Authors' objectives:

To undertake a systematic literature review followed by a primary study to assess the performance of digital imaging, compared with other modalities, in screening for, and monitoring the development of, diabetic retinopathy.

The study addressed three questions: - Can a digital imaging system detect retinopathy irrespective of sort or level? - Can a digital imaging system detect progression of retinopathy? - Can a digital imaging system determine when treatment is required?

Authors' results and conclusions: Question 1: can a digital imaging system detect retinopathy irrespective of sort or level? - Any retinopathy Manual grading of 35-mm colour slides produced the highest sensitivity (89%) and specificity (89%) figures, with optometrist examination recording most false negatives (sensitivity 75%). Manual and automated analysis of digital images had intermediate sensitivity. - Referable retinopathy Both manual grading of 35-mm colour slides and digital images gave sensitivities of over 90% with few false positives (specificity 89 and 87%, respectively). Digital imaging produced 50% fewer ungradable images than colour slides. Question 2: can a digital imaging system detect progression of retinopathy? This part of the study was limited as patients with the more severe levels of retinopathy opted for treatment. There was an increase in the number of microaneurysms in those patients who developed from mild to moderate. There was no difference between the turnover rate of either new or regressed microaneurysms for patients with mild or with sight-threatening retinopathy. Question 3: can a digital imaging system determine when treatment is warranted? Since there was no definite answer to question 2, then the answer must be 'no' at present.

Authors' recommendations: Digital imaging: In the context of a national screening programme for referable retinopathy, digital imaging is an effective method. In addition, technical failure rates are lower with digital imaging than conventional photography. Digital imaging is also a more sensitive technique than slit-lamp examination by optometrists. Automated grading of digital images: Automated grading can improve efficiency by correctly identifying just under half the population as having no retinopathy.

Authors' methods: Systematic review, Primary research

Project Status: Completed

URL for project: http://www.hta.ac.uk/965

Year Published: 2003

English language abstract: An English language summary is available

Publication Type: Not Assigned

Country: England, United Kingdom

Organisation Name: NIHR Health Technology Assessment programme

Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK

Contact Name: journals.library@nihr.ac.uk

Contact Email: journals.library@nihr.ac.uk

Copyright: 2009 Queen's Printer and Controller of HMSO