Weak to no correlation between quantitative high-resolution computed tomography metrics and lung function change in fibrotic diseases.

Background: Identifying systemic sclerosis (SSc) and idiopathic pulmonary fibrosis (IPF) patients at risk of more rapid forced vital capacity (FVC) decline could improve trial design. The purpose of the present study was to explore the prognostic value of quantitative high-resolution computed tomography (HRCT) metrics derived by Imbio lung texture analysis (LTA) tool in predicting FVC slope. Methods: This retrospective study used data from patients who were not treated with investigational drugs with and without background antifibrotic therapies in tocilizumab phase 3 SSc, lebrikizumab phase 2 IPF, and zinpentraxin alfa phase 2 IPF studies conducted from 2015 to 2021. Controlled HRCT axial volumetric multidetector computed tomography scans were evaluated using the Imbio LTA tool. Associations between HRCT metrics and FVC slope were assessed through the Spearman correlation coefficient and adjusted R2 in a linear regression model adjusted by demographics and baseline clinical characteristics. Results: A total of 271 SSc and IPF patients were analysed. Correlation coefficients of highest magnitude were observed in the SSc study between the extent of ground glass, normal volume, quantification of interstitial lung disease, reticular pattern, and FVC slope (-0.25, 0.28, -0.28, and -0.33, respectively), while the correlation coefficients observed in IPF studies were in general <0.2. The incremental prognostic value of the baseline HRCT metrics was marginal after adjusting baseline characteristics and was inconsistent across study arms. Conclusion: Data from the SSc and IPF studies suggested weak to no and inconsistent correlation between quantitative HRCT metrics derived by the Imbio LTA tool and FVC slope in the studied SSc and IPF population.

Multi-ancestry GWAS analysis identifies two novel loci associated with diabetic eye disease and highlights APOL1 as a high risk locus in patients with diabetic macular edema.

Diabetic retinopathy (DR) is a common complication of diabetes. Approximately 20% of DR patients have diabetic macular edema (DME) characterized by fluid leakage into the retina. There is a genetic component to DR and DME risk, but few replicable loci. Because not all DR cases have DME, we focused on DME to increase power, and conducted a multi-ancestry GWAS to assess DME risk in a total of 1,502 DME patients and 5,603 non-DME controls in discovery and replication datasets. Two loci reached GWAS significance (p<5x10-8). The strongest association was rs2239785, (K150E) in APOL1. The second finding was rs10402468, which co-localized to PLVAP and ANKLE1 in vascular / endothelium tissues. We conducted multiple sensitivity analyses to establish that the associations were specific to DME status and did not reflect diabetes status or other diabetic complications. Here we report two novel loci for risk of DME which replicated in multiple clinical trial and biobank derived datasets. One of these loci, containing the gene APOL1, is a risk factor in African American DME and DKD patients, indicating that this locus plays a broader role in diabetic complications for multiple ancestries. Trial Registration: NCT00473330, NCT00473382, NCT03622580, NCT03622593, NCT04108156.

Geographic Atrophy Segmentation Using Multimodal Deep Learning.

Purpose: To examine deep learning (DL)-based methods for accurate segmentation of geographic atrophy (GA) lesions using fundus autofluorescence (FAF) and near-infrared (NIR) images. Methods: This retrospective analysis utilized imaging data from study eyes of patients enrolled in Proxima A and B (NCT02479386; NCT02399072) natural history studies of GA. Two multimodal DL networks (UNet and YNet) were used to automatically segment GA lesions on FAF; segmentation accuracy was compared with annotations by experienced graders. The training data set comprised 940 image pairs (FAF and NIR) from 183 patients in Proxima B; the test data set comprised 497 image pairs from 154 patients in Proxima A. Dice coefficient scores, Bland-Altman plots, and Pearson correlation coefficient (r) were used to assess performance. Results: On the test set, Dice scores for the DL network to grader comparison ranged from 0.89 to 0.92 for screening visit; Dice score between graders was 0.94. GA lesion area correlations (r) for YNet versus grader, UNet versus grader, and between graders were 0.981, 0.959, and 0.995, respectively. Longitudinal GA lesion area enlargement correlations (r) for screening to 12 months (n = 53) were lower (0.741, 0.622, and 0.890, respectively) compared with the cross-sectional results at screening. Longitudinal correlations (r) from screening to 6 months (n = 77) were even lower (0.294, 0.248, and 0.686, respectively). Conclusions: Multimodal DL networks to segment GA lesions can produce accurate results comparable with expert graders. Translational Relevance: DL-based tools may support efficient and individualized assessment of patients with GA in clinical research and practice.

