Breast MRI radiomics and machine learning-based predictions of response to neoadjuvant chemotherapy - How are they affected by variations in tumor delineation?

Manual delineation of volumes of interest (VOIs) by experts is considered the gold-standard method in radiomics analysis. However, it suffers from inter- and intra-operator variability. A quantitative assessment of the impact of variations in these delineations on the performance of the radiomics predictors is required to develop robust radiomics based prediction models. In this study, we developed radiomics models for the prediction of pathological complete response to neoadjuvant chemotherapy in patients with two different breast cancer subtypes based on contrast-enhanced magnetic resonance imaging acquired prior to treatment (baseline MRI scans). Different mathematical operations such as erosion, smoothing, dilation, randomization, and ellipse fitting were applied to the original VOIs delineated by experts to simulate variations of segmentation masks. The effects of such VOI modifications on various steps of the radiomics workflow, including feature extraction, feature selection, and prediction performance, were evaluated. Using manual tumor VOIs and radiomics features extracted from baseline MRI scans, an AUC of up to 0.96 and 0.89 was achieved for human epidermal growth receptor 2 positive and triple-negative breast cancer, respectively. For smoothing and erosion, VOIs yielded the highest number of robust features and the best prediction performance, while ellipse fitting and dilation lead to the lowest robustness and prediction performance for both breast cancer subtypes. At most 28% of the selected features were similar to manual VOIs when different VOI delineation data were used. Differences in VOI delineation affect different steps of radiomics analysis, and their quantification is therefore important for development of standardized radiomics research.

Characteristics of Henle's fiber layer in healthy and glaucoma eyes assessed by polarization-sensitive optical coherence tomography.

Using conventional optical coherence tomography (OCT), it is difficult to image Henle fibers (HF) due to their low backscattering potential. However, fibrous structures exhibit form birefringence, which can be exploited to visualize the presence of HF by polarization-sensitive (PS) OCT. We found a slight asymmetry in the retardation pattern of HF in the fovea region that can be associated with the asymmetric decrease of cone density with eccentricity from the fovea. We introduce a new measure based on a PS-OCT assessment of optic axis orientation to estimate the presence of HF at various eccentricities from the fovea in a large cohort of 150 healthy subjects. By comparing a healthy age-matched sub-group (N = 87) to a cohort of 64 early-stage glaucoma patients, we found no significant difference in HF extension but a slightly decreased retardation at about 2° to 7.5° eccentricity from the fovea in the glaucoma patients. This potentially indicates that glaucoma affects this neuronal tissue at an early state.

Assessing the external validity of machine learning-based detection of glaucoma.

Studies using machine learning (ML) approaches have reported high diagnostic accuracies for glaucoma detection. However, none assessed model performance across ethnicities. The aim of the study is to externally validate ML models for glaucoma detection from optical coherence tomography (OCT) data. We performed a prospective, cross-sectional study, where 514 Asians (257 glaucoma/257 controls) were enrolled to construct ML models for glaucoma detection, which was then tested on 356 Asians (183 glaucoma/173 controls) and 138 Caucasians (57 glaucoma/81 controls). We used the retinal nerve fibre layer (RNFL) thickness values produced by the compensation model, which is a multiple regression model fitted on healthy subjects that corrects the RNFL profile for anatomical factors and the original OCT data (measured) to build two classifiers, respectively. Both the ML models (area under the receiver operating [AUC] = 0.96 and accuracy = 92%) outperformed the measured data (AUC = 0.93; P < 0.001) for glaucoma detection in the Asian dataset. However, in the Caucasian dataset, the ML model trained with compensated data (AUC = 0.93 and accuracy = 84%) outperformed the ML model trained with original data (AUC = 0.83 and accuracy = 79%; P < 0.001) and measured data (AUC = 0.82; P < 0.001) for glaucoma detection. The performance with the ML model trained on measured data showed poor reproducibility across different datasets, whereas the performance of the compensated data was maintained. Care must be taken when ML models are applied to patient cohorts of different ethnicities.

Quantitative assessment of depolarization by the retinal pigment epithelium in healthy and glaucoma subjects measured over a large field of view.

We present measurements of depolarization introduced by the retinal pigment epithelium (RPE) over a 45° field of view using polarization sensitive optical coherence tomography. A detailed spatial distribution analysis of depolarization caused by the RPE is presented in a total of 153 subjects including both healthy and diseased eyes. Age and sex related differences in the depolarizing character of the RPE are investigated.

