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12 pages, 2069 KiB  
Article
Characterization of Risk Profiles for Diabetic Retinopathy Progression
by José Cunha-Vaz and Luís Mendes
J. Pers. Med. 2021, 11(8), 826; https://doi.org/10.3390/jpm11080826 - 23 Aug 2021
Cited by 11 | Viewed by 2956
Abstract
Diabetic retinopathy (DR) is a frequent complication of diabetes and, through its vision-threatening complications, i.e., macular edema and proliferative retinopathy, may lead to blindness. It is, therefore, of major relevance to identify the presence of retinopathy in diabetic patients and, when present, to [...] Read more.
Diabetic retinopathy (DR) is a frequent complication of diabetes and, through its vision-threatening complications, i.e., macular edema and proliferative retinopathy, may lead to blindness. It is, therefore, of major relevance to identify the presence of retinopathy in diabetic patients and, when present, to identify the eyes that have the greatest risk of progression and greatest potential to benefit from treatment. In the present paper, we suggest the development of a simple to use alternative to the Early Treatment Diabetic Retinopathy Study (ETDRS) grading system, establishing disease severity as a necessary step to further evaluate and categorize the different risk factors involved in the progression of diabetic retinopathy. It needs to be validated against the ETDRS classification and, ideally, should be able to be performed automatically using data directly from the examination equipment without the influence of subjective individual interpretation. We performed the characterization of 105 eyes from 105 patients previously classified by ETDRS level by a Reading Centre using a set of rules generated by a decision tree having as possible inputs a set of metrics automatically extracted from Swept-source Optical Coherence Tomography (SS-OCTA) and Spectral Domain- OCT (SD-OCT) measured at different localizations of the retina. When the most relevant metrics were used to derive the rules to perform the organization of the full pathological dataset, taking into account the different ETDRS grades, a global accuracy equal to 0.8 was obtained. In summary, it is now possible to envision an automated classification of DR progression using noninvasive methods of examination, OCT, and SS-OCTA. Using this classification to establish the severity grade of DR, at the time of the ophthalmological examination, it is then possible to identify the risk of progression in severity and the development of vision-threatening complications based on the predominant phenotype. Full article
(This article belongs to the Special Issue Age-Related Macular Degeneration and Diabetic Retinopathy)
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Graphical abstract
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<p>Localization of the 25 subregions that were used to decompose the 15 mm × 9 mm region acquired for each eye using the Zeiss PLEXT Elite 9000 (Carl Zeiss Meditec, Dublin, CA, USA). For each subregion, the mean value of the VD and GCL was measured. Aggregate measures were also used. The values of the inner ring (2,3,4,5), outer ring (6,7,8,9), inner circle (1,2,3,4,5), outer circle (1,2,3,4,5,6,7,8,9), and rings of the extended circles C1 (10,11,12,13,14,15,16), C2 (18,19,20,21), C3 (22, 23,24,25) were also used.</p>
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<p>Rules derived using a CART decision tree when the task was to organize the values of the OCT and OCTA metrics extracted from the dataset comparing eyes with ETDRS 10–20 and ETDRS 35 levels. At each leaf, the number (#) of eyes selected by that rule and the most popular class (the assigned class) are presented.</p>
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<p>Rules derived using a CART decision tree when the task was to organize the values of the OCT and OCTA metrics extracted from the dataset when comparing with ETDRS 35 and ETDRS 43–47 level having into account the ETDRS level. At each leaf, the number (#) of eyes selected by that rule and the most popular class (the assigned class) are presented.</p>
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8 pages, 561 KiB  
Article
Factors Associated with Increased Neuroretinal Rim Thickness Measured Based on Bruch’s Membrane Opening-Minimum Rim Width after Trabeculectomy
by Do-Young Park and Soon-Cheol Cha
J. Clin. Med. 2021, 10(16), 3646; https://doi.org/10.3390/jcm10163646 - 18 Aug 2021
Cited by 4 | Viewed by 1876
Abstract
Purpose: To investigate the factors associated with an increase in the neuroretinal rim (NRR) thickness measured based on Bruch’s membrane opening-minimum rim width (BMO-MRW) after trabeculectomy in patients with primary open-angle glaucoma (POAG). Methods: We analyzed the BMO-MRW using spectral-domain optical coherence tomography [...] Read more.
Purpose: To investigate the factors associated with an increase in the neuroretinal rim (NRR) thickness measured based on Bruch’s membrane opening-minimum rim width (BMO-MRW) after trabeculectomy in patients with primary open-angle glaucoma (POAG). Methods: We analyzed the BMO-MRW using spectral-domain optical coherence tomography (SD-OCT) of patients with POAG who underwent a trabeculectomy for uncontrolled intraocular pressure (IOP) despite maximal IOP reduction treatment. The BMO-MRW was measured before and after trabeculectomy in patients with POAG. Demographic and systemic factors, ocular factors, pre- and post-operative IOP, and visual field parameters were collected, together with SD-OCT measurements. A regression analysis was performed to investigate the factors that affected the change in the BMO-MRW after the trabeculectomy. Results: Forty-four eyes of 44 patients were included in the analysis. The IOP significantly decreased from a preoperative 27.0 mmHg to a postoperative 10.5 mmHg. The mean interval between the trabeculectomy and the date of post-operative SD-OCT measurement was 3.3 months. The global and sectoral BMO-MRW significantly increased after trabeculectomy, whereas the peripapillary retinal nerve fiber layer thickness did not show a difference between before and after the trabeculectomy. Younger age and a greater reduction in the IOP after the trabeculectomy were significantly associated with the increase in the BMO-MRW after trabeculectomy. Conclusions: The NRR thickness measured based on the BMO-MRW increased with decreasing IOP after trabeculectomy, and the increase in the BMO-MRW was associated with the young age of the patients and greater reduction in the IOP after trabeculectomy. Biomechanically, these suggest that the NRR comprises cells and substances that sensitively respond to changes in the IOP and age. Full article
(This article belongs to the Special Issue Intraocular Pressure and Ocular Hypertension)
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<p>Scatter plot showing the relationship between the increase in the Bruch’s membrane opening-minimum rim width (BMO-MRW) after trabeculectomy and the patients’ age (left) and the amount of IOP reduction after trabeculectomy (right).</p>
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16 pages, 11134 KiB  
Case Report
Acute Zonal Occult Outer Retinopathy (AZOOR) Results from a Clinicopathological Mechanism Different from Choriocapillaritis Diseases: A Multimodal Imaging Analysis
by Carl P. Herbort, Ilir Arapi, Ioannis Papasavvas, Alessandro Mantovani and Bruno Jeannin
Diagnostics 2021, 11(7), 1184; https://doi.org/10.3390/diagnostics11071184 - 29 Jun 2021
Cited by 11 | Viewed by 6973
Abstract
Background and aim: AZOOR is a rare disease characterized by loss of zones of outer retinal function, first described by J Donald Gass in 1993. Symptoms include acute onset photopsias and subjective visual field losses. The syndrome is characterized by a normal fundus [...] Read more.
