June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Spatial distribution modelling of retinal lesions with application to retinal capillary non-perfusion in malarial retinopathy.
Author Affiliations & Notes
  • Gabriela Czanner
    Department of Eye and Vision Science and Biostatistics, University of Liverpool, Liverpool, United Kingdom
    St. Paul’s Eye Unit, Royal Liverpool University Hospital, Liverpool, United Kingdom
  • Ian James MacCormick
    Malawi-Liverpool-Wellcome Trust, Blantyre, Malawi
    Centre for Clinical Brain Research, University of Edinburgh, Edinburgh, United Kingdom
  • Yalin Zheng
    Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom
    St. Paul’s Eye Unit, Royal Liverpool University Hospital, Liverpool, United Kingdom
  • Silvester Czanner
    Manchester Metropolitan University, Manchester, United Kingdom
  • Yitian Zhao
    School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
  • Peter Diggle
    CHICAS Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
  • Simon P Harding
    Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom
    St. Paul’s Eye Unit, Royal Liverpool University Hospital, Liverpool, United Kingdom
  • Footnotes
    Commercial Relationships   Gabriela Czanner, None; Ian MacCormick, None; Yalin Zheng, None; Silvester Czanner, None; Yitian Zhao, None; Peter Diggle, None; Simon Harding, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 4819. doi:
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      Gabriela Czanner, Ian James MacCormick, Yalin Zheng, Silvester Czanner, Yitian Zhao, Peter Diggle, Simon P Harding; Spatial distribution modelling of retinal lesions with application to retinal capillary non-perfusion in malarial retinopathy.. Invest. Ophthalmol. Vis. Sci. 2017;58(8):4819.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Evaluation of retinal disease typically focuses on assessing the number or size of lesions, but this ignores the fact that the retina is made up of diverse anatomical regions. Adding spatial location to analyses may increases the power to detect retinal disease features. We use capillary non-perfusion (CNP) as an example because CNP is common and relevant for diabetic retinopathy, retinal vein occlusion and posterior uveitis. We use malarial retinopathy as an example with death as a clear endpoint.

Methods : Comatose Malawian children with cerebral malaria and malarial retinopathy were recruited into a prospective observational study and underwent dilated ophthalmoscopic exam and fluorescein angiography (FA) on admission. We divided the macula and mid periphery (6.3 mm radius) into 48 sectors (see Figure) and used percentage of CNP pixels in each sector to characterise the spatial distribution of lesions across the retina. We developed a hierarchical statistical model to represent the CNP spatial distribution with goniometric functions, estimated the model parameters by maximum likelihood and tested associations with the primary outcome, death.

Results : 172 cases were recruited (2009 to 2014) amongst whom 138 had fair, good or excellent quality FA images (120 survived and 18 died). Using our spatial model we found that in malarial retinopathy macular CNP generally occurs around the fovea and in the temporal macula with increased CNP in death (p=0.03). The highest CNP differences were in the macular temporal area (27% vs 31%, for survived vs died, p=0.01) and peripheral temporal area (15% vs 22%, for survived vs died, p<0.01). Less strong associations were found using two-sample t-tests, with insignificant associations between the macula and outcome (all 24 p-values >0.05) and one significant sector for periphery (p-value=0.02, other 23 p-values >0.05). Lower image quality led to higher within-eye variation (17% and 28% higher SD for good and fair vs. excellent quality images).

Conclusions : We developed a novel statistical modelling approach to analyse spatial lesion in the retina. We illustrated the spatial approach in the analysis of lesions of macular CNP and showed that it provides both a richer description of lesions than existing methods and increased power to detect associations with clinical outcome. This technique is relevant to a range of retinal diseases.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

 

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