Component Perimetry: A Fast Method to Detect Visual Field Defects Caused by Brain Lesions

Abstract

purpose. Noise field campimetry, performed according to Aulhorn and Köst, confronts patients with a large field of irregularly flickering dots, and many patients immediately perceive their visual field defects. The original method had a somewhat low specificity and sensitivity, especially for patients with visual field defects caused by cortical lesions.

methods. The method was improved in two ways. First, the grain of the visual noise was increased toward the periphery of the visual field to accommodate the peripheral decrease in visual acuity. Second, the type of stimulus pattern was varied to include separate investigations of different visual components or functions (color, motion, temporal resolution, line orientation, stereoscopic depth, acuity, and figure–ground segmentation). To evaluate the reliability of the method, the visual fields were compared, as assessed by the new method, with those of conventional perimetry in 41 patients with neurologic disorders and 22 normal control subjects.

results. The results were encouraging. All patients with suprageniculate lesions subjectively experienced visual field defects in component perimetry. Sizes of visual field defects obtained with both methods corresponded qualitatively with each other, with a highly significant correlation. The specificity of component perimetry was higher than that of the original noise field campimetry.

conclusions. This pilot study indicates that component perimetry is a subjective but relatively reliable method for detecting disorders of visual perception caused by lesions at different stages along the visual pathway, permitting fast screening of the visual field. In addition, this method seems to allow examination of the visual field, not only for defects in contrast sensitivity, as does conventional light perimetry, but also for the status of other components of vision such as color or motion perception. Further evaluation with larger patient cohorts is needed to allow exact assessment of the clinical usefulness of the method.

Patients suffering from visual field defects usually do not perceive the scotomata as circumscribed areas differing from the background. Instead, the visual field defects share some properties with the blind spot, in that both are detected only through the invisibility of objects located within their borders, and they are filled in by the visual pattern of the immediate surround. 

In conventional light perimetry, defects are detected sequentially in the visual field by using point-by-point testing. This type of perimetry is time consuming and depends on the attentiveness of the patient. Aulhorn and Köst ¹ developed, to the best of our knowledge, the first method of truly simultaneous perimetry, termed noise field campimetry, which tests a large part of the visual field simultaneously. The noise field is an area filled with small black and white dots randomly distributed and flickering at high frequencies, similar to the snowstorm on a television screen after the end of transmission (Fig. 1A , pattern 1). When patients fixate a central spot in the noise field, scotomata are perceived subjectively as circumscribed areas with less or no flicker and sometimes with a brightness differing from the surround. The advantages of noise field perimetry are the simultaneous examination of the whole visual field and the subjective experience of visual field defects, allowing the development of a fast screening method for visual field defects. However, noise field campimetry has two disadvantages in comparison with conventional perimetric methods: First, it has somewhat low sensitivity for homonymous hemianopias caused by suprageniculate damage, which are either not perceived at all in the noise field or are perceived over a much smaller spatial extent ^{1 2 3 4} ; and second, the method cannot quantitatively determine the exact size, location, and depth of visual field defects. 

Our purpose was to modify the method so that, ideally, all visual field defects caused by suprageniculate damage could be detected, the perimetric stimuli would not be subject to filling in, and different components or functions of visual perception could be tested selectively. 

The concept of examining different visual functions simultaneously in the whole visual field is based on the finding that humans can discriminate between certain elementary stimulus features such as luminance, color, orientation, motion, and stereoscopic depth in parallel. In our opinion, the only way to achieve this feat is by using a large number of dedicated processors for the different components of visual perception in parallel, one for each visual component and field position. ^{5 6 7 8 9} This concept is supported by both electrophysiological ^{10 11 12 13} and neuroanatomical data. ^{14 15 16} For many visual features, processors seem to be organized in a retinotopically ordered map, and each individual map can be tested individually and simultaneously by the appropriate perimetric pattern. There is also evidence from neuropsychological studies that visual perception depends on several relatively autonomous mechanisms, each of which contributes distinct components. Various studies report selective disturbances or even losses of visual functions after circumscribed cerebral damage in humans, resulting, for example, in isolated achromatopsia, loss of color vision, or impaired perception of motion. ^{17 18 19 20 21}  

The disturbance of one elementary visual function, for example color perception, does not always lead to a pathologic visual field when tested with conventional light perimetry. ^{18 22 23} Testing different visual components or functions such as color, motion, stereoscopic depth, orientation, visual acuity, or figure–ground segmentation is impossible with conventional perimeters and would be time consuming if done sequentially, as in conventional perimetry. Therefore, we developed new perimetric stimuli to reveal specific visual field defects. These stimuli selectively test different components or functions of visual perception such as color, motion, temporal resolution, line orientation, stereoscopic depth, acuity, and figure–ground segmentation (Fig. 1) . Moreover, element size of the (noise) pattern for those parts stimulating the peripheral visual field was progressively increased with eccentricity to achieve a stimulation equally far above resolution threshold at each position of the visual field. ^{24 25} In this pilot study we assessed the ability of component perimetry as a screening test to detect (absolute) visual field defects caused by suprageniculate damage by testing patients who had homonymous hemianopia and, as control groups, patients with neurologic but no visual disorders and intact visual fields, as well as normal control subjects. In addition, we evaluated the reliability of the new method by comparing the results of component perimetry with those of conventional light perimetry. 

Materials and Methods

First, we will describe in detail the different stimuli used in component perimetry. Subsequently, the parameters of perimetric stimuli and the procedure of testing, as well as the patients and controls will be presented. Finally, we will describe the procedure for data analysis—i.e., how the results of component and conventional light perimetry were compared. The research followed the tenets of the Declaration of Helsinki and was approved by the local ethics committee. Informed consent of all patients and normal observers was obtained after the nature and possible consequences of the study were explained. 

Types of Perimetric Stimuli

Thirteen perimetric stimuli served to test different submodalities of vision (Fig. 1) . Figures 1A 1B 1C 1D 1E display the perimetric patterns as static representations of one frame of the stimulus, whereas the remaining perimetric stimuli (Figs. 1F 1G) are shown schematically. All patterns were generated by computer (Macintosh; Apple Computer, Cupertino, CA) and presented on a 20-in. color monitor (Trinitron Multiscan; Sony, Tokyo, Japan; 20se, 40 cm wide and 30 cm high). We examined a visual field area of approximately ±45° horizontally and ±36° vertically at a viewing distance of 20 cm. Correcting lenses were used if necessary. 

Noise Field Perimetry: Contrast Noise Field.

Pattern 1 in Figure 1 shows a static representation of one frame of a noise field stimulus. Black and white dots flickered independently and at irregular intervals at high temporal frequencies. Each white or black pattern element turned to black or white randomly after one or two frames, so that not all pattern elements changed luminance at the same time (see Appendix A). In the case of homogeneous dot size (Fig. 1A , pattern 1), the stimulus resembled the flicker on a television screen after the end of transmission, eliciting association with a snowstorm. Pattern 2 in Figure 1A shows a modification of the noise field with element size increasing toward the periphery of the visual field to compensate for the increasingly poorer resolution of the periphery. 

