Evaluation of a Fully Digital, In-House Virtual Surgical Planning Workflow for Bimaxillary Orthognathic Surgery
Bibliographic record
Abstract
BACKGROUND: The advantages of virtual surgical planning (VSP) for orthognathic surgery are clear. Previous studies have evaluated in-house VSP; however, few fully digital, in-house protocols for orthognathic surgery have been studied. PURPOSE: The purpose of this study was to evaluate the difference between the virtual surgical plan and actual surgical outcome for orthognathic surgery using a fully digital, in-house VSP workflow. STUDY DESIGN, SETTING, SAMPLE: This is a prospective cohort study from September 2020 to November 2022 of patients at the Victoria General Hospital in Halifax, NS, Canada who underwent bimaxillary orthognathic surgery. Patients were excluded if they had previously undergone orthognathic surgery or were diagnosed with a craniofacial syndrome. MAIN OUTCOME VARIABLES: The primary outcome variables were the mean 3-dimensional (3D) (Euclidean) distance error, as well as mean error and mean absolute error in the transverse (x axis), vertical (y axis), and anterior-posterior (z axis) dimensions. COVARIATES: Covariates included age, sex, and surgical sequence (mandible-first or maxilla-first). ANALYSES: The primary outcome was tested using Z and t critical value confidence intervals. The P value was set at .05. The 3D distance error for mandible-first and maxilla-first groups was compared using a 2-sample t-test as well as analysis of variance. RESULTS: The study sample included 52 subjects (24 males and 28 females) with a mean age of 27.7 (± 12.1) years. Forty three subjects underwent mandible-first surgery and 9 maxilla-first surgery. The mean absolute distance error was largest in the anterior-posterior dimension for all landmarks (except posterior nasal spine, left condyle, and gonion) and exceeded the threshold for clinical acceptability (2 mm) in 16 of 23 landmarks. Additionally, mean distance error in the anterior-posterior dimension was negative for all landmarks, indicating deficient movement in that direction. The effect of surgical sequence on 3D distance error was not statistically significant (P = .37). CONCLUSION AND RELEVANCE: In general, the largest contributor to mean 3D distance error was deficient movement in the anterior-posterior direction. Otherwise, mean absolute distance error in the vertical and transverse dimensions was clinically acceptable (< 2 mm). These findings were felt to be valuable for treatment planning purposes when using a fully digital, in-house VSP workflow.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".