Ras homolog family (Rho)/ Rho-associated coiled-coil kinase (ROCK) signaling pathway widely exists in human and mammal cells, which is closely related to inhibition of repair after optic nerve damage. The expression level of Rho/ROCK signaling pathway-related proteins is up-regulated in glaucoma, and related with the death of retinal ganglionic cell (RGC) and the axon activity. ROCK inhibitors can protect the surviving RGC and promote axon extension with a dose-dependent manner. ROCK inhibitors also can inhibit glial scar formation, lower intraocular pressure and inhibit inflammatory response to some degrees. Rho/ROCK signaling pathway correlates with the optic nerve disease progression, and ROCK inhibitors hope to become a new therapeutic drug.
Outer retinal tubulations (ORT) are tubular structures that are visualized on spectral domain optical coherence tomography in single B-scans as nonedematous circular or ovoid structures at the level of the outer nuclear layer. It is most commonly seen in exudative age-related macular degeneration and pseudoxanthoma elasticum, as well as in multifocal choroiditis, panuveitis, geographic atrophy, central serous chorioretinopathy, polypoid choroidal neovascularization, choroideremia and some other diseases related to outer retinal structural damage. ORT is the structure of dislocation junction of outer membrane and ellipsoid band in the process of self-repair after destroyed. Cystoid retinal edema, subretinal fluid and photoreceptor layer damage are important factors for ORT formation. Anti-vascular endothelial growth factor (VEGF) drugs cannot make ORT disappear, and distinguishing between ORT and retinal cystoid edema is helpful to avoid unnecessary anti-VEGF treatment. ORT has a certain predictive value for the prognosis of vision, and has guiding significance for clinical treatment. However, the mechanism of ORT formation and its relationship with clinical practice are not yet fully understood. More advanced imaging equipment and a large number of cases are needed to study the formation of ORT and its relationship with classical choroidal neovascularization, retinal fibrous scarring and retinal atrophy.
The prevention and treatment of retinopathy of prematurity (ROP) is an important strategic content of blindness prevention and treatment in China. Medical institutions including remote areas have strengthened the awareness of neonatal fundus screening, however, there are problems of vague screening standards, mainly manifested in expanding the scope of screening and even universal screening of newborns. At the same time, all kinds of fundus changes found in the examination cannot be correctly interpreted and handled, which increase the economic and psychological burden of children's families. In addition, with the wide application of intravitreal injection of anti-neovascular endothelial growth factor, problems such as improper grasp of indications and improper treatment of complications have become increasingly prominent. At this stage, it is urgent to strengthen the construction of ROP prevention and control network, which is suitable for China's national conditions, led by the government and coordinated participation of health and medical institutions at all levels.
ObjectiveTo assess changes of blood flow density of idiopathic choroidal neovascularization (ICNV) treated with intravitreal anti-vascular endothelial growth factor (anti-VEGF).MethodsRetrospective case analysis. Sixteen eyes of 16 patients with ICNV diagnosed with FFA and OCT were included in this study. Among them, 12 were female and 4 were male. The mean age was 33.94±9.83 years. The mean course of diseases was 5.13±4.44 weeks. The BCVA, indirect ophthalmoscope, OCT and OCT angiography (OCTA) were performed at the first diagnosis in all patients. The BCVA was converted to logMAR. The macular fovea retinal thickness (CMT) was measured by OCT, and the selected area of CNV (CSA) and flow area of CNV (CFA) were measured by OCTA. The mean logMAR BCVA, CMT, CSA and CFA were 0.336±0.163, 268.500±57.927 μm, 0.651±0.521 mm2, 0.327±0.278 mm2 , respectively. All patients were treated with intravitreal ranibizumab (IVR, 10 mg/ml, 0.05 ml). Follow-up results including the BCVA, fundus color photography, OCT and OCTA were obtained 1 month after treatment. To compare the changes of BCVA, CMT, CSA, CFA of ICNV treated with anti-VEGF. Pearson method was used to analyze the correlation between logMAR BCVA and CMT, CSA and CFA before and after the treatment.ResultsOne month after treatment, the average logMAR BCVA, CMT, CSA and CFA were 0.176±0.111, 232.500±18.910 μm, 0.420±0.439 mm2, 0.215±0.274 mm2. The mean logMAR BCVA (t=5.471, P＜0.001), CMT (t=2.527, P=0.023), CSA (t=4.039, P=0.001), CFA (t=4.214, P=0.001) significantly decreased at 1 month after injection compared to baseline, and the difference had statistical significance. The results of correlation analysis showed that the post-logMAR BCVA was moderately positively correlated with pre-CSA and post-CSA (r=0.553, 0.560; P=0.026, 0.024), and strongly correlated with pre-CFA and post-CFA (r=0.669, 0.606; P=0.005, 0.013), but not correlated with pre-CMT and post-CMT (r=0.553, 0.560; P=0.026, 0.024).ConclusionThe blood flow density of ICNV measured by OCTA were significantly decreased in the treatment of anti-VEGF drugs.
