International journal of computer assisted radiology and surgery · 2026
Semi-continuous non-invasive intracranial pressure monitoring via automated optic nerve sheath diameter image acquisition and analysis: a benchtop proof-of-concept study.
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Kashkoush Ahmed, Li Sean, El-Abtah Mohamed, Bain Mark, Gomes Joao, Raymond Scott
Аннотация
PURPOSE: Invasive intracranial pressure (ICP) monitoring is associated with up to a 17% complication rate. There are no clinically accepted non-invasive, continuous ICP monitors. Optic nerve sheath diameter (ONSD) has a high diagnostic accuracy for invasive ICPs; however, it only provides information at a point in time. We aimed to build a system for non-invasive automated ONSD image acquisition as a proxy for semi-continuous ICP monitoring.
METHODS: We built a frame-based system attachable to a patient's head for robotic ONSD acquisition, termed ICP goggles. Phantom optic nerve sheaths filled with gel were constructed in 5-, 8-, and 11-mm diameters to be interchanged in a skull model orbit. Twenty trials of ICP goggle ONSD measurements were performed for each phantom nerve sheath size and compared to manual measurements using a Pearson's correlation coefficient. Intra-rater reliability of the automated system was evaluated using an intra-class correlation coefficient. A one-way Analysis of Variance (ANOVA) test was used to evaluate the classification accuracy of the ICP goggle measurements for each phantom size.
RESULTS: Sixty total trials were performed across the three phantom optic nerve sheath sizes. Mean ICP goggle measured ONSDs correlated with manual measurements (R2 = 0.99), across the three phantom sizes. Intra-rater reliability of the automated system was high (intra-class correlation coefficient 0.995). ICP goggle ONSD measurements were able to differentiate each of the three phantom nerve sheaths without overlapping measurements across nerve sheath sizes (p < 0.001, ANOVA).
CONCLUSION: We demonstrate a proof-of-concept model with validation data for automated ONSD image acquisition. These results validate mechanical performance and measurement consistency, but do not establish clinical-grade interpretation or robustness to real-world artifacts (e.g., motion, eyelids, and speckle) or anatomically accurate localization. Future work will focus on realistic globe-orbit phantoms, improved segmentation, coupling strategy, and staged human feasibility testing.
METHODS: We built a frame-based system attachable to a patient's head for robotic ONSD acquisition, termed ICP goggles. Phantom optic nerve sheaths filled with gel were constructed in 5-, 8-, and 11-mm diameters to be interchanged in a skull model orbit. Twenty trials of ICP goggle ONSD measurements were performed for each phantom nerve sheath size and compared to manual measurements using a Pearson's correlation coefficient. Intra-rater reliability of the automated system was evaluated using an intra-class correlation coefficient. A one-way Analysis of Variance (ANOVA) test was used to evaluate the classification accuracy of the ICP goggle measurements for each phantom size.
RESULTS: Sixty total trials were performed across the three phantom optic nerve sheath sizes. Mean ICP goggle measured ONSDs correlated with manual measurements (R2 = 0.99), across the three phantom sizes. Intra-rater reliability of the automated system was high (intra-class correlation coefficient 0.995). ICP goggle ONSD measurements were able to differentiate each of the three phantom nerve sheaths without overlapping measurements across nerve sheath sizes (p < 0.001, ANOVA).
CONCLUSION: We demonstrate a proof-of-concept model with validation data for automated ONSD image acquisition. These results validate mechanical performance and measurement consistency, but do not establish clinical-grade interpretation or robustness to real-world artifacts (e.g., motion, eyelids, and speckle) or anatomically accurate localization. Future work will focus on realistic globe-orbit phantoms, improved segmentation, coupling strategy, and staged human feasibility testing.