青光眼黄斑区结构和功能改变的对比研究
|
摘要
第一部分
目的:探索利用傅立叶光学干涉断层扫描和电脑辅助手动分层技术对青光眼局部(黄斑区)视网膜神经节细胞层厚度测量的可行性。
方法:对26例青光眼患者的26只眼和20例正常人的20只眼在视网膜黄斑区进行3D和水平中线线性傅立叶光学干涉断层扫描,视网膜不同层次的厚度用电脑程序辅助的手动分层技术测量。青光眼患者根据标准自动视野计检测的中心凹阈值敏感度分为低敏感度组和高敏感度组。
结果:低敏感度组的视网膜神经节细胞合并内丛状层和视网膜神经纤维层的厚度明显比高敏感度组薄,青光眼患者的这些层次的厚度比正常对照组薄,而内核层和感光细胞层的厚度在低敏感度组、高敏感度组和正常对照组均相似,而且其中一例青光眼的视网膜节细胞层变薄和10-2视野敏感性丢失呈现定性相关关系。
结论:利用傅立叶光学干涉断层扫描和电脑辅助手动分层技术能够获得对局部视网膜节细胞层厚度的测量,测量结果和视野敏感性改变一致。
第二部分
目的:探讨如何训练和指导操作者做电脑辅助的手动视网膜分层,以及分层的重复可靠性,并对自动分层算法提供改进的信息。
方法:40位受试者的40帧傅立叶光学干涉断层扫描的黄斑线性扫描分为培训组和测试组,每组20帧,其中10帧来自10位正常对照,10帧来自10位青光眼病人。分层过程分为培训阶段和测试阶段,在培训阶段学员和老师各完成20帧扫描的分层,老师可指导学员,学员可向老师咨询。在测试阶段,学员和老师在无任何讨论的前提下独立完成另20帧扫描的分层。由分层标定的边界得到视网膜神经纤维层、节细胞层和全视网膜的厚度。计算并比较测试阶段每个学员和老师间各层视网膜厚度和各层视网膜平均厚度的和谐相关系数。
结果:两位学员全视网膜厚度和谐相关系数的中位数分别为0.999(平均数为0.998)(学员1)和(平均数为0.998)(学员2),和谐相关性好,平均全视网膜厚度也显示出好的一致性;RNFL厚度的和谐相关性比全视网膜厚度弱,变化也较大。和老师相比学员1比学员2的相关性差,学员1相关性中位数为0.940(均数为0.851),而学员2的中位数是0.972(均数为0.893)。RNFL的平均厚度也显示出好的一致性,和学员1的中位数差值3.4μm相比,学员2的一致性稍好,其中位数差值是-0.3μm。学员1测量的RNFL厚度始终比学员2和老师的厚。RGC+厚度的相关性学员2好于学员1,学员2的相关性中位数是0.980(均数为0,967);学员1的相关性中位数是0.943(均数为0.932);学员2的中位数差值是0μm,学员1是3.5μm;学员1的分层显示的RGC+厚度较薄。RGC+的平均厚度也显示出良好的一致性。
结论:经过训练的分层者能对全视网膜、RNFL和RGC+的分层产生良好的一致性;训练应当包括一个测试阶段和定量分析;电脑辅助的手动分层能用于评价自动算法的分层,也可以用于一些自动算法不能进行的少量的实验性分层。
第三部分
目的:比较微视野、标准自动视野计、多焦视觉诱发电位和傅立叶光学干涉断层扫描在青光眼黄斑损害中的改变,建立青光眼黄斑区结构和功能损害的研究模式,并从多方面的对比研究中探讨对青光眼黄斑区结构和功能改变的关系。
方法:6例有中心视野缺损的青光眼患者的7只眼纳入研究,视野检查采用标准自动视野计Humphrey Field AnalyzerⅡ,检测程序采用24-2和10-2瑞典相关阈值算法(Swedish Interactive Threshold Algorithm,SITA),患者最佳矫正视力≥0.8;球镜屈光度在±6.0屈光度以内;柱镜屈光度在±2.0屈光度以内。所有正常受试者最佳矫正视力≥0.8。微视野采用4-2阈值程序,视标为GoldmannⅠ,刺激点间隔1°,刺激点阵列为8×8,刺激范围7°(直径)。VERIS 5.0多焦电生理系统用于记录多焦视觉诱发电位,采用由60个扇形区组成的飞镖盘刺激图形,每个扇形区内有16个棋盘格,8个白色(亮度为200cd/m~2),8个黑色(亮度＜3cd/m~2),刺激范围44.6°(直径)。傅立叶光学干涉断层扫描用于扫描正常对照的20例正常个体的20只眼和6例青光眼的7只眼,每只眼做3D扫描和水平线性扫描,应用电脑辅助手动分层技术对视网膜神经纤维层、视网膜节细胞层、内核层和全感光细胞层进行分层并计算其厚度。
结果:患者组黄斑区视网膜节细胞层的厚度明显比正常对照组薄(p＜0.001),神经纤维层、内核层和全感光细胞层在各组间无显著性差异;水平中线附近及上下方微视野和10-2视野缺损部位与神经节细胞厚度降低的区域呈现良好的一致性;在mfVEP和微视野及10-2视野的对比中,微视野光敏感度越低,mfVEP的信噪比也越低,10-2视野敏感度阈值和mfVEP信噪比的关系也表现出同样的趋势;在微视野检测范围内,mfVEP振幅降低的区域和微视野敏感度降低的部位有良好的一致性。
结论:黄斑区细致结构和功能改变的研究模式有效可行,黄斑区的结构和功能改变有良好的一致性,客观功能检查(mfVEP)能证实主观功能检查的可靠性,该研究模式为青光眼黄斑区结构和功能研究提供了有效研究途径,也为青光眼的早期诊断和治疗以及青光眼进展的监控提供了重要手段。
Part One:Local Retinal Ganglion Cell Thickness Can Be Measured in Patients with Glaucoma Using Frequency-Domain Optical Coherence Tomography
Objective:To explore the feasibility of obtaining a local measure of the thickness of the retinal ganglion cell layer in patients with glaucoma using frequency-domain optical coherence tomography(FD-OCT) and a computer assisted manual segmentation procedure.
Methods:FD-OCT scans of 3D and horizontal line were obtained from one eye of 26 glaucoma patients and 20 control subjects.The thickness of various layers was measured with a manual segmentation procedure aided by a computer program.The patients were divided into low and high sensitivity groups based upon their foveal sensitivity on standard automated perimetry.
Results:The thicknesses of the RGC plus inner plexiform and the retinal nerve fiber layers of the low sensitivity group were significantly thinner than those of the high sensitivity group.While the thickness of these layers in the patients was thinner than controls,the thicknesses of INL and receptor layer were similar in all 3 groups. Further,the thinning of the RGC+layer in one glaucoma eye showed qualitative correspondence to the loss in 10-2 visual field sensitivity.
Conclusions:Local measures of RGC layer thickness can be obtained from FD-OCT scans using a manual segmentation procedure and these measures show a qualitative agreement with visual field sensitivity.
Part Two:Reliability Study of Manual Segmentation for Retinal Layers Using Computer Assisted Procedure
Objective:To explore a training procedure to the trainee on segmenting the retinal layers using computer assisted program and discuss the reliability of segmentation for providing information to the automatic algorithm.