Noise Field Perimetry: Color Noise Field.

To test the color-sensitive mechanisms of the visual system, the noise field was composed of either red and green or blue and yellow dots. The two types of elements in these color noise fields were isoluminant, and color processing was therefore required for the perception of flicker, whereas a black-and-white system would have perceived a stationary gray area. The red-and-green or blue-and-yellow noise fields with magnified elements toward the periphery are shown as patterns 3 and 4 of Figure 1A . (The point of isoluminance was determined in a way analogous to flicker photometry. A red-and-green or blue-and-yellow random dot pattern was presented flickering at a frequency of 12 Hz. The pattern had the same size as the patterns used in component perimetry. Observers adjusted the relative intensity of one of the two colors until the subjective sensation of flicker was minimal. ^{26 27} Because the point of isoluminance varies slightly between the fovea and the periphery, strict isoluminance was restricted to the central visual field in our investigation.) 

Color Perimetry: Colored Dots.

The colored dots represent another stimulus to test color perception. The dots were isoluminant with the background—that is, the background differed from the dots in color, but not in luminance. Either red (Fig. 1B , pattern 5) or yellow dots appeared and disappeared on a green or blue background. The time course of this color modulation followed a sine wave function, and the frequency of the flicker was relatively low (∼0.01 Hz; Appendix A). 

Acuity Perimetry: Rotating Landolt Cs.

Stationary Landolt Cs are a classic tool for visual acuity tests. To test visual acuity over the whole visual field, the Landolt Cs (Fig. 1C , pattern 6) rotated around their centers at a constant speed. The rotation could be perceived only if the gap in the Landolt C was being resolved. The gaps started from random orientations to prevent or complicate potential filling-in processes. The size of the individual rotating Landolt Cs increased toward the periphery, because visual acuity is directly proportional to the cortical magnification factor, ^{28 29} (i.e., to the extent of area in the primary visual cortex devoted to each part of the visual field). 

Orientation Perimetry: Rotating Lines.

The rotating lines served to test motion perception in combination with orientation perception. Differently oriented lines (Fig. 1D , pattern 7) rotated at identical angular speed around their center axes. If orientation and/or motion perception was defective in parts of the visual field, the perception of this rotation should be impaired in those areas. Similar to the gaps of the rotating Landolt Cs, the lines started rotating from random positions. 

Filling-in Perimetry: Interrupted Lines.

Lines interrupted at random positions were arranged to resemble sun rays around the central fixation point (Fig. 1E , pattern 8). To prevent local adaptation, we presented the interrupted lines with a counterphase flicker, so that line elements appeared at positions previously held by interruptions, and vice versa. The design of this pattern is based on the following observation: If the gap between two aligned line elements is projected exactly onto the blind spot, we have the impression of a straight line without any gap; the gap is subjectively filled in by the visual system. If such a filling-in mechanism is also active in cases of cortical scotomata, patients should have the impression of stationary straight lines rather than interrupted lines within defective areas of the visual field. 

Motion Perimetry: Coherent Motion.

This pattern contained a large number of randomly distributed moving dots, with only half of these dots moving coherently in the same direction and the remainder moving in the opposite direction (Fig. 1F , pattern 9). Observers had the impression that the dots moved on two different planes: Fifty percent of the dots seemed to move on a transparent plane, in front of the background plane defined by the remaining 50%. This effect of depth separation could be achieved only by integrating motion information over (parts of) the visual field. With similar coherent motion stimuli, selective impairment of motion perception was found in primates with lesions of the middle temporal area. ³⁰ Patients who have a unilateral lesion and/or one that does not affect the whole middle temporal area should have such a motion perception deficit in part of the visual field only. In these parts, the impression of depth should disappear. 

Segmentation Perimetry.

Our visual system can divide a pattern consisting of many small elements into figure and ground if the local elements within the figure differ in features such as luminance, color, depth, orientation, temporal information, texture, or motion. ^{31 32 33 34} It is supposed that this segmentation is achieved in parallel at an early stage of the visual system. ^{6 7 35 36} Therefore, simultaneous testing of figure–ground segmentation in the whole visual field should be possible. The following perimetric stimuli are based on the concept that an extended (global) stimulus can be segmented into figure and ground only if the visual processing mechanism (e.g., motion perception) for the component defining the global pattern is intact. If, however, the corresponding mechanism contains a defect within at least part of the visual field, a patient should only see randomly distributed local elements within the area of defect without detecting any global structure. 

Motion-Defined Checkerboard.

A checkerboard was defined by motion information: Points in neighboring checkerboard areas moved in directions at right angles (Fig. 1G , pattern 10). Although there were no line borders between the areas, observers had the impression of clear boundaries separating the fields of the checks. These boundaries were purely motion defined. 

Time-Defined Checkerboard.

Neighboring checks differed in the presentation time of the small points displayed within each check (Fig. 1G , pattern 11). This stimulus corresponded to a counterphase flicker checkerboard without differences between the luminance of the checks (i.e., there were no black or white checks). Only patients with a sufficiently precise temporal resolution perceived a checkerboard over all the stimulated visual field. 

Depth-Defined Checkerboard.

In this stimulus, the only difference between the two types of checks relied on stereoscopic depth (Fig. 1G , pattern 12). Points in neighboring areas were presented in a different plane, rather than with a different luminance, as in a conventional checkerboard. With intact stereoscopic vision, observers had the impression of a checkerboard consisting of checks located at two different planes in depth. 

Orientation-Defined Checkerboard.

This checkerboard was defined by the orientation of its line elements. The only difference between the checks of this stimulus was in the orientation of the short lines within each area (Fig. 1G , pattern 13). If patients were not able to analyze line orientation or to group elements of the same orientation, they could not recognize the global checkerboard pattern. 

Stimulus Parameters

Luminance, contrast, size of pattern elements, increase of elements toward the periphery, temporal frequency, and further characteristics of the stimuli are listed in Appendix A. Contrast (C) is always expressed as Michelson contrast ³⁷ and is expressed as a percentage:  

\[C_{\mathrm{M}}{\cdot}100{=}\ \frac{(L_{\mathrm{max}}-L_{\mathrm{min}})}{(L_{\mathrm{max}}{+}L_{\mathrm{min}})}{\cdot}100\]

Luminance (L) was measured five times for each pattern, at the center and at all four corners of the monitor. Means and SDs of the results are indicated in Appendix A. Colors are expressed in Commission Internationale de l’Eclairage (CIE) xyY coordinates. The room was dimly lit by standard light bulbs, and surround luminance was approximately 0.44 cd/m². (The CIE system ³⁸ provides a linear transformation of the three primaries [red, green, blue] that enable visualization of a color as it would be projected on a two-dimensional surface: the CIE chromaticity diagram. The CIE chromaticity coordinates are x and y; the center of the diagram is white[ neutral, achromatic] and has a numerical value of 0.333 both in x and y. Specification of the two CIE chromaticity coordinates x and y determines the color or chroma of a source or object—that is, its hue and saturation. The uppercase Y value specifies the brightness [lightness] or luminosity.) 

For the tests with depth-defined checkerboards, the visual fields of both eyes were separated by means of spectacles with LCD shutters that alternately opened and obstructed the field of view of both eyes in counterphase at a frequency of 75 Hz. Special software and hardware doubled the number of frames presented per second and produced 2 × 75 images on the monitor screen, with small disparities between the images displayed to the two eyes, thus creating a stereoscopic depth impression. 

All patterns could be displayed in two ways: with a homogeneous element size of checkerboard or pattern elements (Fig. 1 , pattern 1) and with an increasing size of checkerboard or pattern elements (Fig. 1 , patterns 2 through 8). Central element size was clearly above threshold even for older observers, and size increased with eccentricity roughly according to the magnification factor ^{28 39} of the human visual system, to achieve a stimulation equally far above threshold at each position of the visual field (Appendix A). 

Patients and Controls

Component perimetry was tested in 41 patients with neuro-ophthalmologic disorders and 22 normal control subjects. Inclusion criteria for patient selection were a good general state of physical and mental health, normal or corrected-to-normal visual acuity, no cataract or glaucoma, no disease of the retina or optic nerve, no severe oculomotor disorders (e.g., inability to maintain fixation), no visual neglect or other deficits of attention, and no sedative medication. Clinical details of the patients and/or results of the different standard tests for basic visual functions (conventional light perimetry, visual acuity, color vision, and stereoscopic vision) are provided in Table 1 . An automatic perimeter (Tübinger Automatic Perimeter[ TAP]; Oculus, Wetzlar, Germany) was used for conventional light perimetry (either before or after component perimetry testing), and visual acuity was checked with Landolt Cs. Central color vision was tested using Ishihara plates, and central stereo vision tests was tested using the Lang and Titmus stereo tests (Oculus). The anatomic analyses were based on computed tomographic or magnetic resonance imaging scans. 

The patients were initially assigned to one of two groups: those with homonymous absolute visual field defects and those with no visual field defect (e.g., a patient with an infarction of the basal ganglia). Among those patients, five had incongruent and/or relative visual field defects, and in four of them the defects had not been known before our examination. We formed a separate (third) group for these patients to compare the results of component perimetry with those of conventional light perimetry (Table 1) , leading to the following categorization: Group 1 contained 24 patients with homonymous absolute visual field defects; group 2 contained 5 patients with incongruent and/or relative visual field defects; and group 3 contained 12 patients without visual field defects (control patients). 

In all 22 subjects of the normal control group basic visual functions were also tested with the different standard tests described earlier (Table 2) , and the visual field was determined to be normal by conventional perimetry (Tübinger Automatic Perimeter; Oculus). Inclusion criteria for controls were normal or corrected-to-normal visual acuity, normal color and stereo vision, an intact visual field, and no ophthalmic disease. 

Task

During the test, the patient’s head was placed on a chin rest. The patient scanned the visual field with the mind’s eye while fixating a central spot—that is, without moving the eyes. The patient had to indicate local differences of the stimuli, for example, whether the pattern on the monitor appeared homogeneous, whether there were parts differing from the remainder, and whether the stimulus extended symmetrically around the fixation point. While maintaining central fixation, the patient outlined any areas of deviating perception experienced. A transparent sheet of plastic covered the monitor screen, on which the patient used colored pens for outlining and to correct the drawings, if necessary. After an explanation of the component perimetry procedure, patients typically required between 1 and 5 minutes to complete the test with one stimulus. All tests of component perimetry were performed binocularly in all patients as well as in the controls, to reduce the test duration to an acceptable time. 

Data Analysis

To compare the results of component and conventional light perimetry, we determined the size of visual field defects revealed by the different perimetric methods. As a first step, the margins of visual field defects, as they appeared on the patients’ drawings after component perimetry, and the printouts of conventional light perimetry were fed into a computer by means of a digitizing tablet and transformed to a common format. To obtain the binocular visual field as revealed by conventional perimetry, we superimposed the printouts of both eyes to determine the margins of the homonymous visual field defect. Figure 2 illustrates the differences between the testing situations and the scaling of length in the printouts. Test stimuli are presented in a sphere in conventional perimetry and, in contrast, on an almost flat monitor in component perimetry. In a sphere the length of line a′ seen under a given visual angle is independent of eccentricity, whereas on a monitor the length of line a seen under the same visual angle increases with eccentricity. After transformation, the length of line a′, seen on the printouts under a given visual angle, was also independent of eccentricity. 

After transformation, the size of visual field defects is indicated in arc degrees squared (arcdeg²; for definition see Appendix B). 

Results

Patients with Visual Field Defects

Twenty-nine patients with brain lesions affecting the visual pathway were examined by component perimetry. All 24 patients of group 1 (Table 1) with homonymous visual field defects subjectively experienced visual field defects with all patterns tested (Fig. 3a ). The lesions affected structures of the visual pathway located between the optic chiasm and the primary visual cortex, V1. All our patients perceived at least a part of their visual field defects when looking at the different perimetric stimuli, even in the case of the classic noise field. Therefore, sensitivity of the method was 100% in this patient group. 

Patients in group 2 (Table 1) with incongruent and/or relative visual field defects described degraded visual perception in the contralesional visual field, but not for all functions tested (Fig. 3B) . The absence of subjective visual field defects was most pronounced for the noise fields, whereas almost all patients in this group subjectively perceived their visual field defects when tested with segmentation tasks. Three of these five patients had brain lesions of higher visual areas not including V1. 

Healthy Control Subjects and Control Patients

As a control, 22 normal observers (Fig. 3D) and 12 patients (Fig. 3C) with brain lesions not affecting the visual pathway were examined with component perimetry. Some controls described areas where perception deviated (indicated schematically at the bottom of Fig. 3 ). Those areas counted as pathologic (Figs. 3C 3D ; dark bars) if they extended asymmetrically around the fixation point, that is, if they were similar to the results described by the patients who had visual field defects. However, those areas counted as physiological changes of visual performance across the visual field, if they lay symmetrically around the fixation point (Figs. 3C 3D ; hatched bars). 

In the patient control group, false-positive results were mostly observed with the classic noise field (pattern 1), whereas no false-positive results were obtained with patterns 8 (filling-in perimetry), 12, and 13 (depth-defined and orientation-defined segmentation perimetry, respectively). Physiological changes were experienced with all patterns of component perimetry except pattern 8 (filling-in perimetry; Figs. 3C 3D ). The normal control group showed false-positive results only for the classic noise field (pattern 1), the rotating lines (pattern 7), and motion-defined segmentation perimetry (pattern 10; Fig. 3D ). On average, normal control subjects showed fewer false-positive and physiological results than the patient control group. Most of the controls, patients, and normal subjects perceived homogenous patterns without local differences and were therefore classified as having negative results (Figs. 3B 3C 3D ; light bars). 

