Einsatz von künstlicher Intelligenz im Screening auf diabetische Retinopathie an einer diabetologischen Schwerpunktklinik

Hintergrund Seit 2018 ist mit IDx-DR ein Verfahren auf dem Markt, welches den Grad der diabetischen Retinopathie (DR) mittels künstlicher Intelligenz (KI) bestimmt. Methoden Wir haben IDx-DR in die Sprechstunde an einer diabetologischen Schwerpunktklinik integriert und berichten über die Übereinstimmung zwischen IDx-DR (IDx Technologies Inc., Coralville, IA, USA) und Funduskopie sowie IDx-DR und ophthalmologischer Bildbeurteilung sowie über den Einfluss unterschiedlicher Kamerasysteme. Ergebnisse Mit der Topcon-Kamera (n = 456; NW400, Topcon Medical Systems, Oakland, NJ, USA) konnte im Vergleich zur Zeiss-Kamera (n = 47; Zeiss VISUCAM 500, Carl Zeiss Meditec AG, Jena, Deutschland) häufiger eine ausreichende Bildqualität in Miosis erreicht werden. Insgesamt war bei etwa 60 % der Patienten eine IDx-DR-Analyse in Miosis möglich. Alle Patienten, bei denen keine IDx-DR-Analyse in Miosis möglich war, konnten in Mydriasis funduskopiert werden. Innerhalb der Gruppe der auswertbaren Befunde zeigte sich eine Übereinstimmung zwischen IDx-DR und augenärztlicher Funduoskopie in ca. 55 %, ein Überschätzen des Schweregrads durch IDx-DR in ca. 40 % und ein Unterschätzen in ca. 4 %. Die Sensitivität (Spezifität) für das Erkennen einer schweren, behandlungsbedürftigen Retinopathie lag bei 95,7 % (89,1 %) für Fälle mit auswertbaren Fundusaufnahmen und bei 65,2 % (66,7 %), wenn alle Fälle betrachtet werden (inklusive derjeniger ohne verwertbare Aufnahme in Miosis). Der Kappa-Koeffizient zeigt mit 0,334 (p < 0,001) eine ausreichende Übereinstimmung zwischen IDx-DR und ärztlicher Bildauswertung anhand des Fundusfotos unter Berücksichtigung aller Patienten mit auswertbarer IDx-DR-Analyse. Der Vergleich zwischen IDx-DR mit der ärztlichen Funduskopie ergibt unter denselben Voraussetzungen eine geringe Übereinstimmung mit einem Kappa-Wert von 0,168 (p < 0,001). Schlussfolgerung Die vorliegende Studie zeigt Möglichkeiten und Grenzen des KI-gestützten DR-Screenings auf. Eine wesentliche Einschränkung liegt in der Tatsache, dass bei ca. 40 % der Patienten keine ausreichenden Aufnahmen in Miosis gewonnen werden konnten. Wenn ausreichende Aufnahmen vorlagen, stimmten IDx-DR und augenärztliche Diagnose in über 50 % der Fälle überein. Ein Unterschätzen des Schweregrades durch IDx-DR kam selten vor. Für die Integration in augenärztlich unterstützten Sprechstunden erscheint uns das System grundsätzlich geeignet. Die hohe Rate an fehlenden Aufnahmen in Miosis stellt allerdings eine Limitation dar, die einen Einsatz ohne augenärztliche Kontrollmöglichkeit schwierig erscheinen lässt.Background In 2018, IDx-DR was approved as a method to determine the degree of diabetic retinopathy (DR) using artificial intelligence (AI) by the FDA. Methods We integrated IDx-DR into the consultation at a diabetology focus clinic and report the agreement between IDx-DR and fundoscopy as well as IDx-DR and ophthalmological image assessment and the influence of different camera systems. Results Adequate image quality in miosis was achieved more frequently with the Topcon camera (n = 456; NW400, Topcon Medical Systems, Oakland, NJ, USA) compared with the Zeiss camera (n = 47; Zeiss VISUCAM 500, Carl Zeiss Meditec AG, Jena, Germany). Overall, IDx-DR analysis in miosis was possible in approximately 60% of the patients. All patients in whom IDx-DR analysis in miosis was not possible could be assessed by fundoscopy with dilated pupils. Within the group of images that could be evaluated, there was agreement between IDx-DR and ophthalmic fundoscopy in approximately 55%, overestimation of severity by IDx-DR in approximately 40% and underestimation in approximately 4%. The sensitivity (specificity) for detecting severe retinopathy requiring treatment was 95.7% (89.1%) for cases with fundus images that could be evaluated and 65.2% (66.7%) when all cases were considered (including those without images in miosis which could be evaluated). The kappa coefficient of 0.334 (p < 0.001) shows sufficient agreement between IDx-DR and physician’s image analysis based on the fundus photograph, considering all patients with IDx-DR analysis that could be evaluated. The comparison between IDx-DR and the physician’s funduscopy under the same conditions shows a low agreement with a kappa value of 0.168 (p < 0.001). Conclusion The present study shows the possibilities and limitations of AI-assisted DR screening. A major limitation is that sufficient images cannot be obtained in miosis in approximately 40% of patients. When sufficient images were available the IDx-DR and ophthalmological diagnosis matched in more than 50% of cases. Underestimation of severity by IDx-DR occurred only rarely. For integration into an ophthalmologist’s practice, this system seems suitable. Without access to an ophthalmologist the high rate of insufficient images in miosis represents an important limitation