Methods:Forty FD-OCT line scans from 40 individuals were divided into 2 sets of 20,the Training Set and Test Set.Each set had scans from 10 individual with normal vision and 10 patients with glaucoma.The segmentation was divided into 2 sessions, Training Session and Testing Session.Trainees and experts segmented 20 scans in the Training Session with teaching and consulting.In the Testing Session,trainees and experts completed segmentation for another 20 scans without consulting.The thickness of the RNFL,RGC+ and total retina were calculated based on the boundaries of each layer.Concordance correlation coefficient of the thickness of each layer and the average thickness of each layer were calculated between trainees and experts.
Results:For the total retinal thickness,the concordance correlations were very good for both trainees and for all 20 scans with a median of 0.999(mean:0.998) and 0.999 (mean:0.998) for trainee 1 and 2,respectively.The average total retinal thickness also showed good agreement.The concordance correlation of the RNFL was slight lower than the total retina.Compared to the trainee 2 with a median of 0.972(mean:0.892), trainee 1 was worse with a median of 0.940(mean:0.851).The average thickness of RNFL showed good agreement.The agreement was slightly better for trainee 2, whose median difference was-0.3μm,as compared to a median difference of 3.4μm for trainee 1.Trainee 1's RNFL thickness was constantly thicker than trainee 2 and experts.For the correlation of the RGC+ thickness,trainee 1 had a median of 0.934 (0.932) and trainee 2 had a median of 0.980(mean:0.967).The median difference of trainee 1 was 3.5μm and trainee 2 had a median difference of 0μm.The average thickness of RGC+ also showed good agreement.
Conclusions:Trainees showed good agreement to the thickness of total retina,RNFL and RGC+ after training session.Training should contain a test session and quantitative analysis.Computer assisted manual segmentation can be used to assess segmentation done by algorithms.It also can be used for experiments with limited number scans and algorithms not available and/or are of questionable value.
Part Three:An Evaluation of Local Glacomatous Damage in the Macula Using Microperimetry,Standard Automated Perimetry, Multifocal Visual Evoked Potential and Frequency Domain Optical Coherence Tomography
Objective:To compare the changes of microperimetry,standard automatic perimetry, multifocal visual evoked potential and frequency domain optical coherence tomography in macular damage of glaucoma.To establish a study approach for glaucomatous macular damage and discuss the correlation of structure and function changes in macular area of glaucoma.
Methods:Seven eyes of 6 glaucoma patients were included in the study.Humphrey visual field with 24-2 and 10-2 threshold strategy(SITA) was used to test the visual field.Patients had best corrected visual acuity greater than 0.8,spherical refraction within±6.00 diopters and cylinder correction within±2.00 diopters.Normal controls had corrected visual acuity greater than 0.8.Microperimetry was performed on all subjects using the MP-1 Microperimeter.4-2 strategy was used.The stimulus size was GoldmannⅠ.Microperimetry setting was customized using 8×8 grid pattern of 64 stimuli covering 7°.All glaucoma patients underwent the mfVEP using VERIS 5.0 software The dartboard pattern consisted of 60 sectors,each with a checkerboard pattern of 16 checks,8 white (luminance=200 cd/m~2),and 8 black(luminance＜3 cd/m~2).The display had a diameter of 44.6°. All patients and normal controls underwent frequency domain OCT scan.The scan types were macular line scan and 3D scan.Computer assisted segmentation program was used to segment the layers of RNFL,RGC+,INL and total receptor.The thickness of these 4 layers was calculated.
Results:RGC+ thickness in patient's group was thinner than controls(p＜0.001).The thickness of RNFL,INL and total retina had no significance.It had good agreement between the structural changes and microperimetry and 10-2 HVF defect around horizontal meridian.Some area showed the structural changes earlier than functional defect.In the comparison between mfVEP and microperimetry,the lower the sensitivity,the lower the mfVEP signal to noise ratio.Compared 10-2 HVF to mfVEP,it also showed the same tendency.In the testing area of microperimetry,the amplitude reduction of the local responses corresponded to the local sensitivity loss well.
Conclusions:The approach for study the detailed changes on structure and function in macular is feasible.The changes between structure and function showed good agreement.The objective functional test(mfVEP) confirmed the reliability of the subjective test.The approach provided an effective method to study glaucomatous changes in macular.It is also a useful tool for early diagnosis of glaucoma and monitoring the progression of the disease.
目的:探索利用傅立叶光学干涉断层扫描和电脑辅助手动分层技术对青光眼局部(黄斑区)视网膜神经节细胞层厚度测量的可行性。
方法:对26例青光眼患者的26只眼和20例正常人的20只眼在视网膜黄斑区进行3D和水平中线线性傅立叶光学干涉断层扫描,视网膜不同层次的厚度用电脑程序辅助的手动分层技术测量。青光眼患者根据标准自动视野计检测的中心凹阈值敏感度分为低敏感度组和高敏感度组。
结果:低敏感度组的视网膜神经节细胞合并内丛状层和视网膜神经纤维层的厚度明显比高敏感度组薄,青光眼患者的这些层次的厚度比正常对照组薄,而内核层和感光细胞层的厚度在低敏感度组、高敏感度组和正常对照组均相似,而且其中一例青光眼的视网膜节细胞层变薄和10-2视野敏感性丢失呈现定性相关关系。
结论:利用傅立叶光学干涉断层扫描和电脑辅助手动分层技术能够获得对局部视网膜节细胞层厚度的测量,测量结果和视野敏感性改变一致。
第二部分
目的:探讨如何训练和指导操作者做电脑辅助的手动视网膜分层,以及分层的重复可靠性,并对自动分层算法提供改进的信息。
方法:40位受试者的40帧傅立叶光学干涉断层扫描的黄斑线性扫描分为培训组和测试组,每组20帧,其中10帧来自10位正常对照,10帧来自10位青光眼病人。分层过程分为培训阶段和测试阶段,在培训阶段学员和老师各完成20帧扫描的分层,老师可指导学员,学员可向老师咨询。在测试阶段,学员和老师在无任何讨论的前提下独立完成另20帧扫描的分层。由分层标定的边界得到视网膜神经纤维层、节细胞层和全视网膜的厚度。计算并比较测试阶段每个学员和老师间各层视网膜厚度和各层视网膜平均厚度的和谐相关系数。
结果:两位学员全视网膜厚度和谐相关系数的中位数分别为0.999(平均数为0.998)(学员1)和(平均数为0.998)(学员2),和谐相关性好,平均全视网膜厚度也显示出好的一致性;RNFL厚度的和谐相关性比全视网膜厚度弱,变化也较大。和老师相比学员1比学员2的相关性差,学员1相关性中位数为0.940(均数为0.851),而学员2的中位数是0.972(均数为0.893)。RNFL的平均厚度也显示出好的一致性,和学员1的中位数差值3.4μm相比,学员2的一致性稍好,其中位数差值是-0.3μm。学员1测量的RNFL厚度始终比学员2和老师的厚。RGC+厚度的相关性学员2好于学员1,学员2的相关性中位数是0.980(均数为0,967);学员1的相关性中位数是0.943(均数为0.932);学员2的中位数差值是0μm,学员1是3.5μm;学员1的分层显示的RGC+厚度较薄。RGC+的平均厚度也显示出良好的一致性。
结论:经过训练的分层者能对全视网膜、RNFL和RGC+的分层产生良好的一致性;训练应当包括一个测试阶段和定量分析;电脑辅助的手动分层能用于评价自动算法的分层,也可以用于一些自动算法不能进行的少量的实验性分层。
第三部分
目的:比较微视野、标准自动视野计、多焦视觉诱发电位和傅立叶光学干涉断层扫描在青光眼黄斑损害中的改变,建立青光眼黄斑区结构和功能损害的研究模式,并从多方面的对比研究中探讨对青光眼黄斑区结构和功能改变的关系。
