ABSTRACT
AIM:To investigate the effect of 3% diquafosol sodium eye drops combined with intense pulsed light on the treatment of meibomian gland dysfunction and the change of meibomian glands.METHODS: Prospective study. A total of 141 patients(282 eyes)who were diagnosed with meibomian gland dysfunction from January 2021 to May 2022 in our hospital were selected and they were randomly divided into the control group(73 cases, 146 eyes)and the observation group(68 cases, 136 eyes)according to random number table. The control group was given 0.3% sodium hyaluronate eye drops combined with intense pulsed light, and the observation group was treated with 3% diquafosol sodium eye drops combined with intense pulsed light. The subjective symptom score, physical sign score, non-invasive tear break-up time, tear meniscus height, lipid layer thickness, and meibomian gland density before and after the treatment were compared between the two groups at 2wk after the end of treatment.RESULTS: There were no differences in the subjective symptom score, physical sign score, non-invasive tear break-up time, tear meniscus height, lipid layer thickness, and meibomian gland density between the two groups of patients before treatment(P>0.05). After 2wk of treatment, the symptom scores and physical sign scores of patients in the two groups continued to decrease, non-invasive tear break-up time and lipid layer thickness continued to increase, and the meibomian gland density also increased. The tear meniscus height in the observation group increased, while the control group showed no significant changes. The observation group had better clinical indicators than the control group(P<0.05). No obvious complications were observed in all patients.CONCLUSION: The combination of diquafosol sodium eye drops and intense pulsed light is synergistic in the treatment of meibomian gland dysfunction, with significant therapeutic effects and improvement of meibomian gland repair, which is significantly superior to simple intense pulsed light therapy.
ABSTRACT
@#AIM:To construct an artificial intelligence(AI)system based on convolutional neural network(CNN), which can automatically evaluate the morphological changes of meibomian gland(MG)in meibomian gland dysfunction(MGD)patients. <p>METHODS:The right eyes of 145 subjects who were treated at the Hangzhou Branch of the Eye Hospital of Wenzhou Medical University from January to November 2021 were selected for inclusion in the study. Meibography images of 60 of these subjects were randomly selected for AI training. The meibomian region and each MG in meibography were annotated and formed into datasets. The datasets were used for training and obtaining an AI system based on residual neural network(ResNet)combined with the U-Net model. The AI system was used to automatically analyze the MG morphological parameters in 85 subjects, including 53 patients with obstructive MGD and 32 volunteers with normal meibomian glands. The clinical indices including ocular surface disease index(OSDI), tear meniscus height, tear film break-up time(TBUT), corneal fluorescein staining, lid margin score, meiboscore, and meibomian gland expressibility score were also observed. The correlation between MG morphological parameters and clinical indices were analyzed.<p>RESULTS: After several iterations, we finally obtained an AI system with Intersection over Union of 92.0%. Using this AI system, we found that there was a significant correlation between the MG density in the upper eyelid with OSDI(<i>r</i><sub>s</sub>=-0.320), TBUT(<i>r</i><sub>s</sub>=0.484), lid margin score(<i>r</i><sub>s</sub>=-0.350), meiboscore(<i>r</i><sub>s</sub>=-0.749), and meibum expressibility score(<i>r</i><sub>s</sub>=0.425)(all <i>P</i><0.05). The MG density in the lower eyelid was significantly correlated with OSDI(<i>r</i><sub>s</sub>=-0.420), TBUT(<i>r</i><sub>s</sub>= 0.598), lid margin score(<i>r</i><sub>s</sub>=-0.396), meiboscore(<i>r</i><sub>s</sub>=-0.720), and meibum expressibility score(<i>r</i><sub>s</sub>=0.438)(all <i>P</i><0.05). The MG density in the total eyelid was significantly correlated with OSDI(<i>r</i><sub>s</sub>=-0.404), TBUT(<i>r</i><sub>s</sub>=0.601), lid margin score(<i>r</i><sub>s</sub>=-0.416), meiboscore(<i>r</i><sub>s</sub>=-0.805), and meibum expressibility score(<i>r</i><sub>s</sub>=0.480)(all <i>P</i><0.05).<p>CONCLUSION:The AI system based on CNN in this study is an accurate and efficient MG morphological evaluation system, which can be conveniently used to evaluate the MG morphology of MGD patients quickly and accurately by using the MG density index established by us. MG density is a new quantitative index to evaluate meibomian gland atrophy, which is more accurate than meiboscore.