In critically ill patients, pupillary light reflex (PLR) is commonly used to explore brainstem dysfunction. After retinal stimulation from light, part of the fibres transmitting the neural impulse along the optic nerve stimulates the parasympathetic Edinger–Westphal nucleus cells in the midbrain’s pretectal area. The preganglionic fibres from the Edinger–Westphal nucleus travel along the oculomotor nerve and activate the ciliary ganglion, whose postganglionic fibres stimulate the iris sphincter muscle causing pupillary constriction (Fig. 1a).
Standard PLR (s-PLR) assessment using a penlight is simple and inexpensive, but qualitative and prone to subjectivity [1]. Unlike s-PLR, automated pupillometry (AP) standardises the intensity, the distance from the eye and duration of the light stimulus and displays a quantitative and highly reproducible measurement of the pupillary response.
Automated pupillometry technique
Pupil reactivity should be measured in the dark to avoid interference from ambient light. AP is performed using pupillometers, portable devices including an infrared and a visible light source coupled with a camera. The device measures the baseline pupil size using infrared light, which does not stimulate the retina, then delivers a 3 s flash of visible light and records the pupillary response with the camera (Fig. 1b). Measured parameters generally include maximum and minimum pupil size, constriction latency (Lat), velocity (CV), and percentage (CH), and dilation velocity (DV) (Fig. 1b and ESM Table 1). The NeuroOptics pupillometer summarises these variables in a proprietary parameter, the neurological pupil index (NPi), whose values range from 0 to 5, with normal values being ≥ 3. Modern pupillometers can display a graphic representation of the change in pupillary size during the test, generally known as the pupillogram (Fig. 1b). In addition, they show a video playback of the elicited pupillary reflex, store patient data, and provide a trend of the AP values over time to track the patient’s clinical trajectory, making it a portable, non-invasive monitoring tool at the bedside.
Clinical use of automated pupillometry
Neurological assessment and detection of intracranial hypertension
New-onset unreflective anisocoria frequently occurs in neurologic emergencies and signals neurological deterioration. In severe brain injury from multiple aetiologies, intracranial hypertension (ICHT) may cause transtentorial herniation (TTH) of the medial temporal lobe and ipsilateral pupillary dilation due to either compression of the oculomotor nerve or distortion of the midbrain. The rationale of assessing or monitoring AP in unconscious brain-injured patients is to detect a functional compromise of the midbrain early, to prompt additional investigations and treatment. In a small case series [2], NPi changes preceded clinical deterioration by a median of 7.4 h in 73% of the events and returned to normal at a median of 43 min after treatment. In a single-centre cohort [3] of 54 patients with severe traumatic brain injury (TBI) and predominantly focal injuries who underwent intracranial pressure (ICP) monitoring and repeated AP assessment, episodes of sustained elevated ICP were associated with a concomitant NPi fall. In 17 patients who developed refractory ICHT requiring decompression, NPi was < 3 for 38% of the monitored time vs 1% of the time in 15 patients with non-refractory ICHT. In another study [4] on 23 ICP-monitored patients with nontraumatic supratentorial intracerebral haemorrhage who underwent AP every 30 min (total 1973 measurements), low CV had the highest sensitivity (89[79–95]%) and high Lat had the highest specificity (83[81–85]%) for detecting ICHT. Due to a low incidence of ICHT (total 74/1934 ICP readings in seven patients), the positive predictive values for both CV and Lat were also low (7[6–9]% and 8[5–11]%, respectively). Interestingly, the median values of CV, CH and DV decreased linearly with increasing ICP values from 0 to ≤ 20 mmHg.
In summary, in comatose patients with acute brain injury, deterioration of AP parameters such as NPi and CV on serial AP measurements may herald the occurrence of ICHT and prompt additional investigations, such as brain imaging or ICHP treatment. In that regard, pupillometry can be comparable to other tools such as transcranial Doppler or optical nerve sheath diameter. Because of its quantitative and reproducible results, AP is preferable to the conventional assessment of pupil size and reactivity using visual inspection.