方法:6例有中心视野缺损的青光眼患者的7只眼纳入研究,视野检查采用标准自动视野计Humphrey Field AnalyzerⅡ,检测程序采用24-2和10-2瑞典相关阈值算法(Swedish Interactive Threshold Algorithm,SITA),患者最佳矫正视力≥0.8;球镜屈光度在±6.0屈光度以内;柱镜屈光度在±2.0屈光度以内。所有正常受试者最佳矫正视力≥0.8。微视野采用4-2阈值程序,视标为GoldmannⅠ,刺激点间隔1°,刺激点阵列为8×8,刺激范围7°(直径)。VERIS 5.0多焦电生理系统用于记录多焦视觉诱发电位,采用由60个扇形区组成的飞镖盘刺激图形,每个扇形区内有16个棋盘格,8个白色(亮度为200cd/m~2),8个黑色(亮度＜3cd/m~2),刺激范围44.6°(直径)。傅立叶光学干涉断层扫描用于扫描正常对照的20例正常个体的20只眼和6例青光眼的7只眼,每只眼做3D扫描和水平线性扫描,应用电脑辅助手动分层技术对视网膜神经纤维层、视网膜节细胞层、内核层和全感光细胞层进行分层并计算其厚度。
结果:患者组黄斑区视网膜节细胞层的厚度明显比正常对照组薄(p＜0.001),神经纤维层、内核层和全感光细胞层在各组间无显著性差异;水平中线附近及上下方微视野和10-2视野缺损部位与神经节细胞厚度降低的区域呈现良好的一致性;在mfVEP和微视野及10-2视野的对比中,微视野光敏感度越低,mfVEP的信噪比也越低,10-2视野敏感度阈值和mfVEP信噪比的关系也表现出同样的趋势;在微视野检测范围内,mfVEP振幅降低的区域和微视野敏感度降低的部位有良好的一致性。
结论:黄斑区细致结构和功能改变的研究模式有效可行,黄斑区的结构和功能改变有良好的一致性,客观功能检查(mfVEP)能证实主观功能检查的可靠性,该研究模式为青光眼黄斑区结构和功能研究提供了有效研究途径,也为青光眼的早期诊断和治疗以及青光眼进展的监控提供了重要手段。
Part One:Local Retinal Ganglion Cell Thickness Can Be Measured in Patients with Glaucoma Using Frequency-Domain Optical Coherence Tomography
Objective:To explore the feasibility of obtaining a local measure of the thickness of the retinal ganglion cell layer in patients with glaucoma using frequency-domain optical coherence tomography(FD-OCT) and a computer assisted manual segmentation procedure.
Methods:FD-OCT scans of 3D and horizontal line were obtained from one eye of 26 glaucoma patients and 20 control subjects.The thickness of various layers was measured with a manual segmentation procedure aided by a computer program.The patients were divided into low and high sensitivity groups based upon their foveal sensitivity on standard automated perimetry.
Results:The thicknesses of the RGC plus inner plexiform and the retinal nerve fiber layers of the low sensitivity group were significantly thinner than those of the high sensitivity group.While the thickness of these layers in the patients was thinner than controls,the thicknesses of INL and receptor layer were similar in all 3 groups. Further,the thinning of the RGC+layer in one glaucoma eye showed qualitative correspondence to the loss in 10-2 visual field sensitivity.
Conclusions:Local measures of RGC layer thickness can be obtained from FD-OCT scans using a manual segmentation procedure and these measures show a qualitative agreement with visual field sensitivity.
Part Two:Reliability Study of Manual Segmentation for Retinal Layers Using Computer Assisted Procedure
Objective:To explore a training procedure to the trainee on segmenting the retinal layers using computer assisted program and discuss the reliability of segmentation for providing information to the automatic algorithm.
Methods:Forty FD-OCT line scans from 40 individuals were divided into 2 sets of 20,the Training Set and Test Set.Each set had scans from 10 individual with normal vision and 10 patients with glaucoma.The segmentation was divided into 2 sessions, Training Session and Testing Session.Trainees and experts segmented 20 scans in the Training Session with teaching and consulting.In the Testing Session,trainees and experts completed segmentation for another 20 scans without consulting.The thickness of the RNFL,RGC+ and total retina were calculated based on the boundaries of each layer.Concordance correlation coefficient of the thickness of each layer and the average thickness of each layer were calculated between trainees and experts.
Results:For the total retinal thickness,the concordance correlations were very good for both trainees and for all 20 scans with a median of 0.999(mean:0.998) and 0.999 (mean:0.998) for trainee 1 and 2,respectively.The average total retinal thickness also showed good agreement.The concordance correlation of the RNFL was slight lower than the total retina.Compared to the trainee 2 with a median of 0.972(mean:0.892), trainee 1 was worse with a median of 0.940(mean:0.851).The average thickness of RNFL showed good agreement.The agreement was slightly better for trainee 2, whose median difference was-0.3μm,as compared to a median difference of 3.4μm for trainee 1.Trainee 1's RNFL thickness was constantly thicker than trainee 2 and experts.For the correlation of the RGC+ thickness,trainee 1 had a median of 0.934 (0.932) and trainee 2 had a median of 0.980(mean:0.967).The median difference of trainee 1 was 3.5μm and trainee 2 had a median difference of 0μm.The average thickness of RGC+ also showed good agreement.
Conclusions:Trainees showed good agreement to the thickness of total retina,RNFL and RGC+ after training session.Training should contain a test session and quantitative analysis.Computer assisted manual segmentation can be used to assess segmentation done by algorithms.It also can be used for experiments with limited number scans and algorithms not available and/or are of questionable value.
Part Three:An Evaluation of Local Glacomatous Damage in the Macula Using Microperimetry,Standard Automated Perimetry, Multifocal Visual Evoked Potential and Frequency Domain Optical Coherence Tomography
Objective:To compare the changes of microperimetry,standard automatic perimetry, multifocal visual evoked potential and frequency domain optical coherence tomography in macular damage of glaucoma.To establish a study approach for glaucomatous macular damage and discuss the correlation of structure and function changes in macular area of glaucoma.
Methods:Seven eyes of 6 glaucoma patients were included in the study.Humphrey visual field with 24-2 and 10-2 threshold strategy(SITA) was used to test the visual field.Patients had best corrected visual acuity greater than 0.8,spherical refraction within±6.00 diopters and cylinder correction within±2.00 diopters.Normal controls had corrected visual acuity greater than 0.8.Microperimetry was performed on all subjects using the MP-1 Microperimeter.4-2 strategy was used.The stimulus size was GoldmannⅠ.Microperimetry setting was customized using 8×8 grid pattern of 64 stimuli covering 7°.All glaucoma patients underwent the mfVEP using VERIS 5.0 software The dartboard pattern consisted of 60 sectors,each with a checkerboard pattern of 16 checks,8 white (luminance=200 cd/m~2),and 8 black(luminance＜3 cd/m~2).The display had a diameter of 44.6°. All patients and normal controls underwent frequency domain OCT scan.The scan types were macular line scan and 3D scan.Computer assisted segmentation program was used to segment the layers of RNFL,RGC+,INL and total receptor.The thickness of these 4 layers was calculated.