Statistics for False-Positive and False-Negative Results

To estimate the number of false-positive and false-negative results using conventional perimetry as the gold standard, all results from all subjects (patient groups 1 and 2, patient controls, and normal control subjects) were pooled together in Table 3 as follows: 

Type A results

•  
  Matched cases: Results of component perimetry agreed qualitatively with results of conventional perimetry, i.e., both were positive (P), or both were negative (N).
•  
  PP (pathologic): some form of visual field defect in component as well as in conventional perimetry.
•  
  NN (normal): intact visual field in component as well as in conventional perimetry.

Type B results

•  
  PN false positive: visual field defect in component perimetry but a full visual field in conventional perimetry.

Type C results

•  
  NP false negative: completely intact visual field in component perimetry but a visual field defect in conventional perimetry.

Because conventional perimetry served as the standard method, results of five patients in group 2 showing visual field defects in conventional perimetry but an intact visual field for some functions tested with component perimetry were classified as false negatives, although this discrepancy was probably caused by selective visual field defects based on lesions of higher visual cortical areas not affecting detection of luminance differences as tested in conventional perimetry. 

We calculated the sensitivity and specificity of component perimetry using conventional perimetry as the gold standard as follows (Table 3) :

•  
  Sensitivity: number of patients with a visual field defect in component perimetry and in conventional perimetry, divided by all patients with a visual field defect in conventional perimetry: P sensitivity = PP/(PP + NP).
•  
  Specificity: number of patients with an intact visual field in component perimetry and conventional perimetry divided by all patients with an intact visual field in conventional perimetry: P specificity = NN/(NN + PN).

Types of Results

Testing the visual field with component perimetry can lead to three different types of visual field defect, as demonstrated in Figure 4 . For comparison, the corresponding visual field revealed by conventional light perimetry is shown. When looking at the stimuli of component perimetry, most patients outlined areas where they did not experience any visual stimulation. Either sharp boundaries (Fig. 4 , Type A) or transitional areas (Fig. 4 , Type B) separated these blind areas from the intact visual field. Within the transition area, patients always had the impression of degraded visual perception. Other patients, particularly those with relative visual field defects, perceived their whole visual field defect as an area of degraded vision without any blind portions (Fig. 4 , Type C). 

Patients were also asked to describe their perceptions within the transition areas and the areas of degraded vision. Table 4 summarizes some common descriptions for each perimetric stimulus. 

Reproducibility

We were able to retest four of the patients (P6, P23, P25, and P35). Figure 5 shows the results for two of these, patients 6 and 23. Patients 6, 23, and 35 had an infarction of the right posterior cerebral artery that led to left hemianopia. Patient 25 had suffered from meningoencephalitis, which also led to left hemianopia. As shown in Figures 5A and 5B , visual field defects on the left side as revealed by component perimetry corresponded well to those revealed by conventional perimetry in patients 6 and 23, as was the case in patients 25 and 35. When patient 23 was retested after 16 months, the size of his visual field in both conventional and component perimetry as well as the transitional areas had not changed since the first test (Fig. 5A , right; two-tailed paired t-test; P = 0.5). For patients 25 and 35, the size of the visual field defect also did not change significantly over time (two-tailed paired t-test; patient 25: P = 0.5; patient 35: P = 0.8). 

In contrast to the size of the field defect in patient 23, the overall size of the visual field defect in patient 6 was significantly smaller when retested after 11 months (Fig. 5B ; two-tailed paired t-test; P = 0.001). This recovery appeared in conventional and component perimetries and was most pronounced in the upper left quadrant. 

Conventional Perimetry versus Component Perimetry

To evaluate how well the results of component and conventional perimetry agree, we calculated the correlation between the size of corresponding visual field defects by component and conventional light perimetry. The correlation was calculated twice: physiological results were classified either as false positive (i.e., visual field defects; Fig. 6 , dark bars) or as negative results (i.e., intact visual field; Fig. 6 , hatched bars). (Because the data might not have been distributed normally, we selected a nonparametric measurement of association. The correlation coefficient r is given as Spearman’s rho [rank order correlation] indicating relative rather than absolute correlations.) 

The sizes of visual field defects found with both methods correlated well, with all correlation coefficients significant on the 1% level for both types of calculation and for all patterns of component perimetry. 

Moreover, we estimated the size and the degree of spatial overlap between corresponding visual field defects in component and conventional light perimetry. In Figure 7A the size of the visual field defects in component perimetry and the size of overlapping areas are represented as the proportion of the corresponding size of the visual field defects in conventional perimetry. The normalized average size of visual field defects (Fig. 7 , light bars) and the normalized average size of overlapping areas (Fig. 7 , dark bars) are shown for each perimetric pattern except pattern 6 (insufficient data to calculate paired t-tests). The difference between the light and dark bars corresponds to the nonoverlapping areas of the visual field defects. 

The size of visual field defects shown by component perimetry tended to be smaller than the corresponding results of conventional perimetry except for pattern 12, the stereoscopically defined checkerboard. For patterns 2, 3, and 9 only, the defects were significantly smaller for component perimetry. The degree of overlap between the corresponding visual field defects for all patterns of component perimetry was much larger than the noncorresponding area. Four categories of overlap can be discriminated (Fig. 7B , bottom):

•  
  No overlap: The scotomata of the two different perimetric methods do not overlap at all.
•  
  Small overlap: The scotomata overlap but are not exclusively in one hemifield (in patients with unilateral suprageniculate brain lesions, visual field defects are expected only in the contralesional visual field).
•  
  Adequate overlap: Visual field defects obtained with both methods overlap and are located in the contralesional visual hemifield, but not exclusively in the same quadrant.
•  
  Good overlap: Visual field defects overlap and extend exclusively in the same hemifield and quadrant.

For each component perimetry stimulus the proportion of results for the different categories of overlap is shown in Figure 7B . Except for pattern 10 (motion-defined checkerboard) there was at least a small overlap between all corresponding visual field defects. Unilateral suprageniculate lesions of the visual system cause visual defects only in the contralesional visual hemifield. A small overlap between corresponding visual field defects—and that comprises both hemifields—usually constitutes an unsatisfactory result. Testing the visual field with stimulus 12 (depth-defined checkerboard) led to a small overlap in approximately 50% of cases. With all other stimuli of component perimetry, more than 80% of the results agreed adequately or well with the results of conventional light perimetry (i.e., comprised only corresponding hemifields). Also for the categories of adequate and good overlap, the average size of visual field defects revealed by component perimetry was usually smaller than the corresponding visual field defect revealed by conventional light perimetry (Fig. 7C) . Defects are significantly smaller (Fig 7 , *on the 5% level; **on the 1% level) for pattern 2 (black-and-white noise field with increasing elements), pattern 3 (red-and-green noise field), pattern 9 (coherent motion), and patterns 10 and 13 of segmentation perimetry (motion- and orientation-defined checkerboards). 

