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Computational Imaging Biomarker Correlation with Intraocular Cytokine Expression in Diabetic Macular Edema: Radiomics Insights from the IMAGINE Study.
Kar, Sudeshna Sil; Abraham, Joseph; Wykoff, Charles C; Sevgi, Duriye Damla; Lunasco, Leina; Brown, David M; Srivastava, Sunil K; Madabhushi, Anant; Ehlers, Justis P.
Afiliação
  • Kar SS; The Tony and Leona Campane Center for Excellence in Image-Guided Surgery and Advanced Imaging Research, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio.
  • Abraham J; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.
  • Wykoff CC; The Tony and Leona Campane Center for Excellence in Image-Guided Surgery and Advanced Imaging Research, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio.
  • Sevgi DD; Retina Consultants of Texas, Retina Consultants of America, Houston, Texas.
  • Lunasco L; Blanton Eye Institute, Houston Methodist Hospital, Houston, Texas.
  • Brown DM; The Tony and Leona Campane Center for Excellence in Image-Guided Surgery and Advanced Imaging Research, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio.
  • Srivastava SK; The Tony and Leona Campane Center for Excellence in Image-Guided Surgery and Advanced Imaging Research, Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio.
  • Madabhushi A; Retina Consultants of Texas, Retina Consultants of America, Houston, Texas.
  • Ehlers JP; Blanton Eye Institute, Houston Methodist Hospital, Houston, Texas.
Ophthalmol Sci ; 2(2): 100123, 2022 Jun.
Article em En | MEDLINE | ID: mdl-36249694
ABSTRACT

Purpose:

Various pathways and cytokines are implicated in pathogenesis of diabetic macular edema (DME). Computational imaging biomarkers (CIBs) of vessel tortuosity from ultra-widefield fluorescein angiography (UWFA) and texture patterns from OCT images have been associated with anti-vascular endothelial growth factor (VEGF) therapy treatment response in DME. This analysis was a radiogenomic assessment of the association between underlying cytokines, UWFA, and OCT-based DME CIBs.

Design:

Biclustering analysis based on UWFA and OCT CIBs to identify a common imaging phenotype across patients with subsequent assessment of underlying cytokine signatures and treatment response attributes.

Participants:

The IMAGINE DME study was a post hoc study of cytokine expressions that included 24 eyes with sufficient baseline aqueous humor samples and an in-depth assessment of the imaging studies obtained during the phase I/II DmeAntiVEgf study (DAVE) that measured different cytokine expressions.

Methods:

A total of 151 graph or morphologic features quantifying leakage shape, size, density, interobject distance, and architecture of leakage spots and 5 vessel tortuosity features were extracted from the baseline UWFA scans, and 494 texture-based radiomics features were extracted from each of the fluid and retinal tissue compartments of OCT images. Biclustering enables simultaneous clustering of patients and features and was used to aggregate patients in terms of their commonality of phenotypes (based on similar imaging attributes) and to identify commonality in terms of cytokine expression and treatment response to anti-VEGF therapy. Main Outcome

Measures:

Identification of eyes with similar imaging phenotypes to evaluate commonalities of patterns and underlying cytokine expression.

Results:

Strong correlations between VEGF and 7 UWFA leakage morphologic features (Pearson correlation coefficient [PCC], 0.45-0.51; P < 0.05), 1 vascular tortuosity-based UWFA feature (PCC, 0.45; P = 0.00016), and 2 OCT-derived intraretinal fluid texture features (PCC, 0.58-0.63; P < 0.05) were identified. Strong correlation between intraretinal fluid features and other cytokines (PCC, 0.41-0.59; P < 0.05) were also observed.

Conclusions:

This study identified groups of eyes with similar imaging phenotypes as defined by UWFA and OCT CIBs that demonstrated similar treatment response patterns and cytokine expression, including a strong association between VEGF with UWFA-derived leakage morphologic and vessel tortuosity features.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article