Your browser doesn't support javascript.
loading
Retinal capillary perfusion heterogeneity in diabetic retinopathy detected by optical coherence tomography angiography.
Yuan, Po Hsiang Shawn; Athwal, Arman; Shalaby, Mena; Mehnert, Andrew; Yu, Dao-Yi; Preti, Rony C; Sarunic, Marinko; Navajas, Eduardo V.
Afiliação
  • Yuan PHS; Department of Ophthalmology and Visual Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
  • Athwal A; School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada.
  • Shalaby M; School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada.
  • Mehnert A; Centre for Ophthalmology and Visual Science, University of Western Australia, Perth, Australia.
  • Yu DY; Lions Eye Institute, Nedlands, WA, Australia.
  • Preti RC; Centre for Ophthalmology and Visual Science, University of Western Australia, Perth, Australia.
  • Sarunic M; Lions Eye Institute, Nedlands, WA, Australia.
  • Navajas EV; Department of Ophthalmology, University of Sao Paulo, Sau Paulo, Brazil.
Int J Retina Vitreous ; 10(1): 12, 2024 Jan 25.
Article em En | MEDLINE | ID: mdl-38273321
ABSTRACT

BACKGROUND:

Diabetic retinopathy (DR) is a leading cause of blindness and involves retinal capillary damage, microaneurysms, and altered blood flow regulation. Optical coherence tomography angiography (OCTA) is a non-invasive way of visualizing retinal vasculature but has not been used extensively to study blood flow heterogeneity. The purpose of this study is to detect and quantify blood flow heterogeneity utilizing en-face swept source OCTA in patients with DR.

METHODS:

This is a prospective clinical study which examined patients with either type 1 or 2 diabetes mellitus. Each included eye was graded clinically as no DR, mild DR, or moderate-severe DR. Ten consecutive en face 6 × 6 mm foveal SS-OCTA images were obtained from each eye using a PLEX Elite 9000 (Zeiss Meditec, Dublin, CA). Built-in fixation-tracking, follow-up functions were utilized to reduce motion artifacts and ensure same location imaging in sequential frames. Images of the superficial and deep vascular complexes (SVC and DVC) were arranged in temporal stacks of 10 and registered to a reference frame for segmentation using a deep neural network. The vessel segmentation was then masked onto each stack to calculate the pixel intensity coefficient of variance (PICoV) and map the spatiotemporal perfusion heterogeneity of each stack.

RESULTS:

Twenty-nine eyes were included 7 controls, 7 diabetics with no DR, 8 mild DR, and 7 moderate-severe DR. The PICoV correlated significantly and positively with DR severity. In patients with DR, the perfusion heterogeneity was higher in the temporal half of the macula, particularly in areas of capillary dropout. PICoV also correlates as expected with the established OCTA metrics of perfusion density and vessel density.

CONCLUSION:

PICoV is a novel way to analyze OCTA imaging and quantify perfusion heterogeneity. Retinal capillary perfusion heterogeneity in both the SVC and DVC increased with DR severity. This may be related to the loss of retinal capillary perfusion autoregulation in diabetic retinopathy.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article