J 2019

Spectral domain optical coherence tomography based imaging biomarkers for diabetic retinopathy

SAXENA, Sandeep, Martin CAPRNDA, Surabhi RUIA, Senthamizh PRASAD, Ankita ANKITA et. al.

Basic information

Original name

Spectral domain optical coherence tomography based imaging biomarkers for diabetic retinopathy

Authors

SAXENA, Sandeep (356 India), Martin CAPRNDA (703 Slovakia), Surabhi RUIA (356 India), Senthamizh PRASAD (356 India), Ankita ANKITA (356 India), Julia FEDOTOVA (643 Russian Federation), Peter KRUŽLIAK (703 Slovakia, guarantor, belonging to the institution) and Vladimir KRASNIK (703 Slovakia)

Edition

ENDOCRINE, NEW YORK, SPRINGER, 2019, 1355-008X

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30202 Endocrinology and metabolism

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 3.235

RIV identification code

RIV/00216224:14110/19:00112408

Organization unit

Faculty of Medicine

DOI

UT WoS

000504207800010

Keywords in English

Diabetic retinopathy; Diabetic macular edema; Central subfield thickness; Cube average thickness; Cube volume; Spectral-domain optical coherence tomography

Tags

Tags

International impact, Reviewed
Změněno: 24/1/2020 14:49, Mgr. Tereza Miškechová

Abstract

V originále

To evaluate the role of central subfield thickness (CST), cube average thickness (CAT), and cube volume (CV) as imaging biomarkers for severity of diabetic retinopathy within the ETDRS-based grades of retinopathy using spectral domain optical coherence tomography (SD-OCT). This study aims to evaluate the role of macular CST, CAT, and CV on SD-OCT as imaging biomarkers for severity of DR. One hundred ninety-four consecutive cases of type 2 diabetes mellitus were divided according to ETDRS classification: diabetes mellitus without retinopathy (No DR; n = 65), nonproliferative diabetic retinopathy (NPDR; n = 66), and proliferative diabetic retinopathy (PDR; n = 63). Sixty-three healthy controls were included. CST, CAT, and CV were analyzed using SD-OCT. Data were analyzed statistically. Analysis of variance revealed a significant increase in levels of CST, CAT, CV, and LogMAR visual acuity with the increase in severity of DR. Independent t-test revealed significant difference in CST, CAT, and CV between cases with DME and cases without DME. On multivariate linear regression analysis, increase in CST, CAT, and CV were found to indicate the increase in severity of DR. SD-OCT-based imaging biomarkers CST, CAT, and CV are effective tools for documenting the severity of diabetic retinopathy. These imaging biomarkers serve as significant indicators of severity of disease.