Detection of Parkinson's Disease Through Automated Pupil Tracking of the Post-illumination Pupillary Response

Melanopsin retinal ganglion cell function in Alzheimer's vs. Parkinson's disease an exploratory meta-analysis and review of pupillometry protocols

BACKGROUND

Neurodegenerative diseases share retinal abnormalities. Chromatic pupillometry allows in vivo assessment of photoreceptor functional integrity, including melanopsin-expressing retinal ganglion cells. This exploratory meta-analysis assesses retinal photoreceptor functionality in Alzheimer's vs. Parkinson's disease and conducts an in-depth review of applied pupillometric protocols.

METHODS

Literature reviews on PubMed and Scopus from 1991 to August 2023 identified chromatic pupillometry studies on Alzheimer's disease (AD; n = 42 patients from 2 studies) and Parkinson's disease (PD; n = 66 from 3 studies). Additionally, a pre-AD study (n = 10) and an isolated REM Sleep Behavior Disorder study (iRBD; n = 10) were found, but their results were not included in the meta-analysis statistics.

RESULTS

Melanopsin-mediated post-illumination pupil response to blue light was not significantly impaired in Alzheimer's (weighted mean difference = -1.54, 95% CI: 4.57 to 1.49, z = -1.00, p = 0.319) but was in Parkinson's (weighted mean difference = -9.14, 95% CI: 14.19 to -4.08, z = -3.54, p < 0.001). Other pupil light reflex metrics showed no significant differences compared to controls. Studies adhered to international standards of pupillometry with moderate to low bias. All studies used full-field stimulation. Alzheimer's studies used direct while Parkinson's studies used consensual measurement. Notably, studies did not control for circadian timing and Parkinson's patients were on dopaminergic treatment.

CONCLUSION AND RELEVANCE

Results affirm chromatic pupillometry as a useful method to assess melanopsin-related retinal cell dysfunction in Parkinson's but not in Alzheimer's disease. While adhering to international standards, future studies may analyze the effects of local field stimulation, dopaminergic treatment, and longitudinal design to elucidate melanopsin dysfunction in Parkinson's disease.

Chromatic pupillometry for evaluating melanopsin retinal ganglion cell function in Alzheimer's disease and other neurodegenerative disorders: a review

The evaluation of pupillary light reflex (PLR) by chromatic pupillometry may provide a unique insight into specific photoreceptor functions. Chromatic pupillometry refers to evaluating PLR to different wavelengths and intensities of light in order to differentiate outer/inner retinal photoreceptor contributions to the PLR. Different protocols have been tested and are now established to assess in-vivo PLR contribution mediated by melanopsin retinal ganglion cells (mRGCs). These intrinsically photosensitive photoreceptors modulate the non-image-forming functions of the eye, which are mainly the circadian photoentrainment and PLR, via projections to the hypothalamic suprachiasmatic and olivary pretectal nucleus, respectively. In this context, chromatic pupillometry has been used as an alternative and non-invasive tool to evaluate the mRGC system in several clinical settings, including hereditary optic neuropathies, glaucoma, and neurodegenerative disorders such as Parkinson's disease (PD), idiopathic/isolated rapid eye movement sleep behavior disorder (iRBD), and Alzheimer's disease (AD). The purpose of this article is to review the key steps of chromatic pupillometry protocols for studying in-vivo mRGC-system functionality and provide the main findings of this technique in the research setting on neurodegeneration. mRGC-dependent pupillary responses are short-wavelength sensitive, have a higher threshold of activation, and are much slower and sustained compared with rod- and cone-mediated responses, driving the tonic component of the PLR during exposure to high-irradiance and continuous light stimulus. Thus, mRGCs contribute mainly to the tonic component of the post-illumination pupil response (PIPR) to bright blue light flash that persists after light stimulation is switched off. Given the role of mRGCs in circadian photoentrainment, the use of chromatic pupillometry to perform a functional evaluation of mRGcs may be proposed as an early biomarker of mRGC-dysfunction in neurodegenerative disorders characterized by circadian and/or sleep dysfunction such as AD, PD, and its prodromal phase iRBD. The evaluation by chromatic pupillometry of mRGC-system functionality may lay the groundwork for a new, easily accessible biomarker that can be exploited also as the starting point for future longitudinal cohort studies aimed at stratifying the risk of conversion in these disorders.

