Objective To observe the affection of optic nerve under acute ocular hypertension and the effect of protection of bFGF on optic nerve. Methods BSS was perfused into anterior chamber of rabbits to increase the intraocular pressure to cause retinal ischemia. A computer image analysis system was used to count the optic nerve axons.Eyes were intravitreally injected with bFGF and then the number of optic nerve axons of the normal rabbits,and hypertension with and without bFGE treatment groups were counted respectively. Results The number of optic nerve axons in ocular hypertension eyes was less than the normal eyes(P=0.00003).The bFGF treated eyes had more optic nerve axons than the controls(P=0.0078). Conclusions The acute ocular hypertension may cause the loss of the nerve axons,and bFGF may be effective in protecting optic nerve in acute ocular hypertension. (Chin J Ocul Fundus Dis,2000,16:94-96)
Purpose To identify and quantitatively evaluate age-related changes in the retinal pigment epithelium (RPE) and underlying Bruch is membrane and choroid in donor human eyes. Methods 36unpaired human eyes of varying age (3-39 years) from Caucasian donors were supplied by Manchester Eye Bank (UK) or National Disease Research Interchange (Philadephia,USA).Modified Masson is trichrome staining was used to illustrate age-related changes in RPE cell, Bruch is membrane thickness, and density of choriocapillaries and thickness of the choroid. Data were assessed using computer-aided quantitative morphometric analysis method. ResultsThe thickness of Bruch is membrane increased with age while there is a change in morphology of RPE cells including a decrease in number and RPE cell thickening with age. RPE cells decreased at a rate of 8 cells/mm2 middot; year, RPE cell height and thickness of Bruch is membrane increased at rates of 0.01(mu;m/year) and 0.02 (mu;m/year) respectively. The luminal area of choriocapillaries and the thickness of choroid showed no close relation with age. Conclusion RPE cell loss and thickening of Bruch is membrane and RPE cells may be the earlier and primary alteration with age. (Chin J Ocul Fundus Dis,2000,16:236-239)
This paper is aimed to develop a computerized three dimensional system for displaying and analyzing mandibular helical axis pathways. Mandibular movements were recorded using a six-degrees-of-freedom ultrasonic jaw movement recording device. The three-dimensional digital models of the midface and the mandible were reconstructed and segmented from CT skull images. The digital models were then transformed to the coordinate system of mandibular motion data by using an optical measuring system. The system was programmed on the base of the Visualization ToolKit and Open Scene Graphics Library. According to the motion data, transformation matrices were calculated to simulate mandibular movements. Meanwhile, mandibular helical axis pathways were calculated and displayed three dimensionally by means of an eigenvalues method. The following parameters of mandibular helical axis were calculated: the rotation around instantaneous helical axis, the translation along it, its spatial orientation, its position and distance relative to any special reference point. These parameters could be exported to describe comprehensively the whole mandiblular movements. It could be concluded that our system would contribute to the study of mandiblular helical axis pathways.
ObjectiveTo estimate the early effectivenss of computer navigation-assisted total knee arthroplasty (TKA) by comparing with traditional TKA.MethodsThe clinical data of 89 patients (100 knees) underwent primary TKA between October 2017 and July 2018 were analyzed retrospectively, including 44 patients (50 knees) who completed the TKA under the computer-assisted navigation system as the navigation group and 45 patients (50 knees) treated with traditional TKA as the control group. There was no significant difference between the two groups (P>0.05) in gender, age, body mass index, diagnosis, side, disease duration, Kellgren-Lawrence classification of osteoarthritis, and preoperative American Hospital for Special Surgery (HSS) score, range of motion (ROM), hip-knee-ankle angle (HKA) deviation. The operation time, incision length, difference in hemoglobin before and after operation, postoperative hospital stay, and the complications were recorded and compared between the two groups. The HSS score, ROM, and joint forgetting score (FJS-12) were used to evaluate knee joint function in all patients. Unilateral patients also underwent postoperative time of up and go test and