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Aim To create and validate a prediction model for retinopathy of prematurity (ROP) reactivation after anti-VEGF therapy with clinical risk factors and retinal images. Methods Infants with TR-ROP undergoing anti-VEGF treatment were recruited from two hospitals, and three models were constructed using machine learning and deep learning algorithms. The areas under the curve (AUC), sensitivity (SEN) and specificity (SPC) were used to show the performances of the prediction models. Results Finally, we included 87 cases, including 21 with recurrent and 66 nonrecurrent cases. The AUC for the clinical risk factor model was 0.80 and 0.77 in the internal and external validation groups, respectively. The average AUC, sensitivity, and specificity in the internal validation for the retinal image model were 0.82, 0.93, and 0.63, respectively. The SPC, AUC, and SEN for the combined model were 0.73, 0.84, and 0.93, separately. Conclusion We constructed a prediction model for the reactivation of ROP. Using this prediction model, we can optimize strategies for treating TR-TOP infants and developing screening plans after treatment.

Background We aimed to validate the predictive performance of the DIGIROP-Birth model for identifying treatment-requiring retinopathy of prematurity (TR-ROP) in Chinese preterm infants to evaluate its generalizability across countries and races. Methods We retrospectively reviewed the medical records of preterm infants who were screened for retinopathy of prematurity (ROP) in a single Chinese hospital between June 2015 and August 2020. The predictive performance of the model for TR-ROP was assessed through the construction of a receiver-operating characteristic (ROC) curve and calculating the areas under the ROC curve (AUC), sensitivity, specificity, and positive and negative predictive values. Results Four hundred and forty-two infants (mean (SD) gestational age = 28.8 (1.3) weeks; mean (SD) birth weight = 1237.0 (236.9) g; 64.7% males) were included in the study. Analyses showed that the DIGIROP-Birth model demonstrated less satisfactory performance than previously reported in identifying infants with TR-ROP, with an area under the receiver-operating characteristic curve of 0.634 (95% confidence interval = 0.564–0.705). With a cutoff value of 0.0084, the DIGIROP-Birth model showed a sensitivity of 48/93 (51.6%), which increased to 89/93 (95.7%) after modification with the addition of postnatal risk factors. In infants with a gestational age Conclusions Although the predictive performance was less satisfactory in China than in developed countries, modification of the DIGIROP-Birth model with postnatal risk factors shows promise in improving its efficacy for TR-ROP. The model may also be effective in infants with a younger gestational age or with an extremely low birth weight.

An image-based deep learning model was developed to detect different morphological patterns of diabetic macular edema based on optical coherence tomography images with high accuracy and transparency. This model could help ophthalmologists to make personalized therapeutic strategies for patients with diabetic macular edema., Purpose: To develop a deep learning (DL) model to detect morphologic patterns of diabetic macular edema (DME) based on optical coherence tomography (OCT) images. Methods: In the training set, 12,365 OCT images were extracted from a public data set and an ophthalmic center. A total of 656 OCT images were extracted from another ophthalmic center for external validation. The presence or absence of three OCT patterns of DME, including diffused retinal thickening, cystoid macular edema, and serous retinal detachment, was labeled with 1 or 0, respectively. A DL model was trained to detect three OCT patterns of DME. The occlusion test was applied for the visualization of the DL model. Results: Applying 5-fold cross-validation method in internal validation, the area under the receiver operating characteristic curve for the detection of three OCT patterns (i.e., diffused retinal thickening, cystoid macular edema, and serous retinal detachment) was 0.971, 0.974, and 0.994, respectively, with an accuracy of 93.0%, 95.1%, and 98.8%, respectively, a sensitivity of 93.5%, 94.5%, and 96.7%, respectively, and a specificity of 92.3%, 95.6%, and 99.3%, respectively. In external validation, the area under the receiver operating characteristic curve was 0.970, 0.997, and 0.997, respectively, with an accuracy of 90.2%, 95.4%, and 95.9%, respectively, a sensitivity of 80.1%, 93.4%, and 94.9%, respectively, and a specificity of 97.6%, 97.2%, and 96.5%, respectively. The occlusion test showed that the DL model could successfully identify the pathologic regions most critical for detection. Conclusion: Our DL model demonstrated high accuracy and transparency in the detection of OCT patterns of DME. These results emphasized the potential of artificial intelligence in assisting clinical decision-making processes in patients with DME.

