Pupillary Light Reflex Parameters Research Articles

Machine learning approach for ambient-light-corrected parameters and the Pupil Reactivity (PuRe) score in smartphone-based pupillometry.

The pupillary light reflex (PLR) is the constriction of the pupil in response to light. The PLR in response to a pulse of light follows a complex waveform that can be characterized by several parameters. It is a sensitive marker of acute neurological deterioration, but is also sensitive to the background illumination in the environment in which it is measured. To detect a pathological change in the PLR, it is therefore necessary to separate the contributions of neuro-ophthalmic factors from ambient illumination. Illumination varies over several orders of magnitude and is difficult to control due to diurnal, seasonal, and location variations. We assessed the sensitivity of seven PLR parameters to differences in ambient light, using a smartphone-based pupillometer (AI Pupillometer, Solvemed Inc.). Nine subjects underwent 345 measurements in ambient conditions ranging from complete darkness (<5 lx) to bright lighting (≲10,000 lx). Lighting most strongly affected the initial pupil size, constriction amplitude, and velocity. Nonlinear models were fitted to find the correction function that maximally stabilized PLR parameters across different ambient light levels. Next, we demonstrated that the lighting-corrected parameters still discriminated reactive from unreactive pupils. Ten patients underwent PLR testing in an ophthalmology outpatient clinic setting following the administration of tropicamide eye drops, which rendered the pupils unreactive. The parameters corrected for lighting were combined as predictors in a machine learning model to produce a scalar value, the Pupil Reactivity (PuRe) score, which quantifies Pupil Reactivity on a scale 0-5 (0, non-reactive pupil; 0-3, abnormal/"sluggish" response; 3-5, normal/brisk response). The score discriminated unreactive pupils with 100% accuracy and was stable under changes in ambient illumination across four orders of magnitude. This is the first time that a correction method has been proposed to effectively mitigate the confounding influence of ambient light on PLR measurements, which could improve the reliability of pupillometric parameters both in pre-hospital and inpatient care settings. In particular, the PuRe score offers a robust measure of Pupil Reactivity directly applicable to clinical practice. Importantly, the formulae behind the score are openly available for the benefit of the clinical research community.

404 Mobile Pupillometry for Detection of Vasospasm, Delayed Cerebral Ischemia, and Neuro Exam Change in Subjects With Aneurysmal Subarachnoid Hemorrhage

INTRODUCTION: The pupillary light reflex (PLR) parameters are quantitative biomarkers that can be used to detect neurological disease. Vasospasm complicates aneurysmal subarachnoid hemorrhage (aSAH) trajectory, causing morbidity and mortality. METHODS: We prospectively collected PLR parameters from patients with aSAH admitted to a neurological intensive care unit twice daily using quantitative smartphone pupillometry recordings. PLR parameters included: Maximum pupil diameter (MAX), minimum pupil diameter (MIN), percent change in pupil diameter (CHANGE), latency in beginning of pupil constriction to light (LAT), mean constriction velocity (MCV), maximum constriction velocity (MAXCV), mean dilation velocity (MDV). One-tailed t-tests were performed to determine changes in PLR parameters between the following comparisons: (1) patients with and without radiographic vasospasm (defined by computed tomography angiography (CTA) or digital subtraction angiography (DSA)); (2) patients with and without delayed cerebral ischemia (DCI); and (3) patients with and without neurological exam change due to vasospasm. RESULTS: 42 total subjects were enrolled. For patients with (n = 13) and without (n = 29) radiographic vasospasm, significant PLR parameter differences were observed in: MAX (p = .024) and MIN (p = .0018). For patients with (n = 14) and without (n = 28) DCI, significant PLR parameter differences were observed in: CHANGE (p = .008). For patients with (n = 13) and without (n = 29) neurological exam change due to vasospasm, significant PLR parameter differences were observed in: MIN (34.7 vs 31.7, p = .014), CHANGE (20.6 vs 24.7, p = .025), and LAT (.36 vs .2, p = .0002). All other PLR parameters were not significantly different between groups for the three comparisons. CONCLUSIONS: Quantitative smartphone pupillometry may be of clinical use in the detection of radiographic vasospasm, DCI, and neuro exam changes via separate and distinct parameters from the PLR.

