Diagnosis, assessment and management of nystagmus in childhood

Waveform characterisation and comparison of nystagmus eye-tracking signals

OBJECTIVE

Pathological nystagmus is a symptom of oculomotor disease where the eyes oscillate involuntarily. The underlying cause of the nystagmus and the characteristics of the oscillatory eye movements are patient specific. An important part of clinical assessment in nystagmus patients is therefore to characterise different recorded eye-tracking signals, i.e. waveforms.

APPROACH

A method for characterisation of the nystagmus waveform morphology is proposed. The method extracts local morphologic characteristics based on a sinusoidal model, and clusters these into a description of the complete signal. The clusters are used to characterise and compare recordings within and between patients and tasks. New metrics are proposed that can measure waveform similarity at different scales; from short signal segments up to entire signals, both within and between patients.

MAIN RESULTS

The results show that the proposed method robustly can find the most prominent nystagmus waveforms in a recording. The method accurately identifies different eye movement patterns within and between patients and across different tasks.

SIGNIFICANCE

In conclusion, by allowing characterisation and comparison of nystagmus waveform patterns, the proposed method opens up for investigation and identification of the underlying condition in the individual patient, and for quantifying eye movements during tasks.

Modeling and quality assessment of nystagmus eye movements recorded using an eye-tracker

Mathematical modeling of nystagmus oscillations is a technique with applications in diagnostics, treatment evaluation, and acuity testing. Modeling is a powerful tool for the analysis of nystagmus oscillations but quality assessment of the input data is needed in order to avoid misinterpretation of the modeling results. In this work, we propose a signal quality metric for nystagmus waveforms, the normalized segment error (NSE). The NSE is based on the energy in the error signal between the observed oscillations and a reconstruction from a harmonic sinusoidal model called the normalized waveform model (NWM). A threshold for discrimination between nystagmus oscillations and disturbances is estimated using simulated signals and receiver operator characteristics (ROC). The ROC is optimized to find noisy segments and abrupt waveform and frequency changes in the simulated data that disturb the modeling. The discrimination threshold, 𝜖, obtained from the ROC analysis, is applied to real recordings of nystagmus data in order to determine whether a segment is of high quality or not. The NWM parameters from both the simulated dataset and the nystagmus recordings are analyzed for the two classes suggested by the threshold. The optimized 𝜖 yielded a true-positive rate and a false-positive rate of 0.97 and 0.07, respectively, for the simulated data. The results from the NWM parameter analysis show that they are consistent with the known values of the simulated signals, and that the method estimates similar model parameters when performing analysis of repeated recordings from one subject.

Characteristics of Acute Nystagmus in the Pediatric Emergency Department

OBJECTIVES

Acute nystagmus (AN) is an uncommon neurologic sign in children presenting to pediatric emergency departments. We described the epidemiology, clinical features, and underlying causes of AN in a large cohort of children, aiming at identifying features associated with higher risk of severe underlying urgent conditions (UCs).

METHODS

Clinical records of all patients aged 0 to 18 years presenting for AN to the pediatric emergency departments of 9 Italian hospitals in an 8-year period were retrospectively reviewed. Clinical and demographic features and the underlying causes were analyzed. A logistic regression model was applied to detect predictive variables associated with a higher risk of UCs.

RESULTS

A total of 206 patients with AN were included (male-to-female ratio: 1.01; mean age: 8 years 11 months). The most frequently associated symptoms were headache (43.2%) and vertigo (42.2%). Ataxia (17.5%) and strabismus (13.1%) were the most common neurologic signs. Migraine (25.7%) and vestibular disorders (14.1%) were the most common causes of AN. Idiopathic infantile nystagmus was the most common cause in infants <1 year of age. UCs accounted for 18.9% of all cases, mostly represented by brain tumors (8.3%). Accordant with the logistic model, cranial nerve deficits, ataxia, or strabismus were strongly associated with an underlying UC. Presence of vertigo or attribution of a nonurgent triage code was associated with a reduced risk of UCs.

CONCLUSIONS

AN should be considered an alarming finding in children given the risk of severe UCs. Cranial nerve palsy, ataxia, and strabismus should be considered red flags during the assessment of a child with AN.

Nystagmus and optical coherence tomography findings in CNGB3-associated achromatopsia

PURPOSE

To describe the nystagmus characteristics of subjects with molecularly confirmed CNGB3-associated achromatopsia and report the spectral domain optical coherence tomography (SD-OCT) findings in these individuals.

METHODS

Adults and children with CNGB3-achromatopsia underwent visual acuity testing, ocular motility assessments, video nystagmography, and SD-OCT imaging. Qualitative assessment of foveal structure was performed by grading SD-OCT images into one of five categories.

RESULTS

A total of 18 subjects (11 adults) were included. The majority demonstrated a phoria, with manifest strabismus present in only 3 subjects. The predominant nystagmus waveform within the cohort was pure pendular. Nine individuals demonstrated a mixture of waveforms. Nystagmus frequencies were 4-8 cycles/second, with no notable differences in eye movements between adults and children. SD-OCT imaging revealed a continuous ellipsoid zone (EZ) at the fovea in 2 subjects (grade 1) and EZ disruption (grade 2) in the remaining 16. Retinal structure characteristics were symmetrical in both eyes in each subject.

CONCLUSIONS

In our study cohort, nystagmus in CNGB3-associated achromatopsia had distinctive features, and the majority of subjects had retinal abnormalities at the fovea on SD-OCT. Early use of SD-OCT in the clinical work-up may eliminate the need for more invasive investigations, such as neuro-imaging.

A robust method for calibration of eye tracking data recorded during nystagmus

Eye tracking is a useful tool when studying the oscillatory eye movements associated with nystagmus. However, this oscillatory nature of nystagmus is problematic during calibration since it introduces uncertainty about where the person is actually looking. This renders comparisons between separate recordings unreliable. Still, the influence of the calibration protocol on eye movement data from people with nystagmus has not been thoroughly investigated. In this work, we propose a calibration method using Procrustes analysis in combination with an outlier correction algorithm, which is based on a model of the calibration data and on the geometry of the experimental setup. The proposed method is compared to previously used calibration polynomials in terms of accuracy, calibration plane distortion and waveform robustness. Six recordings of calibration data, validation data and optokinetic nystagmus data from people with nystagmus and seven recordings from a control group were included in the study. Fixation errors during the recording of calibration data from the healthy participants were introduced, simulating fixation errors caused by the oscillatory movements found in nystagmus data. The outlier correction algorithm improved the accuracy for all tested calibration methods. The accuracy and calibration plane distortion performance of the Procrustes analysis calibration method were similar to the top performing mapping functions for the simulated fixation errors. The performance in terms of waveform robustness was superior for the Procrustes analysis calibration compared to the other calibration methods. The overall performance of the Procrustes calibration methods was best for the datasets containing errors during the calibration.