Comparison of Central Macular Fluid Volume with Central Subfield Thickness in Patients with Diabetic Macular Edema Using Optical Coherence Tomography Angiography

Qi Sheng You, Kotaro Tsuboi, Yukun Guo, Jie Wang, Christina J. Flaxel, Steven T. Bailey, David Huang, Yali Jia, Thomas S. Hwang

Research output: Contribution to journalArticlepeer-review

Abstract

Importance: Diabetic macular edema (DME) is the predominant cause of visual impairment in patients with type 1 or 2 diabetes. Automated fluid volume measurements using optical coherence tomography (OCT) may improve the diagnostic accuracy of DME screening. Objective: To assess the diagnostic accuracy of an automated central macular fluid volume (CMFV) quantification using OCT for DME. Design, Setting, and Participants: A cross-sectional observational study was conducted at a tertiary academic center among 215 patients with diabetes (1 eye each) enrolled from January 26, 2015, to December 23, 2019. All participants underwent comprehensive examinations, 6 × 6-mm macular structural OCT horizontal raster scans, and 6 × 6-mm macular OCT angiography volumetric scans. From January 1 to March 30, 2020, 2 retinal specialists reviewed the structural OCT scans independently and diagnosed DME if intraretinal or subretinal fluid was present. Diabetic macular edema was considered center involved if fluid was present within the central fovea (central 1-mm circle). A third retinal specialist arbitrated any discrepancy. The mean central subfield thickness (CST) within the central fovea was measured on structural OCT horizontal raster scans. A deep learning algorithm automatically quantified fluid volumes on 6 × 6-mm OCT angiography volumetric scans and within the central foveas (CMFV). Main Outcomes and Measures: The area under the receiver operating characteristic curve (AUROC) and the sensitivity and specificity of CST and CMFV for DME diagnosis. Results: We enrolled 1 eye each of 215 patients with diabetes (117 women [54.4%]; mean [SD] age, 59.6 [12.4] years). Diabetic macular edema was present in 136 eyes; 93 cases of DME were center involved. The AUROC of CMFV for diagnosis of center-involved DME (0.907 [95% CI, 0.861-0.954]) was greater than the AUROC of CST (0.832 [95% CI, 0.775-0.889]; P =.02). With the specificity set at 95%, the sensitivity of CMFV for detection of center-involved DME (78.5% [95% CI, 68.8%-86.3%]) was higher than that of CST (53.8% [95% CI, 43.1%-64.2%]; P =.002). Center-involved DME cases not detected by CST but detected by CMFV were associated with a thinner CST (290.8 μm [95% CI, 282.3-299.3 μm] vs 369.4 μm [95% CI, 347.1-391.7 μm]; P <.001), higher proportion of previous macular laser treatment (11 of 28 [39.3%; 95% CI, 21.5%-59.4%] vs 12 of 65 [18.5%; 95% CI, 9.9%-30.0%]; P =.03), and female sex (20 of 28 [71.4%; 95% CI, 51.3%-86.8%] vs 31 of 65 [47.7%; 95% CI, 35.1%-60.5%]; P =.04). Conclusions and Relevance: These findings suggest that an automated CMFV is a more accurate diagnostic biomarker than CST for DME and may improve screening for DME.

Original languageEnglish (US)
JournalJAMA ophthalmology
DOIs
StateAccepted/In press - 2021

ASJC Scopus subject areas

  • Ophthalmology

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