Background and aim: AZOOR is a rare disease characterized by loss of zones of outer retinal function, first described by J Donald Gass in 1993. Symptoms include acute onset photopsias and subjective visual field losses. The syndrome is characterized by a normal fundus appearance, scotomas and electroretinographic changes pointing towards outer retinal dysfunction. Evolution, response to immunosuppressive treatment and outcome are difficult to predict. The aim of this small case series was to identify the morphological changes and sequence of events in AZOOR thanks to multimodal imaging. Methods: Charts of AZOOR patients seen in the Centre for Ophthalmic Specialized care (COS, Lausanne, Switzerland) were analyzed by multimodal imaging including fundus photography, fluorescein angiography (FA), indocyanine green angiography (ICGA), blue light fundus autofluorescence (BL-FAF) and spectral domain optical coherence tomography (SD-OCT) in addition to a complete ophthalmological examination including visual field testing and microperimetry, as well as OCT angiography (OCT-A) and ganglion-cell complex analysis when available. Cases and Results: Three AZOOR patients with a mean follow-up of 47 ± 25.5 months were included following the clinical definitions laid down by J Donald Gass. The primary damage was identified at the level of the photoreceptor outer segments with an intact choriocapillaris and retinal pigment epithelium (RPE) layer, these structures being only secondarily involved with progression of the disease. Conclusion: Although AZOOR has often been included within white dot syndromes, some of which are now known to be choriocapillaris diseases (choriocapillaritis entities), our findings clearly commend to differentiate AZOOR from entities such as MEWDS (Multiple evanescent white dot syndrome), APMPPE (Acute Posterior Multifocal Placoid Pigment Epitheliopathy), MFC (Multifocal Choroiditis) and others, as the damage to photoreceptors is primary in AZOOR (a retinopathy) and secondary in choriocapillaritis (a choriocapillaropathy). Full article
(This article belongs to the Section Biomedical Optics)
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Figure 1
<p>Fundus photographs, FA &amp; ICGA frames ODS in AZOOR patient 1 at presentation. (<b>A</b>) No manifest changes are visible on the fundus photographs ODS. (<b>B</b>) FA shows discreet late hyperfluorescence in the posterior pole around the fovea OD and around the inferior part of the optic disc OS and along the superior temporal vascular arcade OS. (<b>C</b>) ICGA ODS (late angiographic frames) does not show capillary drop-out.</p>
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<p>BL-FAF &amp; SD-OCT in AZOOR patient 1 at presentation. (<b>A</b>) Increased FAF of the whole posterior pole OD (<b>A</b>,<b>C</b>) except the central foveolar and peri-foveolar area (blue arrows) explained by the loss of the screen of the photoreceptor outer segments as shown on the SD-OCT (<b>G</b>) sections (yellow arrows). On the left eye in FAF (<b>B</b>,<b>D</b>) there is peripapillary hyperautofluorescent demarcating line (orange arrows) corresponding also to a limited area of loss of photoreceptor outer segments (<b>E</b>–<b>G</b>, yellow bracket in <b>F</b>, yellow arrows in <b>G</b>).</p>
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<p>Visual fields OD in AZOOR patient 1. Shows tubular visual field at presentation (<b>A</b>) and increase of annular scotoma after 6 years of follow-up (<b>B</b>).</p>
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<p>Microperimetry OD in patient 1 with AZOOR at presentation (<b>A</b>) and after 6 years of follow-up (<b>B</b>). Decrease of microperimetry score especially among the peripheral measurement points after 6 years of evolution indicating slow progression of the process.</p>
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<p>Fundus photographs, FA and ICGA frames ODS in AZOOR patient 1 after 6 years of evolution. The right fundus (<b>A</b>) shows an evolution towards pseudo retinitis pigmentosa with a faint bone spicule aspect (yellow arrows). No other manifest changes are visible on the fundus photographs (<b>A</b>,<b>B</b>). FA shows discreet late annular hyperfluorescence around the fovea OD (<b>C</b>, yellow arrows) and increased late hyperfluorescence (window effect/staining) in the more peripheral areas due to chorioretinal atrophy. FA in OS shows hyperfluorescence inferior to the optic nerve (<b>D</b>). (<b>E</b>,<b>F</b>) ICGA shows maintained late fluorescence around the normal central area (<b>E</b>, yellow arrows), indicating preserved choriocapillaris.</p>
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<p>Follow-up of BL-FAF and SD-OCT in AZOOR patient 1 after 6 years of evolution. (<b>A</b>) FAF OD shows a rim of more pronounced hyperautofluorescence around the preserved central area indicating centripetal progression of the process as well as apparition of dark areas in the posterior pole hyperautofluorescence rim (white arrows) indicating secondary atrophic evolution. FAF OS (<b>B</b>) shows a demarcation hyperautofluorescent line around the optic nerve (yellow arrows). SD-OCT (<b>C</b>,<b>D</b>) shows the loss of photoreceptor outer segments (yellow brackets, yellow arrows).</p>
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<p>Fundus photographs, FA and ICGA in patient 2 with AZOOR at presentation and follow-up. (<b>A</b>) Fundus OD shows pale ring around fovea (white circle) while fundus OG (<b>B</b>) is normal. FA OD shows a discreetly hyperfluorescent ring around fovea with an arcuate form of bright hyperfluorescence along superior temporal arcade OD indicating chorioretinal atrophy (<b>C</b>, crimson arrow) which slightly increased after 18 months (<b>E</b>, crimson arrow). (<b>D</b>) ICGA in OD showed a reinform, C-shaped hyperfluorescence around the fovea indicating preserved choriocapillaris (white arrows), except in the area of atrophy (hyperfluorescent on FA) (<b>D</b>, crimson arrow). The latter area slightly increased after 18 months (<b>F</b>, crimson arrow). (<b>G</b>) FA showed discreet peripheral vasculitis (yellow arrow). (<b>H</b>) The extension of ICGA hyperfluorescence is shown.</p>
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<p>BL-FAF &amp; SD-OCT in AZOOR patient 2 at presentation and follow-up. Blue light FAF ODS at presentation (<b>A</b>)and after 18 months (<b>B</b>) showing OD a reniform (C-shaped, yellow arrows) hyperfluorescence due to loss of outer segments of photoreceptors except in the arcuate area along the superior temporal arcade (white arrows) corresponding to FA hyperfluorescence and ICGA hypofluorescence due to chorioretinal atrophy. The bl-FAF of the left eye shows discreet hyperautofluorescence temporal superior to the fovea (<b>A</b>,<b>B</b>, FAF OS1 and FAF OS2 white arrow). SD-OCT OD shows ± identical loss of the photoreceptor outer segment line at presentation (<b>C</b>) and after 18 months (<b>D</b>).</p>
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<p>Visual field findings, ganglion cell layer and microperimetry in case of AZOOR at presentation and after 18 months of follow-up in patient 2. Visual field (<b>1a</b>) showed a limited scotoma also seen after 18 months (<b>2a</b>). Ganglion cell layer (<b>1b</b>,<b>2b</b>) shows a substantial loss outside the fovea (corresponding to scotoma in <b>1a</b>) which increased slightly after 18 months (<b>2b</b>). Microperimetry shows a score of 448 OD at presentation (<b>1c</b>) which did not decrease after 18 months of follow-up (<b>2c</b>).</p>
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<p>Fundus, FA and ICGA of AZOOR patient 3 at presentation. (<b>a</b>) Fundus shows bilateral discolored rings around fovea (white arrows). (<b>b</b>) FA shows extensive peripheral retinal vasculitis ODS (yellow arrows). Late ICGA frames present ICGA fluorescence indicating conserved choriocapillaris except for two interpapillo-macular dark dots (<b>c</b>, crimson arrow) in the left eye also present on the FA image (<b>b</b>, crimson arrow).</p>
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<p>(<b>a</b>). BL-FAF and SD-OCT of AZOOR patient 3 at presentation. Diffuse FAF hyperautofluorescence of the posterior poles ODS due to loss of screen of photopigment present in the photoreceptor outer segments lost in the whole posterior pole except in the central foveolar area surrounded by a more hyperautofluorescent ring probably indicating centripetal progression of the process. Only a very central area of conserved outer segments can be seen ODS (yellow brackets). (<b>b</b>). BL- FAF and SD-OCT of AZOOR patient 3, 4 years earlier. Well visible annular hyperautofluorescence (<b>A</b>, yellow arrows) with partial to complete loss of outer segment line (<b>B</b>, yellow brackets).</p>
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<p>Visual fields ODS in AZOOR patient 3 at presentation. Severe visual fields loss ODS.</p>
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<p>Microperimetry OD in AZOOR patient 3 at presentation. Severe loss of score reduced to 174/560.</p>
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<p>Imaging illustration of the clinicopathology of AZOOR. (<b>A</b>) Fundus shows a pale discolored halo around the fovea that retains a normal color (yellow circle) due to loss of photoreceptor photopigment. (<b>C</b>) FA OD shows the same halo of discreet hyperfluorescence due to photopigment loss and an area of bright hyperfluorescence (window effect) along superior temporal arcade due to chorioretinal atrophy (dark on ICGA—<b>D</b>, black arrow- and FAF—<b>E</b>, yellow arrow). ICGA (<b>D</b>) shows preserved choriocapillaris (except in the arciform area of chorioretinal atrophy-black arrow) with increased fluorescence in the area of loss of the screen of photopigments, which also explains fundus hyperautofluorescence (<b>E</b>). SD-OCT (<b>B</b>) shows the loss photoreceptor outer segments.</p>
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<p>OCT-A in AZOOR patient 2. Capillary plane: no capillary drop out ODS.</p>
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10 pages, 1615 KiB  
Article
Functional Evaluation of Splicing for Variants of Uncertain Significance in Patients with Inherited Retinal Diseases
by Margarita Mauro-Herrera, John Chiang, Bojana Radojevic and Lea D Bennett
Genes 2021, 12(7), 993; https://doi.org/10.3390/genes12070993 - 29 Jun 2021
Cited by 3 | Viewed by 2227
Abstract
Inherited retinal diseases (IRD) comprise a heterogeneous set of clinical and genetic disorders that lead to blindness. Given the emerging opportunities in precision medicine and gene therapy, it has become increasingly important to determine whether DNA variants with uncertain significance (VUS) are responsible [...] Read more.
