Korean J Orthod.  2016 Sep;46(5):323-330. 10.4041/kjod.2016.46.5.323.

Quantitative evaluation of midpalatal suture maturation via fractal analysis

• Kwak KH
• Kim SS
• Kim YI
• Kim YD

• KMID: 2352294
• DOI: http://doi.org/10.4041/kjod.2016.46.5.323

Abstract

OBJECTIVE
The purpose of this study was to determine whether the results of fractal analysis can be used as criteria for midpalatal suture maturation evaluation.
METHODS
The study included 131 subjects aged over 18 years of age (range 18.1-53.4 years) who underwent cone-beam computed tomography. Skeletonized images of the midpalatal suture were obtained via image processing software and used to calculate fractal dimensions. Correlations between maturation stage and fractal dimensions were calculated using Spearman's correlation coefficient. Optimal fractal dimension cut-off values were determined using a receiver operating characteristic curve.
RESULTS
The distribution of maturation stages of the midpalatal suture according to the cervical vertebrae maturation index was highly variable, and there was a strong negative correlation between maturation stage and fractal dimension (−0.623, p < 0.001). Fractal dimension was a statistically significant indicator of dichotomous results with regard to maturation stage (area under curve = 0.794, p < 0.001). A test in which fractal dimension was used to predict the resulting variable that splits maturation stages into ABC and D or E yielded an optimal fractal dimension cut-off value of 1.0235.
CONCLUSIONS
There was a strong negative correlation between fractal dimension and midpalatal suture maturation. Fractal analysis is an objective quantitative method, and therefore we suggest that it may be useful for the evaluation of midpalatal suture maturation.

Keyword

Cone-beam computed tomography; Midpalatal suture; Rapid palatal expansion; Fractal analysis

MeSH Terms

Cervical Vertebrae
Cone-Beam Computed Tomography
Evaluation Studies as Topic*
Female
Fractals*
Methods
ROC Curve
Skeleton
Sutures*

Figure

• 

  Figure 1 Cone-beam computed tomography (CBCT) imaging. A, Antero-posterior reference lines in the axial plane; the line passing through the midpalatal suture. B, A horizontal reference line in the coronal plane; the line connecting the center of the palate in the maxillary first molar area. C, Generation of a panoramic curve that connects the vertical center points of the palate in the sagittal plane passing through the midpalatal suture. D, Palatal area after generating the panoramic curve. A box indicates the region of interest (ROI). A narrow ROI was established from the rear of the incisive canal to the front of the posterior nasal spine, in order to exclude parts other than the midpalatal suture.

• 

  Figure 2 The fractal dimension calculation process. A, Image subtracted from the original image after performing Gaussian blurring of the region of interest. B, Image skeletonized after creating a binary image. C, Fractal dimension calculated via the box counting method.

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  Figure 3 Scatter plot depicting maturation stage (x-axis) and fractal dimension (y-axis).

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  Figure 4 Receiver operating characteristic curve. When the optimal fractal dimension cut-off value was 1.0235, sensitivity, specificity, false positive rate, false negative rate, positive predictability, and negative predictability were 64.9%, 86.6%, 35.1%, 13.4%, 80.3%, and 74.6% respectively.

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