Deviation map algorithm may improve glaucoma detection

This prospective study showed that the deviation map algorithm performed better at detecting localized glaucomatous visual field defects compared with traditional peripapillary retinal nerve fiber layer (pRNFL) thickness measurements when both were determined using Cirrus spectral domain (SD) OCT. There were statistically significant correlations between the deviation map algorithm and visual field (VF) indices. Techniques for evaluating nerve fiber layer changes in patients with VF defects show that SD-OCT is not as sensitive without modification of the analyzer.

The study included 54 patients with glaucoma with localized VF defects confined to one hemifield and 54 normal controls who underwent RNFL measurements with SD-OCT.

The authors calculated mean pRNFL thickness corresponding to localized VF defect. A deviation score (DS) was assigned by customized Image J software calculating the number of abnormal superpixels in the deviation maps corresponding to localized VF defect.

DS and average pRNFL thickness measurements showed a strong correlation (P < 0.0001). There were also significant correlations between DS, mean deviation and pattern standard deviation. The areas under receiver operating characteristic curves of the mean pRNFL thickness (0.892) and DS (0.958) differed significantly (P = 0.0051). The sensitivities at 80 percent, 90 percent and 95 percent specificities were 94.4 percent, 90.6 percent and 88.6 percent, respectively, for DS and 74.5 percent, 58.8 percent and 47.3 percent for mean pRNFL thickness.

The authors say that further work is needed to establish the role of the Cirrus OCT deviation map algorithm in the detection and monitoring of glaucomatous progression.