AIM: To evaluate the predicting efficacy of severe retinopathy of prematurity (ROP) by the WINROP algorithm (http://winrop.com) in Southern China. METHODS: All preterm infants with the gestational age (GA) less than 32wk were included. Their ROP screening results and serial postnatal body weight were analysed retrospectively. Weekly body weight was entered into and measured by the WINROP system. The outcomes were analysed, and the sensitivity, specificity, positive predictive value and negative predictive value (NPV) were calculated. RESULTS: Totally 432 infants with a median GA of 30.0 (24.0-31.9)wk, and a median birth weight (BW) of 1360 (540-2700) g were included. Among these 432 infants, 50 were diagnosed as type 1 ROP but only 28 were identified by the WINROP algorithm. The sensitivity was 56% (28/50) and the NPV was 92% (252/274). However, for infants with BW 28wk in China.

The vitreous substitute for proliferative vitreoretinopathy (PVR) surgery remains an unmet clinical need in ophthalmology. In our study, we developed an in situ formed hydrogel by crosslinking polyvinyl alcohol (PVA) and chitosan as a potential vitreous substitute. 5-fluorouracil (5-FU) Poly (lactic-co-glycolic acid) (PLGA) microspheres were developed and loaded onto the PVA/chitosan hydrogels to treat PVR. In vitro, PVA/chitosan hydrogels at four concentrations were subjected to morphological, physical, rheological analyses, and cytotoxicity was evaluated together with the characterization of 5-FU PLGA microspheres. In vivo, pharmacologically induce PVR rabbits were performed a vitrectomy. In the PVA group, 3% PVA/chitosan hydrogel was injected into the vitreous cavity. In the PVA/MS group, 3% PVA/chitosan hydrogel and 5-FU PLGA microspheres were injected. In the Control group, phosphate-buffered saline was injected. Therapeutic efficacy was evaluated with postoperative examinations and histological analyses. This study demonstrated that the 3% PVA/chitosan hydrogel showed properties similar to those of the human vitreous and could be a novel in situ crosslinked vitreous substitute for PVR. Loading 5-FU PLGA microspheres onto this hydrogel may represent an effective strategy to improve the prognosis of PVR.

Dry eye disease (DED), a multifactorial ocular surface disorder affecting millions of individuals worldwide, is characterized by inflammation and damage to the ocular surface. It is unclear whether corneal autophagy participates in ocular surface inflammation observed in DED. To test this involvement, dry eye (DE) was induced in female C57BL/6 mice housed in a controlled environment by subcutaneous injection of scopolamine. Expression of the autophagy-related proteins LC3B and ATG5 and activation of autophagy were detected in the corneas of these mice. Treatment with LYN-1604, an activator of autophagy, alleviated the clinical indications in DE mice, including tear production and corneal fluorescence staining. LYN-1604 also reduced the corneal levels of inflammatory response products, including tumor necrosis factor alpha (TNF-α) and matrix metalloproteinases-3 and -9. By contrast, treatment of DE mice with the autophagy inhibitor 3-MA, exacerbated the clinical indications of DE and increased the levels of inflammatory response products. This is the first study to show that autophagy could regulate the level of ocular surface inflammation, suggesting that agents that regulate autophagy could relieve ocular surface inflammation and treat DED.

The maturation state of dendritic cell (DC) plays an important role in immune activities. Previously we had found that NF-κB (p65) pathway could promote DC maturation and subsequent immune effects. But the upstream mechanism of this pathway was still unclear. Extracellular adenosine triphosphate (ATP) activating its receptor P2X7R has recently been considered as the fourth signal to activate T lymphocytes. Here we aimed to find out the connection between P2X7R and NF-κB (p65) pathway in DC maturation. Results showed that the expression of P2X7R and the intracellular ATP levels were increased along with the maturation of DC. P2X7R agonist stimulated the morphological changes of DCs into the appearance of mature DCs, and promoted the expression of NF-κB (p65), as well as the release of IFN-γ and IL-12. Whereas, P2X7R inhibitor had the opposite influences. Co-immunoprecipitation assay confirmed the binding of P2X7R and NF-κB (p65). Our study suggested that extracellular ATP could promote DC maturation and release of inflammatory cytokines through the binding of P2X7R and NF-κB (p65). This is the first study to show the P2X7R-NF-κB (p65) pathway in DC. Interference with this pathway may be able to regulate immune responses in areas like infectious diseases, inflammation, transplantation, tumor and autoimmune diseases. In addition, intracellular ATP level could be a new indicator of the maturation state of DC.

