Clear aligner differs from conventional fixed appliances in biomechanics. For clear aligners, tooth movements are achieved through compressive force on teeth produced by elastic changes of aligners. In contrast, teeth are moved through both compressive and traction forces generated by the interaction between brackets and archwires. Moreover, distinct from fixed appliances, the clear aligner system suffers from a significant disadvantage: teeth may “escape” from the aligners (off-tracking) and force applications cannot be adequately applied on these teeth [17]. This phenomenon results in varying degrees of predictability for different types of tooth movements, with molar distalization being the most predictable (88%) while incisor extrusion being the least (30%) [13,14,15,16]. The evaluation system of treatment complexity elaborated in this study was designed specifically for the clear aligners and our results revealed that the assessment of treatment complexity by this objective evaluation system substantially matched the gold standard results by the two experts (R2 = 0.80).
To date, several evaluation systems for assessing treatment complexity are available for conventional fixed appliances, e.g., PAR and DI [11, 12]. PAR system appraises treatment complexity based on model analysis only, and DI system evaluates treatment complexity through analysing dental models and radiographs. However, neither of above systems includes soft tissue analysis for the assessment of treatment complexity. The evaluation system described in this study took all the three tissues (dental, skeletal and soft tissues) into consideration. The scoring rules in this evaluation system for clear aligners were based on those in PAR and DI with modifications according to the unique characteristics of clear aligner treatment. Specifically, less weight was assigned to the tooth movement that was easy for clear aligners (e.g., molar distalization), while more weight to difficult tooth movement with clear aligners (e.g., molar mesialization). On the other hand, all the evaluation systems, including our present one, assess treatment difficulty through summing up difficulty points of all independent items, (e.g., overbite, overjet and molar relationship), but PAR and DI systems fail to evaluate treatment difficulty in a dynamic way. For example, a full-cusp Class II molar relationship is considered to be more difficult than Class I relationship. In effect, in clinical scenarios, full-cusp Class II molar relationship is clinically acceptable and molar movement is not necessarily required. Thus, for molar movement, the treatment difficulty is the same for a Class I relationship and a full Class II relationship. The only difference was the overjet: a patient with full-cusp Class II were more difficult due to a larger overjet that should be corrected rather than due to molar relationship. Thus, no point was added for patients whose molar relationship will be maintained in our present evaluation system. Therefore, molar relationship was evaluated in a dynamic way in our evaluation system, rather than a simple classification of molar relationship.
The multivariable regression test revealed that complexity level was positively correlated with difficulty score (β = 0.13, 95% CI 0.11 ~ 0.16; p < 0.001), indicating that complexity level will be increased by 0.13 if difficulty score is increased by one. Moreover, we found that complexity level was positively associated with tooth extraction and the number of difficult tooth movement. Although clear aligners are able to manage extraction patients with good treatment outcomes [18, 19], premolar extractions followed by anterior teeth retraction requires meticulous design of aligner biomechanics, which will definitely increase treatment complexity. Difficult tooth movement was defined by the clear aligner software based on predicted distances of movement for each tooth, e.g., molar intrusion greater than 5 mm. Conceivably, a higher complexity level is anticipated with a larger number of difficult tooth movements. Interestingly, we found that complexity level was negatively associated with patient age (β = −0.04, p = 0.015 < 0.05). This may be attributed to a selection bias that adult patients with high treatment complexity were not included in this study given that patients with greater age had smaller number of difficult tooth movement (p = 0.01 < 0.05).
