Harriet Lloyd

Purpose: Soft drusen and subretinal drusenoid deposits (SDD) aka reticular macular disease (RMD) characterize two pathways to advanced age-related macular degeneration (AMD). We propose these pathways are distinct diseases, with distinct genetic risks, serum risks and associated systemic diseases. Methods: 126 Subjects with AMD had: retinal imaging for RMD status, serum risks, genetic testing, and histories of cardiovascular disease (CVD) and stroke. Results: 62 subjects had RMD, 64 were nonRMD (drusen only), 51 had CVD or Stroke. RMD correlated significantly with: ARMS2 risk allele (p= 0.019); lower mean serum HDL (61±18 vs. 69±22 mg/dl, p= 0.038, t test); CVD and troke (34/51 RMD, p= 0.001).NonRMD correlated/trended with APOE2 (p= 0.032) and CETP (p= 0.072) risk alleles. 97 subjects total had some drusen, which correlated with CFH risk (p= 0.016). Multivariate independent risks for RMD were: CVD and Stroke (p= 0.008), and ARMS2 homozygous risk (p= 0.038). Conclusion: The RMD and soft drusen AMD pathways have distinct systemic associations, serum and genetic risks. RMD is associated with CVD and stroke, ARMS2 risk, and lower HDL; drusen with CFH risk and two lipid risk genes. These pathways appear to be distinct diseases leading to advanced AMD. Summary Statement: Two phenotypes of age-related macular degeneration, soft drusen and reticular macular disease (the combination of subretinal drusenoid deposits and choriocapillaris insufficiency), are shown here to have distinct systemic vascular, serum, and genetic risks. These findings support the concept that these phenotypes actually represent distinct disease processes.

Importance: High-risk vascular diseases (HRVs) may remain undetected until catastrophe ensues. Detection from non-invasive retinal imaging would be highly significant. Objective: To demonstrate that certain lesions of Age-Related Macular Degeneration (AMD) found on retinal imaging correlate with co-existing HRVs. Design: Cross-sectional cohort study. Two years. Retinal image graders blinded to HRV status. Setting: 2 retina referral clinics. Participants: 151 consecutive AMD patients, ages 50-90, 97 females, 54 males, with lesions of soft drusen and/or subretinal drusenoid deposits (SDD). 12 others approached, 10 refused, 2 excluded. Methods: Patients were classified by retinal imaging into SDD (SDD present, +/- drusen) or nonSDD (soft drusen only), and by history into HRV (cardiac pump defect (myocardial infarction (MI), coronary artery bypass grafting (CABG), congestive heart failure (CHF)), valve defect, and carotid stroke) or nonHRV, with serum risk factors and medical histories. Main Outcome Measures: Correlations of HRV with SDD and other covariates (Univariate chi-square and multivariate regression). Performance of Machine Learning predicting HRV. Results: 75 SDD subjects; 76 nonSDD subjects; HRV prevalence 19.2% (29/151). High density lipoprotein (HDL) < 62 mg/Dl was found in 24/29 HRV, 42/122 nonHRV, OR 12.40, 95% Confidence Interval (CI) 5.125-30.014; p= 0.0002. 15 Pump defects, 14/15 SDD, 8 Valve defects, 6/8 SDD (4 severe aortic stenosis), 6 carotid strokes, 5/6 SDD. Total HRVs 29, 25/29 SDD, OR 9.0, 95% CI 2.95-27.46; p= 0.000012. Adjusted multivariate correlations. HRV with SDD (p= 0.000333). SDD and HDL < 62 with HRV (p= 0.000098 and 0.021). Machine Learning prediction of HRVs from SDD status and HDL level: specificity 87.4%, sensitivity 77.4%, accuracy 84.9%; 95% CIs(%) 79.0-93.3, 58.0-90.4, 77.5-90.7, respectively. Conclusions and Relevance: High-risk vascular diseases were accurately identified in a cohort of AMD patients from the presence of characteristic deposits (SDDs) on imaging and HDL levels. The SDDs are directly consequent to inadequate ocular perfusion resulting from the systemic vasculopathies. Further validation in larger cohorts of both vasculopathic and AMD subjects could bring this system into widespread medical practice, to reduce mortality and morbidity from vascular disease, particularly in women, where undiagnosed cardiac disease remains a serious issue. Key Points: Question: What is the relationship and driving mechanism between High Risk Vascular Diseases (HRVs) and Age-Related Macular Degeneration (AMD)? Findings: The specific AMD lesions of Subretinal Drusenoid Deposits (SDDs) were found to be highly correlated with and directly consequent to the inadequate ocular perfusion resulting from the HRVs of severe cardiac pump insufficiency or valve defect, and carotid occlusion, These vasculopathies could be predicted from the presence of SDDs on spectral domain optical coherence tomography (SD-OCT) imaging and serum HDL. Meaning: Screening for SDDs with SD-OCT imaging could reduce mortality and morbidity from severe vascular disease, particularly in women, where undiagnosed cardiac disease remains a serious issue.

Purpose: Ultrasound and optical coherence tomography (OCT) are widely used techniques for diagnostic imaging of the eye. OCT provides excellent resolution, but limited penetration. Ultrasound provides better penetration, but an order-of-magnitude poorer resolution than OCT. Photoacoustic imaging is relatively insensitive to scattering, and so offers a potential means to image deeper than OCT. Furthermore, photoacoustic imaging detects optical absorption, a parameter that is independent of that detected by conventional ultrasound or OCT. Our aim was to develop a photoacoustic system suitable for imaging the eye. Methods: We developed a prototype system utilizing a focused 20 MHz ultrasound probe with a central aperture through which optics were introduced. The prototype system produced 1-μJ, 5-nsec pulses at 532 or 1064 nm with a 20-μm spot size at a 500 Hz repetition rate. The photoacoustic probe was mounted onto computer-controlled linear stages and pulse-echo ultrasound and photoacoustic images obtained on ex vivo pig eyes and in vivo mouse eyes. Results: Lateral resolution was significantly improved by use of a laser spot size much smaller than the acoustic beamwidth. Photoacoustic signals were obtained primarily from melanin in ex vivo tissues and from melanin and hemoglobin in vivo. Image fusion allowed superposition of photoacoustic signals upon the anatomic features detected by conventional ultrasound. Conclusion: Photoacoustic imaging detects the presence of clinically relevant pigments, such as melanin and oxyand deoxy-hemoglobin, and, potentially, from other pathologic pigments occurring in disease conditions (tumors, nevii, macular degeneration). Fine-resolution photoacoustic data provides information not detected in current ophthalmic imaging modalities.