Abstract TP241: Correlation of Smartphone Pupillometry Parameters With NIH Stroke Scale and CT Perfusion Core to Penumbra Volume Ratio

Introduction: Objective pupillometry involves the quantitative measurement of the pupillary light reflex (PLR). We investigated changes in the PLR, National Institutes of Health Stroke Scale (NIHSS), and core infarct to penumbra volume ratio in acute large vessel occlusion (LVO). Methods: A smartphone pupillometry application was used. Subjects with LVO were enrolled prior to intervention. PLR parameters obtained included: maximum diameter (MAX), minimum diameter (MIN), percent change (CHANGE), latency (LAT), mean constriction velocity (MCV), maximum constriction velocity (MAXCV), and mean dilation velocity (MDV). Computed Tomography Perfusion (CTP) and NIHSS values were also obtained prior to intervention. Pearson correlation was performed between the PLR parameters, NIHSS, and CTP core infarct to penumbra volume ratio. This ratio was used instead of the traditional mismatch ratio due to the presence of 0 mL core infarcts and a desire to bound these at a ratio of zero instead of leaving them unbounded at an infinite ratio value for analysis. Results: N=22 subjects were enrolled with mean age 69 years. A significant negative correlation between NIHSS and CHANGE (p=0.04) as well as MCV (p=0.005), was observed (Table 1). A significant negative correlation between the core infarct to penumbra volume ratio on CTP and MAX (p=0.04), CHANGE (p&lt;0.001), and MCV (p=0.04) was observed (Table 2). Conclusions: This study illustrates the potential value of smartphone pupillometry as a bedside test in the early workup of LVO. Larger trials are needed.

Diagnostic accuracy test of quantitative pupillary light reflex as an indicator of increased intracranial pressure in traumatic brain injury patients: a cross-sectional study

Introduction: The gold standard of intracranial pressure (ICP) measurement is an invasive procedure of inserting ICP monitor and one of the limitations of its surrogate, ultrasonography-based (US) optic nerve sheath diameter (ONSD) measurement is operator-dependent. Quantitative pupillary light reflex (PLR) measurement provides objective data promisingly able to predict ICP elevation. The aim of this study was to evaluate diagnostic accuracy of PLR as an indicator of ICP elevation in traumatic brain injury (TBI) patients compared to US-ONSD measurement. Methods: This was a cross-sectional study involving moderate and severe TBI patients aged 18-65 years without any eye lesion, nor medication and illness that may influence PLR. Healthy volunteers were recruited as control group. ONSD and quantitative PLR measurements (baseline diameter, maximum constriction, constriction velocity, latency and amplitude) were assessed to both groups. The Student t-test or Mann-Whitney U-test was used to compare the ONSD and PLR between case and control group. Further analyses were done to determine the sensitivity, specificity and cut-off value of PLR compared to ONSD in case group. Result: ONSD measurements or parameters were significantly different between case and control group (p&lt;0.001), while all PLR parameters were significantly different (p&lt;0.005) except for right eye constriction latency. The baseline diameter of the right eye had the highest accuracy with cut-off value of &gt;3.9 mm (specificity of 100%, sensitivity of 50%). Other PLR components had variable in accuracy. Conclusion: The baseline diameter of the right eye was the most accurate PLR component as an indicator of ICP elevation, represented by ONSD.

Validation of a Smartphone Pupillometry Application in Diagnosing Severe Traumatic Brain Injury.

