Impact of low intensity pulsed ultrasound on volumetric root resorption of maxillary incisors in patients treated with clear aligner therapy: A retrospective study
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to evaluate the volumetric root resorption in maxillary incisors following clear aligner therapy (CAT) with low-intensity pulsed ultrasound (LIPUS), and compare the results to CAT alone. MATERIAL AND METHODS: This retrospective study evaluated pretreatment (T0) and post-treatment (T1) cone-beam computed tomography imaging of 42 adult patients. Twenty-one patients (14 females, 7 males, mean age= 38.1±12.96 years) were treated using CAT with LIPUS device, whereas the other twenty-one matching controls patients (15 females, 6 males, mean age= 35.6±11.7 years) were treated using CAT alone. Images were analyzed and a segmentation protocol was applied on the maxillary incisors. Each segmented tooth volume was exported as a surface mesh in the Visualization Toolkit (VTK) file format. The VTK files for all maxillary incisors were coded and corresponding teeth volumes from T0 and T1 were superimposed. Clipping the crown of each tooth was done, then measurements of root volumes and differences between groups were performed. Changes in root volumes were assessed (p<0.05). RESULTS: Root loss was evident in all teeth in both groups, but was significantly increased in all maxillary incisors of the control group (p<0.001) and in upper left central incisor of LIPUS group (p=0.009). When both groups were compared, there was statistically significant minimal volumetric root loss in LIPUS group (3.50-7.32 mm3), when compared to control group (11.48-12.95 mm3) (p<0.05). CONCLUSION: LIPUS group showed less volumetric root resorption compared to control group during the studied treatment time using clear aligners.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".