We present a protocol of using a smartphone app to perform Hirschberg test for measuring manifest and intermittent ocular misalignment (strabismus) under near and far fixation conditions.
A smartphone app has been developed to perform the automated photographic Hirschberg test for objective measurement of ocular misalignment. By computing the difference in corneal reflection generated by the phone camera flash relative to the iris center based on high resolution images, the app can measure misalignment with a much higher precision than the naked eye performing the Hirschberg test. It has been validated in a previous clinical evaluation study by comparing to the clinical gold standard-prism and alternate cover test. The goal of this article is to describe the testing techniques regarding how to use the app to measure ocular alignment for different fixation distances, without or with cover to break fusion, as well as angle kappa, so that users can use the app to perform equivalent tests typically done in clinic using prisms.
Measurement of eye alignment is frequently performed in vision care clinics. Cover test with prism neutralization is the commonly used clinical method for quantifying the degree of eye misalignment (strabismus). This method requires a high degree of training and experience. Accurate measurement becomes more challenging when patients cannot fully engage in the exam such as young children1, individuals with brain injuries or stroke2, or developmental disabilities3. Furthermore, there is a need for ocular alignment testing in school screening, because strabismus develops during childhood in an estimated 5−8% of the US population4, and is a substantial risk factor for amblyopia with about 30−40% of cases of amblyopia attributed to strabismus5,6,7. However, school nurses are normally not trained to conduct the standard cover test with prism neutralization for such screening. For non-eye care professionals, an additional challenge in strabismus screening is that intermittent strabismus (misalignment is not always manifested) and smaller magnitudes of misalignment are not visually obvious (<15 prism diopters [Δ])8.
In an attempt to address the challenges in the detection and measurement of strabismus, we have developed a smartphone app (EyeTurn) that implements and automates the photographic Hirschberg method9 by comparing the displacement of corneal reflections between the eyes. While conventional photographic Hirschberg method has been shown to have good reproducibility in clinics10,11, the cost for dedicated, standalone devices is a barrier for wide adoption. By providing an easy-to-use tool to measure eye alignment with standard smartphones, we hypothesize it will be widely adopted in school vision screening and used by non-eye care professionals. Our previous evaluation studies have shown that the app measurement is consistent with the current clinical standard of prism and alternate cover test12, for strabismus magnitudes of esotropia and exotropia up to 60Δ. In a pilot school screening study, we also showed that the app can help the school nurse detect children with intermittent exotropia who were missed by standard school vision screening protocols13.
The iOS version of the app is currently available to researchers and clinicians upon request for research purposes. The requesters have thus far included school nurses, pediatric ophthalmologists, optometrists, neuro-ophthalmologists, and strabismus specialists. The purpose of this article is to share the detailed app protocols for using the app to evaluate ocular alignment under different viewing conditions, namely, near and far fixation distance; with and without eye covering to break binocular fusion.
This study was conducted in accordance with the tenets of the Declaration of Helsinki, at Schepens Eye Research Institute (Boston, MA) and Spaulding Rehabilitation Hospital (Boston, MA). Informed consent was obtained from all the participants. The study was approved by the local institutional review boards of Mass Eye and Ear (Boston, MA).
NOTE: Patient inclusion criteria were prior diagnosis of horizontal strabismus (constant or intermittent exotropia or esotropia) and no other visual impairments. This study was a part of a larger one reported previously12. Data for 14 patients recruited in the US in the larger study12 are reported here with permission. An optometrist specialized in vision rehabilitation who routinely evaluate strabismus in clinic performed prism and alternate cover test, following by measurement with the app to prevent bias of the cover test results by the objective app measurement.
1. Prepare the test
NOTE: Testing can be performed in any environment; however, the following controls are likely to aid in successful testing.
2. Measure tropia (manifest strabismus) with single snapshot−near fixation
3. Measure tropia (manifest strabismus) with snapshot−far fixation
NOTE: To measure tropia for far fixation, the angle kappa for each eye needs to be measured at least once. The app will automatically choose the latest measurement of angle kappa in the history. If it is not available for either eye, the app will give a reminder to first obtain this measurement (see section 6 for details of angle kappa measurement).
4. Measure intermittent strabismus or phoria with cover test−near fixation
5. Measure intermittent strabismus or phoria with cover test−far fixation
NOTE: To measure intermittent ocular misalignment for far fixation, the angle kappa for each eye needs to be measured at least once. The app will automatically choose the latest angle kappa measure. If it is not available for either eye, the app will give a reminder to first obtain this measurement (see section 6 for details of angle kappa measurement).