The pupillary light reflex (PLR) is an important biomarker for the detection and management of traumatic brain injury (TBI). We investigated the performance of PupilScreen, a smartphone-based pupillometry app, in classifying healthy control subjects and subjects with severe TBI in comparison to the current gold standard NeurOptics pupillometer (NPi-200 model with proprietary Neurological Pupil Index [NPi] TBI severity score). A total of 230 PLR video recordings taken using both the PupilScreen smartphone pupillometer and NeurOptics handheld device (NPi-200) pupillometer were collected from 33 subjects with severe TBI (sTBI) and 132 subjects who were healthy without self-reported neurological disease. Severe TBI status was determined by Glasgow Coma Scale (GCS) at the time of recording. The proprietary NPi score was collected from the NPi-200 pupillometer for each subject. Seven PLR curve morphological parameters were collected from the PupilScreen app for each subject. A comparison via t-test and via binary classification algorithm performance using NPi scores from the NPi-200 and PLR parameter data from the PupilScreen app was completed. This was used to determine how the frequently used NPi-200 proprietary NPi TBI severity score compares to the PupilScreen app in ability to distinguish between healthy and sTBI subjects. Binary classification models for this task were trained for the diagnosis of healthy or severe TBI using logistic regression, k-nearest neighbors, support vector machine, and random forest machine learning classification models. Overall classification accuracy, sensitivity, specificity, area under the curve, and F1 score values were calculated. Median GCS was 15 for the healthy cohort and 6 (interquartile range 2) for the severe TBI cohort. Smartphone app PLR parameters as well as NPi from the digital infrared pupillometer were significantly different between healthy and severe TBI cohorts; 33% of the study cohort had dark eye colors defined as brown eyes of varying shades. Across all classification models, the top performing PLR parameter combination for classifying subjects as healthy or sTBI for PupilScreen was maximum diameter, constriction velocity, maximum constriction velocity, and dilation velocity with accuracy, sensitivity, specificity, area under the curve (AUC), and F1 score of 87%, 85.9%, 88%, 0.869, and 0.85, respectively, in a random forest model. The proprietary NPi TBI severity score demonstrated greatest AUC value, F1 score, and sensitivity of 0.648, 0.567, and 50.9% respectively using a random forest classifier and greatest overall accuracy and specificity of 67.4% and 92.4% using a logistic regression model in the same classification task on the same dataset. The PupilScreen smartphone pupillometry app demonstrated binary healthy versus severe TBI classification ability greater than that of the NPi-200 proprietary NPi TBI severity score. These results may indicate the potential benefit of future study of this PupilScreen smartphone pupillometry application in comparison to the NPi-200 digital infrared pupillometer across the broader TBI spectrum, as well as in other neurological diseases.

Investigating the development of the autonomic nervous system in infancy through pupillometry.

We aim to investigate early developmental trajectories of the autonomic nervous system (ANS) as indexed by the pupillary light reflex (PLR) in infants with (i.e. preterm birth, feeding difficulties, or siblings of children with autism spectrum disorder) and without (controls) increased likelihood for atypical ANS development. We used eye-tracking to capture the PLR in 216 infants in a longitudinal follow-up study spanning 5 to 24months of age, and linear mixed models to investigate effects of age and group on three PLR parameters: baseline pupil diameter, latency to constriction and relative constriction amplitude. An increase with age was found in baseline pupil diameter (F(3,273.21) = 13.15, p < 0.001, [Formula: see text] = 0.13), latency to constriction (F(3,326.41) = 3.84, p = 0.010, [Formula: see text] = 0.03) and relative constriction amplitude(F(3,282.53) = 3.70, p = 0.012, [Formula: see text] = 0.04). Group differences were found for baseline pupil diameter (F(3,235.91) = 9.40, p < 0.001, [Formula: see text] = 0.11), with larger diameter in preterms and siblings than in controls, and for latency to constriction (F(3,237.10) = 3.48, p = 0.017, [Formula: see text] = 0.04), with preterms having a longer latency than controls. The results align with previous evidence, with development over time that could be explained by ANS maturation. To better understand the cause of the group differences, further research in a larger sample is necessary, combining pupillometry with other measures to further validate its value.

