Subjective Evaluation of the Accuracy of Video Imaging Prediction Following Orthognathic Surgery in Chinese Patients

Purpose

The aims of this retrospective study were to assess the subjective accuracy of predictions generated by a computer imaging software in Chinese patients who had undergone orthognathic surgery and to determine the influence of initial dysgnathia and complexity of the surgical procedure on prediction accuracy.

Patients and Methods

The sample consisted of 40 Chinese patients who had completed treatment involving orthodontics and orthognathic surgery. All the patients had lateral cephalometric radiographs and profile photographs taken within 3 months before surgery and at least 6 months after surgery. The computer-generated predicted images and the actual post-treatment images were displayed simultaneously to a panel of orthodontists, oral maxillofacial surgeons and laypersons to allow side-by-side comparison. The panel was asked to determine which image was more esthetic and to rate the likeness between the actual and predicted images using a 10 cm visual analog scale.

Results

The results showed that the actual image was judged to be more esthetic in 82% of the cases, with the orthodontists more likely to select the actual profile compared to laypersons (P = .005). Orthodontists and surgeons rated the likeness of the images similarly while laypersons rated the likeness significantly lower than the clinicians (P = .012 and P = .015, respectively). Skeletal III cases were judged to be less accurately predicted than skeletal II cases by laypersons (P = .006) and orthodontists (P = .036). Cases treated by single-jaw osteotomy were given better ratings compared to cases with bimaxillary osteotomy by all panel groups but the differences did not reach significant level.

Conclusions

Skeletal III cases managed by bimaxillary osteotomy were least accurately predicted by the computer program. As there exists a possibility that the predicted image may be judged to be more esthetic than the actual image, clinicians must make extra effort to manage patient expectations when using computer simulations for patient education.