Background To develop a machine learning (ML) model for the prediction of the idiopathic macular hole (IMH) status at 1 month after vitrectomy and internal limiting membrane peeling (VILMP) surgery. Methods A total of 288 IMH eyes from four ophthalmic centers were enrolled. All eyes underwent optical coherence tomography (OCT) examinations upon admission and one month after VILMP. First, 1,792 preoperative macular OCT parameters and 768 clinical variables of 256 eyes from two ophthalmic centers were used to train and internally validate ML models. Second, 224 preoperative macular OCT parameters and 96 clinical variables of 32 eyes from the other two centers were utilized for external validation. To fulfill the purpose of predicting postoperative IMH status (i.e., closed or open), five ML algorithms were trained and internally validated by the ten-fold cross-validation method, while the best-performing algorithm was further tested by an external validation set. Results In the internal validation, the mean area under the receiver operating characteristic curves (AUCs) of the five ML algorithms were 0.882-0.951. The AUC, accuracy, sensitivity, and specificity of the best-performing algorithm (i.e., random forest, RF) were 0.951, 0.892, 0.973, and 0.904, respectively. In the external validation, the AUC of RF was 0.940, with an accuracy of 0.875, a specificity of 0.875, and a sensitivity of 0.958. Conclusions Based on the preoperative OCT parameters and clinical variables, our ML model achieved remarkable accuracy in predicting IMH status after VILMP. Therefore, ML models may help optimize surgical planning for IMH patients in the future.

Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Prediction of ROP before onset holds great promise for reducing the risk of blindness.To develop and validate a deep learning (DL) system to predict the occurrence and severity of ROP before 45 weeks' postmenstrual age.This retrospective prognostic study included 7033 retinal photographs of 725 infants in the training set and 763 retinal photographs of 90 infants in the external validation set, along with 46 characteristics for each infant. All images of both eyes from the same infant taken at the first screening were labeled according to the final diagnosis made between the first screening and 45 weeks' postmenstrual age. The DL system was developed using retinal photographs from the first ROP screening and clinical characteristics before or at the first screening in infants born between June 3, 2017, and August 28, 2019.Two models were specifically designed for predictions of the occurrence (occurrence network [OC-Net]) and severity (severity network [SE-Net]) of ROP. Five-fold cross-validation was applied for internal validation.Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity to evaluate the performance in ROP prediction.This study included 815 infants (450 [55.2%] boys) with mean birth weight of 1.91 kg (95% CI, 1.87-1.95 kg) and mean gestational age of 33.1 weeks (95% CI, 32.9-33.3 weeks). In internal validation, mean AUC, accuracy, sensitivity, and specificity were 0.90 (95% CI, 0.88-0.92), 52.8% (95% CI, 49.2%-56.4%), 100% (95% CI, 97.4%-100%), and 37.8% (95% CI, 33.7%-42.1%), respectively, for OC-Net to predict ROP occurrence and 0.87 (95% CI, 0.82-0.91), 68.0% (95% CI, 61.2%-74.8%), 100% (95% CI, 93.2%-100%), and 46.6% (95% CI, 37.3%-56.0%), respectively, for SE-Net to predict severe ROP. In external validation, the AUC, accuracy, sensitivity, and specificity were 0.94, 33.3%, 100%, and 7.5%, respectively, for OC-Net, and 0.88, 56.0%, 100%, and 35.3%, respectively, for SE-Net.In this study, the DL system achieved promising accuracy in ROP prediction. This DL system is potentially useful in identifying infants with high risk of developing ROP.

Recurrent epithelial erosion and refractory corneal ulcer are the clinical features of diabetic keratopathy (DK), which eventually lead to corneal scar and visual disturbance. In this study, we sought to determine the abnormalities of cell junction in diabetic corneal epithelial cells and the effect of high glucose on the β-catenin/E-cadherin complex. Corneal histology showed that corneal epithelial cells of high glucose mice were loosely arranged, and the immunohistochemistry showed that the expression of E-cadherin decreased, the levels of β-catenin increased in nuclear. High glucose-induced degradation and endocytosis of E-cadherin of corneal epithelial cells reduce the formation of β-catenin/E-cadherin complex and promote the nuclear translocation of β-catenin. Moreover, high glucose also activated the transcription and expression of matrix metallopeptidase and snail, which interfered with the adhesion of corneal epithelial cells to the basement membrane. These findings reveal that DK is associated with the dissociation of cell junctions. The maintenance of the stability of the β-catenin/E-cadherin complex may be a potential therapeutic target of refractory corneal ulcers in patients with diabetes.

