Differential diagnosis algorithms of сentral serous chorioretinopathy and adult-onset vitelliform dystrophies

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Abstract

Purpose. To optimize the differential diagnosis of chronic central serous chorioretinopathy (CSCR) and of adult-onset vitelliform dystrophies (VD). Research objectives. On the multimodal diagnosis basis, to investigate signs characteristic for VD and chronic CSCR using mathematic modeling, to elaborate algorithms of their differential diagnosis in settings of differently equipped clinics.

Materials and methods. 61 patient (90 eyes) with long-term neuroepithelial detachments (NEDs) were included in the study. In all patients, the disease history was collected, including the family history; all patients underwent a standard ophthalmologic examination: visual acuity testing including best corrected visual acuity (BCVA), biomicroophthalmoscopy, fundus photography, spectral domain optical coherence tomography (SD-OCT) and optical coherence tomography angiography (OCT-A), short-wavelength autofluorescence (SW-AF), fluorescein angiography (FA), indocyanine green angiography (ICGA). Patients were divided into two groups: with vitelliform dystrophies — 30 patients (30 eyes), and with CSCR — 31 patients (31 eyes). To estimate the probability of disease detection, binary logistic regression method was used.

Results. Diagnostic predictors found in both groups were scrutinized; mathematical models for estimating the probability of disease detection were obtained. Differential diagnostics algorithms have been developed taking into account the resulting formulas for calculating the probability of disease detection, including criteria of different examination combinations: SD-OCT (area under ROC curve 0.946); BAF (area under ROC curve 0.955), SD-OCT and SW-AF (area under ROC curve 0.980); SW-AF, FA and ICGA (area under ROC curve 0.989).

Conclusion. The obtained models make it possible to carry out differential diagnosis of vitelliform dystrophies and chronic CSCR in settings of differently equipped clinics.

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About the authors

Nataliia V. Matcko

S. Fyodorov Eye Microsurgery Federal State Institution, the Saint Petersburg Branch; I.I. Mechnikov North-Western State Medical University

Author for correspondence.
Email: matsko.natalia@mail.ru
ORCID iD: 0000-0001-8909-9999
SPIN-code: 9790-4066

Ophthalmologist, S. Fyodorov Eye Microsurgery Federal State Institution, Saint Petersburg Branch, PhD Student, I.I. Mechnikov North-Western State Medical University

Russian Federation, St. Petersburg; St. Petersburg

Marina V. Gatsu

S. Fyodorov Eye Microsurgery Federal State Institution, the Saint Petersburg Branch; I.I. Mechnikov North-Western State Medical University

Email: m-gatsu@yandex.ru

Dr. Sci. (Med.), Deputy Director of Clinical Services, S. Fyodorov Eye Microsurgery Federal State Institution, the Saint Petersburg Branch, professor, I.I. Mechnikov North-Western State Medical University

Russian Federation, St. Petersburg; St. Petersburg

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2. Fig. 1. Optical coherence tomograms of patients with adult-onset vitelliform dystrophy (a, c) and with chronic central serous chorioretinopathy (b, d). On all scans, detachment of the neuroepithelium is visible, deposition of optically dense deposits on the posterior surface of the neuroepithelium detachment, elongation of photoreceptor cells: a, b — without deposition of subretinal material along the retinal pigment epithelium; c, d — with deposition of subretinal material along the retinal pigment epithelium

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3. Fig. 2. Example of multimodal diagnosis, patient with adult-onset foveomacular vitelliform dystrophy; a — fundus photo (in the macula, there is a light area less than 1 optic disc diameter, dyspigmentation area), b — short-wavelength autofluorescence (SW-AF) (hyperAF area, surrounded by a ring of hypoAF with a zone of confluent more intensive hyperAF under them, hyperAF brightness — 3, according to Grayscale); e — SD-OCT (NED, hyperreflective partially resorbed vitelliform material, massive subretinal deposits, diffusely enlarged choroidal vessels, hyperreflective dots in the subretinal space); f — OCT-A (shadow of the NED with subretinal material, rarefication of the choriocapillaris along the rand of the NED, in the areas of RPE atrophy; g — ICGA (blockage of the fluorescence in the vitelliform material’s deposition area, choroidal vessels are not enlarged); c, d — FA — arteriovenous phase and dye recirculation phase, respectively (blockage of the fluorescence by the vitelliform material, with subsequent dye accumulation in this area)

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4. Fig. 3. Example of multimodal diagnosis, patient with chronic CSCR. a — fundus photo (in the macula, there is a light area about 1 optic disc diameter), b — short-wavelength autofluorescence (SW-AF) of the eye fundus (background hypoAF, central confluent hyperAF, diffuse hyper AF along the lower rand of the lesion, hyperAF brightness — 2, according to Grayscale); c — fluorescein angiography (dye accumulation in the temporal parafoveolar area out of undetermined source); d – indocyanine green angiography, middle phase (enlargement of choroidal veins, choroidal hyperpermeability); e — spectral domain optical coherence tomography (neuroepithelial detachment, hyperreflective deposits along the retinal pigment epithelium, elongation of photoreceptors, deposits in the shape of “dense fringe”, diffusely enlarged choroidal vessels); f – optical coherence tomography angiography (half-shade from neuroepithelial detachment by subretinal material)

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5. Fig. 4. ROC — curves of the resulting models. Model 1 — criteria of spectral domain optical coherence tomography; Model 2 — criteria of spectral domain optical coherence tomography, and those of optical coherence tomography angiography; Model 3 — criteria of spectral domain optical coherence tomography, and those of short-wavelength autofluorescence; Model 4 — criteria of spectral domain optical coherence tomography, those of optical coherence tomography angiography, and those of short-wavelength autofluorescence; Model 5 (expert model) — criteria of spectral domain optical coherence tomography, those of optical coherence tomography angiography, those of short-wavelength autofluorescence, those of fluorescein angiography, and those of indocyanine green angiography

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6. Fig. 5. Example of applying the formula for calculating the probability of detecting central serous chorioretinopathy, Model 4: a — high-resolution spectral domain optical coherence tomography; b — short-wavelength autofluorescence

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7. Fig. 6. Example of applying the formula for calculating the probability of detecting vitelliform dystrophy, Model 4: a — high-resolution spectral domain optical coherence tomography; b — short-wavelength autofluorescence

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Copyright (c) 2020 Matcko N.V., Gatsu M.V.

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