DCT-Net: An effective method to diagnose retinal tears from B-scan ultrasound images.

Retinal tears (RTs) are usually detected by B-scan ultrasound images, particularly for individuals with complex eye conditions. However, traditional manual techniques for reading ultrasound images have the potential to overlook or inaccurately diagnose conditions. Thus, the development of rapid and accurate approaches for the diagnosis of an RT is highly important and urgent. The present study introduces a novel hybrid deep-learning model called DCT-Net to enable the automatic and precise diagnosis of RTs. The implemented model utilizes a vision transformer as the backbone and feature extractor. Additionally, in order to accommodate the edge characteristics of the lesion areas, a novel module called the residual deformable convolution has been incorporated. Furthermore, normalization is employed to mitigate the issue of overfitting and, a Softmax layer has been included to achieve the final classification following the acquisition of the global and local representations. The study was conducted by using both our proprietary dataset and a publicly available dataset. In addition, interpretability of the trained model was assessed by generating attention maps using the attention rollout approach. On the private dataset, the model demonstrated a high level of performance, with an accuracy of 97.78%, precision of 97.34%, recall rate of 97.13%, and an F1 score of 0.9682. On the other hand, the model developed by using the public funds image dataset demonstrated an accuracy of 83.82%, a sensitivity of 82.69% and a specificity of 82.40%. The findings, therefore present a novel framework for the diagnosis of RTs that is characterized by a high degree of efficiency, accuracy and interpretability. Accordingly, the technology exhibits considerable promise and has the potential to serve as a reliable tool for ophthalmologists.

DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence.

Medical artificial intelligence (AI) has been moving from the research phase to clinical implementation. However, most AI-based models are mainly built using high-quality images preprocessed in the laboratory, which is not representative of real-world settings. This dataset bias proves a major driver of AI system dysfunction. Inspired by the design of flow cytometry, DeepFundus, a deep-learning-based fundus image classifier, is developed to provide automated and multidimensional image sorting to address this data quality gap. DeepFundus achieves areas under the receiver operating characteristic curves (AUCs) over 0.9 in image classification concerning overall quality, clinical quality factors, and structural quality analysis on both the internal test and national validation datasets. Additionally, DeepFundus can be integrated into both model development and clinical application of AI diagnostics to significantly enhance model performance for detecting multiple retinopathies. DeepFundus can be used to construct a data-driven paradigm for improving the entire life cycle of medical AI practice.

Value of Biochemical Indexes of Bone Metabolism in Predicting Osteoporotic Lumbar Fractures.

Objective: To investigate the value of bone metabolism indexes such as type I procollagen N-terminal propeptide (P1NP), 25-hydroxyvitamin D (25(OH)D), osteocalcin (OSTEOC), and parathyroid hormone (PTH) in predicting osteoporotic lumbar fractures. Methods: 120 female patients with osteoporosis treated in our hospital were selected as research objects. There were 76 cases in the fracture group and 44 cases in the nonfracture group. The relationship between the levels of P1NP, 25(OH)D, OSTEOC, and PTH and the incidence of osteoporotic lumbar fractures were detected and compared between the two groups. The predictive value of biochemical indexes of bone metabolism in patients with osteoporosis was analyzed by ROC curve. Results: The levels of P1NP and PTH in the fracture group were significantly higher than those in the nonfracture group, while 25(OH)D and OSTEOC levels were lower than those in the nonfracture group. Moreover, the levels of P1NP, 25(OH)D, OSTEOC, and PTH are important factors affecting the pathogenesis of osteoporosis. The area under the curve (AUC) of fracture in patients with osteoporosis predicted by the combination of P1NP, 25(OH)D, OSTEOC, and PTH levels was 0.886, which was greater than the AUC predicted by each index (0.796, 0.753, 0.670, and 0.824). The best sensitivity and specificity of comprehensive prediction of each index were 78.95% and 79.10%, respectively. Conclusion: The abnormal changes of P1NP, 25(OH)D, OSTEOC, and PTH in female patients with osteoporotic lumbar fracture are closely related to the occurrence of the disease. The combination of these indicators has relatively significant application value in predicting the occurrence of fracture, which is helpful to formulate and guide relevant preventive measures for female patients with osteoporotic lumbar fracture and improve the prognosis.

Correlation of Serum CysC, IMA, and LP-PLA2 Levels With Type 2 Diabetes Mellitus Patients With Lower Extremity Atherosclerotic Occlusive Disease.