Prognostication in acute brain injury
In patients with cardiac arrest, hypoxic-ischaemic brain injury (HIBI) occurring during and after resuscitation is the leading cause of death and disability [5]. Although there are no clinically available methods to measure cerebral blood flow during resuscitation directly, an indirect estimate of brain perfusion may be provided by pupillary reactivity. In a case series of 30 patients [6], 25 (83%) had detectable PLR using AP for at least part of the resuscitation, and continuous presence—or absence for < 5 min—of PLR during resuscitation was associated with survival and a good neurological outcome. Conversely, no patients with absent or gradually deteriorating PLR during resuscitation survived. An NPI ≤ 2 predicts a poor outcome with 98% specificity on hospital admission in patients who are comatose after return of spontaneous circulation [7].
Midbrain is relatively resistant to anoxia. In comatose cardiac arrest survivors with HIBI, a bilaterally absent PLR indicates a very likely poor outcome [8]. However, a visual pupillary assessment may occasionally miss a present PLR in patients with a good neurological outcome and cause a falsely pessimistic prediction. This is more likely to occur when the pupil size is small. In an observational European multicentre study on 456 adult patients with post-cardiac arrest HIBI [9], PLR on visual assessment was incorrectly rated as being bilaterally absent in five over 78 patients who eventually recovered (false positive rate [FPR] for poor outcome 6[2–14]%) while AP was 100% accurate (FPR 0[0–2]%). In those patients, the mean pupillary size was 1.9 ± 0.22 mm. The current Guidelines for Post-resuscitation Care [10] recommend pupillometry over s-PLR to prognosticate patients with HIBI after cardiac arrest (ESM Fig. 1).
Besides HIBI, AP changes may predict poor outcome in patients with acute brain injury from multiple aetiologies [11]. A multicentre prospective study [12] is investigating the ability of NPi to predict 6-month poor neurological outcome in adults admitted to ICU with acute brain injury from trauma or haemorrhagic stroke.
Limitations of automated pupillomentry
Like s-PLR, AP requires that the mechanism of vision and the afferent and efferent pathways of PLR are intact. Another potential confounder is the interindividual variability in pupil size and reactivity [13] whose impact on AP reliability remains to be investigated. Both anaesthetic agents [14] and opioids at clinical doses [15] that affect s-PLR may also alter some AP parameters. However, NPi remains generally unaffected. AP is more accurate than s-PLR when the pupil size is small, as it may occur due to sedation. However, a consistent threshold of AP values for predicting the correlated clinical event remains to be established. AP requires equipment and consumables, whose costs can make this technology unsuitable for low-resource settings. However, recent smartphone apps for performing AP in these contexts have recently been developed [16].
Take-home message
AP ensures a standard, objective, and reproducible assessment of PLR. In patients with HIBI, AP can detect minimal pupillary reactions that are not detected by visual evaluation and avoid falsely pessimistic predictions. In patients with brain injury at risk of ICHT, AP can be used as a non-invasive track-and-trigger system to detect subtle and progressive changes in PLR that indicate an impending neurological deterioration or increased ICP. Prospective clinical trials are needed to demonstrate the potential clinical benefits of early assessing and monitoring patients with acute brain injury using automated pupillometry.
