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Objectives <p>To 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.</p> Materials &amp; methods <p>A 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.</p> Results <p>Across all regions, the highest prediction errors was in the anteroposterior dimension, with the upper lip showing the greatest deviation (median 2.04&#xa0;mm). The chin region exhibited the lowest overall prediction error of 1.82&#xa0;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.</p> Conclusion <p>Prediction errors across facial regions remained within an acceptable range of less than 2&#xa0;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.</p> Clinical relevance <p> 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.</p>

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State-of-the-art 3D analysis of soft tissue prediction for orthognathic correction of dentofacial deformities in the Egyptian population

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月30日

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  • Nehal Ibrahim Shobair,
  • Xiangyang Ju,
  • Amr Amin Ghanem,
  • Mohamed Diaa Zain El Abedeen,
  • Amr Ekram,
  • Ahmed Abdel Moneim Barakat,
  • Ashraf Farouk Ayoub

摘要

Objectives

To 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 & methods

A 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.

Results

Across 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.

Conclusion

Prediction 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.