Handheld chromatic pupillometry can accurately and rapidly reveal functional loss in glaucoma

Abstract

Background/aimsEarly detection and treatment of glaucoma can delay vision loss. In this study, we evaluate the performance of handheld chromatic pupillometry (HCP) for the objective and rapid detection of functional loss in glaucoma.MethodsIn this clinic-based, prospective study, we enrolled 149 patients (median (IQR) years: 68.5 (13.6) years) with confirmed glaucoma and 173 healthy controls (55.2 (26.7) years). Changes in pupil size in response to 9 s of exponentially increasing blue (469 nm) and red (640 nm) light-stimuli were assessed monocularly using a custom-built handheld pupillometer. Pupillometric features were extracted from individual traces and compared between groups. Features with the highest classification potential, selected using a gradient boosting machine technique, were incorporated into a generalised linear model for glaucoma classification. Receiver operating characteristic curve analyses (ROC) were used to compare the performance of HCP, optical coherence tomography (OCT) and Humphrey Visual Field (HVF).ResultsPupillary light responses were altered in glaucoma compared with controls. For glaucoma classification, HCP yielded an area under the ROC curve (AUC) of 0.94 (95% CI 0.91 to 0.96), a sensitivity of 87.9% and specificity of 88.4%. The classification performance of HCP in early-moderate glaucoma (visual field mean deviation (VFMD) > -12 dB; AUC=0.91 (95% CI 0.87 to 0.95)) was similar to HVF (AUC=0.91) and reduced compared with OCT (AUC=0.97; p=0.01). For severe glaucoma (VFMD ≤ -12 dB), HCP had an excellent classification performance (AUC=0.98, 95% CI 0.97 to 1) that was similar to HVF and OCT.ConclusionHCP allows for an accurate, objective and rapid detection of functional loss in glaucomatous eyes of different severities.

Retinal neural dysfunction in diabetes revealed with handheld chromatic pupillometry

“…Baseline pupil size (i.e., horizontal pupil radius) was smaller in DR (2.6 ± 0.6 mm) compared to controls (3.2 ± 0.6 mm, p < 0.001) and compared to DM without DR (3.0 ± 0.7 mm, p = 0.008). Twenty‐two seconds after blue light offset, and before onset of the red light stimulus, 80% of subjects had returned to within 10% of the baseline pupil size, which is in line with other studies using the same chromatic pupillometry protocol 28,29 . Multiple pupillometric parameters were reduced in DM without DR compared to controls, including max blue ( p < 0.001), max red ( p = 0.005), blue PIPR 6 s ( p = 0.004) and net PIPR 6 s ( p = 0.03) (Table 2, Figure 3).…”

“…Twenty-two seconds after blue light offset, and before onset of the red light stimulus, 80% of subjects had returned to within 10% of the baseline pupil size, which is in line with other studies using the same chromatic pupillometry protocol. 28,29 Multiple pupillometric parameters were reduced in DM without DR compared to controls, including max blue (p < 0.001), max red (p = 0.005), blue PIPR 6 s (p = 0.004) and net PIPR 6 s (p = 0.03) (Table 2, Figure 3). These differences remained significant even when considering only a subgroup of patients with controlled diabetes (Table S1).…”

“…These studies, however, were performed with large cumbersome Ganzfeld domes in laboratory research settings, which are difficult to translate to routine clinical use. We have recently developed a handheld chromatic pupillometer (HCP; Figure 1) for clinic‐based assessment of the PLR in patients with ocular conditions 27,28 . The aim of this study was to evaluate the ability of HCP using a standardised 1‐min testing protocol, to reveal and localise retinal neural dysfunction in diabetic patients with and without DR, compared to controls.…”

Handheld chromatic pupillometry can reliably detect functional glaucomatous damage in eyes with high myopia

“…Logistic regression was used to distinguish glaucomatous high myopes from a combined population of high myopes and emmetropes without glaucoma. Models were generated using combinations of five PLR features found to be associated with glaucoma as linear predictors, 37 and the model with the greatest area under the receiver operating characteristic curve (AUC) was selected as the final model. 37 Predictors considered included Phasic Constriction to Blue Light, Maximum Constriction to Blue Light, Post-Illumination Pupillary Response (PIPR) to Blue Light taken as the area under the pupil constriction Curve 0-12 seconds following light offset (PIPR AUC 0-12s), Phasic Constriction to Red Light, and Maximum Constriction to Red Light; interaction terms were not considered to avoid overfitting.…”

“…26–29 As these cells elicit specific responses to different wavelengths of light, chromatic light stimulations have shown promise in differentially assessing the integrity of the inner and outer retina, as well as detecting glaucoma, even at an early stage. 30–37…”