6. Measure angle kappa
In this work, we describe the protocols to evaluate ocular alignment using a smartphone app that performs the photographic Hirschberg test. The interface of the app is shown in Figure 1. The users can choose to perform cover test or measure a patient with both eyes fixating at a target simultaneously, either at near or far fixation distances. Once the viewing conditions are determined depending on the test purposes, the users can follow the protocols and take a photo of the patient. After image processing, the app will show the analysis results to the users. As an example shown in Figure 2, the limbus boundaries (green circles) of the two eyes as well as the corneal reflection of the flash light (red dots) were detected correctly. This suggests that the ocular alignment measure (18.5Δ) shown below the image is not subject to image analysis error. In this particular case, the patient had left exotropia, which is obvious from the image as the corneal reflection offset was much larger in the left eye. However, the app does not report which eye is deviated, because in cases of small strabismus angle and unknown angle kappa, it would be unreliable for the app to determine the deviated eye. For comparison, an example without strabismus is shown in Figure 3. Figure 4 shows an example of erroneous limbus detection. While the detection of corneal reflection (small red circle) is correct, the green circle apparently does not match the limbus boundary. The test should be redone.
According to cover test on those patients, the range of strabismus angle was between 25Δ esotropia to 50Δ exotropia, with the smallest magnitude of strabismus angle being 6Δ. There were 10 patients with exotropia and 4 patients with esotropia. As the linear regression analysis showed (slope = 1.02, R2 = 0.94, p < 0.001), the app measurements of strabismus angles were consistent with clinical cover test measurements (Figure 5).
Figure 1: User interface of the strabismus testing app. Users can toggle on cover test and fixation distance. Under different conditions, the instructions given to the patient may be different, as described in the protocol. Please click here to view a larger version of this figure.
Figure 2: A case of left exptropia. This is the results shown to the users, who should verify the detection of limbus boundary and corneal reflection before reading the strabismus angle. If those image features are not detected correctly, the users should redo the test. Please click here to view a larger version of this figure.
Figure 3: An example under near fixation without cover test. The corneal reflection and eye center were aligned well in both eyes. Therefore the horizontal (HOR) ocular misalignment was almost zero, as the app reported. Please click here to view a larger version of this figure.
Figure 4: An example of erroneous limbus detection. Please click here to view a larger version of this figure.
Figure 5: Comparison of strabismus angle measurement using the app with clinical measurements done with covert testing (n = 14). Negative values indicate exotropic deviations, positive values indicate esotropic deviations. Overall, measurements with the app were consistent with the clinical measurements of strabismus. This figure has been modified from our previous publication12. Please click here to view a larger version of this figure.
A person without professional training can use the EyeTurn app to capture pictures of the eyes and obtain ocular alignment measurements, which might be interpreted by an eye care specialist onsite or remotely. The app only provides magnitude of the misalignment, rather than any interpretation or diagnosis. Eye care professionals such as optometrists or ophthalmologists should determine if the misalignment is significant or not, and make a diagnosis after considering other factors including the conditions under which the measurement was taken.
Taking good quality pictures is essential for the measurement. The camera should be placed at a position between two eyes. Being too far away from the midline can cause a difference in the image size between two eyes, and consequently result in measurement inaccuracy.
The limbus boundary is one of the key features that the app uses for locating eye position. Verifying the limbus boundary fitting (the green circle in results) is a crucial step. If the fitting appears to be inaccurate, the measurement will be subject to errors and the eye care professional will not be able to correctly interpret the test. Usually for patients with larger eye fissures, i.e., iris area being more revealed, the fitting will be robust and accurate. On the other hand, for patients with smaller eye fissures, which have only a small portion of the left and right boundaries revealed, the fitting may be prone to inaccuracies. In this situation, operators can ask the patients to open their eyes widely, or gently lift the eyelid wide open. The current version does not provide measurement of vertical misalignment, which will be implemented in future versions.
In addition to the promise for use in strabismus clinics, another potential application of the app is in vision screening. For prevention of amblyopia, the American Academy of Pediatrics strongly endorsed the development of cost-effective image-based screening as a means to extend screening to all children14. Red reflex method, which compares the brightness of the "red eye" flash artifact with the strabismus eye being a lighter or brighter red color, can detect both refractive error and strabismus, but cannot quantify the magnitude of the strabismus. Devices implementing the red flex method include Photoscreener and Vision Screener15,16. These photoscreeners have not been widely adopted by school districts, likely due to cost. Compared to standalone systems, modern smartphone cameras provide better value, improved accessibility, and rapidly improved and higher resolution cameras. Recently, there is an app that implements the red reflex method, GCK app17. The GCK app has some limitations in that it does not give a quantitative measurement of strabismus and requires more control of ambient lighting than the Hirschberg methods. The app presented in this article can be potentially an alternative or complementary solution for vision screening, because of its ease of use and equivalent accuracy with standard clinical measurement using prisms.
The authors have nothing to disclose.
This work was supported in part by NIH grant R44EY025902 and by the Mass Eye & Ear Curing Kids Grant.