Birefringent Properties of the Peripapillary Retinal Nerve Fiber Layer in Healthy and Glaucoma Subjects Analyzed by Polarization-Sensitive OCT.

Purpose: To study the circumpapillary retinal nerve fiber layer (RNFL) birefringence (BIR) of early glaucoma and age-matched healthy eyes using polarization-sensitive optical coherence tomography (PS-OCT). Methods: In this prospective cross-sectional study, we compared virtual circular PS-OCT B-scans with a diameter of 3.5 mm centered on the optic disc (OD) acquired with a PS-OCT prototype (860 nm center wavelength). Early glaucoma was defined by the glaucomatous appearance of the OD and a pathologic visual field test with a mean deviation (MD) better than -6 dB. The main outcome parameters were BIR, RNFL-thickness (RNFL-T), and phase retardation (RET). The BIR value at each virtual A-scan position was the quotient of the RET measured at the inner segment/outer segment junction divided by the RNFL-T. Results: The dataset comprised 49 early glaucoma patients (mean ± standard deviation [SD]: 64 ± 10 years) and 49 healthy control subjects (61 ± 9 years). Glaucomatous eyes showed a statistically significant lower BIR globally (mean ± SD: 0.108 ± 0.008°/µm vs. 0.112 ± 0.009°/µm, P = 0.033), superiorly (0.116 ± 0.017°/µm vs. 0.126 ± 0.013°/µm, P = 0.0001), and inferiorly (0.112 ± 0.011°/µm vs. 0.121 ± 0.011°/µm, P < 0.0001), and increased BIR in the temporal quadrant (0.088 ± 0.015°/µm vs. 0.078 ± 0.014°/µm, P = 0.0001) compared to healthy eyes. Conclusions: We report a reduced BIR of the RNFL in early perimetric glaucoma, which can be interpreted as a sign of loss or change of intracellular microtubules and may contribute to a better understanding of early disease development. Prospective longitudinal studies are needed to determine whether BIR is altered in pre-perimetric human glaucoma before RNFL-T decline.

Multi-modal and multi-scale clinical retinal imaging system with pupil and retinal tracking.

We present a compact multi-modal and multi-scale retinal imaging instrument with an angiographic functional extension for clinical use. The system integrates scanning laser ophthalmoscopy (SLO), optical coherence tomography (OCT) and OCT angiography (OCTA) imaging modalities and provides multi-scale fields of view. For high resolution, and high lateral resolution in particular, cellular imaging correction of aberrations by adaptive optics (AO) is employed. The entire instrument has a compact design and the scanning head is mounted on motorized translation stages that enable 3D self-alignment with respect to the subject's eye by tracking the pupil position. Retinal tracking, based on the information provided by SLO, is incorporated in the instrument to compensate for retinal motion during OCT imaging. The imaging capabilities of the multi-modal and multi-scale instrument were tested by imaging healthy volunteers and patients.

A multi-regression approach to improve optical coherence tomography diagnostic accuracy in multiple sclerosis patients without previous optic neuritis.

BACKGROUND: Optical coherence tomography (OCT) is a retinal imaging system that may improve the diagnosis of multiple sclerosis (MS) persons, but the evidence is currently equivocal. To assess whether compensating the peripapillary retinal nerve fiber layer (pRNFL) thickness for ocular anatomical features as well as the combination with macular layers can improve the capability of OCT in differentiating non-optic neuritis eyes of relapsing-remitting MS patients from healthy controls. METHODS: 74 MS participants (n = 129 eyes) and 84 age- and sex-matched healthy controls (n = 149 eyes) were enrolled. Macular ganglion cell complex (mGCC) thickness was extracted and pRNFL measurement was compensated for ocular anatomical factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between groups. RESULTS: Participants with MS showed significantly thinner mGCC, measured and compensated pRNFL (p ≤ 0.026). Compensated pRNFL achieved better performance than measured pRNFL for MS differentiation (AUC, 0.75 vs 0.80; p = 0.020). Combining macular and compensated pRNFL parameters provided the best discrimination of MS (AUC = 0.85 vs 0.75; p < 0.001), translating to an average improvement in sensitivity of 24 percent for differentiation of MS individuals. CONCLUSION: The capability of OCT in MS differentiation is made more robust by accounting OCT scans for individual anatomical differences and incorporating information from both optic disc and macular regions, representing markers of axonal damage and neuronal injury, respectively.