Discussion

Testing the visual field by component perimetry led to results that correspond qualitatively with the results provided by conventional light perimetry, independent of the stimulus used. Component perimetry can therefore be used as a fast screening method for visual field defects caused by suprageniculate lesions of the visual pathways. Furthermore, the equipment required for testing is simpler than in conventional perimetry, because the different stimuli of component perimetry can be displayed on a monitor screen by means of a video player or a personal computer. 

Patients with Homonymous Absolute Visual Field Defects

A fast screening test should fulfill at least two conditions. First, all visual field defects should be detected, and, second, false-positive diagnoses should be minimized. The first condition, high sensitivity, is fulfilled for visual field defects caused by lesions beyond the optic chiasm. All visual field defects were detected by component perimetry. In contrast to previous noise field campimetry studies ^{1 2 3 4} all our patients with absolute homonymous visual field defects caused by suprageniculate lesions subjectively perceived their defects. This was true for all perimetric stimuli tested, even for the classic noise field. 

As outlined in the introduction, earlier studies using the classic noise field as a test stimulus ^{1 2 3 4} yielded a relatively low sensitivity for lesions caused by suprageniculate lesions. There are three probable reasons for the difference between our results and those of Aulhorn and Köst, ^{1 2} Schiefer et al., ³ and Kolb et al. ⁴ Although the stimuli used for the classic noise field were virtually identical (we in addition presented the noise field with element size increasing toward the periphery), there were differences in the instructions to the patients. The first difference among the studies concerns the way patients were introduced to the task. We told them not only to look for local differences within their visual fields but also to pay attention to the boundaries of the visual field. Patients with lesions of the retina or the optic nerve usually have scotomata completely surrounded by areas of intact visual field. These types of scotomata are clearly perceived in the classic noise field. ^{1 2 40} In most patients with suprageniculate visual field defects, however, the defective area is not surrounded by an intact visual field, but the outer boundaries of the visual field are shifted toward the fovea, so that the visual field simply becomes smaller—similar in some respects to the effect of closing one eye. Patients with narrower visual field boundaries seem to habituate to the shrunken visual field. They certainly do not perceive local differences within the remaining intact visual field. But as soon as these patients are asked pay attention to the boundaries of the visual field and to draw them on a monitor, defects become apparent. 

The second and more relevant reason for the differences between the studies may be the increasing element size used in most of the new perimetric stimuli. Most patients reported that the visual field defect is subjectively much more pronounced when the size of pattern elements increased toward the periphery. The increased salience of the defect leads first to a better detection of peripheral elements. Second, the whole stimulus configuration appears as asymmetric in the case of a peripheral defect, because of the absence of larger elements within the defective visual field area. Therefore, the increasing element size not only enables a better discrimination of pattern elements in the periphery but also allows the patients to better perceive and judge the homonymous hemianopia. 

A third possible reason for the difference is that we used a larger stimulus area. 

Size of Visual Field Defects and Areas of Overlap

The ratio between visual field defects calculated by component versus conventional perimetry tended to be smaller than 1, with the exception of the results obtained with pattern 12, the stereoscopically defined checkerboard (Fig. 7) . This is to say that the field defect was smaller for component than for conventional perimetry. It seems that the stereoscopic visual field of patients with homonymous visual field defect was affected to a larger degree than the visual fields for all other components tested. Although the average ratio was smaller than 1 for all other patterns, the deviation from 1 is only significant for patterns 2, 3, and 9 (Fig. 7A) . One reason for the smaller defect size may be fixation instability by the patients during the test, another one filling-in. As mentioned, patients were asked to outline the subjectively perceived visual field defects while maintaining fixation. If fixation was unsteady, the borders of the visual field defect would have moved back and forth. This effect could lead to perception of visual field defects as smaller than they really are. Unsteady fixation can also influence the degree of overlap between corresponding visual field defects. As the subjectively perceived defect moves back and forth, it is hard to outline its correct position. 

The noncorresponding areas between visual field defects revealed by the two methods are probably also influenced by the test conditions. The patients are not allowed to fixate the pen while outlining the defect. Figure 8 illustrates these possible influences on the degree of overlap by presenting our worst case. In the case of small eccentric scotomata, the unsteady fixation and the motor error during drawing can lead to a visual field defect in component perimetry not overlapping with the one revealed by conventional perimetry. 

Patients with Incongruent and/or Relative Visual Field Defects

The results of patient group 2 were heterogeneous. Not all perimetric stimuli of component perimetry revealed incongruent and/or relative visual field defects. This finding was conspicuous with the noise field stimuli (patterns 1 through 4), whereas almost all patients perceived their visual field deficits when looking at the perimetric patterns 7 through 13 (Fig. 3B) . 

Especially in the case of patterns 9 through 13, the visual system has to analyze local elements before a global structure can be extracted by integrating over parts of the visual field. This task is more complex than the detection of dynamic visual noise, and higher cortical visual areas are probably involved. A relative visual field defect, as detected in conventional perimetry, may not impair the perception of dynamic visual noise but may influence visual functions needing additional processing steps (e.g., figure–ground segregation). 

Although the number of subjects in patient group 2 was small, the results indicated that component perimetry may relatively selectively reveal defects of different components or functions of visual perception. Three of the patients in this group had brain lesions of higher visual areas not including the visual pathway up to V1. These lesions probably led to selective visual dysfunction in parts of the visual field selective for some visual functions, whereas others remained spared. Clearly, far larger numbers of patients must be tested to further clarify the selectivity of the new method. 

Control Groups

The control groups served to evaluate the specificity of component perimetry through the number of false-positive results. Most but not all the controls did not experience any inhomogeneities (i.e., defects in the stimuli of component perimetry). There were no abnormalities or deficits in the visual field as measured by component perimetry. 

Physiological Results

Detection thresholds are not homogeneous over the whole visual field but increase from the fovea toward the periphery. Even the outer borders of the visual field vary with the visual function tested. ⁴¹ Some subjects perceived these functional differences between the central and the peripheral parts when looking at some of the perimetric patterns. Several control subjects even indicated the boundaries of their binocular visual field when tested with the depth-defined checkerboard stimulus. They experienced depth only within this binocular field, but not in the monocular field parts. These physiological results do not represent classic false-positive results. They represent inhomogeneities of the normal visual field that most subjects are not aware of. Therefore, Figure 6 includes two evaluations, the physiological results were either counted as normal (Fig. 6 , hatched bars) or as false positive (Fig. 6 , dark bars). We concluded that component perimetry detected not only pathologic visual fields but also physiological inhomogeneities in normal fields. 

Patient Data

In contrast to the results of the control group (normal observers and patients) none of the patients with visual field defects described areas of deviating visual perception lying symmetrically around the fixation point. Perhaps the degraded perception within the areas of visual field defects is so prominent in relation to the physiological changes that the latter were not perceived by the patients. 

