Your browser doesn't support javascript.
loading
Differential Capillary and Large Vessel Analysis Improves OCTA Classification of Diabetic Retinopathy.
Abtahi, Mansour; Le, David; Ebrahimi, Behrouz; Dadzie, Albert K; Rahimi, Mojtaba; Hsieh, Yi-Ting; Heiferman, Michael J; Lim, Jennifer I; Yao, Xincheng.
Afiliación
  • Abtahi M; Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois, United States.
  • Le D; Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois, United States.
  • Ebrahimi B; Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois, United States.
  • Dadzie AK; Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois, United States.
  • Rahimi M; Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois, United States.
  • Hsieh YT; Department of Ophthalmology, National Taiwan University Hospital, Taipei, Taiwan.
  • Heiferman MJ; Department of Ophthalmology and Visual Sciences, University of Illinois Chicago, Chicago, Illinois, United States.
  • Lim JI; Department of Ophthalmology and Visual Sciences, University of Illinois Chicago, Chicago, Illinois, United States.
  • Yao X; Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois, United States.
Invest Ophthalmol Vis Sci ; 65(10): 20, 2024 Aug 01.
Article en En | MEDLINE | ID: mdl-39133470
ABSTRACT

Purpose:

This study aimed to investigate the impact of distinctive capillary-large vessel (CLV) analysis in optical coherence tomography angiography (OCTA) on the classification performance of diabetic retinopathy (DR).

Methods:

This multicenter study analyzed 212 OCTA images from 146 patients, including 28 controls, 36 diabetic patients without DR (NoDR), 31 with mild non-proliferative DR (NPDR), 28 with moderate NPDR, and 23 with severe NPDR. Quantitative features were derived from the whole image as well as the parafovea and perifovea regions. A support vector machine classifier was employed for DR classification. The accuracy and area under the receiver operating characteristic curve were used to evaluate the classification performance, utilizing features derived from the whole image and specific regions, both before and after CLV analysis.

Results:

Differential CLV analysis significantly improved OCTA classification of DR. In binary classifications, accuracy improved by 11.81%, rising from 77.45% to 89.26%, when utilizing whole image features. For multiclass classifications, accuracy increased by 7.55%, from 78.68% to 86.23%. Incorporating features from the whole image, parafovea, and perifovea further improved binary classification accuracy from 83.07% to 93.80%, and multiclass accuracy from 82.64% to 87.92%.

Conclusions:

This study demonstrated that feature changes in capillaries are more sensitive during DR progression, and CLV analysis can significantly improve DR classification performance by extracting features that are specific to large vessels and capillaries in OCTA. Incorporating regional features further improves DR classification accuracy. Differential CLV analysis promises better disease screening, diagnosis, and treatment outcome assessment.
Asunto(s)
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Vasos Retinianos / Capilares / Angiografía con Fluoresceína / Curva ROC / Tomografía de Coherencia Óptica / Retinopatía Diabética Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Invest Ophthalmol Vis Sci Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Vasos Retinianos / Capilares / Angiografía con Fluoresceína / Curva ROC / Tomografía de Coherencia Óptica / Retinopatía Diabética Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Invest Ophthalmol Vis Sci Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos