Hilmi Mohd Radzi, Che Azemin Mohd Zulfaezal, Mohd Kamal Khairidzan, Mohd Tamrin Mohd Izzuddin, Abdul Gaffur Norfazrina, Tengku Sembok Tengku Mohd
a Department of Optometry and Visual Science , Kulliyyah of Allied Health Sciences, International Islamic University Malaysia (IIUM) , Kuantan , Pahang , Malaysia.
b Department of Ophthalmology , Kulliyyah of Medicine, International Islamic University Malaysia (IIUM) , Kuantan , Pahang , Malaysia.
Curr Eye Res. 2017 Jun;42(6):852-856. doi: 10.1080/02713683.2016.1250277. Epub 2017 Jan 24.
The goal of this study was to predict visual acuity (VA) and contrast sensitivity function (CSF) with tissue redness grading after pterygium surgery.
A total of 67 primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The final outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 67 images, and its association with CSF and VA was examined.
The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra-grader and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p < 0.01) and VA (p < 0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA, respectively.
The new grading of pterygium fibrovascular redness can be reliably measured from digital images and showed a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.
本研究的目的是预测翼状胬肉手术后的视力（VA）和对比敏感度函数（CSF）与组织发红分级之间的关系。
从眼科门诊就诊的患者中选取67名原发性翼状胬肉参与者。我们开发了一个半自动计算机程序，用于从数字翼状胬肉图像中测量翼状胬肉纤维血管发红情况。该软件的最终结果是一个从1（最小发红）到3（最大发红）的连续量表分级。使用该软件手动选择感兴趣区域（ROI）。通过对所有67张图像进行重复分级来确定可靠性，并检查其与CSF和VA的相关性。
翼状胬肉纤维血管图像发红情况的平均值和标准差为1.88±0.55。分级者内和分级者间的可靠性估计值较高，组内相关系数范围为0.97至0.98。新的分级与CSF（p<0.01）和VA（p<0.01）呈正相关。发红分级能够分别预测CSF和VA中25%和23%的方差。
翼状胬肉纤维血管发红的新分级可以从数字图像中可靠地测量出来，并且与CSF和VA显示出良好的相关性。除了现有的翼状胬肉分级外，发红分级也可使用。