Inherited retinal diseases (IRD) comprise a heterogeneous set of clinical and genetic disorders that lead to blindness. Given the emerging opportunities in precision medicine and gene therapy, it has become increasingly important to determine whether DNA variants with uncertain significance (VUS) are responsible for patients’ IRD. This research was performed to assess the functional consequence of six VUS identified in patients with IRD. Clinical assessments included an ophthalmic examination, best-corrected visual acuity, and kinetic perimetry. Imaging was acquired with the Optos ultra-widefield camera and spectral domain optical coherence tomography (SD-OCT). Genetic testing was performed by Molecular Vision Laboratories. VUS that were predicted to alter splicing were analyzed with a minigene assay, which revealed that VUS in the genes OPA1, CNGB1, and CLUAP1 altered spicing mechanisms. Due to emerging gene and cell therapies, these results expand the genotype-phenotype correlations for patients diagnosed with an IRD. Full article
(This article belongs to the Section Human Genomics and Genetic Diseases)
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<p>Analysis of <span class="html-italic">OPA1</span> VUS c.2797G &gt; T in a patient with (<b>A</b>) RPE and degenerative changes, arteriole narrowing, and (<b>B</b>) hypo-AF in the macula and around the optic nerve head, illustrated in the right-eye images. (<b>C</b>) The visual field of the right eye was full with minor decreased detection of the IVe stimulus (green line) and an enlarged scotoma (green with underlay) at the area corresponding to the peripapillary atrophy (<b>B</b>). (<b>D</b>) The right (top) eye showed cystoid macular edema on SD-OCT. (<b>E</b>) Schematic illustrations of the pSPL3-OPA1 minigene. The OPA1 exon 28, with wild-type (WT) or mutant (MUT) alleles, was cloned between vector exons (V1 and V2). (<b>F</b>) Representative gel electrophoresis of RT-PCR products from transfected COS-7 cells. (<b>G</b>) WT and MUT transcript content, determined by Sanger sequencing.</p>
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<p>Exon skipping due to <span class="html-italic">CNGB1</span> VUS. (<b>A</b>) Schematic illustrations of the pSPL3-CNGB1 c.2492 + 1G &gt; A and (<b>B</b>) c.583 + 2T &gt; C minigenes. CNGB1 exons (white) and flanking introns (thick black lines) were cloned into the pSPL3 vector (black) with a wildtype (WT) or mutant (MUT) alleles between two pSPL3 exons (V1 and V2). (<b>C</b>) Representative gel electrophoresis of RT-PCR products from transfected COS-7 cells. pSPL3 indicates cells that were transfected with a vector containing no gDNA insert. (<b>D</b>) WT and MUT transcript content, determined by Sanger sequencing (<b>E</b>) a = 260 bp, b = 383 bp, c = 309 bp, d = 563 bp, e = 487 bp, f = 438 bp, g = 514 bp. bp: base pairs.</p>
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<p>The <span class="html-italic">CNGB1 c.2305-34G&gt;A</span> VUS affected splicing efficiency. (<b>A</b>) Diagram showing the genomic region amplified from the patient’s genomic DNA, cloned into the pSPL3 vector. (<b>B</b>) Representative analysis of mRNA from COS7 cells transfected with wild type (WT) or mutant (MUT) genomic sequences. (<b>C</b>) Products identified with Sanger sequencing. (<b>D</b>) Transcript (%) relative to total transcripts was significantly different between WT and MUT.</p>
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<p><span class="html-italic">CLUAP1</span> VUS disrupted splicing in a minigene splice assay. (<b>A</b>,<b>B</b>) Diagrams showing the genomic region and location of the variants cloned into the pSPL3 vector. (<b>C</b>) Representative RT-PCR analysis from COS-7 cells transi-ently transfected with the single constructs as indicated. (<b>D</b>) Sanger sequencing showed vector exons only for the empty vector (V1 + V2), correctly spliced transcripts containing exon 10, and abnormal transcripts that also included ~100 bp of additional sequences. (<b>E</b>) The percentage of wild-type (WT) transcript was significantly different for both VUS. V1 and V2, and vector exons 1 and 2, respectively. bp: base pair.</p>
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13 pages, 3820 KiB  
Article
Morphological Changes in Lamellar Macular Holes According to SD-OCT Examination over a Long Observation Period
by Magdalena Kal, Izabela Chojnowska-Ćwiąkała, Mateusz Winiarczyk, Monika Jasielska and Jerzy Mackiewicz
Diagnostics 2021, 11(7), 1145; https://doi.org/10.3390/diagnostics11071145 - 23 Jun 2021
Cited by 1 | Viewed by 2168
Abstract
Background: The aim of this study was to evaluate the quantitative morphological changes in lamellar macular holes (LMHs) based on SD-OCT examinations and to assess the correlations among minimal retinal thickness (MRT), reading vision (RV), and best corrected visual acuity (BCVA) over a [...] Read more.
Background: The aim of this study was to evaluate the quantitative morphological changes in lamellar macular holes (LMHs) based on SD-OCT examinations and to assess the correlations among minimal retinal thickness (MRT), reading vision (RV), and best corrected visual acuity (BCVA) over a 36-month follow-up period. Methods: A group of 40 patients (44 eyes) with LMH was evaluated, with an average age of 69.87 (SD = 10.14). The quantitative parameters monitored in the follow-up period (at 0, 3, 6, 12, 18, 24, 30, and 36 months) were tested for normality of distribution by Shapiro–Wilk and Kolmogorov–Smirnov tests. Results: The RV and BCVA values were stable, and no significant changes were found at any of the check-ups during the 36-month follow-up period (BCVA p = 0.435 and RV p = 0.0999). The analysis of individual quantitative LMH parameters during the 36-month follow-up period did not demonstrate statistically significant differences: MRT (p = 0.461), Max RT temporal (p = 0.051), Max RT nasal (p = 0.364), inner diameter (ID) (p = 0.089), and outer diameter (OD) (p = 0.985). Conclusions: The observations at 0, 6, 12, 18, 24, 30, and 36 months revealed moderate and significant correlations between RV and MRT. No significant correlation between BCVA and MRT was observed. Full article
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<p>A lamellar macular hole. The presented image is an LMH with a major tractional component, with a “moustache” appearance, according to Govetto et al.</p>
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<p>Mean minimal retinal thickness (MRT) values in LMH patients during the 36-month follow-up period. No significant changes were observed, showing that LMHs were stable over this period.</p>
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<p>Average values of maximal retinal thickness (Max RT) for the temporal area of patients during the 36-month follow-up period. The Max RT temporal value showed no statistically significant changes over this period.</p>
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<p>Mean values of the maximal retinal thickness (Max RT) for the nasal area parameter of patients during the 36-month observation period. The Max RT nasal value showed no statistically significant changes over this period.</p>
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<p>Mean internal diameter (ID) values for the 36-month follow-up period. The ID showed no statistically significant changes over this period.</p>
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<p>Mean values of the outer diameter (OD) parameters in LMH patients during the 36-month follow-up period. The OD showed no statistically significant changes over this period.</p>
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<p>Mean best corrected visual acuity (BCVA) values in LMH patients during the 36-month follow-up period. The BCVA remained stable over the entire follow-up period.</p>
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<p>Mean reading vision (RV) values in LMH patients during the 36-month follow-up period. The RV remained stable over the whole follow-up period.</p>
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<p>Correlation between reading vision (RV) (at 6 months) and minimal retinal thickness (MRT). A statistically significant correlation was observed: better RV correlated with higher MRT values.</p>
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<p>Correlation between reading vision (RV) (at 12 months) and minimal retinal thickness (MRT). A statistically significant correlation was observed: better RV correlated with higher MRT values.</p>
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<p>Correlation between reading vision (RV) (at 18 months) and minimal retinal thickness (MRT). A statistically significant correlation was observed: better RV correlated with higher MRT values.</p>
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11 pages, 2146 KiB  
Article
Biomarkers in Early Response to Brolucizumab on Pigment Epithelium Detachment Associated with Exudative Age-Related Macular Degeneration
by Marco Rispoli, Chiara M. Eandi, Luca Di Antonio, Raphael Kilian, Andrea Montesel and Maria C. Savastano
Biomedicines 2021, 9(6), 668; https://doi.org/10.3390/biomedicines9060668 - 10 Jun 2021
Cited by 15 | Viewed by 3841
Abstract
Background: The purpose of this study was to describe early changes in the morphology of pigment epithelium detachments (PED) after an intravitreal injection of Brolucizumab into eyes with macular neovascularization secondary to exudative age-related macular degeneration (e-AMD). Method: We included twelve eyes of [...] Read more.
