Publications by authors named "Daniel Deussen"

This study investigates the efficacy of predicting age-related macular degeneration (AMD) activity through deep neural networks (DNN) using a cross-instrument training dataset composed of Optical coherence tomography-angiography (OCTA) images from two different manufacturers. A retrospective cross-sectional study analyzed 2D vascular en-face OCTA images from Heidelberg Spectralis (1478 samples: 1102 training, 276 validation, 100 testing) and Optovue Solix (1003 samples: 754 training, 189 validation, 60 testing). OCTA scans were labeled based on clinical diagnoses and adjacent B-scan OCT fluid information, categorizing activity into normal, dry AMD, active wet AMD, and wet AMD in remission.

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Article Synopsis
  • Age-related Macular Degeneration (AMD) leads to central vision loss, and Optical Coherence Tomography Angiography (OCTA) helps diagnose it by showing problematic blood vessels.
  • This study is the first to use OCTA specifically for grading AMD severity through deep learning classifiers.
  • The researchers developed a 2D convolutional neural network that analyzes 3D OCTA volumes, achieving over 80% accuracy in grading AMD stages, outperforming human experts who achieved only around 60%.
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In this retrospective case series on neovascular age-related macular degeneration (nAMD), we aimed to improve Choroidal Neovascularization (CNV) visualization in Optical Coherence Tomography Angiography (OCTA) scans by addressing segmentation errors. Out of 198 eyes, 73 OCTA scans required manual segmentation correction. We compared uncorrected scans to those with minimal (2 corrections), moderate (10 corrections), and detailed (50 corrections) efforts targeting falsely segmented Bruch's Membrane (BM).

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Type 2 diabetes (T2D) has a complex pathophysiology which makes modeling the disease difficult. We aimed to develop a novel model for simulating T2D in vitro, including hyperglycemia, hyperlipidemia, and variably elevated insulin levels targeting muscle cells. We investigated insulin resistance (IR), cellular respiration, mitochondrial morphometry, and the associated function in different T2D-mimicking conditions in rodent skeletal (C2C12) and cardiac (H9C2) myotubes.

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Article Synopsis
  • The study investigates whether using optical coherence tomography angiography (OCTA) can help predict stages of age-related macular degeneration (AMD) by visualizing blood vessel structures, and explores the effectiveness of artificial intelligence (AI) in this prediction process.
  • Researchers analyzed 310 high-resolution OCTA scans, identifying four categories of AMD, and found that AI achieved an accuracy of 80.36%, outperforming human experts in predicting disease status.
  • The findings suggest that choroidal neovascularization (abnormal blood vessel growth) can indicate disease activity, highlighting the need for future research to track its changes over time and improve treatment response predictions using a combination of imaging techniques.
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This cross-sectional study aimed to investigate the hypothesis that permanent capillary damage may underlie the long-term COVID-19 sequela by quantifying the retinal vessel integrity. Participants were divided into three subgroups; Normal controls who had not been affected by COVID-19, mild COVID-19 cases who received out-patient care, and severe COVID-19 cases requiring intensive care unit (ICU) admission and respiratory support. Patients with systemic conditions that may affect the retinal vasculature before the diagnosis of COVID-19 infection were excluded.

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β1 integrins (β1) transduce mechanical signals in many cells, including cardiac myocytes (CM). Given their close localization, as well as their role in mechanotransduction and signaling, we hypothesized that caveolin (Cav) proteins might regulate integrins in the CM. β1 localization, complex formation, activation state, and signaling were analyzed using wild-type, Cav3 knockout, and Cav3 CM-specific transgenic heart and myocyte samples.

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