Results:RGC+ thickness in patient's group was thinner than controls(p＜0.001).The thickness of RNFL,INL and total retina had no significance.It had good agreement between the structural changes and microperimetry and 10-2 HVF defect around horizontal meridian.Some area showed the structural changes earlier than functional defect.In the comparison between mfVEP and microperimetry,the lower the sensitivity,the lower the mfVEP signal to noise ratio.Compared 10-2 HVF to mfVEP,it also showed the same tendency.In the testing area of microperimetry,the amplitude reduction of the local responses corresponded to the local sensitivity loss well.
Conclusions:The approach for study the detailed changes on structure and function in macular is feasible.The changes between structure and function showed good agreement.The objective functional test(mfVEP) confirmed the reliability of the subjective test.The approach provided an effective method to study glaucomatous changes in macular.It is also a useful tool for early diagnosis of glaucoma and monitoring the progression of the disease.
引文
[1] Bowd C, Zangwill LM, Medeiros FA, et al. Structure-function relationships using confocal scanning laser ophthalmoscopy, optical coherence tomography, and scanning laser polarimetry[J]. Invest Ophthalmol Vis Sci, 2006, 47(7):2889-2895.
[2] Garway-Heath DF. Comparison of structural and functional methods. I. In Glaucoma Diagnosis[M]. Structure and Function RNWaELG, eds., Amsterdam:Kugler Publications, 2004:135-143.
[3] Hood DC, Kardon RH. A framework for comparing structural and functional measures of glaucomatous damage[J]. Prog Retin Eye Res, 2007, 26(6):688-710.
[4] Garway-Heath DF, Poinoosawmy D, Fitzke FW, Hitchings RA. Mapping the visual field to the optic disc in normal tension glaucoma eyes[J].Ophthalmology, 2000, 107(10):1809-1815.
[5] Hood DC, Anderson SC, Wall M, Kardon RH. Structure versus function in glaucoma: an application of a linear model[J]. Invest Ophthalmol Vis Sci, 2007, 48(8):3662-3668.
[6] Hood DC, Lin CE, Lazow MA, Locke KG, Zhang X, Birch DG Thickness of Receptor and Post-receptor Retinal Layers in Patients with Retinitis Pigmentosa Measured with Frequency-Domain Optical Coherence Tomography (fdOCT) [J]. Invest Ophthalmol Vis Sci, 2008, 14[Epub].
[7] Lim JI, Tan O, Fawzi AA, Hopkins JJ, Gil-Flamer JH, Huang D. A pilot study of fourier-domain optical coherence tomography of retinal dystrophy patients[J].Am J Ophthalmol, 2008, 146(3):417-426.
[6] Drasdo N, Millican CL, Katholi CR, Curcio CA. The length of Henle fibers in the human retina and a model of ganglion receptive field density in the visual field[J]. Vision Res, 2007, 47(22):2901-2911.
[9] Frishman LJ, Reddy MG, Robson JG Effects of background light on the human dark-adapted electroretinogram and psychophysical threshold[J]. J Opt Soc Am A Opt Image Sci Vis, 1996, 13(3):601-612.
[10] Glovinsky Y, Quigley HA, Pease ME. Foveal ganglion cell loss is size dependent in experimental glaucoma[J]. Invest Ophthalmol Vis Sci, 1993, 34(2):395-400.
[11] Budenz DL, Michael A, Chang RT, McSoley J, Katz J. Sensitivity and specificity of the StratusOCT for perimetric glaucoma[J]. Ophthalmology, Jan 2005,112(1):3-9.
[12] Kanadani FN, Hood DC, Grippo TM, et al. Structural and functional assessment of the macular region in patients with glaucoma[J]. Br J Ophthalmol, 2006, 90(11):1393-1397.
[13] Leung CK, Chan WM, Yung WH, et al. Comparison of macular and peripapillary measurements for the detection of glaucoma: an optical coherence tomography study[J]. Ophthalmology, 2005,112(3):391-400.
[14] Nouri-Mahdavi K, Hoffman D, Tannenbaum DP, Law SK, Caprioli J. Identifying early glaucoma with optical coherence tomography[J]. Am J Ophthalmol, 2004,137(2):228-235.
[ 15] Sanchez-Galeana CA, Bowd C, Zangwill LM, Sample PA, Weinreb RN. Short-wavelength automated perimetry results are correlated with optical coherence tomography retinal nerve fiber layer thickness measurements in glaucomatous eyes[J]. Ophthalmology, 2004, 111(10):1866-1872.
[16] Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography[J]. Science, 1991, 254(5035):l 178-1181.
[17] Baroni M, Fortunato P, La Torre A. Towards quantitative analysis of retinal features in optical coherence tomography[J]. Med Eng Phys, 2007, 29(4):432-441.
[ 18] Burgansky-Eliash Z, Wollstein G, Chu T, et al. Optical coherence tomography machine learning classifiers for glaucoma detection: a preliminary study[J]. Invest Ophthalmol Vis Sci. 2005, 46(11):4147-4152.
[ 19] Chan A, Duker JS, Ishikawa H, Ko TH, Schuman JS, Fujimoto JG Quantification of photoreceptor layer thickness in normal eyes using optical coherence tomography[J].Retina,2006,26(6):655-660.
[20]Ishikawa H,Stein DM,Wollstein G,Beaton S,Fujimoto JG,Schuman JS.Macular segmentation with optical coherence tomography[J].Invest Ophthalmol Vis Sci,2005,46(6):2012-2017.
[21]Ko TH,Fujimoto JG,Schuman JS,et al.Comparison of ultrahigh- and standard-resolution optical coherence tomography for imaging macular pathology[J].Ophthalmology,2005,112(11):1922 e1921-1915.
[22]Koozekanani D,Boyer K,Roberts C.Retinal thickness measurements from optical coherence tomography using a Markov boundary model[J].IEEE Trans Med Imaging,2001,20(9):900-916.
[23]Niemeijer M,Abramoff MD,van Ginneken B.Segmentation of the optic disc,macula and vascular arch in fundus photographs[J].IEEE Trans Med lmaging,2007,26(1):116-127.
[24]Wollstein G,Paunescu LA,Ko TH,et al.Ultrahigh-resolution optical coherence tomography in glaucoma[J].Ophthalmology,2005,112(2):229-237.
[25]Cabrera Fern(?)ndez D SH,Puliafito CA.Automated detection of retinal layer structures on optical coherence tomography images[J].Opt.Express,2005,13(25):10 200-210 216.
[26]Haeker M,Abramoff MD,Wu X,Kardon R,Sonka M.Use of varying constraints in optimal 3-D graph search for segmentation of macular optical coherence tomography images[J].Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv,2007,10(Pt 1):244-251.
[27]Haeker M AM,Kardon R,Sonka M..Segmentation of the surfaces of the retinal layer from OCT images[M].Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCA1 2006),Part I;New York.Springer,2006,Lecture Notes Computer Science:800-807.
[28]Hammer DX,Ferguson RD,Magill JC,et al.Active retinal tracker for clinical optical coherence tomography systems[J].J Biomed Opt,2005,10(2):024038.
[29]Lee S,Abramoff MD,Reinhardt JM.Validation of retinal image registration algorithms by a projective imaging distortion model[J].Conf Proc IEEE Eng Med Biol Soc,2007,6472-6475.
