Distinguishing cognitive impairment by using singularity spectrum and lacunarity analysis of the retinal vascular network

Edmund Arthur, Gabor Mark Somfai, Maja Kostic, Susel Oropesa, Carlos Mendoza Santiesteban, Delia Cabrera DeBuc

Research output: Contribution to journalArticle

Abstract

The development of effective therapies for cognitive impairment (CI), especially due to Alzheimer's disease, demands diagnosing the condition during the prodromal phase. The diagnosis of CI involves expensive and invasive methods, such as positron emission tomography and cerebrospinal fluid assessment via spinal tap. Hence, a comparatively lower cost and noninvasive method of diagnosis is imperative. The human retina is an extension of the brain characterized by similarities in vascular and neural structures. The complications of CI are not only limited to the brain but also affect the retina for which the loss of retinal ganglion cells has been associated with neurodegeneration in the brain. The loss of retinal ganglion cells in individuals with CI may be related to reduced vascular demand and a potential remodeling of the retinal vascular branching complexity. Retinal imaging biomarkers may provide a low cost and noninvasive alternative for the diagnosis of CI. In this study, the retinal vascular branching complexity of patients with CI was characterized using the singularity spectrum multifractal dimension and lacunarity parameter. A reduced vascular branching complexity was observed in subjects with CI when compared to age-and sex-matched cognitively healthy controls. Significant associations were also found between retinal vascular and functional parameters.

Original languageEnglish (US)
Article number041109
JournalNeurophotonics
Volume6
Issue number4
DOIs
StatePublished - Oct 1 2019

Keywords

  • Cognitive impairment
  • Lacunarity
  • Multifractal analysis
  • Retinal vascular complexity
  • Singularity spectrum

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging

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