Retinal Changes in Parkinson's Disease: A Non-invasive Biomarker for Early Diagnosis

Parkinson's disease (PD) is caused due to degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc) which leads to the depletion of dopamine in the body. The lack of dopamine is mainly due to aggregation of misfolded α-synuclein which causes motor impairment in PD. Dopamine is also required for normal retinal function and the light-dark vision cycle. Misfolded α-synuclein present in inner retinal layers causes vision-associated problems in PD patients. Hence, individuals with PD also experience structural and functional changes in the retina. Mutation in LRRK2, PARK2, PARK7, PINK1, or SNCA genes and mitochondria dysfunction also play a role in the pathophysiology of PD. In this review, we discussed the different etiologies which lead to PD and future prospects of employing non-invasive techniques and retinal changes to diagnose the onset of PD earlier.

Application of Pupillometry in Neurocritical Patients

Pupillary light reflex (PLR) assessment is a crucial examination for evaluating brainstem function, particularly in patients with acute brain injury and neurosurgical conditions. The PLR is controlled by neural pathways modulated by both the sympathetic and parasympathetic nervous systems. Altered PLR is a strong predictor of adverse outcomes after traumatic and ischemic brain injuries. However, the assessment of PLR needs to take many factors into account since it can be modulated by various medications, alcohol consumption, and neurodegenerative diseases. The development of devices capable of measuring pupil size and assessing PLR quantitatively has revolutionized the non-invasive neurological examination. Automated pupillometry, which is more accurate and precise, is widely used in diverse clinical situations. This review presents our current understanding of the anatomical and physiological basis of the PLR and the application of automated pupillometry in managing neurocritical patients. We also discuss new technologies that are being developed, such as smartphone-based pupillometry devices, which are particularly beneficial in low-resource settings.

Machine Learning and Eye Movements Give Insights into Neurodegenerative Disease Mechanisms

Humans are a vision-dominated species; what we perceive depends on where we look. Therefore, eye movements (EMs) are essential to our interactions with the environment, and experimental findings show EMs are affected in neurodegenerative disorders (ND). This could be a reason for some cognitive and movement disorders in ND. Therefore, we aim to establish whether changes in EM-evoked responses can tell us about the progression of ND, such as Alzheimer's (AD) and Parkinson's diseases (PD), in different stages. In the present review, we have analyzed the results of psychological, neurological, and EM (saccades, antisaccades, pursuit) tests to predict disease progression with machine learning (ML) methods. Thanks to ML algorithms, from the high-dimensional parameter space, we were able to find significant EM changes related to ND symptoms that gave us insights into ND mechanisms. The predictive algorithms described use various approaches, including granular computing, Naive Bayes, Decision Trees/Tables, logistic regression, C-/Linear SVC, KNC, and Random Forest. We demonstrated that EM is a robust biomarker for assessing symptom progression in PD and AD. There are navigation problems in 3D space in both diseases. Consequently, we investigated EM experiments in the virtual space and how they may help find neurodegeneration-related brain changes, e.g., related to place or/and orientation problems. In conclusion, EM parameters with clinical symptoms are powerful precision instruments that, in addition to their potential for predictions of ND progression with the help of ML, could be used to indicate the different preclinical stages of both diseases.

Memory Deficit in Patients With Temporal Lobe Epilepsy: Evidence From Eye Tracking Technology

Objective: To explore quantitative measurements of the visual attention and neuroelectrophysiological relevance of memory deficits in temporal lobe epilepsy (TLE) by eye tracking and electroencephalography (EEG).

Methods: Thirty-four TLE patients and twenty-eight healthy controls were invited to complete neurobehavioral assessments, cognitive oculomotor tasks, and 24-h video EEG (VEEG) recordings using an automated computer-based memory assessment platform with an eye tracker. Visit counts, visit time, and time of first fixation on areas of interest (AOIs) were recorded and analyzed in combination with interictal epileptic discharge (IED) characteristics from the bilateral temporal lobes.

Results: The TLE patients had significantly worse Wechsler Digit Span scores [F(1, 58) = 7.49, p = 0.008]. In the Short-Term Memory Game with eye tracking, TLE patients took a longer time to find the memorized items [F(1, 57) = 17.30, p < 0.001]. They had longer first fixation [F(1, 57) = 4.06, p = 0.049] and more visit counts [F(1, 57) = 7.58, p = 0.008] on the target during the recall. Furthermore, the performance of the patients in the Digit Span task was negatively correlated with the total number of IEDs [r(28) = −0.463, p = 0.013] and the number of spikes per sleep cycle [r(28) = −0.420, p = 0.026].

Conclusion: Eye tracking appears to be a quantitative, objective measure of memory evaluation, demonstrating memory retrieval deficits but preserved visual attention in TLE patients. Nocturnal temporal lobe IEDs are closely associated with memory performance, which might be the electrophysiological mechanism for memory impairment in TLE.