ObjectiveTo observe the imaging features of cystoid macular edema (CME) in multicolor imaging (MC), and to evaluate the value of MC in the diagnosis of CME.MethodsDescriptive case series study. From August 2017 to June 2018, 42 eyes of 37 patients with CME diagnosed in the people's Hospital of Wuhan University were included in the study. Among them, there were 24 males and 13 females, with an average age of 48.51±10.29 years. There were 14 eyes with diabetic retinopathy, 14 eyes with central retinal vein occlusion, 8 eyes with branch retinal vein occlusion, 4 eyes with uveitis, and 2 eyes with Eales disease. The macular color fundus photography (CFP) was performed with Visucam 200 non-mydriatic fundus camera of Zeiss company in Germany. MC, frequnce domainoptical OCT (SD-OCT) and FFA were examined by Spectralis HRA2 + OCT of Heidelberg company in Germany. According to the MC standard method, five images, including 488 nm blue reflection (BR), 515 nm green reflection (GR), 820 nm infrared reflection (IR) imaging and standard MC and blue-green enhancement (BG), were obtained at the same time. Compared with SD-OCT, CFP and MC images were scored. Friedman M test and Wilcoxon signed rank test were used for statistical analysis.ResultsThe standard MC and BG images showed blue-green uplift area or petal-shaped appearance, surrounded by green reflection areas with clear boundaries. BR image can be seen in the low reflexes area. On the GR image, there were patches or cystic low reflection areas, surrounded by a slightly high reflection. On the IR image, patches or cystoid high reflexes can be seen, surrounded by low reflection dark areas with clear boundaries. The average scores of CFP, standard MC, GB, IR, GR and BR were 1.20±0.94, 3.05±0.99, 2.90±1.04, 2.55±1.27, 2.00±0.94, 0.51±0.85 respectively, and the differences were statistically significant (χ2= 151.61, P=0.000). The score of CFP were significantly lower than that of standard MC (Z=－5.421), BG (Z=－5.354), IR (Z=－4.714), GR (Z=－4.438) and higher than that of BR (Z=－3.435). The differences were statistically significant (P=0.000, 0.000, 0.000, 0.000, 0.001).ConclusionsThe quality of MC imaging is better than that of CFP. Combined with SD-OCT, it can be used as an assistant method to diagnose CME.
ObjectiveTo observe and preliminarily discuss the distribution characteristics of the non-perfusion area (NP) of the retina in different stages of diabetic retinopathy (DR) and its changes with the progression of DR. MethodsA retrospective clinical study. From October 2018 to December 2020, 118 cases of 175 eyes of DR patients diagnosed in Eye Center of Renmin Hospital of Wuhan University were included in the study. Among them, there were 64 males with 93 eyes and 54 females with 82 eyes; the average age was 56.61±8.99 years old. There were 95 eyes of non-proliferative DR (NPDR), of which 25, 47, and 23 eyes were mild, moderate, and severe; 80 eyes were proliferative DR (PDR). Ultra-wide-angle fluorescein fundus angiography was performed with the British Optos 200Tx imaging system, and the fundus image was divided into posterior, middle, and distal parts with Image J software, and the ischemic index (ISI) was calculated. The difference of the retina in different DR staging groups and the difference of ISI were compared in the same area. The Kruskal-Wallis test was used to compare the ISI between the different DR staging groups and the Kruskal-Wallis one-way analysis of variance was used for the pairwise comparison between the groups. ResultsThe ISI of the posterior pole of the eyes in the moderate NPDR group, severe NPDR group, and PDR group were significantly greater than that in the distal periphery, and the difference was statistically significant (χ2=6.551, 3.540, 6.614; P=0.000, 0.002, 0.000). In severe NPDR group and PDR group, the ISI of the middle and peripheral parts of the eyes was significantly greater than that of the distal parts, and the difference was statistically significant (χ2=3.027, 3.429; P=0.015, 0.004). In the moderate NPDR group, there was no significant difference in ISI between the peripheral and distal parts of the eye (χ2=2.597, P=0.057). The ISI of the posterior pole of the eyes in the moderate NPDR group and the PDR group was significantly greater than that in the middle periphery, and the difference was statistically significant (χ2=3.955, 3.184; P=0.000, 0.009). In the severe NPDR group, there was no significant difference in ISI between the posterior pole and the middle periphery of the eye (χ2=0.514, P=1.000). Compared with the mild NPDR group and the moderate NPDR group, the ISI of the whole retina, posterior pole, middle and distal parts of the PDR group was larger, and the difference was statistically significant (χ2=－7.064, －6.349,－6.999, －5.869, －6.695, －6.723, －3.459, －4.098; P=0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 0.003, 0.000). ConclusionThe NP of the eyes with different DR stages is mainly distributed in the posterior pole and the middle periphery. The higher the severity of DR, the greater the NP in the posterior and middle periphery.