AimsTo develop a deep learning (DL) model for automatic classification of macular hole (MH) aetiology (idiopathic or secondary), and a multimodal deep fusion network (MDFN) model for reliable prediction of MH status (closed or open) at 1 month after vitrectomy and internal limiting membrane peeling (VILMP).MethodsIn this multicentre retrospective cohort study, a total of 330 MH eyes with 1082 optical coherence tomography (OCT) images and 3300 clinical data enrolled from four ophthalmic centres were used to train, validate and externally test the DL and MDFN models. 266 eyes from three centres were randomly split by eye-level into a training set (80%) and a validation set (20%). In the external testing dataset, 64 eyes were included from the remaining centre. All eyes underwent macular OCT scanning at baseline and 1 month after VILMP. The area under the receiver operated characteristic curve (AUC), accuracy, specificity and sensitivity were used to evaluate the performance of the models.ResultsIn the external testing set, the AUC, accuracy, specificity and sensitivity of the MH aetiology classification model were 0.965, 0.950, 0.870 and 0.938, respectively; the AUC, accuracy, specificity and sensitivity of the postoperative MH status prediction model were 0.904, 0.825, 0.977 and 0.766, respectively; the AUC, accuracy, specificity and sensitivity of the postoperative idiopathic MH status prediction model were 0.947, 0.875, 0.815 and 0.979, respectively.ConclusionOur DL-based models can accurately classify the MH aetiology and predict the MH status after VILMP. These models would help ophthalmologists in diagnosis and surgical planning of MH.

Background To develop a deep learning (DL) model for prediction of idiopathic macular hole (MH) status after vitrectomy and internal limiting membrane peeling (VILMP) based on optical coherence tomography (OCT) images from four ophthalmic centers. Methods Eyes followed up at 1 month after VILMP for full-thickness MH were included. In the internal training set, 920 preoperative macular OCT images (as the input) and post-operative status of MH (closed or open, as the output) of 256 eyes from two ophthalmic centers were used to train the DL model using VGG16 algorithm. In the external validation set, 72 preoperative macular OCT images of 36 MH eyes treated by VILMP from another two ophthalmic centers were used to validate the prediction accuracy of the DL model. Results In internal training, the mean of overall accuracy for prediction of MH status after VILMP was 84.6% with a mean area under the receiver operating characteristic (ROC) curve (AUC) of 91.04% (sensitivity 85.37% and specificity 81.99%). In external validation, the overall accuracy of predicting MH status after VILMP was 84.7% with an AUC of 89.32% (sensitivity 83.33% and specificity 87.50%). The heatmaps showed that the area critical for prediction was at the central macula, mainly at the MH and its adjacent retina. Conclusions The DL model trained by preoperative macular OCT images can be used to predict postoperative MH status after VILMP. The prediction accuracy of our DL model has been validated by multiple ophthalmic centers.

BACKGROUND: This study aimed to predict the treatment outcomes in patients with diabetic macular edema (DME) after 3 monthly anti-vascular endothelial growth factor (VEGF) injections using machine learning (ML) based on pretreatment optical coherence tomography (OCT) images and clinical variables. METHODS: An ensemble ML system consisting of four deep learning (DL) models and five classical machine learning (CML) models was developed to predict the posttreatment central foveal thickness (CFT) and the best-corrected visual acuity (BCVA). A total of 363 OCT images and 7,587 clinical data records from 363 eyes were included in the training set (304 eyes) and external validation set (59 eyes). The DL models were trained using the OCT images, and the CML models were trained using the OCT images features and clinical variables. The predictive posttreatment CFT and BCVA values were compared with true outcomes obtained from the medical records. RESULTS: For CFT prediction, the mean absolute error (MAE), root mean square error (RMSE), and R(2) of the best-performing model in the training set was 66.59, 93.73, and 0.71, respectively, with an area under receiver operating characteristic curve (AUC) of 0.90 for distinguishing the eyes with good anatomical response. The MAE, RMSE, and R(2) was 68.08, 97.63, and 0.74, respectively, with an AUC of 0.94 in the external validation set. For BCVA prediction, the MAE, RMSE, and R(2) of the best-performing model in the training set was 0.19, 0.29, and 0.60, respectively, with an AUC of 0.80 for distinguishing eyes with a good functional response. The external validation achieved a MAE, RMSE, and R(2) of 0.13, 0.20, and 0.68, respectively, with an AUC of 0.81. CONCLUSIONS: Our ensemble ML system accurately predicted posttreatment CFT and BCVA after anti-VEGF injections in DME patients, and can be used to prospectively assess the efficacy of anti-VEGF therapy in DME patients.