References
Olson DM, Stutzman S, Saju C, Wilson M, Zhao W, Aiyagari V (2016) Interrater reliability of pupillary assessments. Neurocrit Care 24:251–257
Papangelou A, Zink EK, Chang WW, Frattalone A, Gergen D, Gottschalk A, Geocadin RG (2018) Automated pupillometry and detection of clinical transtentorial brain herniation: a case series. Mil Med 183:e113–e121
Jahns FP, Miroz JP, Messerer M, Daniel RT, Taccone FS, Eckert P, Oddo M (2019) Quantitative pupillometry for the monitoring of intracranial hypertension in patients with severe traumatic brain injury. Crit Care 23:155
Giede-Jeppe A, Sprügel MI, Huttner HB, Borutta M, Kuramatsu JB, Hoelter P, Engelhorn T, Schwab S, Koehn J (2021) Automated pupillometry identifies absence of intracranial pressure elevation in intracerebral hemorrhage patients. Neurocrit Care 35:210–220
Sandroni C, Cronberg T, Sekhon M (2021) Brain injury after cardiac arrest: pathophysiology, treatment, and prognosis. Intensive Care Med 47:1393–1414
Behrends M, Niemann CU, Larson MD (2012) Infrared pupillometry to detect the light reflex during cardiopulmonary resuscitation: a case series. Resuscitation 83:1223–1228
Peluso L, Oddo M, Sandroni C, Citerio G, Taccone FS (2022) Early neurological pupil index to predict outcome after cardiac arrest. Intensive Care Med 48:496–497
Sandroni C, D’Arrigo S, Cacciola S, Hoedemaekers CWE, Kamps MJA, Oddo M, Taccone FS, Di Rocco A, Meijer FJA, Westhall E, Antonelli M, Soar J, Nolan JP, Cronberg T (2020) Prediction of poor neurological outcome in comatose survivors of cardiac arrest: a systematic review. Intensive Care Med 46:1803–1851
Oddo M, Sandroni C, Citerio G, Miroz JP, Horn J, Rundgren M, Cariou A, Payen JF, Storm C, Stammet P, Taccone FS (2018) Quantitative versus standard pupillary light reflex for early prognostication in comatose cardiac arrest patients: an international prospective multicenter double-blinded study. Intensive Care Med 44:2102–2111
Nolan JP, Sandroni C, Bottiger BW, Cariou A, Cronberg T, Friberg H, Genbrugge C, Haywood K, Lilja G, Moulaert VRM, Nikolaou N, Olasveengen TM, Skrifvars MB, Taccone F, Soar J (2021) European resuscitation council and European Society of Intensive Care Medicine guidelines 2021: post-resuscitation care. Intensive Care Med 47:369–421
Romagnosi F, Bernini A, Bongiovanni F, Iaquaniello C, Miroz J-P, Citerio G, Taccone FS, Oddo M (2022) Neurological Pupil Index for the early prediction of outcome in severe acute brain injury patients. Brain Sci 12:609
Oddo M, Taccone F, Galimberti S, Rebora P, Citerio G (2021) Outcome prognostication of acute brain injury using the Neurological Pupil Index (ORANGE) study: protocol for a prospective, observational, multicentre, international cohort study. BMJ Open 11:e046948
Bergamin O, Kardon RH (2003) Latency of the pupil light reflex: sample rate, stimulus intensity, and variation in normal subjects. Invest Ophthalmol Vis Sci 44:1546–1554
Shirozu K, Setoguchi H, Tokuda K, Karashima Y, Ikeda M, Kubo M, Nakamura K, Hoka S (2017) The effects of anesthetic agents on pupillary function during general anesthesia using the automated infrared quantitative pupillometer. J Clin Monit Comput 31:291–296
McKay RE, Larson MD (2021) Detection of opioid effect with pupillometry. Auton Neurosci 235:102869
Piaggio D, Namm G, Melillo P, Simonelli F, Iadanza E, Pecchia L (2021) Pupillometry via smartphone for low-resource settings. Biocybern Biomed Eng 41:891–902
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GC and FST are scientific advisors for Neuroptics Inc. GC and CS are, respectively, Editor-in-Chief and Associate Editor of Intensive Care Medicine.
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Supplementary file1 ERC-ESICM prognostication algorithm [10]. NOTES - 1. Major confounders may include sedation, neuromuscular blockade, hypothermia, severe hypotension, hypoglycaemia, sepsis, and metabolic and respiratory derangements. 2. Use an automated pupillometer, when available, to assess pupillary light reflex. 3. Suppressed background ± periodic discharges or burst-suppression, according to ACNS. 4. Increasing NSE values between 24 h and 48 h or 24/48 h and 72 h further confirm a likely poor outcome. 5. Defined as a continuous and generalised myoclonus persisting for 30 min or more. *Caution in case of discordant signs indicating a potentially good outcome. Abbreviations: EEG: electroencephalography; NSE: neuron specific enolase; SSEP: short-latency somatosensory evoked potentials; ROSC: return of spontaneous circulation (PDF 584 KB)
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Sandroni, C., Citerio, G. & Taccone, F.S. Automated pupillometry in intensive care. Intensive Care Med 48, 1467–1470 (2022). https://doi.org/10.1007/s00134-022-06772-4
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DOI: https://doi.org/10.1007/s00134-022-06772-4