The prevalence of pathologic or false-positive results was higher in the patient control group than in normal control subjects (see Table 3 ). This could be caused by lesions of extrastriate visual areas that do not affect the visual field in conventional perimetry but affect the field in component perimetry. In this case, the false-positive results would not really be false positive but the result of a higher sensitivity of component perimetry for this type of defects. Another possible cause of false-positive results is a disturbed microcirculation in the patient’s retina. Erb et al. ⁴² suppose that perturbations of retinal blood flow can lead to temporary visual field defects perceptible in the classic noise field. Indeed, in all subjects of the patient control group the cause of the neurologic disease was a circulatory disturbance (stroke or hemorrhage). 

Evaluation

The good detection of scotomata and the low number of false-positive results in component perimetry encourages the use of this new method to screen for different types of visual field disruptions in patients with neurologic disorders. Of course, component perimetry by itself can only qualitatively detect visual field defects. Although we found a correlation between the results of component and conventional perimetry, component perimetry was unable to measure the exact size and location of visual field defects. The size of the scotoma detected by component perimetry is generally smaller than that found by conventional perimetry. One reason may be a partial filling in of defects in higher cortical areas. In addition, a complete correlation would not be expected between the results of conventional and component perimetry for defects caused by cortical lesions. In these cases, defects detected by component perimetry may be even larger than those obtained by conventional perimetry, because detection of differences in luminance may still be intact, whereas more complex functions such as motion detection are impaired. 

To supplement component perimetry as a screening method, more quantitative perimetric methods, comparable to conventional light perimetry, must be developed for the different components or functions of visual perception. Although component perimetry is a subjective and therefore qualitative perimetric method, all patients in our study were able to perceive their own visual field defects, and the results of the tests were reproducible. 

On the basis of this pilot study, we conclude that component perimetry is a relatively reliable and sensitive method for detecting visual field defects simultaneously over large parts of the visual field. Therefore, a rapid screening of the visual field appears to be possible, not only for defects in the detection of differences in luminance, as with conventional light perimetry, but for other submodalities of vision such as motion and color perception. This study shows that component perimetry provides an effective tool to detect visual field defects, especially in patients with neurologic disorders, at least on an exploratory basis for screening purposes. Subsequent studies with component perimetry should investigate whether the method is also a clinically useful tool to distinguish between different disorders of visual perception and whether the results indeed provide information about the localization of lesions in the visual system. 

Appendix AA

Appendix A:

5 5  

Appendix AB

Appendix B

Transformation of the Unit Sterad into the Unit Arcdeg²

In perimetry, there is no uniform unit for the size of visual field defects. In ophthalmology lengths are usually given in units of arcdeg. A desirable unit for the description of areas in ophthalmology would therefore be the square of arcdeg or arcdeg². A more common unit for the size of an area on a sphere is the steradian. The steradian Φ is usually given as the surface of a unit sphere—that is, in units of sterad. The steradian can be transformed into units of arcdeg² by the following formula  

\[{\Phi}{[}\mathrm{arcdeg}^{2}{]}{=}\ \frac{180^{2}}{{\pi}^{2}}\ {\Phi}{[}\mathrm{sterad}{]}.\]

With this definition, no angular coordinate system is needed to make comparisons or perform calculations with steradians. The steradian for a small square of size Δa by Δa may be calculated as  

\[{\Phi}{[}\mathrm{arcdeg}^{2}{]}{=}{\Delta}a{[}\mathrm{arcdeg}{]}{\cdot}{\Delta}a{[}\mathrm{arcdeg}{]}\]

as might be expected intuitively. The total steradian of a unit sphere is  

\[{\Phi}_{\mathrm{total}}{[}\mathrm{sterad}{]}{=}4{\pi}\ \mathrm{or}\ {\Phi}_{\mathrm{total}}{=}\ \frac{360^{2}}{{\pi}}\ \mathrm{arcdeg}^{2}.\]

 

 Supported by Deutsche Forschungsgemeinschaft (Klinische Forschergruppe Neuroophthalmology).

 Submitted for publication December 10, 1997; revised August 21, 1998, April 6 and September 14, 1999, and January 24, 2000; accepted February 15, 2000.

 Commercial relationships policy: N.

 

Figure 1.

 

Patterns of component perimetry. (A) Static representation of one miniaturized frame of the different noise field stimuli. Also the stimuli for color (B), acuity (C), orientation (D), and filling-in perimetry (E) are represented as one static frame each. In contrast to the other patterns of component perimetry, the stimuli of motion (F) and segmentation perimetry (G) are illustrated schematically.

Table 1.

 

Clinical Details for All Patients Tested

Patient	Age/Sex	Duration (Month)	Lesion Type	Side	Location	Visual Field	Acuity*	Color	Stereo, †
Group 1
P1	45 F	8	Tumor resection	L	O, T, P	Hemianopia R	0.5/0.6	No change	Blind
P2	60 F	18	Infarct	L	O, brain stem	Inferior quadrantanopia R	1.0/1.0	—	40
P4	32 F	24	Cerebral hemorrhage	L	T, brain stem, basal ganglia	Inferior quadrantanopia R	1.0/1.0	—	40
P5	45 M	6	Tumor resection	L	Medial inferior T	Hemianopia R	1.0/1.0	No change	800
P6	55 M	3	Infarct	R	O	Hemianopia L	1.0/1.0	Change	40
P8	32 M	5	Infarct	R	T, basal ganglia	Hemianopia L	1.0/1.0	—	400
P9	41 M	54	Tumor resection	R	T, F, basal ganglia	Hemianopia L	1.2/1.2	—	—
P11	61 F	66	Tumor resection	L	T, basal ganglia	Superior quadrantanopia R	0.9/0.9	—	—
P14	71 M	3	Infarct	R	O, T	Hemianopia L	—	—	—
P17	59 M	54	Infarct	R	O, T, P	Hemianopia L	—	—	—
P18	25 M	5	Tumor resection	L	T, P (O)	Hemianopia R	1.0/1.0	No change	40
P19	46 F	13	Infarct	L	Basal ganglia	Hemianopia R	0.8/0.8	No change	140
P21	67 M	30	Infarct	L	O, basal ganglia	Superior quadrantanopia R	0.8/0.8	—	40
P23	38 M	2.5	Infarct	R	O, basal ganglia	Hemianopia L	1.0/1.0	—	—
P25	53 M	114	Meningoencephalitis	R	(No scans)	Hemianopia L	1.1/1.2	—	—
P26	73 M	4	Infarct	R	Medial T, O	Superior quadrantanopia L	0.9/1.0	Change	—
P29	33 F	24	Tumor resection	L	O	Hemianopia R	1.0/0.7	—	—
P32	32 F	30	Tumor resection	L	O	Inferior quadrantanopia R	1.7/1.7	—	—
P33	61 M	12	Infarct	L	Medial T, O, thalamus	Superior quadrantanopia R	1.2/1.2	No change	40
P34	49 M	24	Infarct	R	O	Hemianopia L	0.9/0.9	No change	40
P35	79 M	1	Infarct	R	O, (T)	Hemianopia L	0.3/0.6	No change	50
P38	62 M	18	Infarct	R	O, T, P	Hemianopia L	1.0/1.0	No change	Blind
P40	41 M	30	Head trauma	R/L	O (R), T (R), F (R & L)	Superior quadrantanopia R	1.0/1.0	—	—
P41	66 F	24	Infarct	L	O, basal ganglia	Superior quadrantanopia R	1.0/1.0	No change	200
Group 2
P7	39 M	4	Infarct	L	Lateral T, F, basal ganglia	Relative scotomata R in both eyes	0.5/0.63	No change	Blind
P20	41 M	6	Tumor resection	L	O, P	Homonymous scotoma R in both eyes	1.5/1.5	No change	100
P27	41 F	5	Cerebral hemorrhage	L	Thalamus	Incongruent superior scotomata R in both eyes	—	—	—
P28	34 F	12	Subarachnoid hemorrhage and infarct	L	T, P	Relative scotomata R in both eyes	1.0/1.0	No change	40
P37	49 M	12	Infarct	L	Lateral T, F, (P)	Relative scotomata R in both eyes	1.0/1.0	No change	40
Group 3
P3	52 M	9	Infarct	R	T, P, F, basal ganglia	Full	0.5/0.4	—	100
P10	48 F	5	Transient ischemic episode	R	No change (NMR)	Full	0.9/0.9	No change	40
P12	33 F	18	Infarct	R	Capsule/putamen	Full	—	—	—
P13	36 F	3.5	Infarct	L	T, F	Full	—	—	—
P15	59 M	2.5	Infarct	R	Basal ganglia	Full	1.0/1.0	No change	40
P16	34 F	36	Infarct	L	T, F, basal ganglia	Full	1.0/1.0	No change	40
P22	51 M	42	Infarct	L	invisible on CT (1990)	Full	1.2/1.2	Change	40
P24	34 F	216	Infarct	L	(No scans)	Full	1.0/1.0	No change	40
P30	28 F	6	Infarct	R	T, F	Full	1.0/1.0	No change	40
P31	48 M	12	Infarct	L	T	Full	1.0/1.0	No change	40
P36	63 M	3	Infarct	L	O, basal ganglia	Full	1.0/1.0	No change	40
P39	34 M	18	Infarct	R	Lateral T, F, basal ganglia	Full	1.2/1.2	No change	100

