Corneal Nerve Fractal Dimension: A Novel Corneal Nerve Metric for the Diagnosis of Diabetic Sensorimotor Polyneuropathy


Chen, Xin, Graham, Jim, Petropoulos, Ioannis N, Ponirakis, Georgios, Asghar, Omar, Alam, Uazman ORCID: 0000-0002-3190-1122, Marshall, Andrew ORCID: 0000-0001-8273-7089, Ferdousi, Maryam, Azmi, Shazli, Efron, Nathan et al (show 1 more authors) (2018) Corneal Nerve Fractal Dimension: A Novel Corneal Nerve Metric for the Diagnosis of Diabetic Sensorimotor Polyneuropathy. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 59 (2). pp. 1113-1118.

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Abstract

Objective: Corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, is a noninvasive and objective imaging biomarker for identifying small nerve fiber damage. We have evaluated the diagnostic performance of previously established CCM parameters to a novel automated measure of corneal nerve complexity called the corneal nerve fiber fractal dimension (ACNFrD). Methods: A total of 176 subjects (84 controls and 92 patients with type 1 diabetes) with and without diabetic sensorimotor polyneuropathy (DSPN) underwent CCM. Fractal dimension analysis was performed on CCM images using purpose-built corneal nerve analysis software, and compared with previously established manual and automated corneal nerve fiber measurements. Results: Manual and automated subbasal corneal nerve fiber density (CNFD) (P < 0.0001), length (CNFL) (P < 0.0001), branch density (CNBD) (P < 0.05), and ACNFrD (P < 0.0001) were significantly reduced in patients with DSPN compared to patients without DSPN. The areas under the receiver operating characteristic curves for identifying DSPN were comparable: 0.77 for automated CNFD, 0.74 for automated CNFL, 0.69 for automated CNBD, and 0.74 for automated ACNFrD. Conclusions: ACNFrD shows comparable diagnostic efficiency to identify diabetic patients with and without DSPN.

Item Type: Article
Uncontrolled Keywords: corneal confocal microscopy, diabetic neuropathy, image segmentation, nerve fiber quantification
Depositing User: Symplectic Admin
Date Deposited: 05 Mar 2018 07:20
Last Modified: 19 Jan 2023 06:38
DOI: 10.1167/iovs.17-23342
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3018621
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