We read with interest the article on 3-dimensional (3D) analysis of soft-tissue changes after orthognathic surgery (Baik HS, Kim SY. Facial soft-tissue changes in skeletal Class III orthognathic surgery patients analyzed with 3-dimensional laser scanning. Am J Orthod Dentofacial Orthop 2010;138:167-78).

This article reports on the use of a laser scanner to evaluate soft-tissue changes after the correction of skeletal Class III malocclusions with plastic surgery. The authors made a good attempt at 3D comparison of soft-tissue changes. But there are still some limitations to which we want to draw attention, and we also have some ideas to share and discuss with the readers.

Recently, there were several articles about evaluation of soft-tissue changes after orthognathic surgery or orthodontic treatment with 3D methodology. It is important to evaluate soft-tissue changes after plastic surgery or orthodontic treatment, because improvement in facial esthetics is judged mainly by the changes in the soft tissues.

Up to now, it is still premature to evaluate soft-tissue changes 3-dimensionally. Most studies have used linear ratios or the relationship between soft- and hard-tissue changes in skeletal and facial landmarks. Actually, these methods use a 2-dimensional index in a 3D evaluation. In our research project, funded by the Medical Foundation of the People’s Liberation Army (No. 09MA018), we attempted to explore a serial of index (the ratio of voluminal discrepancy versus the volume of the standard image, the ratio of areal discrepancy versus the area of the surface of the standard image, the number of points within a certain range of discrepancy, etc) for 3D analysis, including digital image superimposition, distribution patterns of shape discrepancy presented with a histogram, as well as showing different colors on the superimposed images. We also used the ratio of volume change vs the volume of the standard image as an index for 3D evaluation. Our aim was to evaluate 3D changes in a more visualized way, as well as by more persuasive data.

Among all the 3D imaging techniques, including CT, MRI, the moire stripes method, stereophotogrammetry, and laser scanning, 3D laser scanning is suitable for shape evaluation of soft tissues. But during scanning, the stability of body posture and facial expression will inevitably influence the results.

Moreover, it is difficult to select a specific reference point as a landmark in the reconstructed 3D surface images, because the images are made up of millions of points (triangles). These triangles are so tiny that we can hardly locate the same triangle repeatedly, whereas the location of the landmark point greatly influences the end result.

Three-dimensional image reconstruction by laser scanning will go through a series of data processing, including data optimization (feature-point) segmentation, mosaic, and surface reconstruction. How to standardize these operational procedures to minimize the variances or keep the variances consistent distinguishes the research by different authors. In addition, data can’t be segmented automatically, and data segmentation must be provided through an interactive or iterative process. The ability to quickly and accurately extract characters is also a key issue for future research.