Row. Burk et R. Rendon, Clinical detection of optic nerve damage: Measuring changes in cup steepness with use of a new image alignment algorithm, SURV OPHTHA, 45, 2001, pp. S297-S303
The purpose of this study was to study the effect of a subpixel image align
ment algorithm on the standard deviation (SD) of mean topography images obt
ained by laser scanning tomography and to evaluate changes of the cup shape
measure parameter (CSM) over time based upon tile individual parameter var
iability using the new algorithm. Triple measurements fi-om optic nerve hea
ds of 132 eyes of 132 subjects were obtained using the Heidelberg Retina To
mograph HRT. To calculate a mean topography image from three single topogra
phy images, alignment of the raw optical section image data was performed w
ith the standard software and again with a new subpixel-based image alignme
nt algorithm. The effect on the averaged (SD) of the mean topography images
was evaluated. CSM was evaluated in lj eyes of 15 normal subjects (N) and
28 eyes of 14 glaucoma patients (G) over a period of 28.6 +/- 4.6 months (N
) and 28.56 +/- 5.2 months (G) respectively. A change in the CSM value over
time was considered significant if CSM measurements exceeded two standard
deviations of this variable determined for the individual eye. Mean-topogra
phy image SD was 22.86 +/- 8.2 microns (min. 9.5 mum; max. 47.8 mum) with t
he standard alignment procedure and 15.46 +/- 6.8 mum (min. 6.8 mum; max. 4
2.8 mum) with the new algorithm. The average SD improvement was 7.46 +/- 3.
9 microns (min. -8.1 mum; max. 28.7 mum). The coefficient of correlation of
both methods was R-2 = 0.77 (p < 0.0001). No control group eye demonstrate
d significant changes of CSM in the follow-up period. The CSM indicated an
increase ill cup steepness in 4 eyes of 4 glaucoma patients. In one of thes
e four eyes, a deterioration of the visual field was identified by while on
white perimetry. The new image alignment algorithm significantly reduces t
he SD of mean topography images calculated from identical raw data. If topo
metric variables are evaluated over time, the individual variability of dat
a should be taken into account. (C) 2001 by Elsevier Science Inc. All right
s reserved.