 R, right; L, left; O, occipital cortex; T, temporal cortex; P, parietal cortex; F, frontal cortex.

*  Acutiy is listed as a decimal, where 1.0 is 20/20.

†  Values are presented as arc seconds.

Table 2.

 

Patient Data and Test Results for the Control Group

Subjects	Age Gender	Visual Field	Visual Acuity (Near)*	Color Vision, †	Stereo Acuity, ‡
AC	17 M	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
AG	21 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
VW	22 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
AD	23 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 60
CG	24 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
RG	24 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
AW	25 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
AS	25 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
SE	28 M	oB	L: 1,0/R: 0,8	oB	A 550 /B 40
JB	28 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
GB	30 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
TQ	33 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
UH	35 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
GB	37 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
RK	37 M	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
LS	42 F	oB	L: 1,0/R: 1,0	oB	A none/B 80
IW	42 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
WB	43 F	oB	L: 0,8/R: 1,0	oB	A none/B 800
MF	45 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
HW	55 F	oB	L: 1,0/R: 1,0	oB	A 550 /B 40
AH	56 F	oB	L: 1,0/R: 0,8	oB	A 550 /B 40
GD	65 M	oB	L: 1,0/R: 1,0	oB	A 550 /B 40

 oB, no pathologic result.

*  Visual acuity: Optotypes, Landolt C; in decimals where 1.0 = 20/20.

†  Color vision: Ishihara color test.

‡  Stereo acuity: A, Lang stereo test (Oculus, Wetzlar, Germany); B, Titmus stereo test (Oculus).

Figure 2.

 

Left: Test situation for both conventional and component perimetry. Observers are sitting at a distance (d) in front of the sphere or the monitor. Distances a′ represent the line length seen under the angle α. Because patients drew their visual field defects directly on the monitor screen the printouts of component perimetry correspond exactly to the situation on the monitor screen. On the printouts the radius r′ for conventional perimetry (right) and r for component perimetry correspond to the extent of the visual field area examined. γ: Size of the visual field examined in arc degrees squared. Ratio (c) between the radius r′ on the printout and the visual angle of the visual field area examined served as a scaling factor for the transformation procedure.

Figure 3.

 

Specificity of results for all perimetric stimuli tested in (A) patient group 1, (B) patient group 2, (C) patient control group, and (D) normal control group. Distribution of results over the three possible classes (negative, physiological, or pathological) is indicated as the percentage of all tests performed for each stimulus. Bottom: Distinction between false-positive and physiological results. The shaded or black areas correspond to visual field regions with deviating visual perception. The component perimetry stimuli are numbered as in Figure 1 .

Table 3.

 

Sensitivity, Specificity, and the Number of False-Positive and False-Negative Results in Component Perimetry

Pattern	Conventional Perimetry
		Negative Result (Neg.)	Positive Result (Pos.)
1: Classical noise field
Neg.	Specificity P = 0.88	False negative P = 0.09
Pos.	False positive P = 0.12	Sensitivity P = 0.91
2: Noise field black–white
Neg.	Specificity P = 0.97	False negative P = 0.12
Pos.	False positive P = 0.03	Sensitivity P = 0.88
3: Noise field red–green
Neg.	Specificity P = 0.94	False negative P = 0.08
Pos.	False positive P = 0.06	Sensitivity P = 0.92
4: Noise field blue–yellow
Neg.	Specificity P = 0.97	False negative P = 0.12
Pos.	False positive P = 0.03	Sensitivity P = 0.88
5: Colored dots
Neg.	Specificity P = 0.97	False negative P = 0.04
Pos.	False positive P = 0.03	Sensitivity P = 0.96
6: Rotating Landolt Cs
Neg.	Specificity P = 0.97	False negative P = 0.07
Pos.	False positive P = 0.03	Sensitivity P = 0.93
7: Rotating lines
Neg.	Specificity P = 0.94	False negative P = 0.0
Pos.	False positive P = 0.06	Sensitivity P = 1.0
8: Interrupted lines
Neg.	Specificity P = 1.0	False negative P = 0.0
Pos.	False positive P = 0.0	Sensitivity P = 1.0
9: Coherent motion
Neg.	Specificity P = 0.97	False negative P = 0.0
Pos.	False positive P = 0.03	Sensitivity P = 1.0
10: Motion-defined checkerboard
Neg.	Specificity P = 0.94	False negative P = 0.04
Pos.	False positive P = 0.06	Sensitivity P = 0.96
11: Time-defined checkerboard
Neg.	Specificity P = 0.97	False negative P = 0.0
Pos.	False positive P = 0.03	Sensitivity P = 1.0
12: Depth-defined checkerboard
Neg.	Specificity P = 1.0	False negative P = 0.0
Pos.	False positive P = 0.0	Sensitivity P = 1.0
13: Orientation-defined checkerboard
Neg.	Specificity P = 1.0	False negative P = 0.0
Pos.	False positive P = 0.0	Sensitivity P = 1.0

 Neg, negative result (no defect); Pos, positive result (defect).