A multi-regression framework to improve diagnostic ability of optical coherence tomography retinal biomarkers to discriminate mild cognitive impairment and Alzheimer's disease.

BACKGROUND: Diagnostic performance of optical coherence tomography (OCT) to detect Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains limited. We assessed whether compensating the circumpapillary retinal nerve fiber layer (cpRNFL) thickness for multiple demographic and anatomical factors as well as the combination of macular layers improves the detection of MCI and AD. METHODS: This cross-sectional study of 62 AD (n = 92 eyes), 108 MCI (n = 158 eyes), and 55 cognitively normal control (n = 86 eyes) participants. Macular ganglion cell complex (mGCC) thickness was extracted. Circumpapillary retinal nerve fiber layer (cpRNFL) measurement was compensated for several ocular factors. Thickness measurements and their corresponding areas under the receiver operating characteristic curves (AUCs) were compared between the groups. The main outcome measure was OCT thickness measurements. RESULTS: Participants with MCI/AD showed significantly thinner measured and compensated cpRNFL, mGCC, and altered retinal vessel density (p < 0.05). Compensated RNFL outperformed measured RNFL for discrimination of MCI/AD (AUC = 0.74 vs 0.69; p = 0.026). Combining macular and compensated cpRNFL parameters provided the best detection of MCI/AD (AUC = 0.80 vs 0.69; p < 0.001). CONCLUSIONS AND RELEVANCE: Accounting for interindividual variations of ocular anatomical features in cpRNFL measurements and incorporating macular information may improve the identification of high-risk individuals with early cognitive impairment.

Automatic retinal nerve fiber bundle tracing based on large field of view polarization sensitive OCT data.

A technique to accurately estimate trajectories of retinal nerve fiber bundles (RNFB) in a large field of view (FOV) image covering 45° is described. The method utilizes stitched projections of polarization-sensitive optical coherence tomography (PS-OCT) data, as well as a mathematical model of average RNFB trajectories as prior. The fully automatic process was applied to data recorded in healthy subjects and glaucoma patients and automatically detected individual RNFB trajectories are compared to manual traces.

Optical coherence tomography-measured retinal nerve fiber layer thickness values compensated with a multivariate model and discrimination between stable and progressing glaucoma suspects.

PURPOSE: Our previously introduced multivariate model, compensating for intersubject variability, was applied to circumpapillary retinal nerve fiber layer (RNFL) values measured with optical coherence tomography in glaucoma suspects with or without prior progressive optic disc (OD) change in a series of confocal scanning laser tomography (CSLT, HRT III) measurements. METHODS: In this prospective study, OD change during CSLT follow-up was determined with strict, moderate, and liberal criteria of the topographic change analysis (TCA). Model compensation (MC) as well as age compensation (AC) was applied to RNFL sectors (RNFLMC vs. RNFLAC). Diagnostic performance of RNFLMC vs. RNFLAC was tested with an area under the receiver operating characteristic (AUROC) and was compared between methods. RESULTS: Forty-two glaucoma suspects were included. Patients without prior progressive OD change during the CSLT follow-up (= stable) had thicker RNFL thickness values in most areas and for all progression criteria. RNFLMC AUROC for the global RNFL (0.719) and the inferior quadrant (0.711) performed significantly better compared with RNFLAC AUROC (0.594 and 0.631) to discriminate between stable and progressive glaucoma suspects as defined by the moderate criteria of CSLT progression analysis (p = 0.028; p = 0.024). CONCLUSION: MC showed a slight but significant improvement in detection of subjects with prior progressive OD change among a group of glaucoma suspects, when compared to AC, which is the compensation method commonly used during OCT data evaluation in daily routine. Further studies are warranted to validate the present results.

Multivariate Normative Comparison, a Novel Method for Improved Use of Retinal Nerve Fiber Layer Thickness to Detect Early Glaucoma.