[30]Shahidi M,Wang Z,Zelkha R.Quantitative thickness measurement of retinal layers imaged by optical coherence tomography[J].Am J Ophthalmol,2005,139(6):1056-1061.
[31]Legarreta JE,Gregori G,Punjabi OS,Knighton RW,Lalwani GA,Puliafito CA.Macular thickness measurements in normal eyes using spectral domain optical coherence tomography[J].Ophthalmic Surg Lasers Imaging,2008,39(4 Suppl):S43-49.
[32]Niemeijer M,van Ginneken B,Russell SR,Suttorp-Schulten MS,Abramoff MD.Automated detection and differentiation of drusen,exudates,and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis[J].Invest Ophthalmol Vis Sci,2007,48(5):2260-2267.
[33]Suri JS,Liu K,Singh S,Laxminarayan SN,Zeng X,Reden L.Shape recovery algorithms using level sets in 2-D/3-D medical imagery:a state-of-the-art review[J].IEEE Trans Inf Technol Biomed,2002,6(1):8-28.
[34]Hood DC,Raza AS,Kay KY,et al.A comparison of retinal nerve fiber layer (RNFL) thickness obtained with frequency and time domain optical coherence tomography(OCT)[J].Opt Express,2009,17(5):3997-4003.
[35]Garvin MK,Abramoff MD,Kardon R,Russell SR,Wu X,Sonka M.Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search[J].IEEE Trans Med Imaging,2008,27(10):1495-1505.
[36]Lin LI-K.A concordance correlation coefficient to evaluate reproducibility[J].Biometrics,1989,45(1):255-268.
[37]Nickerson CAE.A Note on "A Concordance Correlation Coefficient to Evaluate Reproducibility"[J].Biometrics,1997,53(4):1503-1507.
[38]Zeyen TG,Caprioli J.Progression of disc and field damage in early glaucoma[J].Arch Ophthalmol,1993,111(1):62-65.
[39]Greenfield DS,Bagga H,Knighton RW.Macular thickness changes in glaucomatous optic neuropathy detected using optical coherence tomography[J]. Arch Ophthalmol, 2003,121(l):41-46.
[40] Medeiros FA, Zangwill LM, Bowd C, Vessani RM, Susanna R, Jr., Weinreb RN. Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography[J]. Am J Ophthalmol, 2005,139(1):44-55.
[41] Quigley HA, Dunkelberger GR, Green WR. Retinal ganglion cell atrophy correlated with automated perimetry in human eyes with glaucoma[J]. Am J Ophthalmol, 15 1989,107(5):453-464.
[42] Zeimer R. Nature is teaching us to be humble in our quest to measure structure and function in glaucoma[J]. Br J Ophthalmol, 2007, 91(l):2-3.
[43] Curcio CA, Allen KA. Topography of ganglion cells in human retina[J]. J Comp Neurol, 1990, 300(l):5-25.
[44] Gurses-Ozden R, Teng C, Vessani R, Zafar S, Liebmann JM, Ritch R. Macular and retinal nerve fiber layer thickness measurement reproducibility using optical coherence tomography (OCT-3) [J]. J Glaucoma, 2004,13(3):238-244.
[45] Zeimer R, Asrani S, Zou S, Quigley H, Jampel H. Quantitative detection of glaucomatous damage at the posterior pole by retinal thickness mapping. A pilot study[J]. Ophthalmology, 1998, 105(2):224-231.
[46] Kwon YH PM, Anderson SC, Kim YI, Kardon RH. Quantitative correlation of elevated intraocular pressure with relative afferent pupillary defect change in unilateral glaucoma[J]. Ada Ophthalmol Scand Suppl, 2005, 83(1):127-129.
[47] Nuzzi R BA, Boles-Carenini B. Glaucoma, lighting and color vision. An investigation into their interrelationship[J]. Ophthalmologica, 1997,
[48] Sit AJ MF, Weinreb RN. Short-wavelength automated perimetry can predict glaucomatous standard visual field loss by ten years[J]. Semin Ophthalmol, 2004,19(3-4):122-124.
[49] Stefan C RD, Nenciu A, Tebeanu E. Color vision in glaucoma[J]. Oftalmologia, 2005,49((1)):17-21.
[50] Yamazaki Y MK, Hayamizu F, Tanaka C. Correlation of blue chromatic macular sensitivity with optic disc change in early glaucoma patients[J]. Jpn J Ophthalmol, 2002,46(1):89-94.
[51] E M. Microperimetry[J]. Arch SocEsp Oftalmol, 2006, 81 (4): 183-186.
[52] Midena E RP, Convento E, Cavarzeran F. Macular automatic fundus perimetry threshold versus standard perimetry threshold[J]. Eur J Ophthalmol, 2007, 17(1):63-68.
[53] Miglior S. Microperimetry and glaucoma[J]. Acta Ophthalmol Scand Suppl, 2002,236:19.
[54] Rohrschneider K, Bultmann S, Springer C. Use of fundus perimetry (microperimetry) to quantify macular sensitivity[J]. Prog Retin Eye Res, 2008,27(5):536-548.
[55] Goldberg I, Graham SL, Klistorner AI. Multifocal objective perimetry in the detection of glaucomatous field loss[J]. Am J Ophthalmol, 2002, 133(1):29-39.
[56] Hood DC, Greenstein VC. Multifocal VEP and ganglion cell damage: applications and limitations for the study of glaucoma[J]. Prog Retin Eye Res, 2003,22(2):201-251.
[57] Hood DC, Greenstein VC, Odel JG, et al. Visual field defects and multifocal visual evoked potentials: evidence of a linear relationship[J]. Arch Ophthalmol, 2002, 120(12): 1672-1681.
[58] Hood DC, Zhang X, Hong JE, Chen CS. Quantifying the benefits of additional channels of multifocal VEP recording[J]. Doc Ophthalmol, 2002, 104(3):303-320.
[59] Hood DC, Zhang X, Winn BJ. Detecting glaucomatous damage with multifocal visual evoked potentials: how can a monocular test work? [J]. J Glaucoma, 2003, 12(1):3-15.
[60] Klistorner AI, Graham SL, Grigg JR, Billson FA. Multifocal topographic visual evoked potential: improving objective detection of local visual field defects[J]. Invest Ophthalmol Vis Sci, 1998, 39(6):937-950.
[61] Tan O, Li G, Lu AT, Varma R, Huang D. Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis[J]. Ophthalmology,2008,115(6):949-956.
[62] Witkin AJ, Ko TH, Fujimoto JG, et al. Ultra-high resolution optical coherence tomography assessment of photoreceptors in retinitis pigmentosa and related diseases[J]. Am J Ophthalmol, 2006,142(6):945-952.
[63] Zhang X, Hood DC, Chen CS, Hong JE. A signal-to-noise analysis of multifocal VEP responses: an objective definition for poor records[J]. Doc Ophthalmol, 2002,104(3):287-302.
[64] Zeimer R, Shahidi M, Mori M, Zou S, Asrani S. A new method for rapid mapping of the retinal thickness at the posterior pole[J]. Invest Ophthalmol Vis Sci, 1996, 37(10):1994-2001.
[65] Desatnik H, Quigley HA, Glovinsky Y. Study of central retinal ganglion cell loss in experimental glaucoma in monkey eyes[J]. J Glaucoma, 1996, 5(1):46-53.
