Glaucoma Diagnostics

Research output: ThesisDoctoral Thesis (compilation)

Abstract

This thesis addresses several aspects of glaucoma diagnostics from both a clinical and a screening perspective. New instruments for diagnosing glaucoma have been developed over the past years, but little information is available regarding their performance as screening methods and their usefulness in ordinary clinical practice.
Purpose of the research underlying this thesis
The objectives of the present research were as follows: to compare the accuracy of results of analysis of the optic nerve head (ONH) achieved by computerized imaging using the statistical tools Moorfields Regression Analysis (MRA) and Glaucoma Probability Score (GPS) of the Heidelberg Retina Tomograph (HRT) and by subjective assessment performed by physicians with different degrees of experience of glaucoma (Paper III); to evaluate the effect of a continuous medical education (CME) lecture on subjective assessment of the ONH for diagnosis of glaucoma (Paper II); to investigate subjective assessment of standard automated perimetry (SAP) test results by physicians with varying knowledge of glaucoma with a trained artificial neural network (ANN), and to compare the certainty of the classifications (Paper IV); to compare the diagnostic performance of time-domain Stratus optical coherence tomography (OCT) with that of spectral-domain Cirrus OCT (Paper I), Frequency Doubling Technology (FDT) screening perimetry and scanning laser polarimetry with the GDx VCC in a random population-based sample and in patients with glaucoma of varying disease severity.
Methods and results
In Paper III, the sensitivity of both MRA (87 - 94%) and GPS (79 - 93%) was higher than that of the average of the 45 physicians (62 - 82%). Furthermore, MRA offered better sensitivity compared to ophthalmologists with subspecialties other than glaucoma (53 - 77%), and was non-significantly higher than that of glaucoma experts (72 - 88%). MRA correctly classified all eyes with advanced glaucomatous visual field defects (Andersson et al. 2011).
In Paper II, a one-hour CME lecture on ONH assessment for 96 physicians led to a significant improvement in sensitivity (from 70% to 80%) and a significant decrease in uncertain assessments (from 22% to 13%), whereas specificity remained unchanged (68%) (Andersson et al. 2011).
In Paper IV, 30 physicians assessing SAP test results with full Statpac information was compared with a previously trained ANN. ANN reached significantly higher sensitivity (93%) than the average physician (83%), whereas specificity was similar for these two groups (91% and 90% respectively). Diagnostic accuracy was similar among the different groups of physicians and seemingly rather independent of experience. The ANN attained certainty of classification that was in parity with that provided by the glaucoma experts and did not make any completely incorrect classifications of the visual fields (Andersson et al. 2012).
In Paper I, 170 subjects from a population-based sample of older subjects (aged ≥ 50 years) and 138 randomized clinical patients with different stages of glaucoma underwent a comprehensive examination that included Stratus OCT, Cirrus OCT, an FDT screening program and the GDx VCC. In the population-based sample, both Stratus and Cirrus OCT showed high diagnostic accuracy with area under the receiver operating curve (AROC) values close to 1.0 (Bengtsson et al. 2012). Both OCT instruments correctly classified all of the clinical glaucoma patients with advanced disease. FDT screening showed high sensitivity (91%) but erroneously gave normal test results for some eyes with advanced disease. GDx VCC had lower sensitivity (73 - 92%) and also led to a large proportion of examinations with an atypical retardation pattern that is known to affect the diagnostic efficiency of this instrument.
Conclusions
The HRT MRA performed better than most physicians and was consistent with the glaucoma experts. These results suggest that MRA can be a valuable tool for diagnosing glaucoma in ordinary practice, particularly when only a few glaucoma experts are available.
CME on ONH analysis had a small, but positive effect on diagnostic accuracy for glaucoma.
The ANN trained to classify visual fields performed at least as well as most of the participating physicians, whose performances were remarkably similar regardless of their level of experience. This indicates that available tools for interpreting SAP findings are helpful in assessments of visual field test results. However, SAP is associated with learning effects (Heijl et al. 1989) that may entail low specificity for untrained subjects and hence it is not an ideal screening method for glaucoma. By comparison, the screening test of FDT is rapid and easy, but some eyes with advanced glaucoma were missed.
GDx VCC images for a relatively large number of eyes could not be analysed, and is thus not appropriate for screening.
The OCT instruments offer both high sensitivity and high specificity, and all eyes with advanced disease were correctly classified as glaucomatous. However, these instruments are still expensive and require special operator skills. Additional development to obtain OCT instrument that is more compact, easier to use and less expensive might render such tomography suitable as a screening tool for glaucoma.

Details

Authors
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Medical and Health Sciences

Keywords

  • POAG – glaucoma – diagnostic accuracy – screening – subjective assessment – population-based – GDx VCC – OCT – HRT – FDT – ONH assessment – CME – ANN – artificial neural network – visual field assessment
Original languageEnglish
QualificationDoctor
Awarding Institution
Supervisors/Assistant supervisor
Award date2013 Mar 15
Publisher
  • Wiley-Blackwell
Print ISBNs978-91-87189-90-6
Publication statusPublished - 2013
Publication categoryResearch

Bibliographic note

Defence details Date: 2013-03-15 Time: 09:15 Place: Jubileumsaulan, Jan Waldenströms gata 1, Skånes Universitetssjukhus, Malmö. External reviewer(s) Name: Chen, Enping Title: Docent Affiliation: Karolinska Institutet, Stockholm ---

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