和血明目片联合全视网膜激光光凝术对糖尿病视网膜病变患者视力状况、血液流变学及脉络膜厚度的影响

摘要 目的：探讨和血明目片联合全视网膜激光光凝术（PRP）对糖尿病视网膜病变（DR）患者视力状况、血液流变学及脉络膜厚度的影响。方法：选择2018年3月~2019年12月期间来安徽省第二人民医院接受治疗的60例DR患者,经计算机随机编号按奇偶顺序分为对照组（奇数,n=30）和研究组（偶数,n=30）,两组在接受常规降糖治疗的基础上,对照组患者接受PRP治疗,研究组患者接受和血明目片联合PRP治疗,对比两组临床总有效率,观察两组治疗前后的视力状况、血液流变学及脉络膜厚度变化。结果：研究组的临床总有效率高于对照组（P<0.05）。治疗后,两组裸眼视力、视野、视敏度均升高,研究组的升高程度大于对照组（P<0.05）。治疗后,两组血浆黏度（PV）、红细胞聚集指数（AI）、全血高切黏度（NBH）、全血低切黏度（NBL）、血沉（ESR）均下降,研究组的下降程度大于对照组（P<0.05）。治疗后,两组黄斑中心凹下脉络膜厚度（SFCT）、下方脉络膜厚度（ICT）、上方脉络膜厚度（SCT）、鼻侧脉络膜厚度（NCT）、颞侧脉络膜厚度（TCT）均下降,研究组的下降程度大于对照组（P<0.05）。两组均未见明显的不良反应发生。结论：和血明目片联合PRP可有效改善DR患者的视力状况、血液流变学及脉络膜厚度。     

2型糖尿病视网膜病变患者血清和肽素、脂质运载蛋白2水平的表达及其临床意义

摘要 目的：探讨2型糖尿病（T2DM）视网膜病变（DR）患者血清和肽素（copeptin）、脂质运载蛋白2（LCN2）的表达及其临床意义。方法：选取2021年1月~2023年1月期间江南大学附属医院接收的2型糖尿病（T2DM）患者141例，将所有患者分为不合并糖尿病视网膜病变（DR）组（NDR组，n=49）、非增生期DR组（NPDR组，n=45）和增生期DR组（PDR组，n=47），另选取同期行健康体检的志愿者50例作为对照组。比较各组临床指标、生化指标及血清copeptin、LCN2水平，采用Pearson相关性分析血清copeptin、LCN2水平与临床指标及生化指标的相关性，采用多因素Logistic回归分析DR的危险因素。结果：对照组、NDR组、NPDR组、PDR组的血清copeptin、LCN2水平呈逐渐升高趋势（P<0.05）。NDR组、NPDR组、PDR组的体重指数（BMI）、收缩压（SBP）、舒张压（DBP）、甘油三酯（TG）、总胆固醇（TC）、低密度脂蛋白胆固醇（LDL-C）、空腹血糖（FPG）均高于对照组（P<0.05）；对照组、NDR组、NPDR组、PDR组的糖化血红蛋白（HbAlc）、胰岛素抵抗指数（HOMA-IR）呈逐渐升高趋势（P<0.05）；NDR组、NPDR组、PDR组糖尿病病程呈逐渐递增趋势（P<0.05）。Pearson相关性分析显示，copeptin、LCN2水平与HbAlc、HOMA-IR、糖尿病病程呈正相关（P<0.05），与血压、血脂、FPG、BMI无明显相关性（P>0.05）。多因素Logistic回归分析结果显示：糖尿病病程、HbAlc、HOMA-IR、copeptin、LCN2均为DR发生发展的独立危险因素（P<0.05）。结论：高水平copeptin、LCN2可能与DR的发生、发展有关，且与患者糖尿病病程、HbAlc、HOMA-IR关系密切，可用于DR患者的早期诊断及判断其病情的严重程度。     

