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Purpose <p>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.</p> Methods <p>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.</p> Results <p>Sixty total trials were performed across the three phantom optic nerve sheath sizes. Mean ICP goggle measured ONSDs correlated with manual measurements (<i>R</i><sup>2</sup> = 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 (<i>p</i> &lt; 0.001, ANOVA).</p> Conclusion <p>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.</p>

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Semi-continuous non-invasive intracranial pressure monitoring via automated optic nerve sheath diameter image acquisition and analysis: a benchtop proof-of-concept study

  • 期刊论文

  • 发表日期：

    2026年3月25日

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  • Ahmed Kashkoush,
  • Sean Li,
  • Mohamed El-Abtah,
  • Mark Bain,
  • Joao Gomes,
  • Scott Raymond

摘要

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.