What is pupillometry and how is it relevant to carbon monoxide (CO) and the research into saving lives?
The CO Research Trust is currently funding several projects looking at finding a more robust marker for CO exposure than haemoglobin, the standard measure used currently.
One of them is being carried out by Sean England, a PhD student from the University of Hertfordshire. Sean is carrying out groundbreaking research into the use of pupillometry as a reliable biomarker for CO exposure.
His work is already providing compelling evidence that pupillometry could provide this much-needed breakthrough. Pupillometry could pave the way for far more reliable collection of data into the rates of CO poisoning, which we fear is currently vastly underreported.
Sean's work was initially presented at the CO Research Conference in July 2022. Such was the audience's interest that we invited Sean back to discuss the technique in more depth. Sean explains in more detail what pupillometry is below.
Sean England, PhD Student, University of Hertfordshire
Across centuries of human history many scientists have been fascinated by how the opening of the iris decreases in size when light is focused on the eye. The concept of pupillometry has existed in medicinal practices dating back to the 2nd century, with advancements continuing to be made to this day.
The word ‘pupil’ originates from the Latin word pupilla, which translates to ‘little doll’. This name is believed to have been derived from the fact that when staring into another’s eyes you are faced with a miniature reflection of oneself (Hakerem, 1967). The word was not used to refer to the central aperture of the iris until the 12th century when Gerard of Cremona mistranslated the word alhadaqatu - which more accurately translates to ‘the apple of my eye’ (Arráez-Aybar et al., 2015).
The pupil is a black hole or opening in the centre of iris; a heavily pigmented, thin, flattened ring structure comprised of melanoctyes, blood vessels and two layers of smooth muscle fibres. The individual muscle layers form the iris sphincter and iris dilator muscles, which work in tandem to control the diameter of the pupil via the autonomic nervous system (Martini, 2017). The opening bridges the gap between the anterior and posterior chambers of the eye and controls the level of light reaching the retina (Drake, 2014).
Pupillometry is simply the measurement of pupil size and reactivity. In its basic form it is used in hospitals every day as the Light Response Pupil Test, a key part of the basic clinical neurological exam. It involves a physician shining light from a small torch into each of the patient’s eyes while they focus on a distant object. Any changes in pupil size are viewed manually, with any overt discrepancies noted (Tomy, 2019).
The size of one’s pupil alters in response to three distinct stimuli: light, near fixation and increased cognitive activity (Mathôt, 2018). Using light as a stimulus is the most widely used. When shining a light in a person’s eye you activate the pupillary light response (PLR) causing the pupil to decrease in size. Alternatively, when you decrease the amount of light entering the eye the pupil will increase in size. Visual fixation refers to the maintenance of a person’s gaze on a singular location. When an object is positioned close to an individual's face, the pupil near response (PNR) is activated causing the pupil to constrict allowing for an increased depth of focus (Barral & Croibier, 2009). Finally, the psycho-sensory pupil response (PPR) is triggered in response to increased cognitive activity, such as increased mental effort or arousal levels.
If you consider using light as a stimulus to elicit a pupillary reaction, its traditional form is the Light Response Pupil Test, albeit this method is highly subjective and prone to inaccuracies. Instead, pupils can be examined in an automated fashion using a 'pupillometer' device. Most automated pupillometry is conducted using portable, handheld pupillometers that allow for reliable pupillary size and reactivity measurements by stimulating the PLR (Meeker et al., 2005).
The field of pupillometry was revolutionised in the 20th century by Otto Lowenstein and Irene Loewenfeld. This research began by obtaining multiple photographs of the eye as it was exposed to light with images projected onto a screen. The diameters of the pupils were measured and plotted onto a graph against time. They coined the term ‘pupillogram’ to refer to the generated plots (Hakerem, 1967). Lowenstein and Loewenfeld are accredited with building the first electronic pupillometer in 1957 that incorporated infrared technology (Lowenstein and Loewenfeld, 1958). The modern generation of pupillographic instruments can be attributed to their pioneering efforts.
In the time since the first electronic pupillometer, pupillometry in research has evolved and can be divided it into two distinct forms: dynamic and chromatic. Dynamic pupillometry comprises recording and quantification of the PLR relative to time across a light and dark cycle. It can achieve this as it incorporates infrared technology that illuminates the surface of the eyes allowing for it to be recorded in relative darkness (Siva Kumar et al., 2020). Infrared light falls outside of the light visual spectrum therefore does not elicit a pupillary reaction (Lowenstein and Loewenfeld, 1958). It is a simple, non-invasive method to assess the PLR, offering insight into the health of the sympathetic and parasympathetic branches of the autonomic nervous system.
Chromatic pupillometry consists of exposing the eye to light of different wavelengths and intensities to preferentially stimulate different photoreceptors. The rod, S-cone, M-cone, L-cone and intrinsically photosensitive retinal ganglion cells (ipRGC) of the retina have different roles in mediating the PLR. Most studies that utilise chromatic pupillometry rely solely on blue and red light to specifically stimulate rod and cone cells respectively due to the tonic component of the PLR being controlled by rod cells at low-medium light intensities and by cone cells at high light intensities (Barrionuevo et al., 2014; Rukmini, Milea & Gooley, 2019).
Pupillometry is a simple, non-invasive method of obtaining an abundance of data relating to a range of cognitive processes. It has rich research potential when you consider that any disruption to a single process involved in the mediation of pupil size will be reflected in changes to the PLR. Current research is yet to fully explore many of pupillometry’s possibilities such as its potential for the diagnosis of degenerative eye conditions, neurodegenerative disorders, infections or exposure to toxic substances.
-Ends-
For more information about Sean's research project, his methodology and how it may help in the diagnosis of CO click here.
References
Arráez-Aybar, L.-A., Bueno-López, J.-L., Raio, N., 2015. Toledo School of Translators and their influence on anatomical terminology. Annals of Anatomy - Anatomischer Anzeiger 198, 21–33. https://doi.org/https://doi.or...
Drake, R., 2014. Gray’s anatomy for students, 3rd ed.
Hakerem, G., 1967. Pupillography, in: Venables, P.H., Martin, I. (Eds.), A Manual of Psychophysiological Methods. Amsterdam: North-Holland Publishing Co., pp. 337–349.
Lowenstein, O., Loewenfeld, I.E., 1958. Electronic Pupillography: A New Instrument and Some Clinical Applications. AMA Arch Ophthalmol 59, 352–363. https://doi.org/10.1001/archop...
Mathôt, S., 2018. Pupillometry: Psychology, Physiology, and Function. J Cogn 1. https://doi.org/10.5334/joc.18
Meeker, M., Du, R., Bacchetti, P., Privitera, C.M., Larson, M.D., Holland, M.C., Manley, G., 2005. Pupil Examination. Journal of Neuroscience Nursing 37, 34–40. https://doi.org/10.1097/013765...
Siva Kumar, A. v, Maruthy, K.N., Padmavathi, R., Sowjanya, B., MaheshKumar, K., 2020. Quantitative determination of pupil by dynamic pupillometry using infrared videography – Role in evaluation of autonomic activity. Clin Epidemiol Glob Health 8, 728–732. https://doi.org/https://doi.or...
Tomy, R., 2019. Pupil: Assessment and diagnosis. Kerala Journal of Ophthalmology 31, 167. https://doi.org/10.4103/kjo.kj...