Background: The purpose of this study was to describe early changes in the morphology of pigment epithelium detachments (PED) after an intravitreal injection of Brolucizumab into eyes with macular neovascularization secondary to exudative age-related macular degeneration (e-AMD). Method: We included twelve eyes of 12 patients with PED secondary to e-AMD which were not responding to prior anti-VEGF treatments. An ophthalmic examination and an assessment of PED-horizontal maximal diameter (PED-HMD), PED-maximum high (PED-MH) and macular neovascularization (MNV) flow area (MNV-FA) by the means of structural optical coherence tomography (OCT) and OCT Angiography (OCT-A) were performed at baseline, as well as 1, 7, 14 and 30 days after the injection. Results: The mean age of the population of study was 78.4 (SD ± 4.8). The mean number of previous Ranibizumab or Aflibercept injections was 13 (SD ± 8). At the last follow-up visit, the PED-HMD did not significantly change (p = 0.16; F(DF:1.94, 20,85) = 1.9), the PED-MH showed a significant reduction [p = 0.01; F(DF:1.31, 14.13) = 6.84.] and the MNV-FA did not significantly differ (p = 0.1; F(1.97, 21.67) = 2.54) from baseline. No signs of ocular inflammation were observed during follow-up. Conclusions: A single Brolucizumab injection was able to determine the short-term effects on PEDs’ anatomical features of eyes with an unresponsive e-AMD. Full article
(This article belongs to the Special Issue WAMD: From Pathophysiology to Therapeutic Approaches Treatment)
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<p>SD-OCT scan of two patients with a PED. The red lines correspond to the PED-HMDs and the blue lines to the PED-MHs.</p>
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<p>MNV-flow area (mm<sup>2</sup>) defined by the yellow dotted line (Case 1). In Case 2, no flow could be detected inside the PED; thus, the flow area was considered null.</p>
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<p>Box plots showing the significant reduction in PED-MHs from baseline to the end of the follow-up period. [<span class="html-italic">p</span> = 0.01; F (DF:1.31, 14.13) = 6.84.].</p>
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<p>E-AMD morpho-functional assessment by structural OCT, OCT-A and BCVA. Structural OCT shows the reabsorption of the subretinal hyper-reflective material (SHRM) and the resolution of the subretinal fluid at the end of the follow-up period. PED-HMDs did not significantly change during the visits, whereas the PED-MH did. The red and green line show respectively the vertical and horizontal scan position.</p>
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20 pages, 7784 KiB  
Article
Accuracy of a Machine-Learning Algorithm for Detecting and Classifying Choroidal Neovascularization on Spectral-Domain Optical Coherence Tomography
by Andreas Maunz, Fethallah Benmansour, Yvonna Li, Thomas Albrecht, Yan-Ping Zhang, Filippo Arcadu, Yalin Zheng, Savita Madhusudhan and Jayashree Sahni
J. Pers. Med. 2021, 11(6), 524; https://doi.org/10.3390/jpm11060524 - 8 Jun 2021
Cited by 5 | Viewed by 3094
Abstract
Background: To evaluate the performance of a machine-learning (ML) algorithm to detect and classify choroidal neovascularization (CNV), secondary to age-related macular degeneration (AMD) on spectral-domain optical coherence tomography (SD-OCT) images. Methods: Baseline fluorescein angiography (FA) and SD-OCT images from 1037 treatment-naive study eyes [...] Read more.
Background: To evaluate the performance of a machine-learning (ML) algorithm to detect and classify choroidal neovascularization (CNV), secondary to age-related macular degeneration (AMD) on spectral-domain optical coherence tomography (SD-OCT) images. Methods: Baseline fluorescein angiography (FA) and SD-OCT images from 1037 treatment-naive study eyes and 531 fellow eyes, without advanced AMD from the phase 3 HARBOR trial (NCT00891735), were used to develop, train, and cross-validate an ML pipeline combining deep-learning–based segmentation of SD-OCT B-scans and CNV classification, based on features derived from the segmentations, in a five-fold setting. FA classification of the CNV phenotypes from HARBOR was used for generating the ground truth for model development. SD-OCT scans from the phase 2 AVENUE trial (NCT02484690) were used to externally validate the ML model. Results: The ML algorithm discriminated CNV absence from CNV presence, with a very high accuracy (area under the receiver operating characteristic [AUROC] = 0.99), and classified occult versus predominantly classic CNV types, per FA assessment, with a high accuracy (AUROC = 0.91) on HARBOR SD-OCT images. Minimally classic CNV was discriminated with significantly lower performance. Occult and predominantly classic CNV types could be discriminated with AUROC = 0.88 on baseline SD-OCT images of 165 study eyes, with CNV from AVENUE. Conclusions: Our ML model was able to detect CNV presence and CNV subtypes on SD-OCT images with high accuracy in patients with neovascular AMD. Full article
(This article belongs to the Special Issue Age-Related Macular Degeneration and Diabetic Retinopathy)
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<p>Example of the automated layer segmentation of 13 retinal layers. BM, Bruch’s membrane; BMEIS, boundary of myoid and ellipsoid inner segments; GCL-IPL, ganglion cell layer-inner plexiform layer; IB OPR, inner boundary outer photoreceptor; IB RPE, inner boundary retinal pigment epithelium; ILM, internal limiting membrane; INL-OPL, inner nuclear layer-outer plexiform layer; IPL-INL, inner plexiform layer-inner nuclear layer; ISJ OSJ, inner segment/outer segment junction; OB OPR, outer boundary outer photoreceptor; OB RPE, outer boundary retinal pigment epithelium; OPL-HFL, outer plexiform layer-Henle’s fiber layer; and RNFL-GCL, retinal nerve fiber layer-ganglion cell layer.</p>
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<p>Segmentation pipeline. Sketch of the segmentation pipeline, involving training, prediction, and feature calculation for both fluidic and layer features. See <a href="#app1-jpm-11-00524" class="html-app">Supplementary Table S2</a> for a detailed feature list.</p>
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<p>ROC analysis of predominantly classic versus occult (best-tuned performance). Sensitivity versus specificity for all possible ROC cutoff points with respect to the predicted occult scores in HARBOR, including 95% CIs (bootstrapped). The location of the red crosshair indicates the operating point of the model. AUROC, area under the receiver operating characteristic; FA, fluorescein angiography; NEG, negative; POS, positive; ROC, receiver operating characteristic; Sens, sensitivity; and Spec, specificity.</p>
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<p>(<b>A</b>) Recursive feature elimination cross-validation. Optimal performance for predominantly classic versus occult was reached with 101 features out of 106, and only 21 features were necessary to sustain the average model performance of 91% AUROC. (<b>B</b>) Distribution of the top 20 feature values in the training data (predominantly classic vs. occult classes).</p>
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<p>(<b>A</b>) Recursive feature elimination cross-validation. Optimal performance for predominantly classic versus occult was reached with 101 features out of 106, and only 21 features were necessary to sustain the average model performance of 91% AUROC. (<b>B</b>) Distribution of the top 20 feature values in the training data (predominantly classic vs. occult classes).</p>
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<p>Representative cases showing comparison of machine algorithm with angiography. (<b>A–D</b>) Central SD-OCT B-scans (top), with segmented pixel masks of volumetric measures and Bruch’s membrane (middle left), en-face projections (middle center), and thickness maps (middle right), as well as corresponding FAs (bottom). Colors on the SD-OCT images indicate volumetric measures as follows—intraretinal fluid (red), subretinal fluid (green), PED (blue), and SHRM (cyan). Bruch’s membrane is shown as a red line. In (<b>A</b>), FA shows an area of hypofluorescence due to hemorrhage, and a well-demarcated area of hyperfluorescence due to a predominantly classic CNV that leaks in later frames. This was also identified as classic CNV by our ML algorithm, due to increased SHRM height and volume. In (<b>B</b>), FA demonstrates an ill-defined area of stippled hyperfluorescence, due to an occult CNV that leaks diffusely in mid and late frames, and was also identified as occult CNV by the ML algorithm, due to the presence of the PED. In (<b>C</b>), FA shows an area of well-defined hyperfluorescence in mid frames that stains and leaks in late frames due to fibrosis. The image was classified as classic CNV by the reading center, but was identified as occult CNV by the ML algorithm due to low SHRM height and volume. In (<b>D</b>), FA shows an area of hypofluorescence due to hemorrhage and a poorly demarcated area of hyperfluorescence due to the CNV. This lesion was defined as minimally classic by the reading center, but was identified as classic CNV by the ML algorithm due to the SHRM created by the hemorrhage. CNV, choroidal neovascularization; FA, fluorescein angiogram; ML, machine learning; PED, pigment epithelium detachment; SD-OCT, spectral-domain optical coherence tomography; and SHRM, subretinal hyperreflective material.</p>