不同来源乳铁蛋白对幼鼠肠道发育的影响

目的 探究哺乳期乳铁蛋白（lactoferrin，LF）的缺失及不同来源LF补充后对幼鼠肠道发育的影响。方法 以LF基因敲除型雌鼠作为哺乳母鼠造成幼鼠哺乳期无LF的摄入，且从幼鼠出生第3~21天每日人工饲喂100 mg/kg 牛血清白蛋白（BSA）、牛源乳铁蛋白（bovine Lactoferrin，bLF）及重组人源乳铁蛋白（recombinant human Lactoferrin，rhLF），于幼鼠21日龄取样，测定各组小鼠小肠发育指标。结果 在本实验周期下，哺乳期rhLF的补充显著性增加小鼠回肠绒毛长度/隐窝深度值（P<0.05），且上调回肠Occludin和ZO-1基因的表达（P<0.05），增加小鼠十二指肠、空肠和回肠麦芽糖酶酶活/乳糖酶酶活比值（P<0.05），表明哺乳期rhLF的补充能够增强小鼠肠道消化吸收能力和肠屏障功能；哺乳期bLF的补充显著增加小鼠十二指肠及回肠麦芽糖酶活性/乳糖酶活性比值（P<0.05）。结论 对于哺乳期无LF摄入的乳鼠来说，哺乳期间LF的补充能够增强乳鼠肠道对营养物质的消化吸收能力、促进肠道的发育成熟、增强肠道屏障功能，并且，本实验中rhLF表现出比bLF更加有效的作用。     

基于注意力机制的RNA碱基关联图预测方法

目的 长链非编码RNA在遗传、代谢和基因表达调控等方面发挥着重要作用。然而，传统的实验方法解析RNA的三级结构耗时长、费用高且操作要求高。此外，通过计算方法来预测RNA的三级结构在近十年来无突破性进展。因此，需要提出新的预测算法来准确的预测RNA的三级结构。所以，本文发展可以用于提高RNA三级结构预测准确性的碱基关联图预测方法。方法 为了利用RNA理化特征信息，本文应用多层全卷积神经网络和循环神经网络的深度学习算法来预测RNA碱基间的接触概率，并通过注意力机制处理RNA序列中碱基间相互依赖的特征。结果 通过多层神经网络与注意力机制结合，本文方法能够有效得到RNA特征值中局部和全局的信息，提高了模型的鲁棒性和泛化能力。检验计算表明，所提出模型对序列长度L的4种标准（L/10、L/5、L/2、L）碱基关联图的预测准确率分别达到0.84、0.82、0.82和0.75。结论 基于注意力机制的深度学习预测算法能够提高RNA碱基关联图预测的准确率，从而帮助RNA三级结构的预测。     

间歇性θ节律经颅磁刺激改善大鼠工作记忆的海马与前额叶跨脑区神经网络效应研究

目的 间歇性θ节律刺激（iTBS）作为一种新型的经颅磁刺激模式，已经广泛应用于探索大脑认知功能和神经调控等方面，但其电生理调控机制尚不清晰，探索iTBS对大脑认知功能的影响及其电生理机制，对脑疾病的治疗和磁刺激的临床应用具有重要意义。方法 本文利用iTBS制备磁刺激大鼠模型，采集记录大鼠在执行工作记忆（WM）任务过程中腹侧海马（vHPC）和内侧前额叶皮层（mPFC）的局部场电位（LFPs）信号，应用格兰杰因果网络分析方法，研究了iTBS对大鼠WM过程中vHPC与mPFC跨脑区神经网络协同和信息交互的影响。结果 iTBS增强了大鼠的学习记忆能力，使其完成工作记忆任务所需时长减少（2.67±1.63）d（P<0.05），iTBS显著改善了大鼠的行为学表现；同时iTBS增强了大鼠在WM期间vHPC与mPFC脑区的自因果网络连接，增加了网络连接强度、连接密度和全局效率（P<0.05）；并且iTBS增强了vHPC与mPFC脑区的跨脑区网络连接，增加了vHPC-mPFC跨脑区的节点度和因果流向（P<0.05）。结论 iTBS磁刺激对大鼠工作记忆行为学及相关脑区神经网络均有显著的积极作用，iTBS可以促进大鼠认知能力，提高大脑神经网络的信息交互和传递效率，iTBS的神经调控机制可能是通过增强大脑vHPC与mPFC之间的网络连接和信息交互来提高工作记忆能力。     

