A Deep-Learning Algorithm to Predict Short-Term Progression to Geographic Atrophy on Spectral-Domain Optical Coherence Tomography

IMPORTANCE: The identification of patients at risk of progressing from intermediate age-related macular degeneration (iAMD) to geographic atrophy (GA) is essential for clinical trials aimed at preventing disease progression. DeepGAze is a fully automated and accurate convolutional neural network-based deep learning algorithm for predicting progression from iAMD to GA within 1 year from spectral-domain optical coherence tomography (SD-OCT) scans. OBJECTIVE: To develop a deep-learning algorithm based on volumetric SD-OCT scans to predict the progression from iAMD to GA during the year following the scan. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included participants with iAMD at baseline and who either progressed or did not progress to GA within the subsequent 13 months. Participants were included from centers in 4 US states. Data set 1 included patients from the Age-Related Eye Disease Study 2 AREDS2 (Ancillary Spectral-Domain Optical Coherence Tomography) A2A study (July 2008 to August 2015). Data sets 2 and 3 included patients with imaging taken in routine clinical care at a tertiary referral center and associated satellites between January 2013 and January 2023. The stored imaging data were retrieved for the purpose of this study from July 1, 2022, to February 1, 2023. Data were analyzed from May 2021 to July 2023. EXPOSURE: A position-aware convolutional neural network with proactive pseudointervention was trained and cross-validated on Bioptigen SD-OCT volumes (data set 1) and validated on 2 external data sets comprising Heidelberg Spectralis SD-OCT scans (data sets 2 and 3). MAIN OUTCOMES AND MEASURES: Prediction of progression to GA within 13 months was evaluated with area under the receiver-operator characteristic curves (AUROC) as well as area under the precision-recall curve (AUPRC), sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. RESULTS: The study included a total of 417 patients: 316 in data set 1 (mean [SD] age, 74 [8]; 185 [59%] female), 53 in data set 2, (mean [SD] age, 83 [8]; 32 [60%] female), and 48 in data set 3 (mean [SD] age, 81 [8]; 32 [67%] female). The AUROC for prediction of progression from iAMD to GA within 1 year was 0.94 (95% CI, 0.92-0.95; AUPRC, 0.90 [95% CI, 0.85-0.95]; sensitivity, 0.88 [95% CI, 0.84-0.92]; specificity, 0.90 [95% CI, 0.87-0.92]) for data set 1. The addition of expert-annotated SD-OCT features to the model resulted in no improvement compared to the fully autonomous model (AUROC, 0.95; 95% CI, 0.92-0.95; P = .19). On an independent validation data set (data set 2), the model predicted progression to GA with an AUROC of 0.94 (95% CI, 0.91-0.96; AUPRC, 0.92 [0.89-0.94]; sensitivity, 0.91 [95% CI, 0.74-0.98]; specificity, 0.80 [95% CI, 0.63-0.91]). At a high-specificity operating point, simulated clinical trial recruitment was enriched for patients progressing to GA within 1 year by 8.3- to 20.7-fold (data sets 2 and 3). CONCLUSIONS AND RELEVANCE: The fully automated, position-aware deep-learning algorithm assessed in this study successfully predicted progression from iAMD to GA over a clinically meaningful time frame. The ability to predict imminent GA progression could facilitate clinical trials aimed at preventing the condition and could guide clinical decision-making regarding screening frequency or treatment initiation

Bone Marrow Transplantation Transfers Age-Related Susceptibility to Neovascular Remodeling in Murine Laser- Induced Choroidal Neovascularization

Citation: Espinosa-Heidmann DG, Malek G, Mettu PS, et al. Bone marrow transplantation transfers age-related susceptibility to neovascular remodeling in murine laser-induced choroidal neovascularization. Invest Ophthalmol Vis Sci. 2013;54:7439-7449. DOI:10.1167/iovs.13-12546 PURPOSE. Neovascular remodeling (NVR), the progression of small capillaries into large-caliber arterioles with perivascular fibrosis, represents a major therapeutic challenge in neovascular age-related macular degeneration (AMD). Neovascular remodeling occurs after laser-induced choroidal neovascularization (CNV) in aged but not young mice. Additionally, bone marrowderived cells, including macrophages, endothelial precursor cells, and mesenchymal precursor cells, contribute to CNV severity. In this study, we investigated the impact of aged bone marrow transplantation (BMT) on the degree of fibrosis, size, and vascular morphology of CNV lesions in a mouse model of laser-induced CNV. METHODS. Young (2 months) and old (16 months) mice were transplanted with green fluorescent protein (GFP)-labeled bone marrow isolated from either young or old donors. Laser CNV was induced 1 month following transplant, and eyes were analyzed via choroidal flat mounts and immunohistochemistry 1 month postlaser. The identity of cells infiltrating CNV lesions was determined using specific markers for the labeled transplanted cells (GFPþ), macrophages (F4/80þ), perivascular mesenchymal-derived cells (smooth muscle actin, SMAþ), and endothelial cells (CD31þ). RESULTS. Bone marrow transplantation from aged mice transferred susceptibility to NVR into young recipients. Inversely, transplantation of young marrow into old mice prevented NVR, preserving small size and minimal fibrosis. Mice with NVR demonstrated a greater relative contribution of marrow-derived SMAþ perivascular mesenchymal cells as compared to other cells. CONCLUSIONS. Our findings indicate that the status of bone marrow is an important determining factor of neovascular severity. Furthermore, we find that perivascular mesenchymal cells, rather than endothelial cells, derived from aged bone marrow may contribute to increased CNV severity in this murine model of experimental neovascularization

Bone Marrow Transplantation Transfers Age-Related Susceptibility to Neovascular Remodeling in Murine Laser-Induced Choroidal Neovascularization

PURPOSE. Neovascular remodeling (NVR), the progression of small capillaries into large-caliber arterioles with perivascular fibrosis, represents a major therapeutic challenge in neovascular age-related macular degeneration (AMD). Neovascular remodeling occurs after laser-induced choroidal neovascularization (CNV) in aged but not young mice. Additionally, bone marrow–derived cells, including macrophages, endothelial precursor cells, and mesenchymal precursor cells, contribute to CNV severity. In this study, we investigated the impact of aged bone marrow transplantation (BMT) on the degree of fibrosis, size, and vascular morphology of CNV lesions in a mouse model of laser-induced CNV. METHODS. Young (2 months) and old (16 months) mice were transplanted with green fluorescent protein (GFP)-labeled bone marrow isolated from either young or old donors. Laser CNV was induced 1 month following transplant, and eyes were analyzed via choroidal flat mounts and immunohistochemistry 1 month postlaser. The identity of cells infiltrating CNV lesions was determined using specific markers for the labeled transplanted cells (GFP+), macrophages (F4/80+), perivascular mesenchymal-derived cells (smooth muscle actin, SMA+), and endothelial cells (CD31+). RESULTS. Bone marrow transplantation from aged mice transferred susceptibility to NVR into young recipients. Inversely, transplantation of young marrow into old mice prevented NVR, preserving small size and minimal fibrosis. Mice with NVR demonstrated a greater relative contribution of marrow-derived SMA+ perivascular mesenchymal cells as compared to other cells. CONCLUSIONS. Our findings indicate that the status of bone marrow is an important determining factor of neovascular severity. Furthermore, we find that perivascular mesenchymal cells, rather than endothelial cells, derived from aged bone marrow may contribute to increased CNV severity in this murine model of experimental neovascularization