Objective: To investigate the serum level of cystatin C (CysC), ischemia-modified albumin (IMA), and lipoprotein-associated phospholipase A2 (LP-PLA2) in patients with type 2 diabetes mellitus (T2DM) and with lower extremity atherosclerotic occlusive disease (LEASOD) and their correlation. Methods: From March 2017 to December 2019, 110 patients with T2DM with LEASOD, who were treated in our hospital, were selected as the observation group. One hundred ten healthy persons who received medical examination in our hospital during the same period were selected as the control group. Serum CysC, IMA, LP-PLA2, and ankle-brachial index (ABI) were detected in each group. According to the ABI index, the observation group was divided into three subgroups, namely, the mild group (n = 45), the moderate group (n = 42), and the severe group (n = 23). Pearson correlation analysis was used to analyze the relationship between serum CysC, IMA, and LP-PLA2 levels in patients with T2DM with LEASOD and their condition. The receiver operator characteristic (ROC) curve was used to analyze the diagnostic value of serum CysC, IMA, and LP-PLA2 levels in patients with T2DM with LEASOD. Results: The serum levels of CysC, IMA, and LP-PLA2 in the observation group were higher than those in the control group (p < 0.05). The serum levels of CysC, IMA, and LP-PLA2 in the severe and the moderate group were higher than those in the mild group, and the serum levels of CysC, IMA, and LP-PLA2 in the severe group were higher than those in the moderate group (p < 0.05). Pearson correlation analysis showed that CysC, IMA, and LP-PLA2 levels were all negatively correlated with ABI (r = -0.802, r = -0.757, r = -0.764, p < 0.001). The ROC curve results showed that the area under the curve (AUC) of serum CysC in the diagnosis of T2DM with LEASOD was 0.806, and the best cut-off value was 1.74 mg/L. The AUC of serum IMA for diagnosis of T2DM with LEASOD was 0.772, and the best cut-off value was 92.58 g/L. The AUC of serum LP-PLA2 in the diagnosis of T2DM with LEASOD was 0.781, and the best cut-off value was 544.86 ng/L. The AUC of the three combined diagnoses of T2DM with LEASOD was 0.863. Conclusion: Serum levels of CysC, IMA, and LP-PLA2 were increased in patients with T2DM with LEASOD. Serum CysC, IMA, and LP-PLA2 are closely related to the severity of the disease. The higher the serum levels of CysC, IMA, and LP-PLA2, the more serious the degree of lower extremity arteriosclerosis occlusion, which can be used as an important serum marker to monitor the severity of T2DM with LEASOD. The combined detection of serum CysC, IMA, and LP-PLA2 has good diagnostic value for patients with T2DM with LEASOD.

Effectiveness of surgical management of malignant glaucoma in phakic eyes.

AIM: To assess the effectiveness of core vitrectomy-phacoemulsification-intraocular lens (IOL) implantation-capsulo-hyaloidotomy in treating phakic eye at least 1mo after the onset of malignant glaucoma. METHODS: A retrospective analysis were performed on malignant glaucoma patients treated in Zhongshan Ophthalmic Center between 2016 and 2018. Demographic and clinical data were described. The preoperative and postoperative visual acuity (VA), intraocular pressure (IOP), number of IOP-lowering medications used, and anterior chamber depth (ACD) of the case series were compared by Wilcoxon signed-rank test. RESULTS: Thirteen phakic eyes with long time intervals between onset and surgery were identified in this case series. Core vitrectomy-phacoemulsification-IOL implantation-capsulo-hyaloidotomy reduced the IOP (P=0.046) and the number of IOP-lowering medications used (P=0.004), deepened the ACD (P=0.005). Complete success was achieved in 38.5% of the eyes, and anatomical success was achieved in 100% of the eyes without any recurrence. The only postoperative complication observed is corneal endothelial decompensation. It occurred in two cases. CONCLUSION: Core vitrectomy-phacoemulsification-IOL implantation-capsulo-hyaloidotomy is safe and effective for treatment of long onset phakic malignant glaucoma.

Intraoperative OCT for the assessment of posterior capsular integrity in pediatric cataract surgery.

PURPOSE: To study the morphology of the posterior lens cortex and posterior capsules (PCs) in pediatric patients with posterior lens opacities using intraoperative optical coherence tomography (iOCT). SETTING: Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China. DESIGN: Prospective observational study. METHODS: Pediatric patients with posterior lens opacities were imaged using iOCT during cataract surgery. The morphology of the posterior lens cortex and PC, along with the common patterns to indicate PC integrity, was assessed. Moreover, PC rent during surgery was observed. RESULTS: A total of 62 eyes from 53 patients were included. The mean age of patients was 3.8 years. 4 morphological variants of posterior lens opacity were observed: type I (34/62 [54.8%]) with an intact PC; type II (20/62 [32.3%]) with an intact PC, which protruded into the anterior vitreous; type III (3/62 [4.8%]) with a deficient PC and an inability to delineate the PC; and type IV (5/62 [8.1%]) with dense opacity and an inability to characterize the posterior cortex and PC. Phacoemulsification could be performed in types I and II. In types III and IV, manual nucleus removal was performed instead of phacoemulsification. 3 cases (100%) of type III PC dehiscence developed during surgery, whereas no cases developed PC dehiscence of other types. CONCLUSIONS: The morphology of the PC and posterior lens cortex in pediatric posterior lens opacities could be categorized, and PC integrity could be assessed using iOCT, which was useful to guide surgical strategies and increase safety in pre-existing PC dehiscence in pediatric cataract surgery.

Mineral elements in the hair of amblyopic children.

Amblyopia is a common cause of vision damage in children, and some aspects of its etiology are not clear. A number of mineral elements have important effects on the nerve and visual nerve systems. However, little is known about the relationship between amblyopia and nutritional mineral elements. In this study, hair samples were collected from 67 children with amblyopia and 57 age-matched control groups. The height and weight of each child was measured, and body mass index (BMI) was calculated. Mineral elements were determined by atomic absorption spectrometry and inductively coupled plasma-atomic emission spectrometry. The calcium and magnesium levels in the hair of amblyopic children were higher (p < 0.006), but the level of manganese were lower compared with those in the control groups (p < 0.006). Other elements measured were found to have an insignificant difference between the two groups (p > 0.006). The BMI of amblyopic children was higher (p < 0.001). These results show that mineral elements may play an important role in the visual development of children. Therefore, studies should pay more attention to investigating the impact of mineral elements on child vision.