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<p>Representative cases showing comparison of machine algorithm with angiography. (<b>A–D</b>) Central SD-OCT B-scans (top), with segmented pixel masks of volumetric measures and Bruch’s membrane (middle left), en-face projections (middle center), and thickness maps (middle right), as well as corresponding FAs (bottom). Colors on the SD-OCT images indicate volumetric measures as follows—intraretinal fluid (red), subretinal fluid (green), PED (blue), and SHRM (cyan). Bruch’s membrane is shown as a red line. In (<b>A</b>), FA shows an area of hypofluorescence due to hemorrhage, and a well-demarcated area of hyperfluorescence due to a predominantly classic CNV that leaks in later frames. This was also identified as classic CNV by our ML algorithm, due to increased SHRM height and volume. In (<b>B</b>), FA demonstrates an ill-defined area of stippled hyperfluorescence, due to an occult CNV that leaks diffusely in mid and late frames, and was also identified as occult CNV by the ML algorithm, due to the presence of the PED. In (<b>C</b>), FA shows an area of well-defined hyperfluorescence in mid frames that stains and leaks in late frames due to fibrosis. The image was classified as classic CNV by the reading center, but was identified as occult CNV by the ML algorithm due to low SHRM height and volume. In (<b>D</b>), FA shows an area of hypofluorescence due to hemorrhage and a poorly demarcated area of hyperfluorescence due to the CNV. This lesion was defined as minimally classic by the reading center, but was identified as classic CNV by the ML algorithm due to the SHRM created by the hemorrhage. CNV, choroidal neovascularization; FA, fluorescein angiogram; ML, machine learning; PED, pigment epithelium detachment; SD-OCT, spectral-domain optical coherence tomography; and SHRM, subretinal hyperreflective material.</p>
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<p>Representative cases showing comparison of machine algorithm with angiography. (<b>A–D</b>) Central SD-OCT B-scans (top), with segmented pixel masks of volumetric measures and Bruch’s membrane (middle left), en-face projections (middle center), and thickness maps (middle right), as well as corresponding FAs (bottom). Colors on the SD-OCT images indicate volumetric measures as follows—intraretinal fluid (red), subretinal fluid (green), PED (blue), and SHRM (cyan). Bruch’s membrane is shown as a red line. In (<b>A</b>), FA shows an area of hypofluorescence due to hemorrhage, and a well-demarcated area of hyperfluorescence due to a predominantly classic CNV that leaks in later frames. This was also identified as classic CNV by our ML algorithm, due to increased SHRM height and volume. In (<b>B</b>), FA demonstrates an ill-defined area of stippled hyperfluorescence, due to an occult CNV that leaks diffusely in mid and late frames, and was also identified as occult CNV by the ML algorithm, due to the presence of the PED. In (<b>C</b>), FA shows an area of well-defined hyperfluorescence in mid frames that stains and leaks in late frames due to fibrosis. The image was classified as classic CNV by the reading center, but was identified as occult CNV by the ML algorithm due to low SHRM height and volume. In (<b>D</b>), FA shows an area of hypofluorescence due to hemorrhage and a poorly demarcated area of hyperfluorescence due to the CNV. This lesion was defined as minimally classic by the reading center, but was identified as classic CNV by the ML algorithm due to the SHRM created by the hemorrhage. CNV, choroidal neovascularization; FA, fluorescein angiogram; ML, machine learning; PED, pigment epithelium detachment; SD-OCT, spectral-domain optical coherence tomography; and SHRM, subretinal hyperreflective material.</p>
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<p>SHAP analysis external validation. SHAP analysis for the CNV type predictions in AVENUE. Every prediction contributes exactly one dot to each row. Blue and red colors indicate lower and higher feature values, respectively. SHAP values (x-axis) add up to the predicted probability for occult (only 20 features with highest SHAP variance shown here). BM, Bruch’s membrane; CNV, choroidal neovascularization; HFL, Henle’s fiber layer; IB, inner boundary; ILM, inner limiting membrane; IRF, intraretinal fluid; max, maximum; OB, outer boundary; OPL, outer plexiform layer; PED, pigment epithelial detachment; RPE, retinal pigment epithelium; SHAP, SHapley Additive exPlanations; and SHRM, subretinal hyperreflective material.</p>
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<p>ROC analysis of predominantly classic versus occult external validation. Sensitivity versus specificity for all possible cutoff points with respect to predicted occult scores in AVENUE, including 95% CIs (bootstrapped). The location of the red crosshair indicates the operating point of the model. AUROC, area under the receiver operating characteristic; FA, fluorescein angiography; NEG, negative; POS, positive; ROC, receiver operating characteristic; Sens, sensitivity; and Spec, specificity.</p>
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9 pages, 833 KiB  
Article
Optical Coherence Tomography Angiography Metrics Monitor Severity Progression of Diabetic Retinopathy—3-Year Longitudinal Study
by Inês P. Marques, Sophie Kubach, Torcato Santos, Luís Mendes, Maria H. Madeira, Luis de Sisternes, Diana Tavares, Ana Rita Santos, Warren Lewis, Conceição Lobo, Mary K. Durbin and José Cunha-Vaz
J. Clin. Med. 2021, 10(11), 2296; https://doi.org/10.3390/jcm10112296 - 25 May 2021
Cited by 14 | Viewed by 2194
Abstract
To examine retinal vessel closure metrics and neurodegenerative changes occurring in the initial stages of nonproliferative diabetic retinopathy (NPDR) and severity progression in a three-year period. Methods: Three-year prospective longitudinal observational cohort of individuals with type 2 diabetes (T2D), one eye per person, [...] Read more.
To examine retinal vessel closure metrics and neurodegenerative changes occurring in the initial stages of nonproliferative diabetic retinopathy (NPDR) and severity progression in a three-year period. Methods: Three-year prospective longitudinal observational cohort of individuals with type 2 diabetes (T2D), one eye per person, using spectral domain-optical coherence tomography (SD-OCT) and OCT-Angiography (OCTA). Eyes were examined four times with one-year intervals. OCTA vessel density maps of the retina were used to quantify vessel closure. Thickness of the ganglion cell + inner plexiform layer (GCL + IPL) was examined to identify retinal neurodegenerative changes. Diabetic retinopathy ETDRS classification was performed using the seven-field ETDRS protocol. Results: A total of 78 eyes/patients, aged 52 to 80 years, with T2D and ETDRS grades from 10 to 47 were followed for 3 years with annual examinations. A progressive increase in retinal vessel closure was observed. Vessel density (VD) showed higher decreases with retinopathy worsening demonstrated by step-changes in ETDRS severity scale (p < 0.001). No clear correlation was observed between neurodegenerative changes and retinopathy progression. Conclusions: Retinal vessel closure in NPDR correlates with DR severity progression. Our findings provide supporting evidence that OCTA metrics of vessel closure may be used as a surrogate for DR severity progression. Full article
(This article belongs to the Section Ophthalmology)
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<p>Schematic representation of individual vessel density values in the SCP inner ring and thinning of GCL + IPL and its progression over the four visits, presented according to differences and variation in VD across ETDRS groups. The values are given in relation to the control group: Values within a normal range are depicted in green; 2 SD decrease is depicted in red; 1 SD decrease is depicted in yellow; and 2 SD increase are shown in blue. Circles without color indicate that reliable measurements could not be obtained in that specific visit due to insufficient image quality. Arrows indicate ETDRS step progression: one or two increase (↑), maintenance (-) or decrease (↓). VD: Vessel density; GCL: Ganglion cell layer and Inner plexiform layers. V1: Baseline visit; V2: 1 year visit; V3: 2-year visit; V4: Last visit (3 years).</p>
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8 pages, 932 KiB  
Article
Repeatability of Spectral Domain Optical Coherence Tomography Measurements of Bruch’s Membrane Opening-Minimum Rim Width in Epiretinal Membrane Patients with Peripapillary Involvement
by Ki Yup Nam, Bum Jun Kim, Woo Hyuk Lee and Yong Seop Han
J. Clin. Med. 2021, 10(11), 2240; https://doi.org/10.3390/jcm10112240 - 21 May 2021
Cited by 4 | Viewed by 2193
Abstract
The Bruch’s membrane opening-minimum rim width (BMO-MRW) is a recently introduced parameter of the neuroretinal rim. We analyzed the repeatability of spectral-domain optical coherence tomography (SD-OCT) measurements of BMO-MRW in epiretinal membrane (ERM) patients with peripapillary involvement, since the surface around the optic [...] Read more.