Abstract TP49: The Pupillary Light Reflex Detects Large Vessel Occlusion

Introduction: The pupillary light reflex (PLR) is a well-validated biomarker for neurologic monitoring and a decision-making tool for traumatic brain injury patients. We studied a machine learning-based mobile pupillometry platform in patients with acute ischemic stroke (AIS) with a large-vessel occlusion (LVO) prior to thrombectomy, compared to healthy volunteers. Methods: Pupillometry measurements were conducted with a mobile pupillometry platform (PupilScreen) and a digital infrared pupillometer (NeurOptics) for both pre-thrombectomy AIS subjects and healthy volunteers at an academic medical center. To correct for subject age differences, comparisons used the absolute inter-eye difference in each parameter for each subject by measuring the right:left (R:L) eye ratio absolute distance away from 1. Inter-eye difference means across subjects between AIS and healthy cohorts were analyzed for PLR changes in the presence of acute LVO using a t-test for independent means. Results: Seven AIS patients (4 female, 3 male; 1 Hispanic, 6 Caucasian; mean age 60.9 years) and 32 healthy patients (19 female, 13 male; 1 Hispanic, 2 African American, 3 Native American, 5 Asian, 21 Caucasian; mean age 34.4) were enrolled. All LVOs were of the middle cerebral artery, with 3 on the left and 4 on the right. NPi value was above 3 (briskly reactive) for all subjects. However, the smartphone pupillometer demonstrated a statistically significant (p&lt;0.05) increase in mean inter-eye differences for maximum diameter (mean inter-eye difference of 0.14 vs 0.03), minimum diameter (0.21 vs 0.03), and percent change (0.23 vs 0.05). The mean inter-eye differences were lateralized to the side of the LVO for maximum and minimum diameters (right LVO, max pre vs post R:L 0.95 vs 1.0, min 0.91 vs 0.98) (left LVO, max 0.98 vs 0.96, min 1.15 vs 0.93), and were increased in latency and mean constriction velocity whereas they were decreased in maximum constriction velocity and mean dilation velocity, but this was not statistically significant in this cohort. Conclusions: Patients with AIS from LVO demonstrate inter-eye differences in PLR parameters, and mobile pupillometry could be used as a pre-intervention biomarker of AIS in future study. Further investigation in a larger cohort is necessary.

Recommendation of using both initial pupil size and constriction latency in pupillary light reflex as objective indicators reflecting subacute pain-related mental fatigue

A previous study examining clinical subacute pain models under different methodological conditions showed that pain-induced mental fatigue can be associated with decreased initial pupil size (INIT)/shortened constriction latency (LAT) in the pupillary light reflex (PLR). We aimed to investigate the potential of INIT/LAT as objective indicators reflecting mental fatigue under the same methodological conditions. We recruited 118 patients planning to undergo three types of representative otolaryngological head and neck surgery procedures. We used the numerical rating scale (NRS) to assess subjective pain intensity and two mental fatigue-related mood categories of the Profile of Mood States, as well as INIT and LAT measurements (1) in the afternoon one day before surgery (pre1-surgery), (2) in the morning of the day of surgery (pre2-surgery), and (3) in the morning of the day following surgery (post-surgery). We assessed time point-dependent changes using one- or two-way analysis of variance, as well as responses of PLR parameters to mental fatigue using linear mixed-effects models (LMMs). As a result, NRS scores, the two mood categories, as well as LAT and INIT, showed significant time point-dependent changes. In post-hoc analyses, only INIT showed significant changes between the two pre-surgery time points. Thus, INIT values fluctuated even under pain-free conditions due to differences in the time of the day. LMMs demonstrated decreased INIT/shortened LAT related to mental fatigue. All surgical groups showed similar associations between mental fatigue and INIT/LAT findings. As each parameter has advantages and disadvantages, it is recommended to use both INIT and LAT as the indicators.

Age‐related changes in autonomic response: A pupillary light reflex and heart rate variability study

