Anatomic Growth Modelling of Cleft Palate Shape. S.K. Chua, S.H. Ong, K.W.C. Foong**

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1 ABSTRACT Anatomic Growth Modelling of Cleft Palate Shape S.K. Chua*, S.H. Ong*, K.W.C. Foong** *Dept of Electrical and Computer Engineering, **Dept of Preventive Dentistry, National University of Singapore The aim of this project is to utilize computer vision technology to develop algorithms for anatomic growth modelling of cleft lip and palate after surgical correction. Two plaster cleft models (3 months old, before surgery, and 9 months old, after surgery) from the same baby were first scanned with a Minolta VIVID 900 3D scanner. Landmark points were then indicated on the 3D images of each plaster model using the software RAPIDFORM Translation matrices (from 3 to 9 months) were then defined using these landmark points. It was observed that after surgical correction, the gap of the cleft lip and palate decreased in size, while the surface area of the major and minor segments increased. This project, using RAPIDFORM 2002, provides good visualisation and understanding of anatomic growth modelling of cleft lip and palate to the clinician. INTRODUCTION Cleft lip and cleft palate comprise the fourth most common birth defect in the United States, with 1 in 700 babies contracting this defect. Babies born with the cleft lip and palate deformity undergo surgical and dental correction of the palate, upper jaw and upper dentition from birth till 20 years of age. Plaster models of the palate of these babies are taken at defined intervals of postnatal life. The plaster models provide a 3 dimensional representation of the shape of the palate as determined by the actual deformity and as a consequence of surgical and dental treatment. Since a cleft palate child undergoes a series of definitive surgical and dental treatment within the first 10 years of life, the ability to visualize the future shape of the cleft palate while in infancy will permit the clinician to rationalize his treatment approach in the early infant years so as to minimize the likelihood of a poor palate shape in the later childhood. This project uses computer vision technology to develop algorithms for anatomic growth modelling of cleft lip and palate after surgical correction. EQUIPMENT Two cleft plaster models taken from the same baby are used in this project. One of the models was taken when the baby was 3 months old, before he underwent surgical correction, while the other was taken when the baby was 9 months old, after he underwent surgical correction. In this project, a Minolta VIVID 900 3D scanner is used to scan the plaster models, as its laser scanning is fast and able to output the 3D images on the computer accurately. The software RAPIDFORM 2002 is used for editing and measurement of the images. This software not only provides a good visualisation of 3D images, but also it is versatile and provides many functions. 1

2 METHOD This project can be divided into the following steps: 3D data acquisition, computer reconstruction, landmarking, and analysis. 3D Data Acquisition The plaster models were scanned using the Minolta scanner connected to a rotary table. By placing a model on the rotary table, it could be rotated 360 degrees, at an interval of 30 degrees, which allowed the scanner to scan almost every side of the model accurately. In order to scan concave and deep surfaces, the model had to be placed at a specific position for the scanner to have a one-shot scan. Computer Reconstruction Using RAPIDFORM 2002, the images of a model, which was captured at different angles, were merged to form a complete 3D image of the model. RAPIDFORM merged those images captured using the rotary table by locating the images overlapped areas. However, one-shot images had to be merged manually, by indicating more than two common points between the images. Figure 1 shows the complete 3D images of each model. Landmarking 18 common points were landmarked on the 3D images of each model (Figure 1), indicated by the green dots. There were 11 points on the major segment and 7 points on the minor segment of each model. These 18 points were chosen because 6 of these points were important points, while the rest were based on the common features found between the two models. For example, point m4 on the minor segment was chosen because it is at the edge of a significant line crack found on both models. Thus, through observation of the plaster models, 12 common features between the two models were located. The 6 important points, AC, AC, P, P, PC, PC were represented by points M1, m1, M8, m7, M11, m5 respectively. Figure 1. 3D images of the 2 cleft models with landmark points. 2

Analysis Initially, the images of the two models were out of position from one another, but the coordinates of their landmark points were with respect to the same origin, as they were in the same

Common reference points, using points M8, M11, m3 and m7 were then manually indicated to the software such that it would align the two models with respect to these points.

