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Annemiek Coops, David Barry Henson, Anna J. Kwartz, Paul Habib Artes; Automated Analysis of Heidelberg Retina Tomograph Optic Disc Images by Glaucoma Probability Score. Invest. Ophthalmol. Vis. Sci. 2006;47(12):5348-5355. doi: https://doi.org/10.1167/iovs.06-0579.
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purpose. To compare the diagnostic performance of the Heidelberg Retinal Tomograph’s (HRT; Heidelberg Engineering GmbH, Dossenheim, Germany) glaucoma probability score (GPS), an automated, contour line–independent method of optic disc analysis with that of the Moorfields regression analysis (MRA).
methods. HRT images were obtained from one eye of 121 patients with glaucoma (median age, 70.2 years; median mean deviation [MD], −3.6 dB, range, +2.0 to −9.9 dB) and 95 healthy control subjects (median age, 59.7 years; median MD −0.1 dB, range +2.5 to −3.7). The diagnostic performances of GPS and MRA were evaluated by including borderline classifications, either as test negatives (most specific criteria) or as test positives (least specific criteria). Agreement between global and sectoral data of both analyses was established. Logistic regression analyses were performed to evaluate the effect of covariates such as optic disc size and age on the classification outcomes of both the GPS and the MRA.
results. In 8 (7%) patients with glaucoma and 10 (11%) control subjects, the GPS failed to provide a complete global and sectoral optic disc classification. Although we could not identify a single distinct cause of this failure in the glaucoma group, failures in the control subjects occurred most often (7/10) with small and crowded optic discs. In subjects who were successfully classified at least globally by the GPS (117 patients with glaucoma, 88 control subjects), the diagnostic performances of GPS and MRA were similar (areas under the receiver operating characteristic [ROC] curve of 0.78 and 0.77, respectively; P > 0.1). With the GPS, sensitivity and specificity were 59% and 91% (most specific criteria) and 78% and 63% (least specific criteria), respectively. Combining GPS and MRA did not increase diagnostic performance significantly (ROC area of combined classifiers, 0.81). Both GPS and MRA were affected by disc size. In patients with glaucoma as well as healthy control subjects, the odds of a positive GPS classification (borderline or outside normal limits) increased by 21% (95% confidence interval [CI], 12%–30%) for each 0.1 mm2 increase in optic disc area. With the MRA, the corresponding increase was 15% (95% CI, 7%–23%). Optic disc area alone accounted for approximately 30% and 22% of the explained variance with the GPS and MRA, respectively (P < 0.001). The proportional-odds logistic regression confirmed that optic disc size affected mainly the tradeoff between true- and false-positive classifications (criterion) rather than the absolute performance of the analyses (area under the ROC curve). There was some evidence of an age effect with the MRA, which showed a 53% (95% CI, 16%–102%) increase in the odds of a positive test (borderline or outside normal limits) associated with each decade of age (P = 0.002), but no age effects were observed with the GPS (P > 0.1).
conclusions. The diagnostic performance of the contour line–independent GPS analysis is similar to that of the MRA. However, clinicians should be aware of the strong size dependence of both GPS and MRA. In large optic discs, both GPS and MRA are likely to produce many false-positive classifications. Correspondingly, the sensitivity to early damage is likely to be low in small optic discs. There is a need for automated classification systems that explicitly address the size dependence of current analyses.
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