[66] Frishman LJ, Shen FF, Du L, et al. The scotopic electroretinogram of macaque after retinal ganglion cell loss from experimental glaucoma[J]. Invest Ophthalmol Vis Sci, 1996, 37(1): 125-141.
[67] Guedes V, Schuman JS, Hertzmark E, et al. Optical coherence tomography measurement of macular and nerve fiber layer thickness in normal and glaucomatous human eyes[J]. Ophthalmology, 2003, 110(1):177-189.
[68] Huang D CS, Greenfield D, et al.. Advanced Imaging for Glaucoma Study (AIGS)[R]. New Orleans, American Academy of Ophthalmology, 2007
[69] Bagga H, Greenfield DS. Quantitative assessment of structural damage in eyes with localized visual field abnormalities[J]. Am J Ophthalmol, 2004,137(5):797-805.
[70] Quigley HA, Addicks EM, Green WR. Optic nerve damage in human glaucoma. Ⅲ. Quantitative correlation of nerve fiber loss and visual field defect in glaucoma, ischemic neuropathy, papilledema, and toxic neuropathy[J]. Arch Ophthalmol, 1982,100(1): 135-146.
[71] Sommer A, Katz J, Quigley HA, et al. Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss[J]. Arch Ophthalmol, 1991,109(1):77-83.
[72] Wollstein G, Schnman JS, Price LL, et al. Optical coherence tomography (OCT) macular and peripapillary retinal nerve fiber layer measurements and automated visual fields[J]. Am J Ophthalmol, 2004, 138(2):218-225.
[73] Harwerth RS, Carter-Dawson L, Smith EL, 3rd, Barnes G, Holt WF, Crawford ML. Neural losses correlated with visual losses in clinical perimetry[J]. Invest Ophthalmol Vis Sci, 2004,45(9):3152-3160.
[74] Harwerth RS, Quigley HA. Visual field defects and retinal ganglion cell losses in patients with glaucoma[J]. Arch Ophthalmol, 2006,124(6):853-859.
[75] Harwerth RS, Vilupuru AS, Rangaswamy NV, Smith EL, 3rd. The relationship between nerve fiber layer and perimetry measurements[J]. Invest Ophthalmol Vis Sci, 2007,48(2):763-773.
[76] Lederer DE, Schuman JS, Hertzmark E, et al. Analysis of macular volume in normal and glaucomatous eyes using optical coherence tomography[J]. Am J Ophthalmol, 2003,135(6):838-843.
[77] Tanito M, Itai N, Ohira A, Chihara E. Reduction of posterior pole retinal thickness in glaucoma detected using the Retinal Thickness Analyzer[J]. Ophthalmology, 2004, 111(2):265-275.
[78] Bowd C, Zangwill LM, Berry CC, et al. Detecting early glaucoma by assessment of retinal nerve fiber layer thickness and visual function[J]. Invest Ophthalmol Vis Sci, 2001, 42(9): 1993-2003.
[79] Hoh ST, Greenfield DS, Mistlberger A, Liebmann JM, Ishikawa H, Ritch R. Optical coherence tomography and scanning laser polarimetry in normal, ocular hypertensive, and glaucomatous eyes[J]. Am J Ophthalmol, 2000,129(2):129-135.
[80] Mistlberger A, Liebmann JM, Greenfield DS, et al. Heidelberg retina tomography and optical coherence tomography in normal, ocular-hypertensive,and glaucomatous eyes[J]. Ophthalmology, 1999, 106(10):2027-2032.
[81] Weinreb RN, Shakiba S, Sample PA, et al. Association between quantitative nerve fiber layer measurement and visual field loss in glaucoma[J]. Am J Ophthalmol, 1995,120(6):732-738.
[82] Weinreb RN, Shakiba S, Zangwill L. Scanning laser polarimetry to measure the nerve fiber layer of normal and glaucomatous eyes[J]. Am J Ophthalmol, 1995,119(5):627-636.
[83] Zangwill LM, Bowd C, Berry CC, et al. Discriminating between normal and glaucomatous eyes using the Heidelberg Retina Tomograph, GDx Nerve Fiber Analyzer, and Optical Coherence Tomograph[J]. Arch Ophthalmol, 2001,119(7):985-993.
[2] Garway-Heath DF. Comparison of structural and functional methods. I. In Glaucoma Diagnosis[M]. Structure and Function RNWaELG, eds., Amsterdam:Kugler Publications, 2004:135-143.
[3] Hood DC, Kardon RH. A framework for comparing structural and functional measures of glaucomatous damage[J]. Prog Retin Eye Res, 2007, 26(6):688-710.
[4] Garway-Heath DF, Poinoosawmy D, Fitzke FW, Hitchings RA. Mapping the visual field to the optic disc in normal tension glaucoma eyes[J].Ophthalmology, 2000, 107(10):1809-1815.
[5] Hood DC, Anderson SC, Wall M, Kardon RH. Structure versus function in glaucoma: an application of a linear model[J]. Invest Ophthalmol Vis Sci, 2007, 48(8):3662-3668.
[6] Hood DC, Lin CE, Lazow MA, Locke KG, Zhang X, Birch DG Thickness of Receptor and Post-receptor Retinal Layers in Patients with Retinitis Pigmentosa Measured with Frequency-Domain Optical Coherence Tomography (fdOCT) [J]. Invest Ophthalmol Vis Sci, 2008, 14[Epub].
[7] Lim JI, Tan O, Fawzi AA, Hopkins JJ, Gil-Flamer JH, Huang D. A pilot study of fourier-domain optical coherence tomography of retinal dystrophy patients[J].Am J Ophthalmol, 2008, 146(3):417-426.
[6] Drasdo N, Millican CL, Katholi CR, Curcio CA. The length of Henle fibers in the human retina and a model of ganglion receptive field density in the visual field[J]. Vision Res, 2007, 47(22):2901-2911.
[9] Frishman LJ, Reddy MG, Robson JG Effects of background light on the human dark-adapted electroretinogram and psychophysical threshold[J]. J Opt Soc Am A Opt Image Sci Vis, 1996, 13(3):601-612.
[10] Glovinsky Y, Quigley HA, Pease ME. Foveal ganglion cell loss is size dependent in experimental glaucoma[J]. Invest Ophthalmol Vis Sci, 1993, 34(2):395-400.
[11] Budenz DL, Michael A, Chang RT, McSoley J, Katz J. Sensitivity and specificity of the StratusOCT for perimetric glaucoma[J]. Ophthalmology, Jan 2005,112(1):3-9.
[12] Kanadani FN, Hood DC, Grippo TM, et al. Structural and functional assessment of the macular region in patients with glaucoma[J]. Br J Ophthalmol, 2006, 90(11):1393-1397.
[13] Leung CK, Chan WM, Yung WH, et al. Comparison of macular and peripapillary measurements for the detection of glaucoma: an optical coherence tomography study[J]. Ophthalmology, 2005,112(3):391-400.
[14] Nouri-Mahdavi K, Hoffman D, Tannenbaum DP, Law SK, Caprioli J. Identifying early glaucoma with optical coherence tomography[J]. Am J Ophthalmol, 2004,137(2):228-235.
[ 15] Sanchez-Galeana CA, Bowd C, Zangwill LM, Sample PA, Weinreb RN. Short-wavelength automated perimetry results are correlated with optical coherence tomography retinal nerve fiber layer thickness measurements in glaucomatous eyes[J]. Ophthalmology, 2004, 111(10):1866-1872.
