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Retinal OCT biomarkers and their association with cognitive function—clinical and AI approaches

Retinale OCT-Biomarker und ihr Zusammenhang mit kognitiven Funktionen – klinische Praxis und KI-Ansätze. Englische Version

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The Original Article was published on 29 January 2024

Abstract

Retinal optical coherence tomography (OCT) biomarkers have the potential to serve as early, noninvasive, and cost-effective markers for identifying individuals at risk for cognitive impairments and neurodegenerative diseases. They may also aid in monitoring disease progression and evaluating the effectiveness of interventions targeting cognitive decline. The association between retinal OCT biomarkers and cognitive performance has been demonstrated in several studies, and their importance in cognitive assessment is increasingly being recognized. Machine learning (ML) is a branch of artificial intelligence (AI) with an exponential number of applications in the medical field, particularly its deep learning (DL) subset, which is widely used for the analysis of medical images. These techniques efficiently deal with novel biomarkers when their outcome for the applications of interest is unclear, e.g., for diagnosis, prognosis prediction, disease staging, or any other relevance to clinical practice. However, using AI-based tools for medical purposes must be approached with caution, despite the many efforts to address the black-box nature of such approaches, especially due to the general underperformance in datasets other than those used for their development. Retinal OCT biomarkers are promising as potential indicators for decline in cognitive function. The underlying mechanisms are currently being explored to gain deeper insights into this relationship linking retinal health and cognitive function. Insights from neurovascular coupling and retinal microvascular changes play an important role. Further research is needed to establish the validity and utility of retinal OCT biomarkers as early indicators of cognitive decline and neurodegenerative diseases in routine clinical practice. Retinal OCT biomarkers could then provide a new avenue for early detection, monitoring and intervention in cognitive impairment with the potential to improve patient care and outcomes.

Zusammenfassung

Retinale optische Kohärenztomographie (OCT)-Biomarker haben das Potenzial, als frühzeitige, nichtinvasive und kosteneffiziente Marker, Personen mit einem Risiko für kognitive Beeinträchtigungen und neurodegenerative Erkrankungen zu identifizieren. Sie können auch bei der Überwachung des Krankheitsverlaufs inklusive der Wirksamkeit von Maßnahmen gegen den kognitiven Verfall unterstützen. Der Zusammenhang zwischen retinalen OCT-Biomarkern und kognitiver Leistung wurde in mehreren Studien nachgewiesen, und ihre Bedeutung für die kognitive Beurteilung wird zunehmend anerkannt. Das maschinelle Lernen (ML) ist ein Zweig der künstlichen Intelligenz (KI) mit einer exponentiellen Anzahl von Anwendungen im medizinischen Bereich, insbesondere aus deren Untergruppe des tiefen Lernens (Deep Learning [DL]), die weithin für die Analyse medizinischer Bilder verwendet wird. Diese Techniken sind effizient im Umgang mit neuartigen Biomarkern, wenn deren Ergebnis für die im Fokus stehende Anwendung unklar ist. Der Einsatz von KI-basierten Werkzeugen für medizinische Zwecke muss jedoch, trotz der vielen Bemühungen den Blackbox-Charakter solcher Ansätze zu überwinden, mit Vorsicht genossen werden, v. a. wegen der allgemein unzureichenden Leistung der KI bei anderen Datensätzen als denen, die für ihre Entwicklung verwendet wurden. Die retinalen OCT-Biomarker sind vielversprechend als potenzielle Indikatoren für die kognitive Funktion. Die zugrunde liegenden Mechanismen werden aktuell erforscht, um tiefere Einblicke in die Beziehung zu gewinnen, welche Netzhautgesundheit und kognitive Funktion miteinander verbindet. Erkenntnisse aus neurovaskulärer Kopplung und den mikrovaskulären Veränderungen der Netzhaut spielen dabei eine wichtige Rolle. Weitere Forschungsarbeiten sind erforderlich, um die Gültigkeit und den Nutzen retinaler OCT-Biomarker als Frühindikatoren für kognitiven Abbau und neurodegenerative Erkrankungen in der klinischen Routine zu ermitteln. Retinale OCT-Biomarker könnten so die Patientenversorgung mittels Früherkennung und Überwachung potentieller Intervention bei kognitiven Beeinträchtigungen verbessern.

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Authors and Affiliations

  1. Leipzig Research Centre for Civilisation Diseases (LIFE), Leipzig University, Leipzig, Germany

    Franziska G. Rauscher

  2. Institute for Medical Informatics, Statistics, and Epidemiology, Leipzig University, Haertelstraße 16–18, 04107, Leipzig, Germany

    Franziska G. Rauscher

  3. Centre for Medical Informatics - Department of Medical Data Science, Leipzig University Medical Center, Leipzig, Germany

    Franziska G. Rauscher

  4. Coimbra Institute for Biomedical Imaging and Translational Research (CIBIT), Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Azinhaga de Santa Comba, 3000-548, Coimbra, Portugal

    Rui Bernardes

  5. Clinical Academic Center of Coimbra (CACC), Faculty of Medicine (FMUC), University of Coimbra, Azinhaga de Santa Comba, 3000-548, Coimbra, Portugal

    Rui Bernardes

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Rauscher, F.G., Bernardes, R. Retinal OCT biomarkers and their association with cognitive function—clinical and AI approaches. Ophthalmologie (2024). https://doi.org/10.1007/s00347-024-01988-9

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