AbstractBackgroundAutonomic nervous system (ANS) dysfunction has been implicated with cardiovascular diseases, sudden‐cardiac‐death, and aging. The pupillary light reflex (PLR) and heart rate variability (HRV) are noninvasive tools of autonomic evaluation. However, the former remains underutilized in clinical practice.PurposeWe investigated the relationship between PLR, HRV, and aging to determine the normal distribution of age‐adjusted PLR and HRV measurements and to determine which method is best correlated with age.MethodsHealthy participants aged 18–65 years were recruited. Following a dark adaptation period, pupillary reactivity parameters were collected using an automated, commercial pupillometer. HRV measurements were derived using a high‐resolution electrocardiogram. Correlations of PLR and HRV parameters to age were computed using linear‐regression analysis.ResultsA total of 111 healthy participants were included. Older age was correlated with lower maximum and minimum pupillary diameters following dark adaptation and illumination (R = −0.51, p &lt; 0.001 and R = −0.47, p &lt; 0.001, respectively). Average constriction and dilatation velocity were correlated with age (R = 0.33, p &lt; 0.001 and R = −0.21, p = 0.025, respectively). HRV parameters were also associated inversely with age (SDNN; R = −0.31, p &lt; 0.001 and RMSSD; R = −0.33, p &lt; 0.001). Other parameters showed lower significance levels.ConclusionPupillary light reflex measurements demonstrated stronger age correlation than short‐term HRV time‐domain indices. Due to its merit in depicting normal age‐related ANS changes, PLR can be utilized to differentiate between pathological and physiological deviations from age‐adjusted norms, seemingly better than HRV. Further research is warranted on incorporating PLR‐based ANS dysfunction evaluation and monitoring the increasingly aging population.

Decreased initial pupil size and shortened constriction latency due to negative mood states and mental fatigue in clinical subacute pain models

Previous clinical studies on pupillary light reflex parameters showed shortened constriction latency (LAT) and decreased initial pupil size (INIT) due to increased numeric rating scale (NRS) scores, reflecting subjective pain intensity, in subacute pain models. As noxious stimulation causes pupil dilation, decreased INIT (pupil constriction) was an unexpected finding. Pain-related negative moods and mental fatigue might have caused this finding. We aimed to investigate how psychological states affect LAT/INIT in two subacute pain models. For psychological assessment, we used the Profile of Mood States (POMS) and calculated the total mood disturbance (TMD) score using six mood categories. We collected data on NRS scores, POMS-related scores, LAT, and INIT through a longitudinal study. Using linear mixed-effects models, we evaluated the association of TMD scores with NRS scores, LAT, and INIT. Furthermore, we performed subanalyses targeting two mood categories that represent mental fatigue: Fatigue–Inertia (Fatigue) and Vigor–Activity (Vigor). We investigated whether obtained results can be identical in both models. In total, 141 patients were enrolled. Increased NRS scores were associated with increased TMD/Fatigue scores and decreased Vigor scores, being associated with shortened LAT/decreased INIT in both models. Score changes in NRS, TMD, Fatigue, and Vigor indicated that increased subjective pain intensity can be associated with negative mood states, especially mental fatigue. This study revealed that negative moods and mental fatigue induced by acute pain can be associated with shortened LAT/decreased INIT in both models, indicating clinical potential of LAT/INIT as objective indicators reflecting the psychological states for pain assessment.

Assessment of Combination of Automated Pupillometry and Heart Rate Variability to Detect Driving Fatigue.

ObjectivesApproximately 20~30% of all traffic accidents are caused by fatigue driving. However, limited practicability remains a barrier for the real application of available techniques to detect driving fatigue. Use of pupillary light reflex (PLR) may be potentially effective for driving fatigue detection.MethodsA 90 min monotonous simulated driving task was utilized to induce driving fatigue. During the task, PLR measurements were performed at baseline and at an interval of 30 min. Subjective rating scales, heart rate variability (HRV) were monitored simultaneously.ResultsThirty-two healthy volunteers in China participated in our study. Based on the results of subjective evaluation and behavioral performances, driving fatigue was verified to be successfully induced by a simulated driving task. Significant variations of PLR and HRV parameters were observed, which also showed significant relevance with the change in Karolinska Sleepiness Scale at several timepoints (|r| = 0.55 ~ 0.72, P < 0.001). Furthermore, PLR variations had excellent ability to detect driving fatigue with high sensitivity and specificity, of which maximum constriction velocity variations achieved a sensitivity of 85.00% and specificity of 72.34% for driving fatigue detection, vs. 82.50 and 78.72% with a combination of HRV variations, a nonsignificant difference (AUC = 0.835, 0.872, P > 0.05).ConclusionsPupillary light reflex variation may be a potential indicator in the detection of driving fatigue, achieving a comparative performance compared with the combination with heart rate variability. Further work may be involved in developing a commercialized driving fatigue detection system based on pupillary parameters.

