Wide-field corneal subbasal nerve plexus mosaics in age-controlled healthy and type 2 diabetes populations

Scientific data - Tập 5 Số 1
Neil Lagali1, Stephan Allgeier2, Pedro Guimarães3, Reza A. Badian4,5,6, Alfredo Ruggeri3, Bernd Köhler2, Tor Paaske Utheim5,6, Beatrice Peebo1, Magnus Peterson7, Lars B. Dahlin8, Olov Rolandsson9
1Department of Ophthalmology, Institute for Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
2Institute for Applied Computer Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
3Department of Information Engineering, University of Padova, Padova, Italy
4Faculty of Health Sciences, University College of Southeast Norway, Drammen, Norway
5Unit of Regenerative Medicine, Department of Medical Biochemistry, Oslo University Hospital,
6University of Oslo, Oslo, Norway
7Department of Public Health and Caring Sciences, Section of Family Medicine and Preventive Medicine, Uppsala University, Uppsala, Sweden
8Department of Translational Medicine - Hand Surgery, Lund University, Skåne University Hospital, Malmö, Sweden
9Department of Public Health and Clinical Medicine, Section of Family Medicine, Umeå University, Umeå, Sweden

Tóm tắt

AbstractA dense nerve plexus in the clear outer window of the eye, the cornea, can be imaged in vivo to enable non-invasive monitoring of peripheral nerve degeneration in diabetes. However, a limited field of view of corneal nerves, operator-dependent image quality, and subjective image sampling methods have led to difficulty in establishing robust diagnostic measures relating to the progression of diabetes and its complications. Here, we use machine-based algorithms to provide wide-area mosaics of the cornea’s subbasal nerve plexus (SBP) also accounting for depth (axial) fluctuation of the plexus. Degradation of the SBP with age has been mitigated as a confounding factor by providing a dataset comprising healthy and type 2 diabetes subjects of the same age. To maximize reuse, the dataset includes bilateral eye data, associated clinical parameters, and machine-generated SBP nerve density values obtained through automatic segmentation and nerve tracing algorithms. The dataset can be used to examine nerve degradation patterns to develop tools to non-invasively monitor diabetes progression while avoiding narrow-field imaging and image selection biases.

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Tài liệu tham khảo

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