ArticleBMC oral health2026
State-of-the-art 3D analysis of soft tissue prediction for orthognathic correction of dentofacial deformities in the Egyptian population.
Article in BMC oral health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo evaluate the accuracy of soft tissue simulation in bimaxillary osteotomy for orthognathic surgical correction of Class III dentofacial deformities using 3D conformation meshes and facial aesthetic units. MATERIALS &
methodsA retrospective analysis of CBCT scans of 13 Egyptian patients who underwent simultaneous maxillary advancement and mandibular setback surgery for correction of class III skeletal deformities. Preoperative and postoperative CBCT scans were superimposed using voxel-based registration. Dolphin software generated soft tissue predictions according to the measured surgical movements. This was compared with the actual soft tissue changes following orthognathic surgery. Prediction accuracy was assessed using dense surface correspondence analysis with region-specific segmentation into facial aesthetic units, comparing Euclidean and directional (X, Y, Z) distances between predicted and actual outcomes, and color-coded maps were used to visualize the findings.
resultsAcross all regions, the highest prediction errors was in the anteroposterior dimension, with the upper lip showing the greatest deviation (median 2.04 mm). The chin region exhibited the lowest overall prediction error of 1.82 mm. The lower lip and cheek regions showed moderate prediction errors. The prediction error was relatively low at the nose. Color maps indicated a consistent pattern of underprediction of the soft tissue changes following Le Fort I maxillary advancement and mandibular setback surgery.
conclusionPrediction errors across facial regions remained within an acceptable range of less than 2 mm. The sophisticated methodology of this study, incorporating dense correspondence analysis and facial unit segmentation, provided a more precise assessment of soft tissue prediction accuracy of bimaxillary osteotomy for correction of class III deformities. These findings support the clinical reliability of Dolphin software while highlighting the importance of advanced analytical approaches in orthognathic surgical planning. CLINICAL RELEVANCE: The application of the conformation meshes and the mathematical facial segmentation into aesthetic units provided an insight into the magnitude and direction of 3D prediction errors in Egyptian population, this should be considered in planning orthognathic surgery.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.