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Abstract
Purpose
To measure the ocular volume from facial computed tomography (CT) scans using a semi-automatic computer program, and to analyze possible correlations between the axial length and ocular volume using regression analysis.
Methods
Forty eyes from 20 facial CT scans were used to measure the ocular volumes. The cross-sectional ocular areas were calculated using a semi-automatic program based on MATLAB r2009a (MathWorks, Inc., Natick, MA, USA), and the ocular volumes were calculated from serial cross-sectional areas. The axial lengths were measured by A-scan ultrasound. Statistical analysis including regression analysis was used to determine possible correlations between the ocular volumes and axial lengths.
Results
The mean ocular volumes measured in males and females were 7.16 ± 1.80 cm3 and 7.24 ± 3.38 cm3, respectively. The mean axial lengths measured in males and females were 23.47 ± 0.69 mm and 23.23 ± 1.64 mm, respectively. There were positive correlations using Pearson's correlation coefficient and the partial correlation coefficient adjusted by axial length. Using regression analysis, the following statistically significant equation was derived: (ocular volume [cm3] = 0.0056558 × axial length3 [mm3] − 0.1798106 × axial length2 [mm2] + 32.9008570 [p < 0.001, R2 = 0.384]).
Conclusions
The ocular volume measurement tool in this study was noninvasive and very useful, without special equipment. Accurate estimation of ocular volumes by a statistical equation was feasible, and these findings may be helpful in further study of various ocular diseases and in predicting preoperative and postoperative ocular volumes.
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Figure 1.
The process of measurement of cross-sectional areas from axial scans (A) and from coronal scans (B). The white arrows are ocular contours which were automatically displayed by the program. The seed points are marked with arrowheads and the results of automated measurement are marked with black arrows. This process was repeated in all scan sections that show an ocular contours. Each measured cross-sectional area was calculated as a volume through a conversion formula.
Figure 2.
Flow chart of measuring ocular volume from facial computed tomography using MATLAB (MATLAB r2009a, MathWorks, Inc., Natick, MA, USA) based semi-automatic program. Otsu's algorithm and snake algorithm were used to detect eyeball and to check eyeball anatomy.
Figure 3.
Scatter plot of ocular volume (volume, cm3) and AXL (mm). There were positive correlations in Pearson correlation coefficient and partial correlation coefficient adjusted by AXL. AXL = axial length.
Table 1.
The average data of the ocular volume (cm3)
|
Male |
Female |
|||
|---|---|---|---|---|
| Axial scan | Coronal scan | Axial scan | Coronal scan | |
| Right eye | 6.97 ± 1.67 | 7.58 ± 2.09 | 7.43 ± 3.86 | 7.46 ± 3.30 |
| (4.40–9.78)* | (5.05–11.08)* | (4.43–15.18)* | (4.33–14.57)* | |
| Left eye | 7.02 ± 1.81 | 7.05 ± 1.81 | 6.86 ± 3.80 | 7.22 ± 3.21 |
| (4.52–9.77)* | (4.57–9.84)* | (3.84–15.30)* | (3.46–14.00)* | |
| Mean | 7.16 ± 1.80 | 7.24 ± 3.38 | ||
Table 2.
Regression analysis of axial length and ocular volume
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