J Korean Ophthalmol Soc.  2019 Mar;60(3):210-216. 10.3341/jkos.2019.60.3.210.

Semi-automatic Measurement of Ocular Volume from Facial Computed Tomography and Correlation with Axial Length

Affiliations
  • 1Department of Ophthalmology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, Korea. pbloadsky@naver.com
  • 2Department of Ophthalmology, Kyung Hee University Medical Center, Kyung Hee University School of Medicine, Seoul, Korea.
  • 3Department of Bioengineering, Kyung Hee University School of Medicine, Seoul, Korea.

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.

Keyword

Axial length; Facial computed tomography; Ocular volume; Volume measurements
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