Deep Learning to Predict Geographic Atrophy Area and Growth Rate from Multimodal Imaging.

OBJECTIVE: To develop deep learning models for annualized geographic atrophy (GA) growth rate prediction using fundus autofluorescence (FAF) images and spectral-domain OCT volumes from baseline visits, which can be used for prognostic covariate adjustment to increase power of clinical trials. DESIGN: This retrospective analysis estimated GA growth rate as the slope of a linear fit on all available measurements of lesion area over a 2-year period. Three multitask deep learning models-FAF-only, OCT-only, and multimodal (FAF and OCT)-were developed to predict concurrent GA area and annualized growth rate. PARTICIPANTS: Patients were from prospective and observational lampalizumab clinical trials. METHODS: The 3 models were trained on the development data set, tested on the holdout set, and further evaluated on the independent test sets. Baseline FAF images and OCT volumes from study eyes of patients with bilateral GA (NCT02247479; NCT02247531; and NCT02479386) were split into development (1279 patients/eyes) and holdout (443 patients/eyes) sets. Baseline FAF images from study eyes of NCT01229215 (106 patients/eyes) and NCT02399072 (169 patients/eyes) were used as independent test sets. MAIN OUTCOME MEASURES: Model performance was evaluated using squared Pearson correlation coefficient (r2) between observed and predicted lesion areas/growth rates. Confidence intervals were calculated by bootstrap resampling (B = 10 000). RESULTS: On the holdout data set, r2 (95% confidence interval) of the FAF-only, OCT-only, and multimodal models for GA lesion area prediction was 0.96 (0.95-0.97), 0.91 (0.87-0.95), and 0.94 (0.92-0.96), respectively, and for GA growth rate prediction was 0.48 (0.41-0.55), 0.36 (0.29-0.43), and 0.47 (0.40-0.54), respectively. On the 2 independent test sets, r2 of the FAF-only model for GA lesion area was 0.98 (0.97-0.99) and 0.95 (0.93-0.96), and for GA growth rate was 0.65 (0.52-0.75) and 0.47 (0.34-0.60). CONCLUSIONS: We show the feasibility of using baseline FAF images and OCT volumes to predict individual GA area and growth rates using a multitask deep learning approach. The deep learning-based growth rate predictions could be used for covariate adjustment to increase power of clinical trials. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Correlation of Volume of Macular Edema with Retinal Tomography Features in Diabetic Retinopathy Eyes.

Optical coherence tomography (OCT) enables the detection of macular edema, a significant pathological outcome of diabetic retinopathy (DR). The aim of the study was to correlate edema volume with the severity of diabetic retinopathy and response to treatment with intravitreal injections (compared to baseline). Diabetic retinopathy (DR; n = 181) eyes were imaged with OCT (Heidelberg Engineering, Germany). They were grouped as responders (a decrease in thickness after intravitreal injection of Bevacizumab), non-responders (persistent edema or reduced decrease in thickness), recurrent (recurrence of edema after injection), and treatment naïve (no change in edema at follow-up without any injection). The post-treatment imaging of eyes was included for all groups, except for the treatment naïve group. All eyes underwent a 9 × 6 mm raster scan to measure the edema volume (EV). Central foveal thickness (CFT), central foveal volume (CFV), and total retinal volume (TRV) were obtained from the early treatment diabetic retinopathy study (ETDRS) map. The median EV increased with DR severity, with PDR having the greatest EV (4.01 mm3). This correlated positively with TRV (p < 0.001). Median CFV and CFT were the greatest in severe NPDR. Median EV was the greatest in the recurrent eyes (4.675 mm3) and lowest (1.6 mm3) in the treatment naïve group. Responders and non-responders groups had median values of 3.65 and 3.93 mm3, respectively. This trend was not observed with CFV, CFT, and TRV. A linear regression yielded threshold values of CFV (~0.3 mm3), CFT (~386 µm), and TRV (~9.06 mm3), above which EV may be detected by the current scanner. In this study, EV provided a better distinction between the response groups when compared to retinal tomography parameters. The EV increased with disease severity. Thus, EV can be a more precise parameter to identify subclinical edema and aid in better treatment planning.

Quantitative Comparison Between Optical Coherence Tomography Angiography and Fundus Fluorescein Angiography Images: Effect of Vessel Enhancement.

