The Novel Evidenced Assessment of Tortuosity system: interobserver reliability and agreement with clinical assessment

Konstantinos Balaskas, Stephanie Tiew, Gabriela Czanner, Ai Ling Tan, Jane Ashworth, Susmito Biswas, Tariq Aslam

Research output: Contribution to journalArticlepeer-review

Abstract

PURPOSE: Computer-assisted assessment of vessel tortuosity is clinically useful in retinopathy of prematurity (ROP). However, poor image quality is often prohibitive for accurate segmentation by fully automated systems and semi-automated systems are prone to unreliability. In the present work, we describe a method of retinal vessel tortuosity measurement by means of purpose-built image analysis software that does not require high image quality yet is also reliable.

METHODS: Images were obtained from neonates at risk of ROP with Retcam Shuttle(®) . Individual vessels were assessed with the semi-automated Novel Evidenced Assessment of Tortuosity (NEAT) system by two masked experimenters. Scores were compared to assess reliability. They were also compared against clinical scoring of individual vessels by two ROP screeners to assess relationship with clinical assessment. In a second image cohort, the mean of the most tortuous vessel in each of four quadrants in each eye (NEAT-O) was compared against the documented gold standard clinical grading of plus disease.

RESULTS: Reliability of the NEAT system for 50 individual vessels using Bland-Altman plots was excellent. NEAT tortuosity scores for 50 individual vessels compared to clinical scoring showed strong correlation (0.706). Correlation between the NEAT-O score for average tortuosity and gold standard for 167 eyes was modest (0.578).

CONCLUSIONS: The NEAT system is intuitive, user-friendly and robust enough to be clinically useful in poor-quality images. It allows for a rapid, valid and reliable assessment of tortuosity of individual vessels and produces a tortuosity score that correlates well with severity of plus disease.

Original languageEnglish
Pages (from-to)e421-6
JournalActa Ophthalmologica
Volume94
Issue number6
Early online date21 Dec 2015
DOIs
Publication statusPublished - Sept 2016

Keywords

  • Algorithms
  • Humans
  • Image Processing, Computer-Assisted
  • Infant
  • Infant, Newborn
  • Observer Variation
  • Photography
  • Reproducibility of Results
  • Retinal Vessels
  • Retinopathy of Prematurity
  • Software
  • Journal Article

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