3 Analysis Initially, the images of the two models were out of position from one another, but the coordinates of their landmark points were with respect to the same origin, as they were in the same world co-ordinates. Therefore, the two models were superimposed to have an accurate observation of how the landmark points have moved from the 3-month to the 9-month models. Common reference points, using points M8, M11, m3 and m7 were then manually indicated to the software such that it would align the two models with respect to these points. These points were chosen because their co-ordinates were almost similar on the 3- and 9- month models. However, this method of superposition could only be an approximate alignment as the 2 models are of different shapes and sizes. Figure 2 shows an image of the 2 models after superposition. Vector lines were also drawn between the landmark points of the 2 models (i.e. point M1 of the 3 month model was connected to point M1 of the 9 month model) to provide a better visualisation for the clinician to observe the differences between the models, as shown in Figure 3. Coordinates of the landmark points were then obtained, and translation matrices and distances moved by the landmark points from the 3 month to the 9 month models could be found from these coordinates. Figure 2. 3D image of the 2 cleft models after superposition. Figure 3. 3D image of the superposition models with vector lines (red dots represent points from 3 month model and blue dots represent points from 9 month model). 3

RESULTS Figure 4a indicates how the landmark points have moved from the 3 month to the 9 month models in the x and y-directions, while Figure 4b indicates movements in the y and z-directions.

4 RESULTS Figure 4a indicates how the landmark points have moved from the 3 month to the 9 month models in the x and y-directions, while Figure 4b indicates movements in the y and z-directions. The red points represent the 3 month model and the blue points represent the 9 month model. The vector lines are named according to the landmark points as shown in Figure 1. Figure 4a. X-Y co-ordinate graph of movement of landmark points from the 3 month (red) to the 9 month (blue) models. Figure 4b. Y-Z co-ordinate graph of movement of landmark points from the 3 month (red) to the 9 month (blue) models. 4

5 Table 1 shows the distances, measured in mm, moved by the landmark points from the 3- to 9- month models. The distances can be measured using RAPIDFORM. Table 1. Distances (mm) moved by the landmark points from 3 to 9 month models DISCUSSION Validation Points Distances (mm) Points Distances (mm) M M M M M m M m M m M m M m M m M m The measurement results of this project can be validated by using callipers to measure physically the distance between two points on a plaster model and compare with the computer measurement. Using RAPIDFORM, the distance between points M1 and m1 of the 3 months model is 9.65 mm, and the distance between points M11 and m5 is mm. Observation From Results From Figure 4a, it is observed that points M1, M2, M3 and M4 have moved significantly in the positive x-direction. This shows the success of surgical correction of the cleft lip as the gap caused by the cleft has almost closed up. Table 1 provides more evidence by showing that points M1, M2, M3 and M4 have moved considerably. Moreover, the distance between points M5 and M6 has increased from mm, when measured using the 3 month model, to mm, when measured using the 9-month model. This shows that the surface area of the major segment has increased in size. This is the same for the minor segment as point m4 has moved significantly in the positive x-direction. From Figure 4b, most of the points have moved toward the negative z-direction from the 3 month to 9 month models. This indicates that the hole at the centre of the cleft palate shrank in size due to surgery. Since the coordinates of the landmark points are known, it is possible to derive translation matrix for each point, as shown in Eq. (1) using point M1 as an example. 9 Month Pt. M1 3 Month Pt. M1 Translation _ = (1) 5

6 Given a different patient s 3-month cleft palate plaster model, its 9-month point M1 coordinates can be calculated using Eq. (2) given its 3 month point M1 coordinates (i.e. (x, y, z)) x y z 1 = x y + (-2.855) z + (-0.878) 1 (2) The translation matrix in Eq. (2) is obtained from Eq. (1). In order to find the translation matrices for the other landmark points, the same procedures can be applied. Thus, this method will be able to predict approximately other patients 9 month cleft palates shapes after surgery. Other Issues The two plaster models are inconsistent in shapes and sizes, thus it is difficult to superimpose the two models exactly. Due to this problem, the models have to be aligned many times using different reference points to find the most suitable superposition. It should be noted that the plaster models have very thick base and extra surfaces, which are not part of the cleft, thus it will not be appropriate to use reference points that are not part of the cleft surfaces during alignment. Therefore, one can only obtain approximate translation matrices and measured distances of the landmark points from the 3 month to the 9 month models. Moreover, the landmark points on the plaster models are located by the human eye and defined manually onto the 3D images in the computer, thus they will not be accurate. This method of finding the common points to visualise the anatomic growth from the 3 month to the 9 month model may not be suitable if other patient s cleft shapes and sizes are drastically different from the models used in this project. CONCLUSION This project, using RAPIDFORM 2002, provides good visualisation and comparison of 3D images of cleft palates, before surgery and after surgery, to the clinician. Significant differences between the models have been located and discussed in this paper. Translation matrices and measured distances between the landmark points of both models have also been obtained, which can aid patients with cleft lips and palates. REFERENCES Berkowitz, S. (1996), Cleft Lip and Palate - Perspectives in Management - Volume 1, Singular Publishing Group, San Diego, USA, Pages 29-40, 51-64, and INUS Technology, RAPIDFORM 2002 software Manual. 6

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