BACKGROUND AND OBJECTIVE: To compare the vascular parameters derived from optical coherence tomography angiography (OCTA) and fundus fluorescein angiography (FFA) images. PATIENTS AND METHODS: Twenty-two eyes of 22 patients were imaged with OCTA and FFA. FFA images were cropped to the same dimension as OCTA images after registration. Vessel enhancement using a Frangi filter and local fractal analysis was applied to the superficial layer of the OCTA and cropped FFA images. Foveal avascular zone (FAZ) area, vessel density, spacing between large vessels, and spacing between small vessels were quantified. RESULTS: FAZ area was similar between original OCTA, Frangi-filtered OCTA, and FFA images (P = .32). Actual OCTA images had significantly higher vessel density (35.2% ± 1.45%, P < .001) than Frangi-filtered OCTA images (29.8% ± 0.78%) and Frangi-filtered FFA images (25.5% ± 2.41%). Spacing between large vessels was significantly lower in original OCTA images (31.9% ± 1.47%, P < .001) than Frangi-filtered OCTA images (36.8% ± 1.24%) and Frangi-filtered FFA images (60.1% ± 2.68%). Further, FFA images had significantly lower spacing between small vessels (14.4% ± 0.43%, P < .001) than original OCTA images (32.7% ± 1.03%) and Frangi-filtered OCTA images (33.4% ± 0.81%). CONCLUSION: FAZ area was similar between OCTA and FFA, independent of vessel enhancement. However, vessel enhancement improved the agreement of vascular parameters between OCTA and FFA images of the same eye. [Ophthalmic Surg Lasers Imaging Retina. 2018;49:e175-e181.].

Quantitative Comparison of Retinal Vascular Features in Optical Coherence Tomography Angiography Images From Three Different Devices.

BACKGROUND AND OBJECTIVE: To compare optical coherence tomography angiography (OCTA) images from three different devices. PATIENTS AND METHODS: This was a prospective, observational, cross-sectional study. All eyes (n = 24) were imaged thrice each time with swept-source OCT (DRI OCT Triton Plus; Topcon, Tokyo, Japan), spectral-domain OCTA (AngioVue; Optovue, Fremont, CA), and SD-OCT Angioplex (Cirrus HD-OCT 5000; Carl Zeiss Meditec, Jena, Germany). Outcome measures were foveal avascular zone (FAZ) area, vessel density, spacing between large vessels (SLV), and spacing between small vessels (SSV). They were calculated using local fractal analyses and Frangi filter. RESULTS: The vascular parameters showed good to excellent repeatability (intraclass coefficient > 0.8) in the three devices. The FAZ area (P = .3) and vessel density of the superficial layer (P = .8) were similar between the devices. In the deep layer, vessel density was significantly higher (P = .02) with Angio-Vue images compared to those acquired using the other devices. However, SLV was significantly higher (P < .05) and SSV was significantly lower (P < .05) on Angioplex scans compared to other devices. Vessel parameters were significantly altered in Frangi-filtered images as compared to nonfiltered images. CONCLUSIONS: Vessel density showed good repeatability among the three devices, although there were differences in vessel parameters between the devices. Also, vessel parameters changed significantly after Frangi filtering. [Ophthalmic Surg Lasers Imaging Retina. 2018;49:488-496.].

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.

Age and myopia associated optical coherence tomography of retina and choroid in pediatric eyes.

PURPOSE: To evaluate the association between retinal and choroidal thickness and volume along with choroidal vessel volume in children using optical coherence tomography (OCT) images. METHODS: 113 normal eyes of children ranging from 5-17 years of age were imaged with a clinical OCT scanner (Optovue Inc., Fremont, USA). The retina, choroid and choroidal vessels were automatically segmented with algorithms. Parameters evaluated were thickness and volume. Location specific analyses of thickness were also performed at a distance of 2.5 mm from foveal center. Multivariate analyses of variance were used to analyze the effect of age and myopia. Manual segmentation of the fovea and subfoveal choroid thickness was also performed to compare with the algorithm segmentation. RESULTS: There was excellent agreement between manual and automatic segmentation (intra-class correlation of 0.95). Within the same eye, total retinal and choroid thickness of nasal and temporal location were significantly lower than the superior and inferior thickness (P < 0.0001). With age (P = 0.026) and myopia (P < 0.001), foveal thickness increased. Choroid volume, vessel volume and temporal choroid thickness increased with increasing myopia (P < 0.05). There was significant positive correlation between choroid volume and retinal volume (r = 0.62, P < 0.0001), choroid volume and vessel volume (r = 0.48, P < 0.0001), and with foveal thickness (r = 0.31, P = 0.009). Choroid vessel volume also showed significant positive correlations with the other metrics (P < 0.05). CONCLUSION: Retinal and choroidal structural features were quantified simultaneously from OCT images. Magnitude of myopia had a greater effect on retino-choroid features than age in children.