玻璃体腔抗VEGF治疗不同光学相干层析成像技术分型下的糖尿病黄斑水肿临床疗效分析

摘要 目的：研究玻璃体腔内抗血管内皮生长因子（VEGF）抗体治疗不同光学相干层析成像技术（OCT）分型下的糖尿病黄斑水肿临床疗效。方法：选取2019年1月到2021年3月在我院进行治疗的糖尿病黄斑水肿患者60例,根据OCT检测分为分弥漫性黄斑水肿（DRT）组、囊样黄斑水肿（CME）组和浆液性视网膜脱离（SRD）组,每组20例。所有患者均接受玻璃体腔内注射抗VEGF抗体治疗,比较三组患者临床治疗疗效、黄斑水肿形态、最佳矫正视力（BCVA）、黄斑中心凹厚度（CMT）以及不良反应发生率。结果：（1）DRT、CME和SRD组患者临床治疗有效率分别为85.0 %、75.0 %和50.0 %,治疗后黄斑水肿消退率分别为55.0 %、25.0 %和10.0 %,且组间比较差异显著（P<0.05）;（2）三组患者治疗前BCVA和CMT均无差异（P>0.05）,治疗后三组患者BCVA和CMT均降低（P<0.05）,并且治疗后DRT和CME组患者BCVA和CMT均低于SRD组（P<0.05）;（3）DRT、CME和SRD组患者治疗期间不良反应发生率分别为10.0 %、10.0 %和25.0 %,但三组患者治疗期间不良反应发生率比较无差异（P>0.05）。结论：不同OCT分型的糖尿病黄斑水肿经玻璃体腔抗VEGF抗体治疗后临床疗效不同,其中DRT患者临床治疗疗效最好,而SRD患者疗效最差。     

模拟失重不同时长对大鼠抑郁样行为的影响

目的 本研究旨在观察不同持续时间的模拟失重对大鼠抑郁样行为和海马超氧化物歧化酶（SOD）和过氧化氢酶（CAT）的影响，以探究其影响及可能的作用机制。方法 采用后肢悬挂（HLS）尾吊法模拟大鼠失重状态。将大鼠分为对照组和不同模拟失重时间尾吊组（尾吊时长分别为1、2、3、4周）。采用旷场实验（OFT）、新物体识别实验（NORT）、强迫游泳实验（FST）观察大鼠抑郁样行为，采用酶联免疫吸附试验（ELISA）法测定海马SOD和CAT活性。结果 OFT结果显示，与对照组相比，HLS不同时间大鼠的僵滞时间增加（P<0.05，P<0.01）。在NORT中，与对照组相比，HLS不同时间大鼠对新物体的探索潜伏期增加，探索次数和时间减少（P<0.05，P<0.01）。在FST中，与对照组相比，HLS不同时间大鼠在FST中的不动时间增加，攀爬次数减少（P<0.05，P<0.01）。与对照组相比，HLS不同时间组大鼠海马组织中SOD和CAT水平均下降（P<0.05，P<0.01）。结论 短时间或长时间的失重都会导致大鼠产生类抑郁样行为。     

