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Clinical science
Automated grading for diabetic retinopathy: a large-scale audit using arbitration by clinical experts
  1. Alan D Fleming1,
  2. Keith A Goatman1,
  3. Sam Philip2,
  4. Gordon J Prescott3,
  5. Peter F Sharp1,
  6. John A Olson2
  1. 1Biomedical Physics, University of Aberdeen, Foresterhill, UK
  2. 2Diabetes Retinal Screening Service, Aberdeen, UK
  3. 3Section of Population Health, University of Aberdeen, Foresterhill, UK
  1. Correspondence to Dr John A Olson, Diabetes Retinal Screening Service, NHS Grampian, David Anderson Building, Foresterhill Road, Aberdeen AB25 2ZP, UK; john.olson{at}nhs.net

Abstract

Background/aims Automated grading software has the potential to reduce the manual grading workload within diabetic retinopathy screening programmes. This audit was undertaken at the request of Scotland's National Diabetic Retinopathy Screening Collaborative to assess whether the introduction of automated grading software into the national screening programme would be safe, robust and effective.

Methods Automated grading, performed by software for image quality assessment and for microaneurysm/dot haemorrhage detection, was carried out on 78 601 images, obtained from 33 535 consecutive patients, which had been manually graded at one of two regional diabetic retinopathy screening programmes. Cases where the automated grading software assessment indicated gradable images with no disease but the screening programme indicated ungradable images or disease more severe than mild retinopathy were arbitrated by seven senior ophthalmologists.

Results 100% (180/180) of patients with proliferative retinopathy, 100% (324/324) with referable background retinopathy, 100% (193/193) with observable background retinopathy, 97.3% (1099/1130) with referable maculopathy, 99.2% (384/387) with observable maculopathy and 99.8% (1824/1827) with ungradable images were detected by the software.

Conclusion The automated grading software operated to previously published results when applied to a large, unselected population attending two regional screening programmes. Manual grading workload reduction would be 36.3%.

  • Computer-assisted image analysis
  • diabetic retinopathy
  • imaging
  • macula
  • public health
  • retina
  • screening
  • telemedicine

https://doi.org/10.1136/bjo.2009.176784

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    Footnotes

    • Funding Medalytix.

    • Competing interests Implementation in Scotland and elsewhere is being considered. If this occurs it is likely that there will be some remuneration for the University of Aberdeen, NHS Grampian, ADF, JAO and PFS. KAG, SP and GJP have no financial conflict of interest other than by association with the institutions mentioned above.

    • Contributors JAO was the principal investigator. JAO, PFS, KAG, ADF, and GJP contributed to the study design. ADF developed the automated methods, set up the analysis and generated the results. GJP performed statistical analysis. All participated in the interpretation of the data. ADF wrote the first draft of the paper. All authors reviewed and revised the paper for important intellectual content. JAO takes responsibility for the content.

    • Provenance and peer review Not commissioned; externally peer reviewed.