title: Can Automated Imaging for Optic Disc and Retinal Nerve Fiber Layer Analysis Aid Glaucoma Detection?
abstract: OBJECTIVE
  To compare the diagnostic performance of automated imaging for glaucoma.
  
  
  METHODS
  Prospective, direct comparison study.
  
  
  METHODS
  Adults with suspected glaucoma or ocular hypertension referred to hospital eye services in the United Kingdom.
  
  
  METHODS
  We evaluated 4 automated imaging test algorithms: the Heidelberg Retinal Tomography (HRT; Heidelberg Engineering, Heidelberg, Germany) glaucoma probability score (GPS), the HRT Moorfields regression analysis (MRA), scanning laser polarimetry (GDx enhanced corneal compensation; Glaucoma Diagnostics (GDx), Carl Zeiss Meditec, Dublin, CA) nerve fiber indicator (NFI), and Spectralis optical coherence tomography (OCT; Heidelberg Engineering) retinal nerve fiber layer (RNFL) classification. We defined abnormal tests as an automated classification of outside normal limits for HRT and OCT or NFI ≥ 56 (GDx). We conducted a sensitivity analysis, using borderline abnormal image classifications. The reference standard was clinical diagnosis by a masked glaucoma expert including standardized clinical assessment and automated perimetry. We analyzed 1 eye per patient (the one with more advanced disease). We also evaluated the performance according to severity and using a combination of 2 technologies.
  
  
  METHODS
  Sensitivity and specificity, likelihood ratios, diagnostic, odds ratio, and proportion of indeterminate tests.
  
  
  RESULTS
  We recruited 955 participants, and 943 were included in the analysis. The average age was 60.5 years (standard deviation, 13.8 years); 51.1% were women. Glaucoma was diagnosed in at least 1 eye in 16.8%; 32% of participants had no glaucoma-related findings. The HRT MRA had the highest sensitivity (87.0%; 95% confidence interval [CI], 80.2%-92.1%), but lowest specificity (63.9%; 95% CI, 60.2%-67.4%); GDx had the lowest sensitivity (35.1%; 95% CI, 27.0%-43.8%), but the highest specificity (97.2%; 95% CI, 95.6%-98.3%). The HRT GPS sensitivity was 81.5% (95% CI, 73.9%-87.6%), and specificity was 67.7% (95% CI, 64.2%-71.2%); OCT sensitivity was 76.9% (95% CI, 69.2%-83.4%), and specificity was 78.5% (95% CI, 75.4%-81.4%). Including only eyes with severe glaucoma, sensitivity increased: HRT MRA, HRT GPS, and OCT would miss 5% of eyes, and GDx would miss 21% of eyes. A combination of 2 different tests did not improve the accuracy substantially.
  
  
  CONCLUSIONS
  Automated imaging technologies can aid clinicians in diagnosing glaucoma, but may not replace current strategies because they can miss some cases of severe glaucoma.
authors.affiliation: Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom.
authors.forename: Katie
authors.initials: K
authors.lastname: Banister
authors.affiliation: Robertson Centre for Biostatistics, University of Glasgow, Glasgow, United Kingdom.
authors.forename: Charles
authors.initials: C
authors.lastname: Boachie
authors.affiliation: Vision & Eye Research Unit, Postgraduate Institute, Anglia Ruskin University, Cambridge, United Kingdom.
authors.forename: Rupert
authors.initials: R
authors.lastname: Bourne
authors.affiliation: Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Cook
authors.affiliation: School of Medicine, University of St. Andrews, St. Andrews, United Kingdom.
authors.forename: Jennifer M
authors.initials: JM
authors.lastname: Burr
authors.affiliation: Health Services Research Unit, University of Aberdeen, Aberdeen, United Kingdom.
authors.forename: Craig
authors.initials: C
authors.lastname: Ramsay
authors.affiliation: National Institute for Health Research Biomedical Research Centre, Moorfields Eye Hospital and University College London Institute of Ophthalmology, London, United Kingdom.
authors.forename: David
authors.initials: D
authors.lastname: Garway-Heath
authors.affiliation: Faculty of Health and Life Sciences, Northumbria University, Newcastle-upon-Tyne, United Kingdom.
authors.forename: Joanne
authors.initials: J
authors.lastname: Gray
authors.affiliation: Faculty of Health and Life Sciences, Northumbria University, Newcastle-upon-Tyne, United Kingdom.
authors.forename: Peter
authors.initials: P
authors.lastname: McMeekin
authors.affiliation: Health Economics Research Unit, University of Aberdeen, Aberdeen, United Kingdom.
authors.forename: Rodolfo
authors.initials: R
authors.lastname: Hernández
authors.affiliation: Centre for Experimental Medicine, Queen's University, Belfast, United Kingdom. Electronic address: a.azuara-blanco@qub.ac.uk.
authors.forename: Augusto
authors.initials: A
authors.lastname: Azuara-Blanco
mesh_terms: D000368:Aged; D000465:Algorithms; D005189:False Positive Reactions; D005260:Female; D005901:Glaucoma / Q000175:diagnosis*; D006801:Humans; D007429:Intraocular Pressure; D016013:Likelihood Functions; D008297:Male; D008875:Middle Aged; D064847:Multimodal Imaging / Q000379:methods*; D009412:Nerve Fibers / Q000473:pathology*; D009798:Ocular Hypertension / Q000175:diagnosis; D016017:Odds Ratio; D009887:Ophthalmoscopy; D009898:Optic Disk / Q000000981:diagnostic imaging* / Q000473:pathology; D011237:Predictive Value of Tests; D011336:Probability; D011446:Prospective Studies; D012165:Retinal Ganglion Cells / Q000473:pathology*; D057109:Scanning Laser Polarimetry; D012680:Sensitivity and Specificity; D041623:Tomography, Optical Coherence