ObjectiveTo observe the positional relationship between the central fixation point of the retina and the fovea in normal adults.MethodsA retrospective clinical study. From August 2019 to January 2020, 100 eyes of 100 normal adults who underwent physical examination at the Fourth People's Hospital of Shenyang were included in the study. All patients underwent BCVA, diopter, microfield, OCT examination, and axial length (AL) measurement. There were 42 males and 58 females with the average age was 46.4±14.7 years. The average diopter was －1.02±1.99 D, the average AL was 23.22±0.47 mm, the average foveal avascular zone (FAZ) area was 0.38±0.13 mm2. The MP-3 microperimetry was used for central fixation examination. After the examination, high-definition fundus images were automatically taken and the central fixation point of the retina were automatically calculated by the equipment. The Nidek Overlay functional multi-mode imaging platform was used to superimpose the images containing the central fixation point of the retina and the macular fovea, the positional relationship between the two was observed, and the distance between the two was measured. Pearson correlation analysis was performed on the distance between the fixation point of the center of the retina and the center of the fovea, age, diopter, and FAZ area of the macula.ResultsThe fixation point of the retinal center of all tested eyes was within the range of the macular fovea, which did not coincide with the center of the macular fovea. Among 100 eyes, the fixation point of the center of the retina were 53, 23, 15, and 9 eyes at the nose, lower, temporal, and upper sides, respectively. The average distance between the fixation point of the center of the retina and the center of the fovea was 158.31±71.56 μm. The distance between the fixation point of the retinal center and the center of the macular fovea and age (r=0.140), diopter (r=－0.009), FAZ area ( r=0.038) were not correlated (P=0.165, 0.932, 0.707) in correlation analysis.ConclusionThe central fixation point of normal adult retina is more common on the fovea nasal side.
ObjectiveTo observe the changes of visual acuity and fixation properties of eyes with idiopathic macular hole (IMH) before and after surgery. MethodsA prospective clinical study. From September 2019 to December 2020, 25 patients with 25 eyes of IMH diagnosed in Department of Ophthalmology of The Fourth People's Hospital of Shenyang were included in the study. All patients underwent pars plana vitrectomy (PPV) combined with internal limiting membrane stripping. All eyes underwent best corrected visual acuity (BCVA), optical coherence tomography (OCT), and microperimetry before and after surgery. The BCVA examination was carried out using the Snellen visual acuity chart, which was converted into logarithmic minimum resolution angle (logMAR) visual acuity during statistics. The 12° macular sensitivity (MS) and bivariate contour ellipse area (BCEA) were measured by MP-3 microperimetry. The minimum diameter (MIN) and base diameter (BASE) of the macular hole were measured by OCT; the distance between the preferred retinal location (PRL) and the center of the fovea was measured by Image-proplus 6.0 image processing software. At 1 and 3 months follow-up after surgery, the same equipment and methods as before surgery were used to conduct related examinations. The changes of BCVA, PRL distance from the fovea, MS, BCEA, and macular hole shape before and after surgery were compared and observed. One-way analysis of variance was used to compare the indicators before and after surgery. Pearson correlation analysis was used for the correlation between BCVA and preoperative BCVA, PRL and foveal center distance at 3 months after surgery. The correlation between MIN, BCVA, PRL and foveal center before surgery distance, MS, BCEA and BCVA at 3 months after surgery were analyzed by multiple linear regression. ResultsAmong 25 eyes of 25 cases, 1 male had 1 eye, and 24 females had 24 eyes. The macular hole in stage Ⅲ and Ⅳ were 11 eyes and 14 eyes, respectively. MIN and BASE were 537.68±200.09 and 905.48±278.79 μm, respectively. One month after surgery, the hiatus was closed. Before surgery and 1 and 3 months after surgery, the logMAR BCVA of the affected eyes were 0.80±0.17, 0.70±0.21, 0.60±0.25, and the MS were 22.20±3.86, 23.60±3.14, 24.38±2.68 dB, the distances between PRL and the center of the fovea were 537.72±426.05, 402.00±395.06, 236.80±219.54 μm, and BCEA were 7.90±3.43, 6.40±2.67, 4.80±2.32 deg2. Compared with before operation, BCVA (F=7.047, 20.104) and MS (F=1.980, 5.390) were significantly improved at different time after operation, the distance between PRL and fovea center (F=1.265, 9.530), BCEA (F=2.762, 13.617) were decreased, the difference were statistically significant (P＜0.05). The results of correlation analysis showed that BCVA at 3 months after surgery was significantly associated with preoperative MIN (r=0.810), BASE (r=0.664), BCVA before surgery and 1 month after surgery (r=0.854, 0.940), preoperative and surgical MS at 1 month after surgery (r=－0.548, －0.578), distance between PRL and foveal center before surgery and at 1 month after surgery (r=0.833, 0.915), BCEA before surgery and at 1 month after surgery (r=0.636, 0.732) were significantly correlated (P＜0.05). The results of multiple linear regression analysis showed that the distance between PRL and foveal center before surgery and BCVA were risk factors for poor prognosis of BCVA at 3 months after surgery. ConclusionsThe BCVA and MS of eyes with IMH are significantly improved after surgery, and the distance between PRL and foveal center and BCEA decreased. BCVA, PRL and foveal center distance before surgery are risk factors for poor visual acuity after surgery.