维生素D缺乏和2型糖尿病视网膜病变风险度的相关性研究

摘要 目的：是探讨维生素D缺乏与2型糖尿病（T2DM）患者视网膜病变（DR）发生风险度的关系。方法：选取2020年12月至2022年8月在新疆医科大学第二附属医院内分泌科住院的2型糖尿病患者作为研究对象。将209名患者根据眼底检查分为DR组（n=50）和正常眼底（NDR）组（n=159）。比较各组患者一般资料、实验室检查指标;采用Spearman分析法分析病程、FBG、HbAlC、25(OH)D与DR的相关性,采用Pearson分析居住地（城镇）、与维生素D缺乏、SBP与DR的相关性,采用Logistics回归分析DR发生的影响因素,比较各组患者维生素D缺乏、病程、FBG、HbA1c及25(OH)D对DR的预测价值。结果：DR组的居住地（农村）、FBG、HbA1c、病程等均大于NDR组,25(OH)D水平低于NDR组,DR组维生素D缺乏率大于NDR组,差异有统计学意义（P＜0.05）。Pearson相关性分析结果表明DR与居住地（城镇）呈负相关（P＜0.05）,与SBP、维生素D缺乏呈正相关（P＜0.05）;Spearman相关分析表明DR与25(OH)D呈负相关（P＜0.05）,与病程、空腹血糖和糖化血红蛋白等呈正相关（P＜0.05）。Logistic回归分析结果显示,维生素D缺乏、病程、FBG、HbA1c为DR的独立危险因素（P＜0.05）,维生素D缺乏的T2DM患者DR发病风险是维生素D不缺乏者的22.019倍（OR=22.019,95%CL 2.119~228.771,P＜0.05）。受试者工作特征（ROC）曲线分析显示,病程、FBG、HbA1c、25(OH)D作为联合变量可有效预测DR,ROC曲线下面积为0.924。结论：25(OH)D与DR呈负相关,维生素D缺乏可能与T2DM患者DR的发生有关。     

电子病历系统对临床路径管理的影响研究

目的 探讨电子病历系统对临床路径管理的影响。方法 入选河北北方学院附属第一医院2014年1月—2014年6月进入临床路径管理的512例患者（包括胆囊结石腹腔镜胆囊切除术、慢性鼻-鼻窦炎、2型糖尿病3个病种）作为观察对象,其中258例患者采用电子病历系统进行临床路径管理,254例患者采用纸质病历系统进行临床路径管理,比较两组病历质量、路径变异率、病种治疗费用及患者满意度。结果 观察组甲级率明显高于对照组、乙级率明显低于对照组,差异均具有统计学意义（均P<0.05）;观察组路径变异率为7.8%（20/258）,显著低于对照组15.0%（38/254）,差异具有统计学意义（P＜0.05）;观察组3个病种的治疗费用均显著低于对照组,差异均具有统计学意义（均P＜0.05）;观察组患者满意度为95.3%（246/258）,显著高于对照组的77.2%（196/254）,差异具有统计学意义（P＜0.05）。结论 电子病历系统与临床路径管理结合有助于降低路径变异率,提高医护人员工作效率,降低医疗费用,提高患者满意度。     

排队论模型在军队医院门诊超声科设备配置中的应用

目的 探讨排队论模型在军队医院门诊超声科设备配置中的应用效果。方法 运用现场调查法和排队论模型,计算超声科设备工作强度（r）,患者排队等待人数（Lq）,窗口逗留人数（Ls）,平均排队等待时间（Wq）,平均逗留时间（Ws）,设备空闲概率（P0）患者到达必须等待的概率（P）等运行指标,并对应用排队论模型配置设备前后患者及技师进行满意度调查。结果 超声科上下午分别配置6台和3台设备较为合理,在应用排队论模型配置设备后,技师和患者的满意度均得到明显提高（P＜0.05）。结论 利用排队论的方法可以较好地配置超声科设备,为提高服务效率提供科学参考。     

A Multi-Branch Convolutional Neural Network for Screening and Staging of Diabetic Retinopathy Based on Wide-Field Optical Coherence Tomography Angiography

BackgroundDiabetic retinopathy (DR) is one of the major causes of blindness in adults suffering from diabetes. With the development of wide-field optical coherence tomography angiography (WF-OCTA), it is to become a gold standard for diagnosing DR. The demand for automated DR diagnosis system based on OCTA images have been fostered due to large diabetic population and pervasiveness of retinopathy cases.Materials and methodsIn this study, 288 diabetic patients and 97 healthy people were imaged by the swept-source optical coherence tomography (SS-OCT) with 12 mm × 12 mm single scan centered on the fovea. A multi-branch convolutional neural network (CNN) was proposed to classify WF-OCTA images into four grades: no DR, mild non-proliferative diabetic retinopathy (NPDR), moderate to severe NPDR, and proliferative diabetic retinopathy (PDR).ResultsThe proposed model achieved a classification accuracy of 96.11%, sensitivity of 98.08% and specificity of 89.43% in detecting DR. The accuracy of the model for DR staging is 90.56%, which is higher than that of other mainstream convolution neural network models.ConclusionThis technology enables early diagnosis and objective tracking of disease progression, which may be useful for optimal treatment to reduce vision loss.     