Pupil Size Prediction Techniques Based on Convolution Neural Network

The size of one’s pupil can indicate one’s physical condition and mental state. When we search related papers about AI and the pupil, most studies focused on eye-tracking. This paper proposes an algorithm that can calculate pupil size based on a convolution neural network (CNN). Usually, the shape of the pupil is not round, and 50% of pupils can be calculated using ellipses as the best fitting shapes. This paper uses the major and minor axes of an ellipse to represent the size of pupils and uses the two parameters as the output of the network. Regarding the input of the network, the dataset is in video format (continuous frames). Taking each frame from the videos and using these to train the CNN model may cause overfitting since the images are too similar. This study used data augmentation and calculated the structural similarity to ensure that the images had a certain degree of difference to avoid this problem. For optimizing the network structure, this study compared the mean error with changes in the depth of the network and the field of view (FOV) of the convolution filter. The result shows that both deepening the network and widening the FOV of the convolution filter can reduce the mean error. According to the results, the mean error of the pupil length is 5.437% and the pupil area is 10.57%. It can operate in low-cost mobile embedded systems at 35 frames per second, demonstrating that low-cost designs can be used for pupil size prediction.

PupilEXT: Flexible Open-Source Platform for High-Resolution Pupillometry in Vision Research

The human pupil behavior has gained increased attention due to the discovery of the intrinsically photosensitive retinal ganglion cells and the afferent pupil control path's role as a biomarker for cognitive processes. Diameter changes in the range of 10-2 mm are of interest, requiring reliable and characterized measurement equipment to accurately detect neurocognitive effects on the pupil. Mostly commercial solutions are used as measurement devices in pupillometry which is associated with high investments. Moreover, commercial systems rely on closed software, restricting conclusions about the used pupil-tracking algorithms. Here, we developed an open-source pupillometry platform consisting of hardware and software competitive with high-end commercial stereo eye-tracking systems. Our goal was to make a professional remote pupil measurement pipeline for laboratory conditions accessible for everyone. This work's core outcome is an integrated cross-platform (macOS, Windows and Linux) pupillometry software called PupilEXT, featuring a user-friendly graphical interface covering the relevant requirements of professional pupil response research. We offer a selection of six state-of-the-art open-source pupil detection algorithms (Starburst, Swirski, ExCuSe, ElSe, PuRe and PuReST) to perform the pupil measurement. A developed 120-fps pupillometry demo system was able to achieve a calibration accuracy of 0.003 mm and an averaged temporal pupil measurement detection accuracy of 0.0059 mm in stereo mode. The PupilEXT software has extended features in pupil detection, measurement validation, image acquisition, data acquisition, offline pupil measurement, camera calibration, stereo vision, data visualization and system independence, all combined in a single open-source interface, available at https://github.com/openPupil/Open-PupilEXT.

Variable abnormality of the melanopsin-derived portion of the pupillary light reflex (PLR) in patients with Parkinson's disease (PD) and parkinsonism features

OBJECTIVES

Ascertain and quantify abnormality of the melanopsin-derived portion of the pupillary light reflex (PLR) in patients with Parkinson's disease (PD) and parkinsonism features based on a statistical predictive modeling strategy for PLR classification.

METHODS

Exploratory cohort analysis of pupillary kinetics in non-disease controls, PD subjects, and subjects with parkinsonism features using chromatic pupillometry. Receiver operating characteristic (ROC) curve interpretation of pupillary changes consistent with abnormality of intrinsically photosensitive retinal ganglion cells (ipRGCs) was employed using a thresholding algorithm to discriminate pupillary abnormality between study groups.

RESULTS

Twenty-eight subjects were enrolled, including 17 PD subjects (age range 64-85, mean 70.65) and nine controls (age range 48-95, mean 63.89). Two subjects were described as demonstrating parkinsonism symptoms due to presumed Lewy body dementia and motor system atrophy (MSA) respectively. On aggregate analysis, PD subjects demonstrated abnormal but variable pupillary dynamics suggestive of ipRGC abnormality. Subjects with parkinsonism features did not demonstrate pupillary changes consistent with ipRGC abnormality. There was no relationship between levodopa equivalent dosage or PD severity and ipRGC abnormality. The pupillary test sensitivity in predicting PD was 0.75 and likelihood ratio was 1.2.

CONCLUSIONS

ipRGC deficit is demonstrated in PD subjects; however, the degree and constancy of abnormality appear variable.