The Bruch’s membrane opening-minimum rim width (BMO-MRW) is a recently introduced parameter of the neuroretinal rim. We analyzed the repeatability of spectral-domain optical coherence tomography (SD-OCT) measurements of BMO-MRW in epiretinal membrane (ERM) patients with peripapillary involvement, since the surface around the optic disc is distorted in such patients. BMO-MRW and retinal nerve fiber layer (RNFL) thickness measurements were performed using SD-OCT in prospectively enrolled ERM patients and age-matched healthy control individuals. After two consecutive measurements with a 5 min interval, repeatability was analyzed using the intraclass correlation coefficient (ICC), repeatability coefficient (RC), and coefficient of variation (CV). Fifty-two eyes of 52 ERM patients and 62 eyes of 62 healthy controls were included in the study. The ICCs of the mean BMO-MRW/RNFL thickness measurements were 0.999/0.985 in ERM eyes and 0.999/0.999 in normal eyes, respectively. The RC values of mean BMO-MRW/RNFL thickness measurements were 9.0/6.25 μm in ERM eyes and 4.61/0.92 μm in normal eyes, respectively. The CV values were 0.91% and 1.45% for BMO-MRW and RNFL thickness in ERM eyes, and 0.63% and 0.33% in normal eyes, respectively. In ERM eyes, the RC, CV of average BMO-MRW were 1.9 and 1.4 times greater than those of normal eyes, but 6.8 and 4.4 times greater for average RNFL thickness. BMO-MRW and RNFL thickness showed good repeatability in the diseased eyes with peripapillary involvement and healthy control eyes. Based on the ICC, RC, and CV values, the repeatability of BMO-MRW measurements in peripapillary membrane patients was better than that of RNFL thickness. Full article
(This article belongs to the Section Ophthalmology)
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<p>Retinal nerve fiber layer thickness (<b>A</b>) and Bruch’s membrane opening-minimum rim width (<b>B</b>) determined by spectral-domain optical coherence tomography. G: average; TS: superotemporal; T: temporal; TI: inferotemporal; NI: inferonasal; N: nasal; NS: superonasal.</p>
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8 pages, 817 KiB  
Article
Retinal and Optic Disc Vascular Changes in Patients Using Long-Term Tadalafil: A Prospective Non-Randomized Matched-Pair Study
by Marco Capece, Daniela Montorio, Chiara Comune, Achille Aveta, Alberto Melchionna, Giuseppe Celentano, Ciro Imbimbo, Felice Crocetto, Gianluigi Califano and Gilda Cennamo
Diagnostics 2021, 11(5), 802; https://doi.org/10.3390/diagnostics11050802 - 28 Apr 2021
Cited by 6 | Viewed by 3138
Abstract
Retinal, choroidal and optic disc vascularity has never been evaluated in patients taking PDE5is long-term. The aim of our study was to evaluate the neurostructural and vascular changes after long-term use of tadalafil, using spectral domain (SD)-optical coherence tomography (OCT) and optical coherence [...] Read more.
Retinal, choroidal and optic disc vascularity has never been evaluated in patients taking PDE5is long-term. The aim of our study was to evaluate the neurostructural and vascular changes after long-term use of tadalafil, using spectral domain (SD)-optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA). In the present clinical trial, 27 patients who have been taking tadalafil 20 mg on alternate days (OAD) for at least 6 months (Group A) were enrolled. The matched group consisted of 27 healthy men (Group B). Both groups of patients underwent SD-OCT to study ganglion cell complex (GCC), retinal nerve fiber layer (RNFL) and choroidal thickness and OCTA for the evaluation of superficial capillary plexus (SCP), deep capillary plexus (DCP), choriocapillaris (CC) and radial peripapillary capillary (RPC). A reduction in SCP, DCP and RPC vessel density was found in patients using tadalafil long-term. Retinal and optic disc toxicity may be detected using modifications of capillary vessel density. Further studies are needed to investigate the possibility of a causal association. Full article
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<p>Top row. Left eye of a 65-year-old patient undergoing chronic long-term therapy with tadalafil shows an increased subfoveal choroidal thickness (SFCT) (<b>A</b>) and a normal ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL) parameters (<b>B</b>,<b>C</b>). In OCTA images, the retinal superficial, deep capillary plexuses (<b>D</b>,<b>E</b>) and the radial peripapillary capillary plexus (<b>G</b>) reveal areas of reduced vessel density and no change in choriocapillaris vessel density (<b>F</b>). Bottom Row. Left eye of a 63-year-old healthy subject (part of the control group) presents normal SFCT (<b>H</b>) and normal GCC and RNFL parameters (<b>I</b>,<b>J</b>). OCTA images reveal normal vessel density in retinal superficial, deep capillary plexuses, choriocapillaris and radial peripapillary capillary plexus (<b>K</b>–<b>N</b>).</p>
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14 pages, 2902 KiB  
Article
Digital Image Processing and Development of Machine Learning Models for the Discrimination of Corneal Pathology: An Experimental Model
by Andres Bustamante-Arias, Abbas Cheddad, Julio Cesar Jimenez-Perez and Alejandro Rodriguez-Garcia
Photonics 2021, 8(4), 118; https://doi.org/10.3390/photonics8040118 - 10 Apr 2021
Cited by 6 | Viewed by 3696
Abstract
Machine learning (ML) has an impressive capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A [...] Read more.
Machine learning (ML) has an impressive capacity to learn and analyze a large volume of data. This study aimed to train different algorithms to discriminate between healthy and pathologic corneal images by evaluating digitally processed spectral-domain optical coherence tomography (SD-OCT) corneal images. A set of 22 SD-OCT images belonging to a random set of corneal pathologies was compared to 71 healthy corneas (control group). A binary classification method was applied where three approaches of ML were explored. Once all images were analyzed, representative areas from every digital image were also extracted, processed and analyzed for a statistical feature comparison between healthy and pathologic corneas. The best performance was obtained from transfer learning—support vector machine (TL-SVM) (AUC = 0.94, SPE 88%, SEN 100%) and transfer learning—random forest (TL- RF) method (AUC = 0.92, SPE 84%, SEN 100%), followed by convolutional neural network (CNN) (AUC = 0.84, SPE 77%, SEN 91%) and random forest (AUC = 0.77, SPE 60%, SEN 95%). The highest diagnostic accuracy in classifying corneal images was achieved with the TL-SVM and the TL-RF models. In image classification, CNN was a strong predictor. This pilot experimental study developed a systematic mechanized system to discern pathologic from healthy corneas using a small sample. Full article
(This article belongs to the Special Issue Ocular Imaging for Eye Care)
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<p>Workflow diagram of the research methodology. Spectral-domain optical coherence tomography (SD-OCT), region of interest (ROI), random forest (RF), support vector machine (SVM), positive predictive value (PPV), NPV: negative predictive value (NPV) and area under the curve (AUC).</p>
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<p>Digital image segmentation process. In order to extract statistical features, image segmentation was performed into different portions.</p>
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<p>Random forest tree visualization. Ensemble classifiers from the aggregation of multiple decision trees.</p>
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<p>Random forest tree visualization. Ensemble classifiers from the aggregation of multiple decision trees.</p>
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<p>Random forest classification error minimization across the growing trees during training. RF optimizes its performance across several growing trees (e.g., 50 trees) by performing out-of-bag (OBD) error calculation.</p>
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<p>Feature importance using the random forest method. The plot represents the increase in prediction error for any given variable if the values of that variable are permuted across the out-of-bag observations. Therefore, the higher the induced error is, the higher is the importance of that variable; out-of-bag (OOB).</p>
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<p>Confusion charts. Performance visualization using confusion matrix charts for the examined classification problem using the four different approaches (best accuracy out of the ten tests); accuracy (ACC).</p>
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15 pages, 5356 KiB  
Article
The Paediatric Glaucoma Diagnostic Ability of Optical Coherence Tomography: A Comparison of Macular Segmentation and Peripapillary Retinal Nerve Fibre Layer Thickness
by Mael Lever, Christian Halfwassen, Jan Darius Unterlauft, Nikolaos E. Bechrakis, Anke Manthey and Michael R. R. Böhm
Biology 2021, 10(4), 260; https://doi.org/10.3390/biology10040260 - 25 Mar 2021
Cited by 8 | Viewed by 2504
Abstract
Paediatric glaucoma leads to a decreased thickness of the peripapillary retinal nerve fibre layer (pRNFL) and of the macula. These changes can be precisely quantified using spectral domain-optical coherence tomography (SD-OCT). Despite abundant reports in adults, studies on the diagnostic capacity of macular [...] Read more.