PURPOSE: Detection of early glaucoma remains limited with the conventional analysis of the retinal nerve fiber layer (RNFL). This study assessed whether compensating the RNFL thickness for multiple demographic and anatomic factors improves the detection of glaucoma. DESIGN: Cross-sectional study. PARTICIPANTS: Three hundred eighty-seven patients with glaucoma and 2699 healthy participants. METHODS: Two thousand six hundred ninety-nine healthy participants were enrolled to construct and test a multivariate compensation model, which then was applied in 387 healthy participants and 387 patients with glaucoma (early glaucoma, n = 219; moderate glaucoma, n = 97; and advanced glaucoma, n = 71). Participants underwent Cirrus spectral-domain OCT (Carl Zeiss Meditec) imaging of the optic disc and macular cubes. Compensated RNFL thickness was generated based on ethnicity, age, refractive error, optic disc (ratio, orientation, and area), fovea (distance and angle), and retinal vessel density. The RNFL thickness measurements and their corresponding areas under the receiver operating characteristic curve (AUCs) were obtained. MAIN OUTCOME AND MEASURES: Measured and compensated RNFL thickness measurements. RESULTS: After applying the Asian-specific compensation model, the standard deviation of RNFL thickness reduced, where the effect was greatest for Chinese participants (16.9%), followed by Malay participants (13.9%), and Indian participants (12.1%). Multivariate normative comparison outperformed measured RNFL for discrimination of early glaucoma (AUC, 0.90 vs. 0.85; P < 0.001), moderate glaucoma (AUC, 0.94 vs. 0.91; P < 0.001), and advanced glaucoma (AUC, 0.98 vs. 0.96; P < 0.001). CONCLUSIONS: The multivariate normative database of RNFL showed better glaucoma discrimination capability than conventional age-matched comparisons, suggesting that accounting for demographic and anatomic variance in RNFL thickness may have usefulness in improving glaucoma detection.

Temporal phase evolution OCT for measurement of tissue deformation in the human retina in-vivo.

We demonstrate the use of temporal phase evolution (TPE-) OCT methods to evaluate retinal tissue deformation in-vivo over time periods of several seconds. A custom built spectral domain (SD)-OCT system with an integrated retinal tracker, ensuring stable imaging with sub-speckle precision, was used for imaging. TPE-OCT measures and images phase differences between an initial reference B-scan and each of the subsequent B-scans of the evaluated temporal sequence. In order to demonstrate the precision and repeatability of the measurements, retinal nerve fiber (RNF) tissue deformations induced by retinal vessels pulsating with the heartbeat were analyzed in several healthy subjects. We show TPE maps (M-scans of phase evolution as a function of position along B-scan trace vs. time) of wrapped phase data and corresponding deformation maps in selected regions of the RNF layer (RNFL) over the course of several cardiac cycles. A reproducible phase pattern is seen at each heartbeat cycle for all imaged volunteers. RNF tissue deformations near arteries and veins up to ∼ 1.6 µm were obtained with an average precision for a single pixel of about 30 nm. Differences of motion induced by arteries and veins are also investigated.

Identification and quantification of fibrotic areas in the human retina using polarization-sensitive OCT.

Subretinal fibrosis is one of the most prevalent causes of blindness in the elderly population, but a true gold standard to objectively diagnose fibrosis is still lacking. Since fibrotic tissue is birefringent, it can be detected by polarization-sensitive optical coherence tomography (PS-OCT). We present a new algorithm to automatically detect, segment, and quantify fibrotic lesions within 3D data sets recorded by PS-OCT. The algorithm first compensates for the birefringence of anterior ocular tissues and then uses the uniformity of the birefringent optic axis as an indicator to identify fibrotic tissue, which is then segmented and quantified. The algorithm was applied to 3D volumes recorded in 57 eyes of 57 patients with neovascular age-related macular degeneration using a spectral domain PS-OCT system. The results of fibrosis detection were compared to the clinical diagnosis based on color fundus photography (CFP), and the precision of fibrotic area measurement was assessed by three repeated measurements in a sub-set of 15 eyes. The average standard deviation of the fibrotic area obtained in eyes with a lesion area > 0.7 mm2 was 15%. Fibrosis detection by CFP and PS-OCT agreed in 48 cases, discrepancies were only observed in cases of lesion area < 0.7 mm2. These remaining discrepancies are discussed, and a new method to treat ambiguous cases is presented.

Early Identification of Retinal Neuropathy in Subclinical Diabetic Eyes by Reduced Birefringence of the Peripapillary Retinal Nerve Fiber Layer.