short physical performance battery (SPPB) test. At 1 day after operation, the HKA, mechanical lateral distal femoral angle (mLDFA), mechanical medial proximal tibial angle (mMPTA), sagittal femoral component angle (sFCA), and sagittal tibial component angle (sTCA) were measured and calculated the difference between the above index and the target value (deviation); and the joint line convergence angle (JLCA) was also measured. ResultsThe operations of the two groups were successfully completed, and the incisions healed by first intention. The operation time and incision length of the navigation group were longer than those of the control group (P<0.05); the difference in difference of hemoglobin before and after the operation and the postoperative hospital stay between groups was not significant (P>0.05). Patients in the two groups were followed up 27-40 months, with an average of 33.6 months. Posterior tibial vein thrombosis occurred in 1 case in each of the two groups, and 1 case in the control group experienced repeated knee joint swelling. The HSS scores of the two groups gradually increased after operation (P<0.05); HSS scores in the navigation group at 1 and 2 years after operation, and knee ROM and FJS-12 scores at 2 years were significantly higher than those in the control group (P<0.05). There was no significant difference in the postoperative time of up and go test and SPPB results between the two groups at 7 days after operation (P>0.05); the postoperative time of up and go test of the navigation group was shorter than that of the control group at 2 years (t=–2.226, P=0.029), but there was no significant difference in SPPB (t=0.429, P=0.669). X-ray film measurement at 1 day after operation showed that the deviation of HKA after TKA in the navigation group was smaller than that of the control group (t=–7.392, P=0.000); among them, the HKA deviations of 50 knees (100%) in the navigation group and 36 knees (72%) in the control group were less than 3°, showing significant difference between the two groups (χ2=16.279, P=0.000). The JLCA and the deviations of mLDFA, mMPTA, sFCA, and sTCA in the navigation group were smaller than those in the control group (P<0.05).ConclusionCompared with traditional TKA, computer navigation-assisted TKA can obtain more accurate prosthesis implantation position and lower limb force line and better early effectiveness. But there is a certain learning curve, and the operation time and incision length would be extended in the early stage of technology application.
ObjectiveTo compare the application effects between personal specific instrumentation (PSI) and computer-assisted navigation surgery (CAS) in total knee arthroplasty (TKA). MethodsThe literature comparing the application effects of PSI and CAS in TKA in recent years was widely consulted, and the difference between PSI-TKA and CAS-TKA in operation time, lower limb alignment, blood loss, and knee function were compared. ResultsCompared to CAS-TKA, PSI-TKA simplifies operation procedures and shortens operation time but probably has worse lower limb alignment. It is still controversial in comparison of perioperative blood loss and knee function between two techniques. ConclusionPSI-TKA and CAS-TKA both have advantages and disadvantages, and their differences need to be confirmed by further high-quality clinical trial.
Objective To summarize the research progress of the causes and prevention methods of anterior femoral notching in total knee arthroplasty (TKA). Methods The related literature at home and abroad about the causes and prevention methods of the anterior femoral notching in TKA was extensively reviewed and summarized. Results The reasons for the occurrence of anterior femoral notching can be summarized as follows: the application of the posterior reference technique, the increase of the posterior condylar angle, the variant anatomical shape of anterior femoral cortex, the selective reduction of the femoral prosthesis size, backward movement of the entrance point, and the application of computer-assisted navigation technology or patient-specific instrumentation. To prevent the occurrence of anterior femoral notching, programs such as flex the femoral prosthesis, robot-assisted technology, and anterior and posterior reference techniques combination can be used. Conclusion Anterior femoral notching is a common surgical complication of TKA. A complete preoperative plan, assessment of the patient’s knee joint condition, and development of a reasonable surgical plan can effectively reduce the occurrence of anterior femoral notching.