ObjectiveTo apply the multi-modal deep learning model to automatically classify the ultra-widefield fluorescein angiography (UWFA) images of diabetic retinopathy (DR). MethodsA retrospective study. From 2015 to 2020, 798 images of 297 DR patients with 399 eyes who were admitted to Eye Center of Renmin Hospital of Wuhan University and were examined by UWFA were used as the training set and test set of the model. Among them, 119, 171, and 109 eyes had no retinopathy, non-proliferative DR (NPDR), and proliferative DR (PDR), respectively. Localization and assessment of fluorescein leakage and non-perfusion regions in early and late orthotopic images of UWFA in DR-affected eyes by jointly optimizing CycleGAN and a convolutional neural network (CNN) classifier, an image-level supervised deep learning model. The abnormal images with lesions were converted into normal images with lesions removed using the improved CycleGAN, and the difference images containing the lesion areas were obtained; the difference images were classified by the CNN classifier to obtain the prediction results. A five-fold cross-test was used to evaluate the classification accuracy of the model. Quantitative analysis of the marker area displayed by the differential images was performed to observe the correlation between the ischemia index and leakage index and the severity of DR. ResultsThe generated fake normal image basically removed all the lesion areas while retaining the normal vascular structure; the difference images intuitively revealed the distribution of biomarkers; the heat icon showed the leakage area, and the location was basically the same as the lesion area in the original image. The results of the five-fold cross-check showed that the average classification accuracy of the model was 0.983. Further quantitative analysis of the marker area showed that the ischemia index and leakage index were significantly positively correlated with the severity of DR (β=6.088, 10.850; P＜0.001). ConclusionThe constructed multimodal joint optimization model can accurately classify NPDR and PDR and precisely locate potential biomarkers.
ObjectiveTo build a small-sample ultra-widefield fundus images (UWFI) multi-disease classification artificial intelligence model, and initially explore the ability of artificial intelligence to classify UWFI multi-disease tasks. MethodsA retrospective study. From 2016 to 2021, 1 608 images from 1 123 patients who attended the Eye Center of the Renmin Hospital of Wuhan University and underwent UWFI examination were used for UWFI multi-disease classification artificial intelligence model construction. Among them, 320, 330, 319, 268, and 371 images were used for diabetic retinopathy (DR), retinal vein occlusion (RVO), pathological myopia (PM), retinal detachment (RD), and normal fundus images, respectively. 135 images from 106 patients at the Tianjin Medical University Eye Hospital were used as the external test set. EfficientNet-B7 was selected as the backbone network for classification analysis of the included UWFI images. The performance of the UWFI multi-task classification model was assessed using the receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity, and accuracy. All data were expressed using numerical values and 95% confidence intervals (CI). The datasets were trained on the network models ResNet50 and ResNet101 and tested on an external test set to compare and observe the performance of EfficientNet with the 2 models mentioned above. ResultsThe overall classification accuracy of the UWFI multi-disease classification artificial intelligence model on the internal and external test sets was 92.57% (95%CI 91.13%-92.92%) and 88.89% (95%CI 88.11%-90.02%), respectively. These were 96.62% and 92.59% for normal fundus, 95.95% and 95.56% for DR, 96.62% and 98.52% for RVO, 98.65% and 97.04% for PM, and 97.30% and 94.07% for RD, respectively. The mean AUC on the internal and external test sets was 0.993 and 0.983, respectively, with 0.994 and 0.939 for normal fundus, 0.999 and 0.995 for DR, 0.985 and 1.000 for RVO, 0.991 and 0.993 for PM and 0.995 and 0.990 for RD, respectively. EfficientNet performed better than the ResNet50 and ResNet101 models on both the internal and external test sets. ConclusionThe preliminary UWFI multi-disease classification artificial intelligence model using small samples constructed in this study is able to achieve a high accuracy rate, and the model may have some value in assisting clinical screening and diagnosis.