For the domain of model analysis, the multivariable regression test revealed that complexity level was positively associated with all items except for spacing (Table 2). A large overjet requires premolar extractions and subsequent upper anterior retraction, while large overbite requires large amounts of lower incisor intrusions. All of these tooth movement types are considered to be difficult for clear aligners. Therefore, we put more weights on these two items (e.g., 10 points will be added for a patient with an overbite greater than 9 mm and 9 points for a patient with an overbite of 6 mm). Treatment complexity is higher among patients with more crowding (p < 0.001). However, we did not put much weight on this item since severe crowding could be easily resolved through premolar extraction and subsequent minimal incisor retraction (most of the extraction space is used for resolving crowding rather than incisor retraction). As mentioned above, we evaluated molar relationship in a dynamic way: zero point was added for patients with molar relationship maintenance (Class I, full-cusp Class II or full-cusp Class III). Considering molar mesialization is more difficult than molar distalization with clear aligners [20], we put more weights on molar mesialization. For posterior teeth, all the three types of malocclusions (openbite, crossbite and scissorbite) are difficult to treat and thus we added much weight on this item, e.g., 10 points will be added for patients with a posterior tooth with a 5-mm openbite (2 pts/tooth·mm). For the item of spacing, we only analyzed the largest space since patients with one space of 5 mm will be more difficult to treat than those with several small spaces totaling 5 mm (if the spaces are to be closed orthodontically). Moreover, if a space will not be closed orthodontically (e.g., closure through implants), no point will be added. For other model analyses, tooth anomaly, midline deviation, premolar rotation and incisor rotation were also correlated with complexity level. As is well documented, tooth movement is achieved through elastic changes of aligners, and adequate aligner wrapping is critical for achieving the predicted tooth movement. Any tooth anomaly will reduce the adequacy of aligner wrapping, making tooth movement less predictable. Hence, five points will be added for each abnormal tooth. It has been reported that a midline deviation less than 2 mm was accepted by the general population [21]. Thus, only the amount of midline deviation greater than 2 mm was counted in our evaluation system. Rotations of premolar and lateral incisors are difficult to correct in clear aligner system, since premolars are round or oval in shape and lateral incisors are short from the occlusal view (clear aligners are not able to exert adequate tangent forces that are crucial for derotation).
The domain of radiographic examinations encompasses ANB, U1-SN, SN-MP and other radiographic examinations. The deviations of ANB and SN-MP from their normal ranges are indicative of the abnormal development of upper and lower jaws, which will increase clear aligner treatment complexity. Proclined upper incisors require space gaining and subsequent retraction of incisors. Thus, treatment complexity is increased among patients with abnormal U1-SN values. Moreover, tooth impaction, supernumerary teeth, missing teeth, tooth transposition, root resorption and severe skeletal problems needing orthognathic surgery increased clear-aligner treatment difficulty and we put different weights on these items according to their influence on treatment complexity. The multivariable regression test showed that complexity level was associated with all items in the domain of radiographic examinations except for other radiographic examinations. This could be attributed to the fact that small number of patients had these other radiographic problems (e.g., impaction), making this index (other radiographic examinations) similar among patients with different complexity levels. Thus, further studies with larger sample sizes are warranted.
The domain of clinical examinations had three indices: E-line, gummy smile and other clinical examinations. The multivariable regression test found that complexity level was correlated with E-line and other radiographic examinations, while not with gummy smile. Likewise, this may be due to that small number of patients required gummy smile correction. An abnormal E-line (e.g., 4 mm denotes lips are protrusive by 4 mm in reference to E-line) requires space gaining and anterior teeth retraction, thereby increasing aligner case difficulty. Moreover, all of the indices (chin deviation, occlusal canting, periodontitis, TMD and generalized caries) in “other clinical examinations” increased clear aligner treatment complexity. Thus, we put different weights on these indices.
The patients in the second group were included for examining the external validity of the complexity assessment tool. Our results revealed that the difficulty scores (obtained through assessment tool) were significantly correlated with complexity level (assessed by experts) with an R2 of 0.82. This finding was consistent with that from the first group, indicative of the external validity of this assessment tool. However, the limitation of this pilot study was relatively small sample size. Thus, future studies with larger sample sizes in different clinical settings among different races are warranted to further confirm the validity of this complexity assessment tool.