Paediatric glaucoma leads to a decreased thickness of the peripapillary retinal nerve fibre layer (pRNFL) and of the macula. These changes can be precisely quantified using spectral domain-optical coherence tomography (SD-OCT). Despite abundant reports in adults, studies on the diagnostic capacity of macular SD-OCT in paediatric glaucoma are rare. The aim of this study was to compare the glaucoma discriminative ability of pRNFL and macular segment thickness in paediatric glaucoma patients and healthy children. Data of 72 children aged 5–17 years (glaucoma: 19 (26.4%), healthy: 53 (73.6%)) examined with SD-OCT (SPECTRALIS®, Heidelberg Engineering) were analysed retrospectively. The thickness of pRNFL sectors and of macular segment subfields were compared between diseased and healthy participants. Areas under the receiver-operating characteristic curves (AUC), sensitivity, and specificity from logistic regression were used to evaluate the glaucoma discriminative capacity of single and combined pRNFL and macular segments’ thickness. The results revealed a reduced thickness of the pRNFL and of the three inner macular layers in glaucoma patients, which correlates highly with the presence of glaucoma. The highest glaucoma discriminative ability was observed for the combination of pRNFL sectors or inner macular segments (AUC: 0.83 and 0.85, respectively), although sensitivity remained moderate (both 63% at 95% specificity). In conclusion, while confirmation from investigations in larger cohorts is required, SD-OCT-derived pRNFL and macular thickness measurements seem highly valuable for the diagnosis of paediatric glaucoma. Full article
(This article belongs to the Special Issue Glaucoma – Pathophysiology and Therapeutic Options)
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<p>Methodology. (<b>a</b>) shows the peripapillary retinal nerve fibre layer (pRNFL) quadrants and sectors (T: temporal, N: nasal, superior separated into TS: temporal superior and NS: nasal superior, and inferior separated into TI: temporal inferior and NI nasal inferior) measured by the optical coherence tomography (OCT) software. Macular segments (<b>c</b>) are separated semi-automatically (macular retinal nerve fibre layer (mRNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL)–grouped as inner retinal layers (IRL), retinal pigment epithelium (RPE), and outer retinal layers (ORL)), and the thickness of each layer is reported using the Early Treatment Diabetic Retinopathy Study (ETDRS) grid 1, 3.5, 6 mm (<b>b</b>) containing nine subfields (C0: centre, S1 and S2 superior, N1 and N2 nasal, I1 and I2 inferior, and T1 and T2 temporal).</p>
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<p>Overview of the correlation between the thickness of subfields of all macular layers and the presence of glaucoma. The ETDRS subfields with a significant correlation with glaucoma diagnosis by univariate logistic regression are filled in grey. Abbreviations: mRNFL: macular retinal nerve fibre layer; GCL: ganglion cell layer; IPL: inner plexiform layer; INL: inner nuclear layer; OPL: outer plexiform layer; ONL: outer nuclear layer–grouped as inner retinal layers (IRL); ORL: outer retinal layers.</p>
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<p>Receiver-operating characteristic curves of the best performing pRNFL and macular parameters for the discrimination between glaucoma and healthy. The receiver-operating characteristic (ROC) curves in the univariate logistic regression for glaucoma identification of the best performing pRNFL (inferior quadrant) and macular (outer-inferior (I2) subfield of the ganglion cell layer (GCL)) areas are shown in (<b>a</b>,<b>b</b>), respectively. The ROC curves of the multivariate logistic regression of all pRNFL sectors or combining the mean thickness of the inferior and superior subfields of the mRNFL (macular retinal nerve fibre layer), GCL, and inner plexiform layer (IPL) are shown in (<b>c</b>,<b>d</b>), respectively. The AUC (area under the ROC curve) values are presented in the lower-right corner of each graph.</p>
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8 pages, 254 KiB  
Article
The COVID-19 Pandemic Has Had Negative Effects on Baseline Clinical Presentation and Outcomes of Patients with Newly Diagnosed Treatment-Naïve Exudative AMD
by Enrico Borrelli, Marco Battista, Giovanna Vella, Domenico Grosso, Riccardo Sacconi, Lea Querques, Ilaria Zucchiatti, Francesco Prascina, Francesco Bandello and Giuseppe Querques
J. Clin. Med. 2021, 10(6), 1265; https://doi.org/10.3390/jcm10061265 - 18 Mar 2021
Cited by 10 | Viewed by 1911
Abstract
Purpose: To investigate whether the coronavirus disease 2019 (COVID-19) pandemic-associated postponement in care had effects on the baseline clinical presentation of patients with newly diagnosed treatment-naïve exudative neovascular age-related macular degeneration (AMD). Methods: We included the first 50 consecutive patients referred within the [...] Read more.
Purpose: To investigate whether the coronavirus disease 2019 (COVID-19) pandemic-associated postponement in care had effects on the baseline clinical presentation of patients with newly diagnosed treatment-naïve exudative neovascular age-related macular degeneration (AMD). Methods: We included the first 50 consecutive patients referred within the COVID-19 pandemic with a diagnosis of treatment-naïve exudative neovascular AMD. Two groups of fifty consecutive patients with newly diagnosed neovascular exudative AMD presenting in 2018 and 2019 (control periods) were also included for comparisons. Results: Baseline visual acuity was statistically worse in patients referred during the COVID-19 pandemic period (0.87 ± 0.51 logarithm of the minimum angle of resolution (LogMAR)) as compared with both the “2019” (0.67 ± 0.48 LogMAR, p = 0.001) and “2018” (0.69 ± 0.54 LogMAR, p = 0.012) control periods. Data on the visual function after a loading dose of anti-vascular endothelial growth factor (VEGF) was available in a subset of patients (43 subjects in 2020, 45 in 2019 and 46 in 2018, respectively). Mean ± SD best corrected visual acuity (BCVA) at the 1-month follow-up visit after the third anti-VEGF injection was still worse in patients referred during the COVID-19 pandemic (0.82 ± 0.66 LogMAR) as compared with both the “2019” (0.60 ± 0.45 LogMAR, p = 0.021) and “2018” (0.55 ± 0.53 LogMAR, p = 0.001) control periods. On structural optical coherence tomography (OCT), the maximum subretinal hyperreflective material (SHRM) height and width were significantly greater in the COVID-19 pandemic patients. Conclusions: We demonstrated that patients with newly diagnosed treatment-naïve exudative neovascular AMD referred during the COVID-19 pandemic had worse clinical characteristics at presentation and short-term visual outcomes. Full article
(This article belongs to the Special Issue New Advances in Retinal Research)
20 pages, 1799 KiB  
Article
Correlations between Retinal Arterial Morphometric Parameters and Neurodegeneration in Patients with Type 2 Diabetes Mellitus with No or Mild Diabetic Retinopathy
by Ioana Damian and Simona Delia Nicoară
Medicina 2021, 57(3), 244; https://doi.org/10.3390/medicina57030244 - 5 Mar 2021
Cited by 8 | Viewed by 2027
Abstract
Background and Objectives: In patients with diabetes mellitus (DM), the neural retina is starting to degenerate before the development of vascular lesions. Our purpose was to investigate the correlation between the retinal arterial morphometric parameters and structural neurodegeneration in patients with type [...] Read more.