[16] Huang D, Swanson EA, Lin CP, et al. Optical coherence tomography[J]. Science, 1991, 254(5035):l 178-1181.
[17] Baroni M, Fortunato P, La Torre A. Towards quantitative analysis of retinal features in optical coherence tomography[J]. Med Eng Phys, 2007, 29(4):432-441.
[ 18] Burgansky-Eliash Z, Wollstein G, Chu T, et al. Optical coherence tomography machine learning classifiers for glaucoma detection: a preliminary study[J]. Invest Ophthalmol Vis Sci. 2005, 46(11):4147-4152.
[ 19] Chan A, Duker JS, Ishikawa H, Ko TH, Schuman JS, Fujimoto JG Quantification of photoreceptor layer thickness in normal eyes using optical coherence tomography[J].Retina,2006,26(6):655-660.
[20]Ishikawa H,Stein DM,Wollstein G,Beaton S,Fujimoto JG,Schuman JS.Macular segmentation with optical coherence tomography[J].Invest Ophthalmol Vis Sci,2005,46(6):2012-2017.
[21]Ko TH,Fujimoto JG,Schuman JS,et al.Comparison of ultrahigh- and standard-resolution optical coherence tomography for imaging macular pathology[J].Ophthalmology,2005,112(11):1922 e1921-1915.
[22]Koozekanani D,Boyer K,Roberts C.Retinal thickness measurements from optical coherence tomography using a Markov boundary model[J].IEEE Trans Med Imaging,2001,20(9):900-916.
[23]Niemeijer M,Abramoff MD,van Ginneken B.Segmentation of the optic disc,macula and vascular arch in fundus photographs[J].IEEE Trans Med lmaging,2007,26(1):116-127.
[24]Wollstein G,Paunescu LA,Ko TH,et al.Ultrahigh-resolution optical coherence tomography in glaucoma[J].Ophthalmology,2005,112(2):229-237.
[25]Cabrera Fern(?)ndez D SH,Puliafito CA.Automated detection of retinal layer structures on optical coherence tomography images[J].Opt.Express,2005,13(25):10 200-210 216.
[26]Haeker M,Abramoff MD,Wu X,Kardon R,Sonka M.Use of varying constraints in optimal 3-D graph search for segmentation of macular optical coherence tomography images[J].Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv,2007,10(Pt 1):244-251.
[27]Haeker M AM,Kardon R,Sonka M..Segmentation of the surfaces of the retinal layer from OCT images[M].Proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCA1 2006),Part I;New York.Springer,2006,Lecture Notes Computer Science:800-807.
[28]Hammer DX,Ferguson RD,Magill JC,et al.Active retinal tracker for clinical optical coherence tomography systems[J].J Biomed Opt,2005,10(2):024038.
[29]Lee S,Abramoff MD,Reinhardt JM.Validation of retinal image registration algorithms by a projective imaging distortion model[J].Conf Proc IEEE Eng Med Biol Soc,2007,6472-6475.
[30]Shahidi M,Wang Z,Zelkha R.Quantitative thickness measurement of retinal layers imaged by optical coherence tomography[J].Am J Ophthalmol,2005,139(6):1056-1061.
[31]Legarreta JE,Gregori G,Punjabi OS,Knighton RW,Lalwani GA,Puliafito CA.Macular thickness measurements in normal eyes using spectral domain optical coherence tomography[J].Ophthalmic Surg Lasers Imaging,2008,39(4 Suppl):S43-49.
[32]Niemeijer M,van Ginneken B,Russell SR,Suttorp-Schulten MS,Abramoff MD.Automated detection and differentiation of drusen,exudates,and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis[J].Invest Ophthalmol Vis Sci,2007,48(5):2260-2267.
[33]Suri JS,Liu K,Singh S,Laxminarayan SN,Zeng X,Reden L.Shape recovery algorithms using level sets in 2-D/3-D medical imagery:a state-of-the-art review[J].IEEE Trans Inf Technol Biomed,2002,6(1):8-28.
[34]Hood DC,Raza AS,Kay KY,et al.A comparison of retinal nerve fiber layer (RNFL) thickness obtained with frequency and time domain optical coherence tomography(OCT)[J].Opt Express,2009,17(5):3997-4003.
[35]Garvin MK,Abramoff MD,Kardon R,Russell SR,Wu X,Sonka M.Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search[J].IEEE Trans Med Imaging,2008,27(10):1495-1505.
[36]Lin LI-K.A concordance correlation coefficient to evaluate reproducibility[J].Biometrics,1989,45(1):255-268.
[37]Nickerson CAE.A Note on "A Concordance Correlation Coefficient to Evaluate Reproducibility"[J].Biometrics,1997,53(4):1503-1507.
[38]Zeyen TG,Caprioli J.Progression of disc and field damage in early glaucoma[J].Arch Ophthalmol,1993,111(1):62-65.
[39]Greenfield DS,Bagga H,Knighton RW.Macular thickness changes in glaucomatous optic neuropathy detected using optical coherence tomography[J]. Arch Ophthalmol, 2003,121(l):41-46.
[40] Medeiros FA, Zangwill LM, Bowd C, Vessani RM, Susanna R, Jr., Weinreb RN. Evaluation of retinal nerve fiber layer, optic nerve head, and macular thickness measurements for glaucoma detection using optical coherence tomography[J]. Am J Ophthalmol, 2005,139(1):44-55.
[41] Quigley HA, Dunkelberger GR, Green WR. Retinal ganglion cell atrophy correlated with automated perimetry in human eyes with glaucoma[J]. Am J Ophthalmol, 15 1989,107(5):453-464.
[42] Zeimer R. Nature is teaching us to be humble in our quest to measure structure and function in glaucoma[J]. Br J Ophthalmol, 2007, 91(l):2-3.
[43] Curcio CA, Allen KA. Topography of ganglion cells in human retina[J]. J Comp Neurol, 1990, 300(l):5-25.
[44] Gurses-Ozden R, Teng C, Vessani R, Zafar S, Liebmann JM, Ritch R. Macular and retinal nerve fiber layer thickness measurement reproducibility using optical coherence tomography (OCT-3) [J]. J Glaucoma, 2004,13(3):238-244.
[45] Zeimer R, Asrani S, Zou S, Quigley H, Jampel H. Quantitative detection of glaucomatous damage at the posterior pole by retinal thickness mapping. A pilot study[J]. Ophthalmology, 1998, 105(2):224-231.
[46] Kwon YH PM, Anderson SC, Kim YI, Kardon RH. Quantitative correlation of elevated intraocular pressure with relative afferent pupillary defect change in unilateral glaucoma[J]. Ada Ophthalmol Scand Suppl, 2005, 83(1):127-129.
[47] Nuzzi R BA, Boles-Carenini B. Glaucoma, lighting and color vision. An investigation into their interrelationship[J]. Ophthalmologica, 1997,
[48] Sit AJ MF, Weinreb RN. Short-wavelength automated perimetry can predict glaucomatous standard visual field loss by ten years[J]. Semin Ophthalmol, 2004,19(3-4):122-124.
[49] Stefan C RD, Nenciu A, Tebeanu E. Color vision in glaucoma[J]. Oftalmologia, 2005,49((1)):17-21.
