Comparisons of Handheld Retinal Imaging with Optical Coherence Tomography for the Identification of Macular Pathology in Patients with Diabetes.

Diabetic macular edema Diabetic retinopathy Handheld devices Retinal imaging Validation study

Journal

Ophthalmic research
ISSN: 1423-0259
Titre abrégé: Ophthalmic Res
Pays: Switzerland
ID NLM: 0267442

Informations de publication

Date de publication:
20 Apr 2023
Historique:
received: 15 02 2023
accepted: 11 04 2023
pubmed: 21 4 2023
medline: 21 4 2023
entrez: 20 04 2023
Statut: aheadofprint

Résumé

Handheld retinal imaging cameras are relatively inexpensive and highly portable devices that have the potential to significantly expand diabetic retinopathy (DR) screening, allowing a much broader population to be evaluated. However, it is essential to evaluate if these devices can accurately identify vision-threatening macular diseases if DR screening programs will rely on these instruments. Thus, the purpose of this study was to evaluate the detection of diabetic macular pathology using monoscopic macula-centered images using mydriatic handheld retinal imaging compared with spectral domain optical coherence tomography (SDOCT). Mydriatic 40°-60° macula-centered images taken with 3 handheld retinal imaging devices (Aurora [AU], SmartScope [SS], RetinaVue 700 [RV]) were compared with the Cirrus 6000 SDOCT taken during the same visit. Images were evaluated for the presence of diabetic macular edema (DME) on monoscopic fundus photographs adapted from Early Treatment Diabetic Retinopathy Study (ETDRS) definitions (no DME, noncenter-involved DME [non-ciDME], and center-involved DME [ciDME]). Sensitivity, specificity, positive predictive value, and negative predictive value were calculated for each device with SDOCT as gold standard. Severity by ETDRS photos: no DR 33.3%, mild NPDR 20.4%, moderate 14.2%, severe 11.6%, proliferative 20.4%, and ungradable for DR 0%; no DME 83.1%, non-ciDME 4.9%, ciDME 12.0%, and ungradable for DME 0%. Gradable images by SDOCT (N = 217, 96.4%) showed no DME in 75.6%, non-ciDME in 9.8%, and ciDME in 11.1%. The ungradable rate for images (poor visualization in >50% of the macula) was AU: 0.9%, SS: 4.4%, and RV: 6.2%. For DME, sensitivity and specificity were similar across devices (0.5-0.64, 0.93-0.97). For nondiabetic macular pathology (ERM, pigment epithelial detachment, traction retinal detachment) across all devices, sensitivity was low to moderate (0.2-0.5) but highly specific (0.93-1.00). Compared to SDOCT, handheld macular imaging attained high specificity but low sensitivity in identifying macular pathology. This suggests the importance of SDOCT evaluation for patients suspected to have DME on fundus photography, leading to more appropriate referral refinement.

Identifiants

pubmed: 37080187
pii: 000530720
doi: 10.1159/000530720
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

903-912

Informations de copyright

© 2023 The Author(s). Published by S. Karger AG, Basel.

Auteurs

Cris Martin P Jacoba (CMP)

Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA.
Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA.

Recivall P Salongcay (RP)

Philippine Eye Research Institute, University of the Philippines, Manila, Philippines.
Centre for Public Health, Queen's University, Belfast, UK.
Eyes and Vision Institute, The Medical City, Pasig City, Philippines.

Abdulrahman K Rageh (AK)

Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA.
Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA.

Lizzie Anne C Aquino (LAC)

Philippine Eye Research Institute, University of the Philippines, Manila, Philippines.

Glenn P Alog (GP)

Philippine Eye Research Institute, University of the Philippines, Manila, Philippines.
Eyes and Vision Institute, The Medical City, Pasig City, Philippines.

Aileen V Saunar (AV)

Philippine Eye Research Institute, University of the Philippines, Manila, Philippines.
Eyes and Vision Institute, The Medical City, Pasig City, Philippines.

Tunde Peto (T)

Centre for Public Health, Queen's University, Belfast, UK.

Paolo S Silva (PS)

Beetham Eye Institute, Joslin Diabetes Center, Boston, Massachusetts, USA.
Department of Ophthalmology, Harvard Medical School, Boston, Massachusetts, USA.
Philippine Eye Research Institute, University of the Philippines, Manila, Philippines.
Eyes and Vision Institute, The Medical City, Pasig City, Philippines.

Classifications MeSH