Clinical potential of pupillary light reflex parameters as objective indicators reflecting chronic rhinosinusitis-specific quality of life: a 12-month prospective longitudinal study

Pupillary light reflex (PLR) and heart rate variability (HRV) parameters can be objective indicators of chronic rhinosinusitis (CRS) status from the viewpoint of autonomic nervous system activity. This study aimed to establish objective indicators for CRS using the 22-item Sino-Nasal Outcome Test (SNOT-22) and PLR/HRV parameters. Sixty-seven patients were prospectively and longitudinally followed up after surgical treatment. We investigated changes in SNOT-22 scores, representing CRS-specific quality of life (QOL). We prepared two models: linear regression model adjusting clinical factors as predictor variables (model 1) and linear mixed-effects model adjusting clinical factors and among-individual variability (model 2). We compared Akaike’s information criterion (AIC) values and regression coefficients. The model with lower AIC values was defined as the better-fit model. Model 2 showed lower AIC values in all parameters (better-fit model). Three parameters showed opposite results between the two models. The better-fit models showed significances in the five PLR parameters but not in any HRV parameters. Among these PLR parameters, constriction latency can be the most robust indicator because of the narrowest 95% confidence intervals. Adjusting the among-individual variability while investigating clinical potential of PLR/HRV parameters to reflect CRS-specific QOL can improve the model fit, thereby reaching robust conclusions from obtained data.

A haploscope based binocular pupillometer system to quantify the dynamics of direct and consensual Pupillary Light Reflex

This study described the development of a haploscope-based pupillometer for the parametrization of the Pupillary Light Reflex (PLR), and its feasibility in a set of 30 healthy subjects (light or dark-colored irides) and five patients diagnosed with Relative Afferent Pupillary Defect (RAPD). Our supplementary aim focused on evaluating the influence of iris colour on the PLR to decide whether a difference in PLR parameters should be anticipated when this system is used across ethnicities. All the participants underwent a customized pupillometry protocol and the generated pupil traces, captured by an eye tracker, were analyzed using exponential fits to derive PLR parameters. A Pupil Response Symmetry (PRS) coefficient was calculated to predict the presence of RAPD. The mean (SD) Initial PD during dilation (3.2 (0.5) mm) and the minimum PD during constriction (2.9 (0.4) mm) in the light iris group had a statistically significant (p < 0.001) higher magnitude compared to the dark iris group. The normal limits of the PRS coefficient ranged from − 0.20 to + 1.07 and all RAPD patients were outside the calculated normal limits. This proposed system, analysis strategies, and the tested metrics showed good short-term repeatability and the potential in detecting pupil abnormalities in neuro-ophthalmic diseases.

The pupillary light reflex (PLR) as a marker for the ability to work or drive \u2013 a feasibility study

BackgroundThe PLR (pupillary light reflex) can be a marker for pathological medical conditions, such as neurodegenerative or mental health disorders and diseases as well as marker for physiological alterations, such as age, sex or iris color. PLR alterations have been described in people after alcohol consumption, as well. However, the effect of sleep deprivation on PLR parameters is still under debate.MethodsThe aim of this study was to investigate the feasibility of PLR measurements in sleep-deprived and alcohol-exposed participants. In addition, we wanted to identify PLR parameters that were altered by sleep deprivation and alcohol exposure.ResultsAltogether n = 50 participants have been included in this study. Differences in the PLR parameters initial diameter (dinit), latency (∆tlat), acceleration (∆ta), contraction velocity (ϑcon), quarter dilatation velocity (ϑ1/4dil), half dilatation time (∆t1/2), and the line integral (L(0.3500)) have been evaluated between baseline, sleep deprivation, as well as alcohol exposure. In a generalized linear mixed models design, we could observe statistically significant associations between the type of exposure and the PLR parameters half dilatation time and half dilatation time after the first light pulse (all p < 0.05). The participants’ latency showed a significant association in dependence of the type of exposure after the second light pulse (p < 0.05).ConclusionOur study delivers first promising results to further develop devices that may identify conditions that impair the ability to work or drive.