[50] Yamazaki Y MK, Hayamizu F, Tanaka C. Correlation of blue chromatic macular sensitivity with optic disc change in early glaucoma patients[J]. Jpn J Ophthalmol, 2002,46(1):89-94.
[51] E M. Microperimetry[J]. Arch SocEsp Oftalmol, 2006, 81 (4): 183-186.
[52] Midena E RP, Convento E, Cavarzeran F. Macular automatic fundus perimetry threshold versus standard perimetry threshold[J]. Eur J Ophthalmol, 2007, 17(1):63-68.
[53] Miglior S. Microperimetry and glaucoma[J]. Acta Ophthalmol Scand Suppl, 2002,236:19.
[54] Rohrschneider K, Bultmann S, Springer C. Use of fundus perimetry (microperimetry) to quantify macular sensitivity[J]. Prog Retin Eye Res, 2008,27(5):536-548.
[55] Goldberg I, Graham SL, Klistorner AI. Multifocal objective perimetry in the detection of glaucomatous field loss[J]. Am J Ophthalmol, 2002, 133(1):29-39.
[56] Hood DC, Greenstein VC. Multifocal VEP and ganglion cell damage: applications and limitations for the study of glaucoma[J]. Prog Retin Eye Res, 2003,22(2):201-251.
[57] Hood DC, Greenstein VC, Odel JG, et al. Visual field defects and multifocal visual evoked potentials: evidence of a linear relationship[J]. Arch Ophthalmol, 2002, 120(12): 1672-1681.
[58] Hood DC, Zhang X, Hong JE, Chen CS. Quantifying the benefits of additional channels of multifocal VEP recording[J]. Doc Ophthalmol, 2002, 104(3):303-320.
[59] Hood DC, Zhang X, Winn BJ. Detecting glaucomatous damage with multifocal visual evoked potentials: how can a monocular test work? [J]. J Glaucoma, 2003, 12(1):3-15.
[60] Klistorner AI, Graham SL, Grigg JR, Billson FA. Multifocal topographic visual evoked potential: improving objective detection of local visual field defects[J]. Invest Ophthalmol Vis Sci, 1998, 39(6):937-950.
[61] Tan O, Li G, Lu AT, Varma R, Huang D. Mapping of macular substructures with optical coherence tomography for glaucoma diagnosis[J]. Ophthalmology,2008,115(6):949-956.
[62] Witkin AJ, Ko TH, Fujimoto JG, et al. Ultra-high resolution optical coherence tomography assessment of photoreceptors in retinitis pigmentosa and related diseases[J]. Am J Ophthalmol, 2006,142(6):945-952.
[63] Zhang X, Hood DC, Chen CS, Hong JE. A signal-to-noise analysis of multifocal VEP responses: an objective definition for poor records[J]. Doc Ophthalmol, 2002,104(3):287-302.
[64] Zeimer R, Shahidi M, Mori M, Zou S, Asrani S. A new method for rapid mapping of the retinal thickness at the posterior pole[J]. Invest Ophthalmol Vis Sci, 1996, 37(10):1994-2001.
[65] Desatnik H, Quigley HA, Glovinsky Y. Study of central retinal ganglion cell loss in experimental glaucoma in monkey eyes[J]. J Glaucoma, 1996, 5(1):46-53.
[66] Frishman LJ, Shen FF, Du L, et al. The scotopic electroretinogram of macaque after retinal ganglion cell loss from experimental glaucoma[J]. Invest Ophthalmol Vis Sci, 1996, 37(1): 125-141.
[67] Guedes V, Schuman JS, Hertzmark E, et al. Optical coherence tomography measurement of macular and nerve fiber layer thickness in normal and glaucomatous human eyes[J]. Ophthalmology, 2003, 110(1):177-189.
[68] Huang D CS, Greenfield D, et al.. Advanced Imaging for Glaucoma Study (AIGS)[R]. New Orleans, American Academy of Ophthalmology, 2007
[69] Bagga H, Greenfield DS. Quantitative assessment of structural damage in eyes with localized visual field abnormalities[J]. Am J Ophthalmol, 2004,137(5):797-805.
[70] Quigley HA, Addicks EM, Green WR. Optic nerve damage in human glaucoma. Ⅲ. Quantitative correlation of nerve fiber loss and visual field defect in glaucoma, ischemic neuropathy, papilledema, and toxic neuropathy[J]. Arch Ophthalmol, 1982,100(1): 135-146.
[71] Sommer A, Katz J, Quigley HA, et al. Clinically detectable nerve fiber atrophy precedes the onset of glaucomatous field loss[J]. Arch Ophthalmol, 1991,109(1):77-83.
[72] Wollstein G, Schnman JS, Price LL, et al. Optical coherence tomography (OCT) macular and peripapillary retinal nerve fiber layer measurements and automated visual fields[J]. Am J Ophthalmol, 2004, 138(2):218-225.
[73] Harwerth RS, Carter-Dawson L, Smith EL, 3rd, Barnes G, Holt WF, Crawford ML. Neural losses correlated with visual losses in clinical perimetry[J]. Invest Ophthalmol Vis Sci, 2004,45(9):3152-3160.
[74] Harwerth RS, Quigley HA. Visual field defects and retinal ganglion cell losses in patients with glaucoma[J]. Arch Ophthalmol, 2006,124(6):853-859.
[75] Harwerth RS, Vilupuru AS, Rangaswamy NV, Smith EL, 3rd. The relationship between nerve fiber layer and perimetry measurements[J]. Invest Ophthalmol Vis Sci, 2007,48(2):763-773.
[76] Lederer DE, Schuman JS, Hertzmark E, et al. Analysis of macular volume in normal and glaucomatous eyes using optical coherence tomography[J]. Am J Ophthalmol, 2003,135(6):838-843.
[77] Tanito M, Itai N, Ohira A, Chihara E. Reduction of posterior pole retinal thickness in glaucoma detected using the Retinal Thickness Analyzer[J]. Ophthalmology, 2004, 111(2):265-275.
[78] Bowd C, Zangwill LM, Berry CC, et al. Detecting early glaucoma by assessment of retinal nerve fiber layer thickness and visual function[J]. Invest Ophthalmol Vis Sci, 2001, 42(9): 1993-2003.
[79] Hoh ST, Greenfield DS, Mistlberger A, Liebmann JM, Ishikawa H, Ritch R. Optical coherence tomography and scanning laser polarimetry in normal, ocular hypertensive, and glaucomatous eyes[J]. Am J Ophthalmol, 2000,129(2):129-135.
[80] Mistlberger A, Liebmann JM, Greenfield DS, et al. Heidelberg retina tomography and optical coherence tomography in normal, ocular-hypertensive,and glaucomatous eyes[J]. Ophthalmology, 1999, 106(10):2027-2032.
[81] Weinreb RN, Shakiba S, Sample PA, et al. Association between quantitative nerve fiber layer measurement and visual field loss in glaucoma[J]. Am J Ophthalmol, 1995,120(6):732-738.
[82] Weinreb RN, Shakiba S, Zangwill L. Scanning laser polarimetry to measure the nerve fiber layer of normal and glaucomatous eyes[J]. Am J Ophthalmol, 1995,119(5):627-636.
[83] Zangwill LM, Bowd C, Berry CC, et al. Discriminating between normal and glaucomatous eyes using the Heidelberg Retina Tomograph, GDx Nerve Fiber Analyzer, and Optical Coherence Tomograph[J]. Arch Ophthalmol, 2001,119(7):985-993.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |