Smartphone pupillometry predicts ischemic penumbra in acute ischemic stroke

Area of Science:

• Neurology
• Medical Technology
• Biomarkers

Background:

• Advances in time-sensitive treatments for large vessel occlusion (LVO) necessitate rapid acute ischemic stroke recognition.
• The pupillary light reflex (PLR) serves as a crucial biomarker for neurological status.
• A portable smartphone-based quantitative pupillometry application has been developed to measure PLR metrics without specialized equipment.

Purpose of the Study:

• To evaluate the predictive capability of smartphone pupillometry metrics for National Institutes of Health Stroke Scale (NIHSS) scores.
• To assess the correlation between PLR morphological metrics and the CT Perfusion (CTP) core to penumbra volume ratio in acute ischemic stroke patients.

Main Methods:

• Quantitative pupillometry was performed using a smartphone application on patients with LVO before intervention.
• Data collected included CTP volumetric measures of ischemic core and penumbra, and presenting NIHSS.
• PLR curve morphological parameters were analyzed for correlation with NIHSS and CTP core infarct to penumbra volume ratio.

Main Results:

• Twenty-two patients with LVO were analyzed; 96% had anterior circulation occlusion.
• Significant negative correlations were observed between specific PLR metrics (CHANGE, MCV) and both NIHSS and CTP core to penumbra volume ratio, particularly after Bonferroni correction for the latter.
• The CHANGE metric showed a significant negative correlation with the CTP core to penumbra volume ratio (p < 0.001) post-correction.

Conclusions:

• Quantitative smartphone pupillometry metrics show promise in predicting cerebral ischemia and the ischemic penumbra.
• This technology may aid in the rapid assessment of stroke severity in LVO patients.
• Smartphone pupillometry offers a non-invasive, accessible method for evaluating neurological status in acute stroke.