Comparing Common Retinal Vessel Caliber Measurement Software with an Automatic Deep Learning System

Shuang He, Gabriella Bulloch, Liangxin Zhang, Wei Meng, Danli Shi, Mingguang He

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Purpose: To compare the Retina-based Microvascular Health Assessment System (RMHAS) with Integrative Vessel Analysis (IVAN) for retinal vessel caliber measurement. Methods: Eligible fundus photographs from the Lingtou Eye Cohort Study were obtained alongside their corresponding participant data. Vascular diameter was automatically measured using IVAN and RMHAS software, and intersoftware variations were assessed by intra-class correlation coefficients (ICC), and 95% confidence intervals (CIs). Scatterplots and Bland–Altman plots assessed the agreement between programs, and a Pearson’s correlation test assessed the strength of associations between systemic variables and retinal calibers. An algorithm was proposed to convert measurements between software for interchangeability. Results: ICCs between IVAN and RMHAS were moderate for CRAE and AVR (ICC; 95%CI)(0.62; 0.60 to 0.63 and 0.42; 0.40 to 0.44 respectively) and excellent for CRVE (0.76; 0.75 to 0.77). When comparing retinal vascular calibre measurements between tools, mean differences (MD, 95% confidence intervals) in CRAE, CRVE, and AVR were 22.34 (–7.29 to 51.97 µm),–7.01 (–37.68 to 23.67 µm), and 0.12 (–0.02 to 0.26 µm), respectively. The correlation of systemic parameters with CRAE/CRVE was poor and the correlation of CRAE with age, sex, systolic blood pressure, and CRVE with age, sex, and serum glucose were significantly different between IVAN and RMHAS (p < 0.05). Conclusions: CRAE and AVR correlated moderately between retinal measurement software systems while CRVE correlated well. Further studies confirming this agreeability and interchangeability in large-scale datasets are needed before softwares are deemed comparable in clinical practice.
Original languageEnglish
Pages (from-to)843-849
Number of pages7
JournalCurrent Eye Research
Volume48
Issue number9
DOIs
Publication statusPublished - Sept 2023
Externally publishedYes

Keywords

  • Consistency analysis
  • deep learning system
  • IVAN
  • retinal vessel caliber measurement
  • semi-automated analysis software

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience

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