June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Diabetic retino-choroidopathy: automated morphofunctional assessment
Author Affiliations & Notes
  • Marco Lupidi
    Biomedical and Surgical Sciences, Eye Clinic, University of Perugia, Perugia, Italy
    Odeon Ophthalmology Center, Paris, France
  • Carlo Cagini
    Biomedical and Surgical Sciences, Eye Clinic, University of Perugia, Perugia, Italy
  • Florence Coscas
    Odeon Ophthalmology Center, Paris, France
  • Fiore Tito
    Biomedical and Surgical Sciences, Eye Clinic, University of Perugia, Perugia, Italy
  • Massimo Nicolo'
    Di.N.O.G.Mi, Clinica Oculistica, Università di Genova, Genova, Italy
  • Felice Cardillo Piccolino
    The Macula Onlus Foundation, Genova, Italy
  • Gabriel J Coscas
    Odeon Ophthalmology Center, Paris, France
  • Footnotes
    Commercial Relationships   Marco Lupidi, Allergan (R); Carlo Cagini, None; Florence Coscas, None; Fiore Tito, None; Massimo Nicolo', None; Felice Cardillo Piccolino, None; Gabriel Coscas, Heidelberg Engineering (C)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 1659. doi:
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      Marco Lupidi, Carlo Cagini, Florence Coscas, Fiore Tito, Massimo Nicolo', Felice Cardillo Piccolino, Gabriel J Coscas; Diabetic retino-choroidopathy: automated morphofunctional assessment. Invest. Ophthalmol. Vis. Sci. 2017;58(8):1659.

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

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Purpose : To perform a fully automated quantitative assessment of retinal and choroidal microvasculature in eyes with diabetic maculopathy (DM) using optical coherence tomography angiography (OCT-A) and to identify potential compensatory mechanisms secondary to focal vascular impairment.

Methods : Retrospective case series of 48 eyes of 48 patients with DM (19 females, mean age 66.2 ± 9.4 years) and 47 eyes of 47 age-matched controls evaluated by Spectralis HRA-OCT2 (Heidelberg Engineering, Heidelberg, Germany). The Full-spectrum probabilistic-decorrelation angiography (FS-PDA) generated optical coherence tomography angiograms of the superficial (SCP) and deep (DCP) capillary plexuses and of the choriocapillaris (CC) layer. A fully automated micro-structural analysis, obtained by a custom built software (AngiOCTool+™) provided data on FAZ metrics and SCP, DCP or CC vessel density. A comparative analysis between different vascular layers was performed; the obtained data were also compared with those of healthy subjects.

Results : A statistically significant difference (p<0.05) in FAZ surface values was shown between the SCP and DCP both in diabetic and healthy subjects, while no differences were reported for vascular densities. A negative linear correlation in terms of vessel density was reported between CC and both SCP and DCP in diabetic patients (Spearman’s coefficient of rank correlation); at the reverse a positive linear correlation between the same parameters was noticed in healthy subjects. Capillary density values were significantly lower (p<0.05) in all retinal vascular layers and choriocapillaris of DM patients compared with healthy subjects.

Conclusions : A fully automated quantitative OCT-A approach is a useful imaging system for detecting diabetic-induced focal vascular impairment both in retinal and choroidal layers. Retinal and choroidal vascular networks, although distinct entities, seem functionally interconnected: varying the degree of perfusion may be a mutual compensatory mechanism in response to an ischemic injury.

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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