The choroidal vascular index (CVI) is the ratio of the luminal area to the total choroidal area. It can not only reflect the changes in the vascular composition of the choroid, but also serve as an observation index for follow-up treatment effects. CVI is a new biometric tool, which is gradually applied to the observation of choroidal structure in various eye diseases. It has great application prospects in the study of pathophysiological mechanisms, disease process monitoring and efficacy evaluation such as central serous chorioretinopathy, polypoid choroidal vascular disease, age-related macular degeneration, diabetic retinopathy,etc. Understanding the research progress of CVI in various eye diseases can provide reference for clinical research of CVI.

Retinal vasoproliferative tumor (RVPT) is a rare benign glial proliferative tumor of unknown origin.The fundus is typically characterized by yellow or pink tumor-like lesions of the retina around the inferior temporal region, often accompanied by subretinal fluid, exudation, epiretinal membrane and other complications.Typical RVPT showed high fluorescence on fundus fluorescein angiography, diffuse leakage in venous phase and late stage, uneven middle or high reflection signal on B-ultrasound, and it was not difficult to diagnose combined with fundus changes.Atypical RVPT should be differentiated from retinal capillary hemangioma caused by von Hippel-Lindau disease, Coats disease and familial exudative vitreoretinopathy.The pathogenesis of RVPT is unclear, but histopathology shows that it may be the reactive proliferation of glial cells.At present, there is no unified treatment plan for RVPT, mainly cryotherapy, laser photocoagulation, local radiotherapy, transpupillary thermal therapy or photodynamic therapy for tumor.For patients with vitreous hemorrhage, vitreoretinal surgery is feasible.This article reviewed the clinical features, diagnosis and differential diagnosis, pathology and pathogenesis, and treatment progress of RVPT.

Objective:To 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.Methods:A 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.Results:The 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 ( χ 2=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 ( χ 2=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 ( χ 2=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 ( χ 2=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 ( χ 2=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 ( χ 2=-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). Conclusion:The 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.

Objective:To quantitatively evaluate the retinal ischemia in different retinal regions of diabetic retinopathy (DR) patients in ultra-widefield fluorescein fundus angiography (UWFA) images with ischemic index (ISI), and to explore its correlation with diabetic macular edema (DME).Methods:A cross-sectional study was conducted.Seventy-nine eyes of 79 patients with DR were enrolled in Renmin Hospital of Wuhan University from September 2017 to October 2020, including 44 males (44 eyes) and 35 females (35 eyes) aged 31 to 73 years old, with an average age of (55.95±8.80) years.UWFA and spectral-domain optical coherence tomography (SD-OCT) were performed in all patients.Patients were divided into DME group (37 eyes) and non-DME group (42 eyes) according to the presence or absence of DME in OCT images.The retina in middle phase UWFA images were divided into posterior, middle peripheral and far peripheral regions by ImageJ software, and ISI in each region was calculated.Central macular thickness (CMT) was automatically calculated using the built-in software of the OCT equipment.The correlation between ISI and CMT was analyzed by Spearman rank correlation analysis.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY2019-K037). Written informed consent was obtained from each patient prior to any medical examination.Results:The ISI of the total, posterior, middle peripheral and far peripheral retina was 2.460 (0.603, 5.640)%, 2.670 (1.062, 9.574)%, 1.382 (0.245, 4.378)% and 0.000 (0.000, 1.262)%, respectively, with a statistically significant difference among different regions ( χ2=65.307, P<0.001). There were statistically significant differences in ISI between the total and far peripheral, the posterior and middle peripheral, the posterior and far peripheral, the middle and far peripheral (all at P<0.01). ISI of the total, posterior and middle peripheral retina in DME group were significantly higher than those in non-DME group ( U=424.000, P=0.001; U=403.000, P<0.001, U=493.000, P=0.005), but there was no significant difference in the ISI of the far peripheral region between the two groups ( U=609.000, P=0.061). There was no statistically significant correlation between ISI and CMT in the total, posterior, middle peripheral and far peripheral retina in DME group ( rs=-0.134, -0.018, -0.152, -0.163; all at P>0.05). Conclusions:The retinal non-perfusion area in DR eyes is mainly located in the posterior and middle peripheral retina.The ISI of the posterior and middle peripheral retina in DME eyes is significantly higher than that in eyes without DME.ISI of each retinal region may not be related to the severity of DME.

Objective:To observe the choroidal vascular changes of chronic central serous chorioretinopathy (cCSC), and analyze their correlations with central macular thickness (CMT).Methods:A cross-sectional study was adopted.Seventy-six eyes of 38 patients with monocular cCSC who were treated in Renmin Hospital of Wuhan University from March 2018 to December 2019 were enrolled, and 30 eyes of 30 normal control matched with age, gender, and spherical equivalent (SE) were included.Choroidal images of all subjects, and the CMT, subfoveal choroidal thickness (SFCT), choroidal vascularity index (CVI), total choroidal area (TCA), choroidal stromal area (SA), and choroidal luminal area (LA) were measured by Heidelberg enhanced depth imaging optical coherence tomography.The differences in SFCT, LA, SA, TCA, CMT and CVI between the cCSC eye, fellow eye and normal eye, as well as the correlation between SFCT and CVI, SFCT and CMT, and CVI and CMT were analyzed.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY2020-K234).Results:The CVI and the SFCT of the cCSC eyes, fellow eyes and normal eyes were (71.67±5.60)% and 483.82(409.01, 550.87)μm, (68.33±3.85)% and 444.66(351.25, 505.15)μm, (64.70±1.88)% and 373.46(327.98, 405.48)μm, respectively.The CMT, SFCT, TCA, LA, CVI in cCSC eyes were significantly higher than those in the contralateral eyes and normal control eyes, while SFCT, TCA, LA, CVI in the contralateral eyes were higher than those in normal control eyes (all at P<0.05). Pairwise comparison among the three groups showed no significant difference in SA (all at P>0.05). Correlation analysis showed that in cCSC eyes, SFCT was strongly positively correlated with CVI ( rs=0.703, P<0.001), and there was no correlation between CMT and SFCT ( rs=0.181, P=0.278), or CMT and CVI ( r=0.231, P=0.164). Conclusions:The SFCT and CVI are higher in cCSC and the fellow eyes compared with normal eyes, and the choroidal vessels are significantly dilated in cCSC patients.The SFCT and CVI of the cCSC eye are slightly higher in comparison with the fellow eye.CMT is not correlated with SFCT or CVI in cCSC eyes.

Objective:To 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.Methods:A 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. Results:The 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. Conclusion:The 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.

Liver ischemia-reperfusion injury (IRI) is a major complication of hemorrhagic shock, liver transplantation, and other liver surgeries. It’s important to study the targets towards liver IRI for preventing and mitigating the clinical renal injury. It has been reported that the peroxisome proliferator activated receptor gamma (PPARγ) protects the liver against IRI by targeting family with sequence similarity 3 member A (FAM3A). At the meantime, noncoding RNAs, including lncRNAs and miRNAs, have also been reported to play important roles on the process of hepatic IRI. This review briefly discussed the roles and mechanisms of PPARγ, FAM3A and noncoding RNAs in liver IRI, to find potential targets of gene therapy, aiming to prevent and mitigate the liver IRI as well as to improve postoperative liver function.