Diabetic retinopathy is the leading cause of blindness in working age individuals in developed countries. However, the role of inflammation in the pathogenesis of DR is not completely understood. This is an observational clinical research enrolling 80 type II diabetic patients who had undergone cataract surgeries either with DR or without DR. All cases were further categorized by the proliferative stages of retinal neovascularization and by the lengths of diabetic history. The levels of inflammatory cytokines including IL-1β, IL-6, IL-8, IL-17, and TNF-α in aqueous humour were tested. Results in this study indicated that these cytokine levels were increased in DR patients and might have a synergistic effect on the pathogenesis of this disease. They were also elevated along with the progression of neovascularization, reflecting the severity of DR. The results also suggested that for diabetic patients, the higher these levels are, the sooner retinal complications might appear. In conclusion, the levels of inflammatory cytokines IL-1β, IL-6, IL-8, IL-17A, and TNF-α in aqueous humour may be associated with the pathogenesis, severity, and prognosis of DR.

Polyethylene glycol (PEG) is a short-term (41 days) potential vitreous substitute and is too short for an ideal vitreous substitute. Previously, a foldable capsular vitreous body (FCVB) was designed to mimic vitreous function. The aim of this study is to evaluate whether PEG injected into FCVB can serve as a long-term vitreous substitute. In vitro study, a concentration of 5% (w/v) PEG sols showed natural-like mechanical and optical properties in terms of pH, density, light transmittance, refractive index, interfacial tension, viscosity, rheology, and cytotoxicity. Then in vivo tests, 30 rabbits received standard pars plana vitrectomy, of which 12 eyes were implanted with PEG injected into FCVB, nine eyes were injected with PEG sols alone, and nine others were injected with balance salt solution as control. A clinical evaluation of the anterior segment, fundus, and intraocular pressure was measured pre- and postoperatively up to 180 days, which showed that FCVBs had good retina supporting function, except for a higher incidence of cataracts. Gross pathology, hematoxylin and eosin, and terminal deoxynucleotidyl transferase dUTP nick end labeling staining analysis also showed that FCVBs had good biocompatibility, and that all quadrants of the capsular wall fitted well with the retina. This study demonstrated that PEG injected into FCVB can serve as a long-term vitreous substitute and has potential clinical use.

RelA, the most important regulator of NF-kB activity, and its mechanisms in keratoplasty immune rejection have not been fully investigated. In the present study, lentivirus-mediated silencing of RelA expression in a bone marrow-derived dendritic cell (BMDC) model was tested. The BMDCs were transfected with RelA-shRNA to induce an immature, maturation-resistant and tolerogenic phenotype, while not significantly changing IFN-γ, IL-10 and IL-17 expression. A fully allogeneic rat cornea transplant model was established for in vivo studies. The allograft mean survival time (MST) of lv-shRelA-DC injection groups were significantly longer than the untreated BMDC group and control group. The corneal opacity and neovascularization scale of the lv-shRelA-DC injection groups were slight compared to pair control others. Postoperative flow cytometric analysis revealed that the percentage of Treg positive cells was dramatically increased in animals that received an lv-shRelA-DC injection. ELISA and qRT-PCR analyses of serum showed that IFN-γ and IL-17 expression were suppressed by lv-shRelA-DC treatement. In vivo experiments demonstrated that IL-10 induced immunosuppression was partly attributed to injection of lv-shRelA-DC throughout the experiment, differing from the general anti-inflammatory factors. Luciferase and Chromatin IP evaluation showed that RelA knockdown in BMDCs significantly reduces DNA binding to IFN-γ, IL-10 and the IL-17 promoter and inhibited of transcriptional activity. Taken together, this study illustrates a significant role of RelA in mediating the corneal neovascularization by affecting IL-17 expression. Our comprehensive analysis shows that the significant role of RelA provides a novel and feasible therapeutic approach for the prevention of corneal allograft rejection.