Purpose: To study birefringence of the peripapillary retinal nerve fiber layer (RNFL) of diabetic eyes with no clinical signs of diabetic retinopathy (DR) or mild to moderate DR stages using spectral-domain polarization-sensitive (PS) optical coherence tomography (OCT). Methods: In this observational pilot study, circular PS-OCT scans centered on the optic nerve head were recorded in prospectively recruited diabetic and age-matched healthy eyes. From averaged circumpapillary intensity and retardation tomograms plots of RNFL birefringence were obtained by a linear fit of retardation versus depth within the RNFL tissue for each A-scan position and mean birefringence values for RNFL calculated. Spectral-domain OCT imaging (Heidelberg Engineering) was performed to assess peripapillary RNFL thickness and macular ganglion cell complex (GCC). Results: Out of 70 eyes of 43 diabetic patients (mean ± SD age: 50.86 ± 15.71) 36 showed no signs of DR, 17 mild and 17 moderate nonproliferative DR with no diabetic macular edema. Thirty-four eyes of 34 healthy subjects (53.21 ± 13.88 years) served as controls. Compared with healthy controls (0.143° ± 0.014°/µm) mean total birefringence of peripapillary RNFL was significantly reduced in subclinical diabetic eyes (0.131° ± 0.014°/µm; P = 0.0033), as well as in mild to moderate DR stages (0.125° ± 0.018°/µm, P < 0.0001) with borderline statistically significant differences between diabetic patients (P = 0.0049). Mean birefringence values were significantly lower in inferior compared with superior RNFL sectors (P < 0.0001) of diabetic eyes with no such difference detected in the healthy control group. Conclusions: We identified evidence of early neuroretinal alteration in diabetic eyes through reduced peripapillary RNFL birefringence assessed by PS-OCT occurring before appearance of clinical microvascular lesions or GCC alterations.

Analysis of retinal nerve fiber layer birefringence in patients with glaucoma and diabetic retinopathy by polarization sensitive OCT.

The retinal nerve fiber layer (RNFL) is a fibrous tissue that shows form birefringence. This optical tissue property is related to the microstructure of the nerve fiber axons that carry electrical signals from the retina to the brain. Ocular diseases that are known to cause neurologic changes, like glaucoma or diabetic retinopathy (DR), might alter the birefringence of the RNFL, which could be used for diagnostic purposes. In this pilot study, we used a state-of-the-art polarization sensitive optical coherence tomography (PS-OCT) system with an integrated retinal tracker to analyze the RNFL birefringence in patients with glaucoma, DR, and in age-matched healthy controls. We recorded 3D PS-OCT raster scans of the optic nerve head area and high-quality averaged circumpapillary PS-OCT scans, from which RNFL thickness, retardation and birefringence were derived. The precision of birefringence measurements was 0.005°/µm. As compared to healthy controls, glaucoma patients showed a slightly reduced birefringence (0.129 vs. 0.135°/µm), although not statistically significant. The DR patients, however, showed a stronger reduction of RNFL birefringence (0.103 vs. 0.135°/µm) which was highly significant. This result might open new avenues into early diagnosis of DR and related neurologic changes.

Diagnostic Ability of Individual Macular Layers by Spectral-Domain OCT in Different Stages of Glaucoma.

PURPOSE: To compare the diagnostic ability of macular intraretinal layer thickness with circumpapillary retinal nerve fiber layer (cpRNFL) thickness, either when used individually or in combination with cpRNFL for detecting early, moderate, and advanced glaucoma. DESIGN: Cross-sectional study. PARTICIPANTS: A total of 423 glaucoma participants and 423 age- and gender-matched normal participants. METHODS: Participants underwent Cirrus spectral-domain OCT (SD-OCT) imaging (Carl Zeiss Meditec, Dublin, CA) using the optic disc and macular scanning protocols. Iowa Reference Algorithms (version 3.8.0) were used for intraretinal layer segmentation, and mean thickness of intraretinal layers was rescaled with magnification correction using axial length value. Thickness measurements of each layer/sector and their corresponding areas under the receiver operating characteristic curve (AUCs) were obtained. Glaucoma eyes were subdivided based on of their visual field severity (early, n = 234; moderate, n = 107; advanced, n = 82). MAIN OUTCOME MEASURES: Intraretinal layers. RESULTS: Some 67% of participants were male, their average ± standard deviation age was 65±9 years. Circumpapillary retinal nerve fiber layer, macular ganglion cell layer (mGCL), and macular inner plexiform layer (mIPL) were significantly thinner in the glaucoma groups (P < 0.0005). The 2 best parameters for detecting normal eyes from early glaucoma was cpRNFL (AUC = 0.861) and mGCL (AUC = 0.842), from moderate glaucoma was mGCL combined with inner plexiform layer (IPL) (AUC = 0.915) and cpRNFL (AUC = 0 .914), and from advanced glaucoma was mGCL-IPL (AUC = 0.984) and cpRNFL (AUC = 0.977). There was no statistical significance between AUCs for the macular parameter and cpRNFL thickness measurement at any of the severities (P > 0.05). Combining macular and cpRNFL parameters improved the diagnostic performance for early glaucoma (AUC = 0.908; P = 0.002) and moderate glaucoma (AUC = 0.944; P = 0.031) but not for advanced glaucoma (AUC = 0.991; P > 0.05). CONCLUSIONS: Single-layer mGCL thickness is comparable to the traditional cpRNFL thickness for the diagnosis of early/moderate glaucoma, whereas cpRNFL thickness remains the most efficient for advanced glaucoma. Combining macular measurements (GCL and GCL-IPL) and cpRNFL improved the discrimination of early/moderate glaucoma but not of advanced glaucoma. For the diagnosis of early glaucoma, both macular and optic disc scans should be used.