Quantitative evaluation of optical coherence tomography angiography images of diabetic retinopathy eyes before and after removal of projection artifacts

Projection artifacts (PAs) affect the quantification of vascular parameters in the deep layer optical coherence tomography (OCT) angiography image. This study eliminated PA and quantified its effect on imaging. 53 eyes (30 subjects) of normal Indian subjects and 113 eyes (92 patients) of type 2 diabetes mellitus with retinopathy (DR) underwent imaging with a scan area of 3 mm × 3 mm. In this study, a normalized cross‐correlation between superficial and deep layer was used to remove PA in deep layer. Local fractal analysis was done to compute vascular parameters such as foveal avascular zone area (mm²), vessel density (%), spacing between large vessels (%) and spacing between small vessels (%). Before PA removal, vessel density for mild nonproliferative (NPDR), moderate NPDR, severe NPDR and proliferative DR were 42.56 ±1.69%, 40.69 ±0.72%, 37.34 ±0.85% and 35.61 ±1.26%, respectively. After artifact removal, vessel density was 28.9 ±1.22%, 29.9 ±0.56%, 26.19 ±0.59% and 24.02 ±0.94%, respectively. All the vascular parameters were statistically significant (P <.001) between normal and disease eyes, irrespective of superficial and deep retinal layers. Parafoveal sectoral analyses showed that temporal zone had the lowest vessel density and may undergo DR‐related changes first. The current approach enabled rapid and accurate quantitative interpretation of DR eyes, without PA.      

High-Resolution Imaging of Parafoveal Cones in Different Stages of Diabetic Retinopathy Using Adaptive Optics Fundus Camera

PurposeTo assess cone density as a marker of early signs of retinopathy in patients with type II diabetes mellitus.MethodsAn adaptive optics (AO) retinal camera (rtx1^™; Imagine Eyes, Orsay, France) was used to acquire images of parafoveal cones from patients with type II diabetes mellitus with or without retinopathy and from healthy controls with no known systemic or ocular disease. Cone mosaic was captured at 0° and 2°eccentricities along the horizontal and vertical meridians. The density of the parafoveal cones was calculated within 100×100-μm squares located at 500-μm from the foveal center along the orthogonal meridians. Manual corrections of the automated counting were then performed by 2 masked graders. Cone density measurements were evaluated with ANOVA that consisted of one between-subjects factor, stage of retinopathy and the within-subject factors. The ANOVA model included a complex covariance structure to account for correlations between the levels of the within-subject factors.ResultsTen healthy participants (20 eyes) and 25 patients (29 eyes) with type II diabetes mellitus were recruited in the study. The mean (± standard deviation [SD]) age of the healthy participants (Control group), patients with diabetes without retinopathy (No DR group), and patients with diabetic retinopathy (DR group) was 55 ± 8, 53 ± 8, and 52 ± 9 years, respectively. The cone density was significantly lower in the moderate nonproliferative diabetic retinopathy (NPDR) and severe NPDR/proliferative DR groups compared to the Control, No DR, and mild NPDR groups (P < 0.05). No correlation was found between cone density and the level of hemoglobin A_1c (HbA_1c) or the duration of diabetes.ConclusionsThe extent of photoreceptor loss on AO imaging may correlate positively with severity of DR in patients with type II diabetes mellitus. Photoreceptor loss may be more pronounced among patients with advanced stages of DR due to higher risk of macular edema and its sequelae.     

Plasma angiogenesis and oxidative stress markers in patients with diabetic retinopathy

Abstract

Background: Neovascularization in the retina and hyperglycaemia-induced oxidative stress are implicated in the pathogenesis of diabetic retinopathy (DR). In this study, we hypothesized that the plasma angiogenic and oxidative stress markers associated with these derangements could aid in the screening of diabetic patients who are at an increased risk of developing retinopathy.

Methods: This study included normal (n?=?148), type2 diabetes without retinopathy (DNR; n?=?148), proliferative DR (PDR; n?=?74) and non-PDR (NPDR; n?=?148) subjects. Plasma concentrations of vascular endothelial growth factor-A (VEGF-A), hypoxia-inducible factor-1α (HIF-1α), matrix metalloproteinase-9 (MMP-9), pigment epithelium-derived factor (PEDF), nitric oxide (NO), soluble receptors for advanced glycation end products (sRAGE), malondialdehyde (MDA) and protein thiols were estimated.

Results: A statistically significant increase was observed in the plasma concentrations of pro-angiogenic factors and markers of oxidative stress in both retinopathy groups. By contrast, the concentrations of anti-angiogenic factors and antioxidants were decreased significantly in these groups. Receiver operating characteristic analysis indicated that the plasma thresholds of HIF-1α and PEDF can be suitable markers in case of NPDR. However, in PDR, HIF-1α, NO, MMP-9 and PEDF showed high sensitivity and specificity.

Conclusions: The factors associated with hypoxia, matrix degradation and angiogenic inhibition play a crucial role in predicting DR.     

Automated quantification of superficial retinal capillaries and large vessels for diabetic retinopathy on optical coherence tomographic angiography

Optical coherence tomography angiography (OCTA) is a relatively new technique with capillary‐level resolution, which has shown great potential for the diagnosis of diabetic retinopathy (DR). A fully automatic algorithm for the quantitative measurement of microcirculatory changes in sight‐threatening DR is presented. The foveal avascular zone (FAZ) segmentation was improved with a graph‐theoretic method and the large vessels and capillaries were separately identified and analyzed. The method was evaluated in healthy and diabetic eyes with various stages of retinopathy. Results showed that, compared with the healthy group, the diabetic group showed a significantly larger large vessel density, but a significantly smaller capillary density (P < .001). Circularity of FAZ was significantly smaller while nonperfusion area was significantly larger in the diabetic group. The combined variable of all image metrics reached an area under the ROC of 0.853 (95% CI, 0.784‐0.923) for mild to moderate nonproliferative DR and 0.950 (95% CI, 0.922‐0.979) for proliferative DR. Microvascular and FAZ changes with various DR stages can be accurately delineated using the developed automatic program. Quantitative metrics on OCTA serve as potential biomarkers for the staging of DR.     

Convolution Neural Networks and Support Vector Machines for Automatic Segmentation of Intracoronary Optical Coherence Tomography

Cardiovascular diseases are closely associated with deteriorating atherosclerotic plaques. Optical coherence tomography (OCT) is a recently developed intravascular imaging technique with high resolution approximately 10 microns and could provide accurate quantification of coronary plaque morphology. However, tissue segmentation of OCT images in clinic is still mainly performed manually by physicians which is time consuming and subjective. To overcome these limitations, two automatic segmentation methods for intracoronary OCT image based on support vector machine (SVM) and convolutional neural network (CNN) were performed to identify the plaque region and characterize plaque components. In vivo IVUS and OCT coronary plaque data from 5 patients were acquired at Emory University with patient’s consent obtained. Seventy-seven matched IVUS and OCT slices with good image quality and lipid cores were selected for this study. Manual OCT segmentation was performed by experts using virtual histology IVUS as guidance, and used as gold standard in the automatic segmentations. The overall classification accuracy based on CNN method achieved 95.8%, and the accuracy based on SVM was 71.9%. The CNN-based segmentation method can better characterize plaque compositions on OCT images and greatly reduce the time spent by doctors in segmenting and identifying plaques.     