ObjectivesTo evaluate and preliminarily analyze the application value and efficacy of artificial intelligence optical coherence tomography (AI-OCT) technology in the early screening of retinal diseases among the elderly, hypertension, hyperglycemia, high myopia and hyperlipidemia (referred to as "Five-High") population. Methods A diagnostic trial was conducted. A total of 3 834 patients (7 668 eyes) with "Five-High" risk factors who visited the outpatient clinics of Shenyang Fourth People’s Hospital from July to December 2024 were included. Optical coherence tomography imaging of the macular and peripheral retina was performed using the Bigway AI-OCT image analysis system (wide-field three-dimensional scanning mode). The deep learning-based system automatically identified and labeled eight types of high-risk retinal lesions: subretinal fluid (SRF), intraretinal fluid (IRF), epiretinal membrane (ERM), choroidal neovascularization (CNV), hyper-reflective foci (HRF), retinal pigment epithelium detachment, retinal hemorrhage, and macular hole (MH). The positive rate of AI-OCT screening and the distribution of high-risk lesions were analyzed. Consistency between AI-OCT screening results and ophthalmologist review was assessed using Cohen’s Kappa test. Logistic regression was used to identify independent predictors of positive AI-OCT screening. Referral and treatment rates were also analyzed. ResultsAmong 3 834 cases involving 7 668 eyes, 803 cases (1 606 eyes) were positive in AI-OCT screening, with a positive rate of 20.9% (803/3 834), including 266 high-risk and 537 non-high-risk patients, respectively. The positive screening rates of patients with "Five Highs" were as follows: hyperlipidemia 25.2% (185/735), advanced age 24.9% (746/1 998), hyperglycemia 24.8% (345/1 392), hypertension 23.8% (228/956), and high myopia 19.0% (40/210). Among 1 606 positive eyes, 1 355 high-risk lesions were identified by consensus. Among them, ERM had the largest number of identifications (780, 57.6%), followed by HRF (255, 18.8%), and MH had the smallest number of identifications (7, 0.5%). Physicians randomly reexamined 1 352 cases and 2 704 eyes. The number of positive and negative eyes diagnosed was 753 and 1 952 respectively. The number of positive and negative eyes screened by AI-OCT was 828 and 1 876 respectively. There was an excellent consistency between AI-OCT screening and physician diagnosis (Kappa=0.866, P=0.011). Multivariate logistic regression analysis showed that age [odds ratio (OR) =1.071, P＜0.001], high myopia (OR=1.921, P=0.001), and hyperglycemia (OR=1.287, P=0.005) were independent predictors of positive AI-OCT screening. Among 1 355 high-risk lesions, a total of 703 were referred (referral rate 51.9%). The three lesions with the highest referral rates were SRF (71.1%, 27/38), IRF (69.2%, 54/78), and CNV (61.5%, 24/39), respectively. Among the 803 cases with positive AI-OCT screening, 385 cases (47.9%) actually received referral suggestions, 259 cases (32.3%) were eventually diagnosed, and 109 cases (13.6%) received treatment. Compared with low-risk patients, the referral rate and diagnosis rate of high-risk patients were significantly higher (χ2=6.87, 4.48; P＜0.05), but there was no statistically significant difference in the final treatment acceptance rate between groups (χ2=1.15, P=0.280). ConclusionsThe established AI-OCT based screening model for fundus diseases in the “Five-High” population effectively improves the detection rate of early-stage lesions and promotes a shift from universal to precision screening. Patients with positive screening results have obvious referral and treatment obstacles, which requires clinical attention.