Clinical factors affecting pupillary light reflex parameters: a single-centre, cross-sectional study.

To evaluate the effects of stimulus intensity, aging, sex, smoking and eye symmetry on pupillary light reflex (PLR) parameters. We evaluated 2812 eyes from 1406subjects in a single-centre, cross-sectional study. PLR data were collected using four different stimulus intensities. We prepared two models for each of the eight PLR parameters, and defined the model with the lowest values of Akaike's information criterion (AIC) as being the best-fit. Model A was a linear regression model without adjustment for among-individual variability, while the Model B linear mixed-effects models (LMMs) were adjusted for among-individual variability. The regression coefficients of the two models were compared. Model B showed the lowest AIC values for all parameters and the best fit. For light stimulus intensity, age and eye symmetry, the two models yielded similar results for all PLR parameters. For sex and smoking index, some PLR parameters showed the opposite results, i.e., Model A showed significant effects while Model B did not. These results indicate that light stimulus intensity, aging, sex, smoking and eye symmetry are factors that affect PLR parameters. These should be adjusted when evaluating the clinical potential of PLR as a diagnostic tool. In addition, adjusting for among-individual variability due to LMMs can improve the model fit and reduce false positives. This can reveal the association between clinical factors and PLR parameters with increased accuracy.

Pupillary light reflex in ethambutol-induced optic neuropathy

We evaluated changes in the pupillary light reflex (PLR) of ethambutol (EMB)-induced optic neuropathy and analyzed the correlations between PLR parameters and other structural changes in EMB-induced optic neuropathy. This retrospective, observational, case–control study involved thirty-two eyes of 17 patients with EMB-induced optic neuropathy (EON group), sixty eyes of 60 patients without EMB-induced optic neuropathy (non-EON group) while taking ethambutol, and forty-five eyes of 45 normal controls. PLR was measured by digital pupillometry. The clinical characteristics, optical coherence tomography measurements and PLR parameters including pupil diameter, constriction latency, constriction ratio/velocity, and dilation velocity were noted. The differences in PLR measurements were compared among the three groups. Correlations between PLR parameters and other structural parameters in EMB-induced optic neuropathy were evaluated. The pupillary constriction ratio, constriction and dilation velocities were significantly reduced in the EON group compared to the non-EON group and controls (all P < 0.05). In EMB-induced optic neuropathy, average outer macular ganglion cell layer (mGCL) thickness showed a significant correlation with the pupillary constriction ratio (ß = 4.14, P = 0.003) and maximal constriction velocity (ß = 1.08, P < 0.001). This study confirmed that pupillary constriction and dilation velocities were significantly decreased in patients with EMB-induced optic neuropathy, compared to normal controls. Digital pupillometry may be a useful tool in the evaluation of EMB-induced optic neuropathy.

Assessment of pupillary light reflex using dynamic pupillometry in laser-treated eyes with retinal vein occlusion.

This study aims to evaluate the pupillary light reflex measured with dynamic pupillometry in patients who underwent retinal laser photocoagulation due to unilateral retinal vein occlusion (RVO). A total of 48 patients with unilateral RVO were included in the study. Thirty-four patients had undergone retinal laser photocoagulation while the remaining 14 patients that did not undergo laser treatment were observed for control purposes. Of the laser-treated eyes, 14 eyes (41.2%) had central RVO (CRVO) and 20 eyes (58.8%) had branch RVO (BRVO). Among the 14 patients with RVO without laser treatment, nine eyes (64.3%) had CRVO and five eyes (35.7%) had BRVO. Pupillary light reflexes were assessed with dynamic pupillometry (MonPackOne®; Metrovision, France). The parameters of the eyes with RVO were compared with that of fellow healthy eyes. Mean patient age was 65.8 ± 10.4 years and median time after photocoagulation was 25.5 months. Eyes that received laser photocoagulation had lower pupil contraction amplitude (p = 0.037), prolonged contraction latency (p = 0.027), slower contraction velocity (p = 0.043), and slower dilation velocity (p < 0.001) compared to healthy fellow eyes. Subgroup analysis revealed that eyes with CRVO had lower contraction amplitude (p = 0.013) and slower dilation velocity (p = 0.003), and eyes with BRVO had slower dilation velocity (p = 0.003). Non-laser-treated eyes with RVO revealed no significant difference in any of the pupillary light reflex parameters compared to fellow eyes. Laser-treated eyes with RVO demonstrated changes in pupillary light reflex parameters including reduced contraction amplitude, prolonged contraction latency, and slower contraction and dilation velocities measured with dynamic pupillometry.