An automated framework to quantify areas of regional ischemia in retinal vascular diseases with OCT angiography.

In this observational and cross-sectional study, capillary nonperfusion (CNP) and vascular changes in branch retinal vein occlusion (BRVO, sample size [n] = 26) and choroidal neovascularization (CNV, n = 29) were evaluated. Subjects underwent imaging using Optical coherence tomography angiography (Angiovue OCTA, RTVue XR, Optovue Inc., Fremont, California). Local fractal analysis was applied to the OCTA images of superficial, deep and choriocapillaris layer. CNP area (BRVO eyes) and vascular parameters were computed using local fractal-based method. Sensitivity and specificity of vascular parameters were assessed with receiver operating characteristics curve. Automated CNP area showed excellent agreement with manually quantified CNP areas in both superficial (intraclass coefficient [ICC] = 0.96) and deep (ICC = 0.96) layers. BRVO eyes showed significantly altered (P < .05) vascular parameters in both superficial and deep layer as compared to normal eyes (n = 30). CNVM eyes had significantly higher capillary free zones (P < .001) as compared to normal eyes. In normal vs BRVO eyes, vessel density and spacing between the large vessels had similar area under the curve (AUC) (P > .05) in both superficial (0.97 and 0.97, respectively) and deep layer (0.99 and 0.98, respectively). Further, capillary free zones showed high AUC (0.92) in differentiating CNV eyes from normal eyes.

A Prospective OCT Study of Rubella Retinopathy.

PURPOSE: To analyze rubella retinopathy qualitatively and quantitatively in children diagnosed with congenital rubella syndrome (CRS) using a handheld spectral-domain (SD) OCT device. DESIGN: Prospective, cross-sectional, nonrandomized, comparative observational study in a tertiary eye care center in south India. PARTICIPANTS: Cases comprised 24 eyes of 13 children diagnosed with CRS based on seropositivity with rubella retinopathy. Controls comprised 26 eyes of 13 age-matched healthy children with normal retina. METHODS: All participants underwent retinal imaging with RetCam fundus photography (Natus Medical Inc, Pleasanton, CA) and handheld SD OCT (Bioptigen, Inc., Durham, NC). The SD OCT images of both cases and controls were segmented. Retinal and choroid thickness parameters were computed. MAIN OUTCOME MEASURES: Qualitative and quantitative changes were observed in SD OCT images of rubella retinopathy compared with those from controls. RESULTS: Characteristic salt-and-pepper appearance was observed on fundus photography in children with rubella compared with the healthy children. The appearance of fovea and retinal features such as foveal dip, external limiting membrane, inner segment-outer segment boundary, outer segment-retinal pigment epithelium boundary, and retinal pigment epithelium were significantly different (P < 0.05) in eyes with rubella retinopathy compared with healthy eyes Furthermore, eyes with rubella retinopathy exhibited significantly reduced central foveal thickness (P = 0.025), subfoveal outer retinal thickness (P = 0.01), and subfoveal choroid thickness (P = 0.007) compared with healthy eyes. CONCLUSIONS: Distinct qualitative and quantitative differences were observed in the SD OCT images of eyes with rubella retinopathy compared with those from healthy eyes.

Discriminant Function of Optical Coherence Tomography Angiography to Determine Disease Severity in Glaucoma.