Increased Expression of Angiogenic and Inflammatory Proteins in the Vitreous of Patients with Ischemic Central Retinal Vein Occlusion

<div><p>Background</p><p>Central retinal vein occlusion (CRVO) is a common disease characterized by a disrupted retinal blood supply and a high risk of subsequent vision loss due to retinal edema and neovascular disease. This study was designed to assess the concentrations of selected signaling proteins in the vitreous and blood of patients with ischemic CRVO.</p><p>Methods</p><p>Vitreous and blood samples were collected from patients undergoing surgery for ischemic CRVO (radial optic neurotomy (RON), n = 13), epiretinal gliosis or macular hole (control group, n = 13). Concentrations of 40 different proteins were determined by an ELISA-type antibody microarray.</p><p>Results</p><p>Expression of proteins enriched in the vitreous (CCL2, IGFBP2, MMP10, HGF, TNFRSF11B (OPG)) was localized by immunohistochemistry in eyes of patients with severe ischemic CRVO followed by secondary glaucoma. Vitreal expression levels were higher in CRVO patients than in the control group (CRVO / control; p < 0.05) for ADIPOQ (13.6), ANGPT2 (20.5), CCL2 (MCP1) (3.2), HGF (4.7), IFNG (13.9), IGFBP1 (14.7), IGFBP2 (1.8), IGFBP3 (4.1), IGFBP4 (1.7), IL6 (10.8), LEP (3.4), MMP3 (4.3), MMP9 (3.6), MMP10 (5.4), PPBP (CXCL7 or NAP2) (11.8), TIMP4 (3.8), and VEGFA (85.3). In CRVO patients, vitreal levels of CCL2 (4.2), HGF (23.3), IGFBP2 (1.23), MMP10 (2.47), TNFRSF11B (2.96), and VEGFA (29.2) were higher than the blood levels (vitreous / blood, p < 0.05). Expression of CCL2, IGFBP2, MMP10, HGF, and TNFRSF11B was preferentially localized to the retina and the retinal pigment epithelium (RPE).</p><p>Conclusion</p><p>Proteins related to hypoxia, angiogenesis, and inflammation were significantly elevated in the vitreous of CRVO patients. Moreover, some markers known to indicate atherosclerosis may be related to a basic vascular disease underlying RVO. This would imply that local therapeutic targeting might not be sufficient for a long term therapy in a systemic disease but hypothetically reduce local changes as an initial therapeutic approach.</p></div

Immunohistochemical staining (alkaline phosphatase, red; blue counter staining: hematoxylin) for CCL2, HGF, IGFBP2, MMP10, and TNFRSF11B in ocular samples of various patients.

<p>These factors were found preferentially in the retina and additionally in nerves and in the RPE. TNFRSF11B was found in the axons and some nuclei of extrascleral nerves. HGF was additionally found in the endothelium and media of some but not all extrascleral vessels. GFAP (glia cell marker), IBA1 (migroglia and macrophage marker, and COL IV (basement membrane marker, e.g. in the basement membrane of vessels and in the membrana limitans interna) are shown for comparison. Note that GFAP is not expressed in the outer segments of the photoreceptors as is the case for CCL2, HGF, IGFBP2, MMP10, and TNFRSF11B. neg: negative control without primary antibody, a: artery, n: nerve, ONL: outer nuclear layer, green arrow: RPE.</p

Antibodies used for immunohistochemistry.

<p>COL IV: collagen IV</p><p>GFAP: glial fibrillary acidic protein</p><p>IBA1: allograft inflammatory factor 1 (AIF1).</p><p>Antibodies used for immunohistochemistry.</p

Patient characteristics.

<p>SD = standard deviation</p><p>BCVA = best corrected visual acuity</p><p>CRVO = central retinal vein occlusion</p><p>Control = epiretinal gliosis or macular hole.</p><p>Patient characteristics.</p

Correlation of the vitreal concentration of PPBP, CCL2, and LEP with the time after occlusion (time between onset of symptoms due to CRVO and surgery).

<p>Each data point represents a pair of data from an individual patient. Note that the significance of LEP is lost if the highest value is omitted.</p

Concentration of various factors in vitreous fluid and blood serum of CRVO patients and controls.

<p>*significant difference as determined by nonparametric comparisons (p < 0.05)</p><p>Criteria for selected factors labeled in bold: vitreous concentration higher than blood values; or vitreous concentration of CRVO and control significantly different, and at least one value for vitreous above the detection limit. Italic factors: Vitreous values below detection limit.</p><p>All values for FGF4 and MMP13 were below the detection limit, and the values for concentrations of ANGPT1, CCL7, CXCL11, EGF, FGF2, IGF1, IGFBP5, IL1B, IL4, IL13, IL18BP, MMP2, MMP8, TNF, and TNFRSF18 in the vitreous of both CRVO patients and controls were below the detection limit.</p><p>The column “Correlation with time after occlusion” shows the Pearson product-moment correlation coefficient that is a measure of the linear correlation between the protein concentration in the vitreous or blood and the time after occlusion. * indicates statistical significance (p < 0.05). Note that the significance of LEP is lost if the highest value is omitted. The time after occlusion is the time between the CRVO and vitrectomy.</p><p>SD = standard deviation</p><p>V / B = vitreous / blood</p><p>CRVO = central retinal vein occlusion.</p><p>Concentration of various factors in vitreous fluid and blood serum of CRVO patients and controls.</p