The Diffuse Defect is an estimate of the portion of a patient’s visual field loss that is diffuse, or spread evenly across all portions of the visual field, in dB. In this graphical display, deviation from the average normal value for each test point is ranked on the x axis from 1 to 59, with 59 being the test point that has the greatest deviation from normal. Deviations from normal at each test point are represented on the y axis, in dB. The patient’s actual test point deviations are represented by the thin blue line. Age corrected normal values are represented by the light blue band. The patient’s deviation from normal at the test point ranked 25% among his or her own deviations is then estimated to be his or her diffuse visual field loss, represented by the dark blue band. This provides a graphical estimate of the remaining visual field loss for this patient, which is then presumed to consist of local visual field defects, which are more significant in management of glaucoma than diffuse defects.
Figure DDD.2-7 Example of Diffuse Defect
The Local Defect is an estimate of the portion of a patient’s visual field loss that is local, or not spread evenly across all portions of the visual field. The x and y axis in this graphical display have the same meaning as in the diffuse defect. In this graphical display the top line/blue band represent age corrected normal values. This line is shifted downward by the amount estimated to be due to diffuse visual field loss for this patient, according to the calculation in Figure DDD.2-7 (Diffuse Defect). The difference between the patient’s test value at each point in the ranking on the horizontal axis and the point on the lower curve at the 50% point is represented by the dark blue section of the graph. This accentuates the degree of local visual field defect, which is more significant in management of glaucoma than diffuse defects. The Local Defect is an index that highly correlates with square root of the loss variance (sLV) but is less susceptible to false positives. In addition to the usage in white/white perimetry it is especially helpful as early identifier for abnormal results in perimetry methods with higher inter subject variability such as blue/yellow (SWAP) or flicker perimetry. An example of Local Defect is shown in Figure DDD.2-8 and is expressed in dark blue in dB and is normalized to be comparable between different test patterns.
Figure DDD.2-8 Example of Local Defect