Optic Neuritis Is Associated with Inner Nuclear Layer Thickening and Microcystic Macular Edema Independently of Multiple Sclerosis

Background

Microcystic macular edema (MME) and inner nuclear layer thickening (INL) were described in multiple sclerosis (MS) and neuromyelitis optica (NMO) patients using optical coherence tomography (OCT). The cause of these findings is currently unknown and a relation to inflammatory or degenerative processes in the optic nerve is discussed.

Objective

The aim of our study was to investigate whether INL thickening and MME are related to optic neuritis (ON) in various neuro-inflammatory disorders causingON: MS, NMO and chronic inflammatory optic neuropathy.

Methods

We retrospectively analyzed data from 216 MS patients, 39 patients with a clinically isolated syndrome, 20 NMO spectrum disorder patients, 9 patients with chronic inflammatory optic neuropathy and 121 healthy subjects. Intra-retinal layer segmentation was performed for the eyes of patients with unilateral ON. Scanning laser ophthalmoscopy (SLO) images were reviewed for characteristic ocular fundus changes.

Results

Intra-retinal layer segmentation showed that eyes with a history of ON displayed MME independent INL thickening compared to contralateral eyes without previous ON. MME was detected in 22 eyes from 15 patients (5.3% of all screened patients), including 7 patients with bilateral edema. Of these, 21 had a prior history of ON (95%). The SLO images of all 22 MME-affected eyes showed crescent-shaped texture changes which were visible in the perifoveal region. A second grader who was blinded to the results of the OCT classified all SLO images for the presence of these characteristic fundus changes. All MME eyes were correctly classified (sensitivity = 100%) with high specificity (95.2%).

Conclusion

This study shows that both MME and INL thickening occur in various neuro-inflammatory disorders associated with ON. We also demonstrate that detection and analysis of MME by OCT is not limited to B-scans, but also possible using SLO images.     

Increased serum urea and creatinine levels correlate with decreased retinal nerve fibre layer thickness in diabetic retinopathy

Abstract

Correlation of increased levels of serum urea and creatinine with retinal nerve fibre layer (RNFL) thinning on spectral domain optical coherence tomography (SD-OCT) was studied in diabetic retinopathy (DR). Sixty consecutive cases and 20 healthy controls were included. Cases were divided into three groups: without DR, non-proliferative DR with macular oedema and proliferative DR with oedema. Serum urea and creatinine were measured using a standard protocol. Average (RNFL) was measured using SD-OCT. Increased severity of DR was associated with decrease in levels of serum urea and serum creatinine levels. RNFL thinning correlated positively with increase in serum urea and creatinine levels.     

Enface Thickness Mapping and Reflectance Imaging of Retinal Layers in Diabetic Retinopathy

Purpose

To present a method for image segmentation and generation of enface thickness maps and reflectance images of retinal layers in healthy and diabetic retinopathy (DR) subjects.

Methods

High density spectral domain optical coherence tomography (SDOCT) images were acquired in 10 healthy and 4 DR subjects. Customized image analysis software identified 5 retinal cell layer interfaces and generated thickness maps and reflectance images of the total retina (TR), inner retina (IR), outer retina (OR), and the inner segment ellipsoid (ISe) band. Thickness maps in DR subjects were compared to those of healthy subjects by generating deviation maps which displayed retinal locations with thickness below, within, and above the normal 95% confidence interval.

Results

In healthy subjects, TR and IR thickness maps displayed the foveal depression and increased thickness in the parafoveal region. OR and ISe thickness maps showed increased thickness at the fovea, consistent with normal retinal anatomy. In DR subjects, thickening and thinning in localized regions were demonstrated on TR, IR, OR, and ISe thickness maps, corresponding to retinal edema and atrophy, respectively. TR and OR reflectance images showed reduced reflectivity in regions of increased thickness. Hard exudates appeared as hyper-reflective spots in IR reflectance images and casted shadows on the deeper OR and ISe reflectance images. The ISe reflectance image clearly showed the presence of focal laser scars.

Conclusions

Enface thickness mapping and reflectance imaging of retinal layers is a potentially useful method for quantifying the spatial and axial extent of pathologies due to DR.