Background and Objectives: In patients with diabetes mellitus (DM), the neural retina is starting to degenerate before the development of vascular lesions. Our purpose was to investigate the correlation between the retinal arterial morphometric parameters and structural neurodegeneration in patients with type 2 DM with no or mild diabetic retinopathy (DR). Materials and Methods: This is a prospective study including 53 eyes of patients with type 2 DM and 32 eyes of healthy controls. Based on SD-OCT (spectral domain—optical coherence tomography) images, using a micro-densitometry method, we measured the outer and luminal diameter of retinal arteries and calculated the AWT (arterial wall thickness), WLR (wall-to-lumen ratio), and WCSA (wall cross-sectional area). GCL (ganglion cell layer) and RNFL (retinal nerve fiber layer) thickness were analyzed in correlation with the retinal arterial morphometric parameters mentioned above. Results: GCL was thinner in the inner quadrants in the NDR (no DR) group compared to controls (p < 0.05). RAOD (retinal artery outer diameter), RALD (retinal artery lumen diameter), AWT, WLR, and WCSA were similar between groups. A regression model considering age, gender, duration of DM, and HbA1C was carried out. Central GCL thickness was correlated positively with RAOD (coefficient 0.360 per µm, p = 0.011), RALD (coefficient 0.283 per µm, p = 0.050), AWT (coefficient 0.304 per µm, p = 0.029), and WCSA (coefficient 3.90 per µm, p = 0.005). Duration of DM was positively correlated with WCSA (coefficient 0.311 per one year duration of diabetes, p = 0.043). Conclusions: Significant GCL thinning in the inner quadrants preceded the morphological retinal arterial morphometric changes, supporting the neurodegeneration as primary pathogenic mechanism in DR. Full article
(This article belongs to the Section Ophthalmology)
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Figure 1

Figure 1
<p>Measurement of the retinal vessel outer and lumen diameters in an OCT image using the micro-densitometry method. (Top left) A circular scan was performed across the vessels at the intersection of zone A to zone B. (Top right) The cross-sectional structure of the retinal artery (red arrow) and vein (blue arrow) could be identified in the OCT image. (Bottom left) The line selection vertically crossed the middle of the upper and lower vessel walls to produce an intensity profile. (Bottom right) The boundary points were estimated at half maximum intensity for each side of the two parabolas in the profile. The distance between the boundary points was calculated for the vessel outer and lumen diameters.</p>
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<p>Cross-section through a simplified artery to illustrate retinal artery morphometric parameters.</p>
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<p>Bland–Altman plots of RAOD and RALD. (<b>A</b>) shows intra−grader reliability for RAOD and (<b>B</b>) shows intra−grader reliability for RALD. The difference was calculated by the 1st measurement minus the 2nd measurement. Pink line represents regression line of difference between 1st and 2nd measurements.</p>
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<p>Correlation between macular RNFL and GCL thickness: left figure in control group, middle figure in NDR and right for NPDR. R, correlation coefficient; <span class="html-italic">p</span>, <span class="html-italic">p</span>-value; strong correlation is highlighted in bold and moderate correlation in italic. No significant correlation between morphometric parameters and creatinine or eGFR was found in the groups of patients with DM (<span class="html-italic">p</span> &gt; 0.05).</p>
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17 pages, 1635 KiB  
Article
Retinal Oxygenation in Inherited Diseases of the Retina
by Cengiz Türksever, Lisette T. López Torres, Christophe Valmaggia and Margarita G. Todorova
Genes 2021, 12(2), 272; https://doi.org/10.3390/genes12020272 - 14 Feb 2021
Cited by 5 | Viewed by 2226
Abstract
(1) Background: The aim of our study was to investigate the relationship between retinal metabolic alterations (retinal vessel oximetry, RO) and structural findings (retinal vessel diameter, central retinal thickness and retinal nerve fiber layer thickness, RNFL) in patients with inherited retinal diseases (IRDs). [...] Read more.
(1) Background: The aim of our study was to investigate the relationship between retinal metabolic alterations (retinal vessel oximetry, RO) and structural findings (retinal vessel diameter, central retinal thickness and retinal nerve fiber layer thickness, RNFL) in patients with inherited retinal diseases (IRDs). (2) Methods: A total of 181 eyes of 92 subjects were examined: 121 eyes of 62 patients with IRDs were compared to 60 eyes of 30 healthy age-matched controls. The retinal vessel oximetry was performed with the oxygen saturation measurement tool of the Retinal Vessel Analyser (RVA; IMEDOS Systems UG, Jena, Germany). The oxygen saturation in all four major peripapillary retinal arterioles (A-SO2; %) and venules (V-SO2; %) were measured and their difference (A-V SO2; %) was calculated. Additionally, retinal vessel diameters of the corresponding arterioles (D-A; µm) and venules (D-V; µm) were determined. The peripapillary central retinal thickness and the RNFL thickness were measured using spectral domain optical coherence tomography (SD-OCT) (Carl Zeiss Meditec, Dublin, CA, USA). Moreover, we calculated the mean central retinal oxygen exposure (cO2-E; %/µm) and the mean peripapillary oxygen exposure (pO2-E; %/µm) per micron of central retinal thickness and nerve fiber layer thickness by dividing the mean central retinal thickness (CRT) and the RNFL thickness with the mean A-V SO2. (3) Results: Rod-cone dystrophy patients had the highest V-SO2 and A-SO2, the lowest A-V SO2, the narrowest D-A and D-V and the thickest RNFL, when compared not only to controls (p ≤ 0.040), but also to patients with other IRDs. Furthermore, in rod-cone dystrophies the cO2-E and the pO2-E were higher in comparison to controls and to patients with other IRDs (p ≤ 0.005). Cone-rod dystrophy patients had the lowest cO2-E compared to controls and patients with other IRDs (p ≤ 0.035). Evaluated in central zones, the cO2-E was significantly different when comparing cone-rod dystrophy (CRD) against rod-cone dystrophy (RCD) patients in all zones (p < 0.001), whereas compared with controls and patients with inherited macular dystrophy this was observed only in zones 1 and 2 (p ≤ 0.018). The oxygen exposure was also the highest in the RCD group for both the nasal and the temporal peripapillary area, among all the evaluated groups (p ≤ 0.025). (4) Conclusions: The presented metabolic-structural approach enhances our understanding of inherited photoreceptor degenerations. Clearly demonstrated through the O2-E comparisons, the central and the peripapillary retina in rod-cone dystrophy eyes consume less oxygen than the control-eyes and eyes with other IRDs. Rod-cone dystrophy eyes seem to be proportionally more exposed to oxygen, the later presumably leading to more pronounced oxidative damage-related remodeling. Full article
(This article belongs to the Special Issue Study of Inherited Retinal Diseases)
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Figure 1

Figure 1
<p>Vessel map of the retinal oximetry (RO) image, showing color-coded oxygen saturation (SO<sub>2</sub>) values of retinal vessels within the peripapillary annulus of a control. Scheme: 1.0–1.5 optic disc diameter distances from the optic disc margin. CRD—cone-rod dystrophy; IMD—inherited macular dystrophy; RCD—rod-cone dystrophy.</p>
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<p>An example of RNFL thickness (12 scans, 6-mm optic nerve head-centered raster) and macular thickness protocol (Macular Cube 512 × 128) of a control subject (top, left eye), a patient with RCD (left eye), a patient with CRD (left eye) and a patient with IMD (bottom, left eye). The naso-temporal values were calculated from the values corresponding to the nasal and temporal main peripapillary vessels. The ETDRS chart for calculation of the central retinal exposure parameters in zones is plotted around the fovea.</p>
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<p>Box plots for the evaluated parameters, as follows: oxygen saturation (<b>a</b>); retinal vessel diameter (<b>b</b>), central retinal thickness (<b>c</b>), RNFL thickness (<b>d</b>), central oxygen exposure in zones (<b>e</b>) and peripapillary naso-temporal oxygen exposure (<b>f</b>) parameters.</p>
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