Visual Field Interpretation With Empiric Probability Maps

Abstract

Automated visual field charts may be difficult to interpret partly because of the magnitude and complex nature of normal threshold variability. We devised two types of empiric probability maps in which this variability is taken into account and the significances of measured threshold values are displayed. These maps are highly sensitive to nonobvious but significant paracentral field loss but will at the same time deemphasize false-positive patterns commonly found more peripherally. They also frequently show field defects before these are obvious in conventional threshold printouts. In addition, they differentiate between generalized loss of sensitivity and localized field defects.