Associations Between Ocular Pulse Dynamics and Structural–Functional Changes in Normal-Tension Glaucoma (iCARENTG)

Normal-tension glaucoma (NTG) is a chronic progressive optic neuropathy characterized by optic nerve damage despite intraocular pressure remaining within the normal range. This indicates that, in addition to intraocular pressure parameters, hemodynamic and biomechanical factors play an important role in the pathogenesis of the disease. Despite recent advances, clinical practice still lacks methods that enable individualized assessment of these dynamic processes in specific patients.

The aim of the project is to perform a retrospective analysis of accumulated clinical and instrumental data and to develop a personalized NTG risk assessment tool using numerical modelling and artificial intelligence methods. Dynamic parameters of ocular pulse waves and optical coherence tomography (OCT) images will be analyzed to characterize their features and identify indicators specific to patients with NTG.

The analysis will be based on previously collected data obtained using the non-invasive intracranial pulsatile wave monitoring system “Archimedes 02”. Previous studies have shown that the amplitude of ocular pulse waves in NTG patients is almost twice as high as in healthy individuals; however, the mechanisms underlying this difference remain unclear. The project will investigate associations between ocular pulse wave dynamics and structural and functional ocular changes at the individual patient level.

During the study, an integrated numerical model will be developed, in which patients’ clinical data (OCT biomarkers and ocular pulse wave parameters) will be transformed into a virtual eye model — a computer-based simulation of disease progression. Algorithms based on differential and integral equations will enable modelling of hemodynamic and biomechanical processes and prediction of disease progression. Additionally, machine learning methods will be applied to analyze relationships between ocular pulse wave parameters and structural and functional changes.

The final outcome of the project will be the development of NTG analysis and progression risk assessment tools, enabling more accurate evaluation of disease progression and supporting personalized monitoring and treatment strategies.

Project partners: Lithuanian University of Health Sciences, Kaunas University of Technology

Project number: INP2026/10