PURPOSE: To determine the discriminant function of optical coherence tomography angiography (OCTA) by disease severity in glaucoma. METHODS: In this prospective, observational cross-sectional study, all subjects underwent visual fields, retinal nerve fiber layer (RNFL) measurements, and OCTA imaging. Local fractal analysis was applied to OCTA images (radial peripapillary capillaries [RPC] layer). Vessel density en face and inside the disc and spacing between large and small vessels were quantified. Stepwise logistic regression was performed and a glaucoma severity score (range, 0-1: 0, normal; 1, severe glaucoma) was developed by using global and regional (superotemporal [ST], inferotemporal [IT], temporal, superonasal [SN], inferonasal, and nasal) vascular parameters. Glaucoma severity score was compared with visual field and RNFL indices. RESULTS: One hundred ninety-nine eyes (112 subjects) with glaucoma (28 eyes preperimetric; 83 early, 43 moderate, and 45 severe glaucoma) and 74 normal (54 subjects) eyes were enrolled. Preperimetric and glaucomatous eyes had significantly altered (P < 0.001) global vascular parameters as compared to normal; regionally, ST, then SN and IT sectors (in that order) showed more change in glaucomatous eyes. Vascular parameters showed better discriminant ability (area under the curve [AUC], sensitivity, and specificity of 0.70, 69.2%, and 72.9%, respectively) than structural parameters between normal and preperimetric glaucomatous eyes. Vascular parameters had comparable AUC (P > 0.05) to visual fields for perimetric glaucoma. Glaucoma severity score identified preperimetric glaucoma and early glaucoma better than did visual fields. CONCLUSIONS: Vascular parameters could be a useful adjunct tool to evaluate/diagnose glaucoma. Longitudinal studies are needed to determine their use in early detection and prognostication.

Linking Retinal Microvasculature Features With Severity of Diabetic Retinopathy Using Optical Coherence Tomography Angiography.

PURPOSE: To correlate retinal vascular features with severity and systemic indicators of diabetic retinopathy (DR) using optical coherence tomography angiography (OCTA). METHODS: A total of 209 eyes of 122 type 2 diabetes mellitus patients with DR and 60 eyes of 31 normal Indian subjects underwent OCTA imaging. The diabetic retinopathy patients were graded as having either nonproliferative diabetic retinopathy (NPDR: mild, moderate, and severe NPDR using Early Treatment Diabetic Retinopathy Study classification) or proliferative diabetic retinopathy (PDR). Local fractal analysis was applied to the superficial and deep retinal OCTA images. Foveal avascular zone area (FAZ in mm2); vessel density (%); spacing between large vessels (%); and spacing between small vessels (%) were analyzed. Sensitivity and specificity of vascular parameters were assessed with receiver operating characteristics (ROC) curve. RESULTS: Normal eyes had a significantly lower FAZ area, higher vessel density, and lower spacing between large and small vessels compared with DR grades (P < 0.001). In the superficial layer, PDR and severe NPDR had higher spacing between large vessels than mild and moderate NPDR (P = 0.04). However, mild NPDR had higher spacing between the small vessels (P < 0.001). Spacing between the large vessels in the superficial retinal layer correlated positively with HbA1c (r = 0.25, P = 0.03); fasting (r = 0.23, P = 0.02); and postprandial (r = 0.26, P = 0.03) blood sugar. The same spacing in the deep retinal vascular plexus had the highest area under the ROC curve (0.99 ± 0.01) and was uniformly elevated in all diabetic eyes (P > 0.05). CONCLUSIONS: Spacing between the large vessels in the superficial and deep retinal layers had superior diagnostic performance than overall vessel density.

Quantification of Vessel Density in Retinal Optical Coherence Tomography Angiography Images Using Local Fractal Dimension.

PURPOSE: To evaluate a fully automated local fractal dimension method to quantify vessel density and foveal avascular zone (FAZ) area in optical coherence tomography angiography (OCTA) images. METHODS: Fifty-two healthy Asian Indian eyes underwent imaging prospectively with OCTA system. Superficial and deep retinal vascular plexus was imaged. Local fractal analysis was applied to the OCTA images. A scan area of 3 × 3 mm was selected in the superficial and deep retinal layers. Foveal avascular zone area and vessel density were quantified in circular and sectoral zones around the fovea. A unique contour map of vessel density and dropout zones was developed to perform regional comparisons. RESULTS: Foveal avascular zone of superficial (0.35 ± 0.013 mm2) and deep (0.49 ± 0.012 mm2) retinal vascular plexus was segmented. The agreement between the manually segmented and local fractal dimension segmented FAZ area was 0.97 (95% confidence interval [CI]: 0.94-0.98) and did not change significantly with age (P = 0.94 and 0.21, respectively). The vessel density was greater in the deep than the superficial retinal vascular plexus (P < 0.0001). When the image was subdivided into sectors around the FAZ, inferior sector had greater vessel density than the others (temporal, superior, and nasal) in both superficial and deep retinal vascular plexus (P < 0.05). These observations were similar to recent studies on animal retinal vasculature map. CONCLUSIONS: A novel implementation of local fractal dimension to calculate vessel density and FAZ area was demonstrated. Age did not impact vessel density but sectoral analyses showed greater vessel density in the inferior zone.