To evaluate the effect of the TLR2 (Toll-like receptor 2)/MyD88/NF-κB axis on the allograft rejection after penetrating keratoplasty (PK).The PK rat models were randomly divided into four groups: allograft group, dexamethasone group, PDTC group and isograft group. The mean survival time (MST) and rejection index of corneal grafts were observed. The immunohistochemical staining of TGF-α was performed on day 15. The messenger RNA (mRNA) and protein expression of TLR2, MyD88 and NF-κB p65 in corneal grafts were detected by reverse transcription-polymerase chain reaction (RT-PCR) and western blotting.On days 5, 7, 9, 11, 13 and 15, the rejection index in the allograft group was higher than in the other three groups (p 0.05). The MST in the PDTC group (MST, 23.30 ± 0.42 days, n = 10) and in the dexamethasone group (MST, 24.40 ± 0.50 days, n = 10) were higher than in the allograft group (MST, 14.7 ± 0.70 days, n = 10) (χ(2) = 18.02, p 0.01; χ(2) = 21.47, p 0.01). The expression of TNF-α in the PDTC group and in the dexamethasone group decreased compared with the allograft group by immunohistochemistry. On day 15, the mRNA and protein expression of TLR2, MyD88 and NF-κB p65 in the PDTC group and the dexamethasone group were less than in the allograft group (p 0.05).Expression of TLR2, MyD88 and NF-κB p65 in rat corneal graft increased significantly and concurred with the allograft rejection, but were effectively inhibited by the treatment with dexamethasone and PDTC after PK. Dexamethasone could improve corneal allograft survival by the TLR2/MyD88/NF-κB axis. PDTC could suppress corneal graft rejection by inhibiting the activity of NF-κB. The TLR2/MyD88/NF-κB axis maybe a potential therapeutic target for corneal allograft rejection.

Hydrogels may be the ideal vitreous substitutes due to their wonderful physical features and biocompatibility. However, their drawbacks, short residence time, and biodegradation in vivo, have led to the fact that none of them have been approved for clinical use. In this study, we developed a novel approach of using a foldable capsular vitreous body (FCVB) injected with polyvinylalcohol (PVA) hydrogel as a vitreous substitute for long-term tamponade. The 3% PVA hydrogel that was cross-linked by gamma irradiation showed good rheological and physical properties and had no toxicity in vitro. After 180 days retention, the 3% PVA hydrogel inside FCVB remained transparent and showed good viscoelasticity without biodegradation and showed good biocompatibility and retina support. This new approach may develop into a valuable tool to improve the stability performance of PVA hydrogel as a vitreous substitute and to extend the application function of FCVB for long-term implantation in vitreous cavity.

Polyethylene glycol (PEG) is a short-term (41 days) potential vitreous substitute and is too short for an ideal vitreous substitute. Previously, a foldable capsular vitreous body (FCVB) was designed to mimic vitreous function. The aim of this study is to evaluate whether PEG injected into FCVB can serve as a long-term vitreous substitute. In vitro study, a concentration of 5% (w/v) PEG sols showed natural-like mechanical and optical properties in terms of pH, density, light transmittance, refractive index, interfacial tension, viscosity, rheology, and cytotoxicity. Then in vivo tests, 30 rabbits received standard pars plana vitrectomy, of which 12 eyes were implanted with PEG injected into FCVB, nine eyes were injected with PEG sols alone, and nine others were injected with balance salt solution as control. A clinical evaluation of the anterior segment, fundus, and intraocular pressure was measured pre- and postoperatively up to 180 days, which showed that FCVBs had good retina supporting function, except for a higher incidence of cataracts. Gross pathology, hematoxylin and eosin, and terminal deoxynucleotidyl transferase dUTP nick end labeling staining analysis also showed that FCVBs had good biocompatibility, and that all quadrants of the capsular wall fitted well with the retina. This study demonstrated that PEG injected into FCVB can serve as a long-term vitreous substitute and has potential clinical use.