Analysis of longitudinal sections of retinal vessels using Doppler OCT.

We present a new method for imaging retinal vessels that provides both structural and hemodynamic information. Our technique is based on a single beam OCT system with an integrated retinal tracker that enables recording of arbitrary scan patterns. We record longitudinal sections along the traces of retinal vessels. The tracker function enables the acquisition of multiple longitudinal sections along the same trace to provide high-quality averaged OCT scans as well as temporal changes of flow dynamics. The vessel walls are clearly identified as narrow, bright lines from which the vessel diameter can be retrieved as a function of position along the vessel. Furthermore, the Doppler angle can be obtained at each position along the vessel trace, enabling measurement of absolute blood flow by Doppler OCT analysis. The method is demonstrated in flow phantoms and in-vivo on retinal vessel bifurcations in healthy volunteers. In 7 of 9 imaged bifurcations, measured in- and outflow deviate by less than 11%, demonstrating the consistency of the method.

Generating large field of view en-face projection images from intra-acquisition motion compensated volumetric optical coherence tomography data.

A technique to generate large field of view projection maps of arbitrary optical coherence tomography (OCT) data is described. The technique is divided into two stages - an image acquisition stage that features a simple to use fast and robust retinal tracker to get motion free retinal OCT volume scans - and a stitching stage where OCT data from different retinal locations is first registered against a reference image using a custom pyramid-based approach and finally stitched together into one seamless large field of view (FOV) image. The method is applied to data recorded with a polarization sensitive OCT instrument in healthy subjects and glaucoma patients. The tracking and stitching accuracies are quantified, and finally, large FOV images of retinal nerve fiber layer retardation that contain the arcuate nerve fiber bundles from the optic nerve head to the raphe are demonstrated.

Compensation of retinal nerve fibre layer thickness as assessed using optical coherence tomography based on anatomical confounders.

BACKGROUND/AIMS: To compensate the retinal nerve fibre layer (RNFL) thickness assessed by spectral-domain optical coherence tomography (SD-OCT) for anatomical confounders. METHODS: The Singapore Epidemiology of Eye Diseases is a population-based study, where 2698 eyes (1076 Chinese, 704 Malays and 918 Indians) with high-quality SD-OCT images from individuals without eye diseases were identified. Optic disc and macular cube scans were registered to determine the distance between fovea and optic disc centres (fovea distance) and their respective angle (fovea angle). Retinal vessels were segmented in the projection images and used to calculate the circumpapillary retinal vessel density profile. Compensated RNFL thickness was generated based on optic disc (ratio, orientation and area), fovea (distance and angle), retinal vessel density, refractive error and age. Linear regression models were used to investigate the effects of clinical factors on RNFL thickness. RESULTS: Retinal vessel density reduced significantly with increasing age (1487±214 µm in 40-49, 1458±208 µm in 50-59, 1429±223 µm in 60-69 and 1415±233 µm in ≥70). Compensation reduced the variability of RNFL thickness, where the effect was greatest for Chinese (10.9%; p<0.001), followed by Malays (6.6%; p=0.075) and then Indians (4.3%; p=0.192). Compensation reduced the age-related RNFL decline by 55% in all participants (ß=-3.32 µm vs ß=-1.50 µm/10 years; p<0.001). Nearly 62% of the individuals who were initially classified as having abnormally thin RNFL (outside the 99% normal limits) were later reclassified as having normal RNFL. CONCLUSIONS: RNFL thickness compensated for anatomical parameters reduced the variability of measurements and may improve glaucoma detection, which needs to be confirmed in future studies.