of genders and ages ranging from 9 to 45 years old, with the majority of the patients being in their teenage years. The orthodontists followed the

prescribed protocols for DIBS AI software treatment planning and clinical procedures as laid out by OrthoSelect. No guidelines were provided for their use of direct bonding techniques.


Using data stored in each practice’s Patient Management System (PMS), information on treatment lengths and number of appointments was collected and aggregated for both direct and indirect bonding cases. While the criteria for case inclusion was based solely on whether it was a direct or indirect case, the difficulty of the case was also noted, with the majority of cases falling into Class II or Class III. In fact, a slightly higher percentage of indirect bonding cases fell into Class III. However, no selection bias was used to determine whether a case was treated using one particular method or the other.


The sample data were analyzed using standard statistical testing methods to determine if meaningful differences exist. In the case of comparing the mean results of both samples, an independent two-sample t-test was used with a p-value threshold < 0.05. An F-test was used for comparing standard deviations between samples, p-value threshold also < 0.05.


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Results:


Based on analysis of the data, the combined results across practices show that mean treatment time for direct bonding was 24.9 months compared to 18.3 months for indirect bonding, an average reduction of treatment time of 6.6 months (26.5%) for indirect bonding. An independent groups t-test was performed to compare and validate the mean treatment time differences between the two treatment modalities. The t-statistic was significant at the 0.05 critical alpha level, t(180)=6.437, p<0.001.

Therefore, we conclude that there is a significant difference between the mean treatment times between direct and indirect bonding protocols. Likewise, the mean number of treatment appointments for direct bonding cases was 16.3 compared to 13.1 for indirect bonding cases—an average reduction of 3.2 appointments (19.6%) for indirect bonding (again, statistically significant at the 0.05 critical alpha level: t(180)=3.932, p<0.001).


It is interesting to note that there was a significant difference in treatment times between the two practices in this study for the same treatment approaches. However, the differences hold true that the treatment times and number of appointments were significantly lower for indirect bonding for each individual practice (see Table 1 below for a summary of the individual results).




Along with shorter average treatment times for indirect bonding cases, it also appears that the

treatment-time variability is less for indirect bonding cases, as borne out by the significantly smaller standard deviation of the indirect bonding sample (see Table 2).



Conclusions:

Based on this analysis, the DIBS AI indirect bonding approach appears to significantly reduce the amount of treatment time required and the number of office visits necessary to complete orthodontic treatment by an average of 6.6 months (26.5%) and 3.2 visits (19.6%) respectively compared to traditional direct bracket bonding. These results hold not only for the aggregate sample, but also for the sub-samples from each practice in the study. While one would expect that treatment time and the number of office visits would be positively correlated, the fact that both are significantly lower for DIBS AI treatment demonstrates that no unusual cadence of treatment or timing was required to achieve the indicated outcomes.


Further, the fact that the standard deviation of treatment time for the DIBS AI treatment sample is statistically lower than for the direct bonding sample indicates that the DIBS AI treatment protocol, in addition to being shorter, is also more predictable. In other words, the smaller standard deviation indicates that there is less variability in average treatment times for the DIBS AI approach. This narrowed range could make treatment planning and setting expectations for the patient easier for the practitioner.


Finally, it is important to note that the orthodontists closely followed established clinical procedures for DIBS AI treatments. Deviation from these techniques would likely yield sub-optimal results and may change the outcomes as presented in this study.



1 Gange, P. The Evolution of Bonding in Orthodontics. Am J Orthod Dentofacial Orthop. 2015; 147: S56- S63.

2 Menini, A., Cozzani, M., Sfondrini, M.F. et al.  A 15-month evaluation of bond failures of orthodontic brackets bonded with direct versus indirect bonding technique: a clinical trial. Prog Orthod 2014; 15:70.

3 Xue C, Xu H, Guo Y, Dhami Y, Wang H, Liu Z, Ma J, Bai D. Accurate bracket placement using a computer- aided design and computer-aided manufacturing-guided bonding device: An in vivo study. Am J Orthod Dentofacial Orthop. 2020; 157:269-77.

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