Objective To evaluate the three-dimensional acetabular orientation in asymptomatic population and patients of developmental dysplasia of the hip (DDH) using a semi-automated measurement software, which provides data for the differential diagnosis, surgical planning, surgical instrument design, and postoperative evaluation of hip related diseases. MethodsEighty-four cases of CT data in asymptomatic population (asymptomatic group) and 47 cases of CT data in DDH patients (DDH group) were collected. There was no significant difference in gender and age (including age of male and female subgroups) between the two groups (P<0.05). MaxTHA, a semi-automatic measurement software, was used to measure acetabular inclination and anteversion, including operative inclination (OI), radiographic inclination (RI), anatomic inclination (AI), operative anteversion (OA), radiographic anteversion (RA), and anatomic anteversion (AA). Comparisons were made between the two populations, between different Crowe classification subgroups, between different gender subgroups, and between left and right sides of acetabula. Results The comparison between asymptomatic group, healthy side of DDH group, and affected side of DDH group showed that there was no significant difference in acetabular orientation between asymptomatic group and healthy side of DDH group (P>0.05). The OI, RI, and AI of affected side of DDH group were significantly higher than those in healthy side of DDH group and asymptomatic group, and AA was significantly lower than that in healthy side of DDH group and asymptomatic group (P<0.05). The comparison between the normal acetabula and DDH acetabula with different Crowe classifications showed that there was no significant difference in the acetabulum orientation between Crowe Ⅰ group and the normal group (P>0.05). The OI, RI, and AI of Crowe Ⅱ, Ⅲ, and Ⅳ groups were significantly higher than those of normal group (P<0.05), the OI of Crowe Ⅲ group, RI and AI of Crowe Ⅳ group were significantly higher than those of Crowe Ⅰ group (P<0.05), the AI of Crowe Ⅳ group was significantly higher than that of Crowe Ⅱ group (P<0.05), and the OA, RA, and AA of Crowe Ⅲ group were significantly lower than other subgroups (P<0.05) except Crowe Ⅰ group. The OA, RA, and AA in asymptomatic female group, and the OA and AI in DDH female group were significantly higher than those in all male groups (P<0.05). The OI, RI, AI, and OA of the right acetabula in asymptomatic male group, and the RI and AI of the right acetabula in asymptomatic female group were significantly higher than those on the left side (P<0.05). ConclusionThere were significant differences in acetabular orientation between asymptomatic and DDH populations, inter-group differences among Crowe classification subgroups, inter-gender differences among subgroups, and bilateral differences among asymptomatic individuals.
ObjectiveTo observe the diagnostic value of six classification intelligent auxiliary diagnosis lightweight model for common fundus diseases based on fundus color photography. MethodsA applied research. A dataset of 2 400 color fundus images from Nanjing Medical University Eye Hospital and Zhejiang Mathematical Medical Society Smart Eye Database was collected, which was desensitized and labeled by a fundus specialist. Of these, 400 each were for diabetic retinopathy, glaucoma, retinal vein occlusion, high myopia, age-related macular degeneration, and normal fundus. The parameters obtained from the classical classification models VGGNet16, ResNet50, DenseNet121 and lightweight classification models MobileNet3, ShuffleNet2, GhostNet trained on the ImageNet dataset were migrated to the six-classified common fundus disease intelligent aid diagnostic model using a migration learning approach during training as initialization parameters for training to obtain the latest model. 1 315 color fundus images of clinical patients were used as the test set. Evaluation metrics included sensitivity, specificity, accuracy, F1-Score and agreement of diagnostic tests (Kappa value); comparison of subject working characteristic curves as well as area under the curve values for different models. ResultCompared with the classical classification model, the storage size and number of parameters of the three lightweight classification models were significantly reduced, with ShuffleNetV2 having an average recognition time per sheet 438.08 ms faster than the classical classification model VGGNet16. All 3 lightweight classification models had Accuracy > 80.0%; Kappa values > 70.0% with significant agreement; sensitivity, specificity, and F1-Score for the diagnosis of normal fundus images were ≥ 98.0%; Macro-F1 was 78.2%, 79.4%, and 81.5%, respectively. ConclusionThe intelligent assisted diagnosis of common fundus diseases based on fundus color photography is a lightweight model with high recognition accuracy and speed; the storage size and number of parameters are significantly reduced compared with the classical classification model.
At present, artificial intelligence (AI) has been widely used in the diagnosis and treatment of various ophthalmological diseases, but there are still many problems. Due to the lack of standardized test sets, gold standards, and recognized evaluation systems for the accuracy of AI products, it is difficult to compare the results of multiple studies. When it comes to the field of image generation, we hardly have an efficient approach to evaluating research results. In clinical practice, ophthalmological AI research is often out of touch with actual clinical needs. The requirements for the quality and quantity of clinical data put more burden on AI research, limiting the transformation of AI studies. The prediction of systemic diseases based on fundus images is making progressive advancement. However, the lack of interpretability of the research lower the acceptance. Ophthalmology AI research also suffer from ethical controversy due to unconstructed regulations and regulatory mechanisms, concerns on patients’ privacy and data security, and the risk of aggravating the unfairness of medical resources.