Figure 4.

 

Left: Three types of typical results for component perimetry (see Table 2 ) are shown. Black areas in the graphs indicate parts of the visual field where the patient did not perceive any stimulation when confronted with the visual stimulus. Hatched areas indicate that the patient experienced a smooth transition between the intact visual field and the visual field defect. Right: Corresponding results of conventional perimetry for each patient. Absolute or relative homonymous visual field defects are indicated by black and coarsely hatched areas, respectively. Fine shading indicates monocular visual field defects.

Table 4.

 

Most Common Subjective Description of the Perception within the Area of Degraded Vision

Perimetric Stimulus	Perception
Noise field perimetry	Reduced or no flicker
Black–white (patterns 1 and 2)	Luminance changed (brighter or darker)
Isoluminant colors (patterns 3 and 4)	Paler or no colors
Color perimetry (pattern 5)	Paler or no colors
Acuity perimetry (pattern 6)	Impression of motion without uniform direction; no Landolt Cs, only dark blobs
Orientation perimetry (pattern 7)	Impression of motion without uniform direction; no lines, only bright blobs
Filling-in perimetry (pattern 8)	Solid lines or interrupted lines without flicker
Motion perimetry (pattern 9)	Impression of motion without motion direction
Segmentation perimetry	No checkerboard structure
Motion-defined (pattern 10)	Motion perceived
Time-defined (pattern 11)	Flicker perceived
Depth-defined (pattern 12)	Depth not perceived
Orientation-defined (pattern 13)	Line elements not perceived, only bright blobs

Figure 5.

 

Results for two patients for the first examination and a retest. Top: Results of conventional perimetry. For component perimetry representative results are shown for two perimetric stimuli tested only. (A) Results from patient 23, retested after 16 months. (B) Corresponding results from patient 6, retested 11 months after the first test.

Figure 6.

 

For each component perimetry stimulus the Spearman’s coefficient (rho) is displayed for the correlation between the size of corresponding visual field defects revealed by the two methods.

Figure 7.

 

(A) Sizes of visual field defects and overlapping areas (means and SEs) expressed as the proportion of the visual field defect revealed with conventional perimetry for stimulus types. (B) For each perimetric stimulus the type of overlap category is indicated as the percentage from all tests. Bottom: Four overlap categories. (C) Sizes of visual field defects (means and SEs) revealed by component perimetry expressed as the proportion of the visual field defect revealed with conventional perimetry for all patterns and patients with an adequate or good overlap. (A, C) Ratios significantly less than 1 *for a 5% level of significance and **for a 1% level of significance.

Figure 8.

 

Results from patient 20, with conventional perimetry (right) and pattern 2 of component perimetry (left) as an example of an artificially small overlap between the results of the two methods.

Table 5A.

 

Variable Parameters and Values Used in the Study for All Perimetric Patterns

Variable Parameters	Values Used
Pattern 1 and 2: Noise field (black and white)
Luminance of black elements	1.26 ± 0.19 cd/m2
Luminance of white elements	70.33 ± 6.14 cd/m2
Contrast	96.5%
Size of pattern elements (pattern 1)	0.66 mm2
Minimum size of pattern elements (Ø)	0.66 mm2
Magnification factor (pattern 2)	7.5%/deg
Highest temporal frequency	37.5 Hz
Pattern 3: Noise field (red and green)
Color space: red elements	0.618 ± 0.002/0.342 ± 0.001/18.44 ± 1.74* (CIE xyY coordinates)
Color space: green elements	0.278 ± 0.001/0.592 ± 0.005/18.19 ± 1.52
Contrast	<0.67%
Minimum size of pattern elements (Ø)	0.66 mm2
Magnification factor	7.5%/deg
Highest temporal frequency	37.5 Hz
Pattern 4: Noise field (blue and yellow)
Color space: blue elements	0.151 ± 0.0004/0.062 ± 0.001/5.3 ± 0.45*
Color space: yellow elements	0.411 ± 0.007/0.490 ± 0.006/10.8 ± 0.79*
Contrast
Measured by flicker-photometry	34.19%
Perception of isoluminance without flicker	6.34%
Minimum size of pattern elements (Ø)	0.66 mm2
Magnification factor	7.5%/deg
Highest temporal frequency	37.5 Hz
Pattern 5: Colored dots (red and green)
Color space: green background	0.278 ± 0.002/0.594 ± 0.004/18.36 ± 1.66*
Color space: red spots	0.621 ± 0.001/0.343 ± 0.0004/19.07 ± 1.55
Minimum size of pattern elements (Ø)	0.66 mm
Magnification factor	10%/deg
Frequency of temporal sine-wave-flicker	0.094 Hz
Pattern 6: Rotating Landolt Cs
Luminance white background	81.49 ± 4.37 cd/m2
Luminance black elements	0.26 ± 0.12 cd/m2
Contrast	99.36%
Minimum size of pattern elements (Ø)	3.3 mm
Magnification factor	10%/deg
Frequency of rotation	1.25 Hz
Pattern 7: Rotating lines
Luminance black background	0.089 ± 0.013 cd/m2
Luminance white elements	80.65 ± 8.18 cd/m2
Contrast	99.78%
Minimum length of pattern elements†	3.3 mm
Magnification factor	10%/deg
Frequency of rotation	1.25 Hz
Pattern 8: Interrupted lines
Luminance black background	0.1 ± 0.037 cd/m2
Luminance white elements	82.4 ± 5.32 cd/m2
Contrast	99.75%
Number of lines	72
Temporal flicker frequency	3.125 Hz
Pattern 9: Coherent motion
Luminance black background	0.098 ± 0.071 cd/m2
Luminance white elements	82.83 ± 5.343 cd/m2
Contrast	99.76%
Number of white elements	1000
Correlation	50%
Velocity	4.72 deg/sec
	(continues)

Table 5B.

 

Appendix A: (continued)

Variable Parameters	Values Used
Segmentation perimetry
Patterns 10–13
Luminance black background	0.098 ± 0.071 cd/m2
Luminance white elements	82.83 ± 5.343 cd/m2
Contrast	99.76%
Size of checkerboard areas	23.1 mm2
Pattern 10–12
Percentage of white elements	3%
Motion-defined checkerboard	Velocity: 16.1 deg/sec
Time-defined checkerboard	Frequency of counterphase flicker: 1.5 Hz
Depth-defined checkerboard	Depth: 10 mm
Pattern 13
Orientation-defined checkerboard
Size of pattern elements	1.98× 0.33 mm
Flicker frequency	0.75 Hz

 Values are presented as mean ± SE.

*  CIE xyY coordinates.

†  Width was a constant 0.33 mm.

The authors thank Marc Repnow for help with the data transformation, Clemens Winter for writing the computer code of the perimetric stimuli, Dirk Petersen for plotting the patients’ lesions, all patients who participated in this study, and the staff of the Schmieder Clinic in Allensbach (Paul Schönle, Director).