A longitudinal study of pupillary light reflex in 6- to 24-month children

Pupillary light reflex (PLR) is an involuntary response where the pupil size changes with luminance. Studies have shown that PLR response was altered in children with autism spectrum disorders (ASDs) and other neurological disorders. However, PLR in infants and toddlers is still understudied. We conducted a longitudinal study to investigate PLR in children of 6–24 months using a remote pupillography device. The participants are categorized into two groups. The ‘high risk’ (HR) group includes children with one or more siblings diagnosed with ASDs; whereas the ‘low risk’ (LR) group includes children without an ASD diagnosis in the family history. The participants’ PLR was measured every six months until the age of 24 months. The results indicated a significant age effect in multiple PLR parameters including resting pupil radius, minimal pupil radius, relative constriction, latency, and response time. In addition, the HR group had a significantly larger resting and minimal pupil size than the LR group. The experimental data acquired in this study revealed not only general age-related PLR changes in infants and toddlers, but also different PLRs in children with a higher risk of ASD.

Automating, Analyzing and Improving Pupillometry with Machine Learning Algorithms

The investigation of the pupillary light reflex (PLR) is a well-known method to provide information about the functionality of the autonomic nervous system. Pupillometry, a non-invasive technique, was applied to study the PLR alterations in a new, schizophrenia-like rat substrain, named WISKET. The pupil responses to light impulses were recorded with an infrared camera; the videos were automatically processed and features were extracted. Besides the classical statistical analysis (ANOVA), feature selection and classification were applied to reveal the significant differences in the PLR parameters between the control and WISKET animals. Based on these results, the disadvantages of this method were analyzed and the measurement process was redesigned and improved. The automated pupil detection method has also been adapted to the new videos. 2564 images were annotated manually and used to train a fully-convolutional neural network to produce pupil mask images. The method was evaluated on 329 test images and achieved 4% median relative error. With the new setup, the pupil detection became reliable and the new data acquisition offers robustness to the experiments.

Technical Note: Effects of age and confinement on pupillary light reflex in sows1

Pupillary reflex has been used as a method to examine psychological problems in human clinics and mental disease research. Intensive animal farming has been shown to lead to chronic stress resulting in depression; however, comparing with humans we lack an effective clinical method to clinically inspect these psychological problems in animals. The goal of this study was to investigate the effect of age and housing conditions (confined crates vs. group pens) on pupillary light reflex (PLR) of sows to explore whether PLR can be used as an effective way to measure the psychological state of farm animals. In total, 270 pregnant sows were selected for PLR testing and divided into 6 treatments (45 sows per treatment) of 2 different environments (group-housed pen and confined gestation crates) and 3 parities (first, third, and fifth parities). Six selected pupil parameters: 1) latency of the pupil constriction onset (LAT); 2) the percent of the constriction (CON); 3) average constriction velocity (ACV); 4) maximum constriction velocity (MCV); 5) average dilation velocity (ADV); and 6) time of 75% recovery after constriction (T75) were examined. The results showed that there was no difference found in these PLR parameters between the breeds (P > 0.05) but the significant effects were found on LAT, CON, ACV, and MCV by age (P < 0.01). The group-housed sows had significantly higher CON, ACV, and MCV than those in the confined crates (P < 0.05). In conclusion, the pupillary light reflex of the sows was not affected by breed but by age. The results also indicate that some of PLR parameters were sensitive to housing conditions and suggest that ACV and MCV have potential to be sensitive indicators in relation to the psychological problem of sows.