Building a Portable Blood Flow Monitor with Near-Infrared Light for ICU Patients

Context and Motivation:

Healthcare poses a complex and global scientific challenge that requires an integrated approach, drawing on expertise from medicine, technology, economics, and social sciences. In neurocritical care – focused on conditions such as stroke and head trauma – these challenges are particularly intricate due to the brain’s complexity and sensitivity, where timely intervention is often crucial. Addressing these challenges is vital, as neurocritical injuries are among the leading causes of disability and mortality worldwide, with their prevalence continuing to rise.

One of the principal difficulties in neurocritical care is monitoring patients’ neurophysiology at the bedside. Following a brain injury, it is critical to monitor cerebral blood flow and brain metabolism closely, especially around the injury onset. Current technologies fall short of addressing this need effectively. MRI requires moving the patient out of the ICU, risking patient destabilization. CT be made on-site but is limited by the use of radioactive materials that only allow intermittent measurements that may miss critical windows during therapeutics. Transcranial ultrasound, though portable, cannot be made continuously and primarily measures haemodynamics in large vessels. This highlights an urgent need for advanced, affordable, and accessible technologies in neurocritical care that can significantly improve patient outcomes.

Project Overview:

This PhD project focuses on developing a pioneering, noninvasive, portable cerebral haemodynamic monitor for bedside use in neurocritical care. The device will integrate two near-infrared spectroscopy techniques: diffuse correlation spectroscopy (DCS) to measure blood flow and frequency-domain diffuse optical spectroscopy (FD-DOS) to measure brain oxygenation (Mesquita & Yodh, 2011; Mesquita et al, 2011).

The first part of the project involves constructing this device —the first of its kind in the UK— and creating a user-friendly graphical user interface that can be used for real-time monitoring in clinical settings (Forti et al, 2020). The second phase will focus on validating the technology at the bench and in healthy subjects. In particular, the project plans to develop artificial intelligence algorithms and simulations to enhance the absolute quantification of the physiological properties measured by these techniques.

By the end of the project, the successful candidate will deliver a robust, innovative device capable of sophisticated data collection and intelligent data analysis, which will be ready for translation to a clinical setting. 

The project will be based in the Medical Imaging Lab at the University of Birmingham’s School of Computer Science, which has facilities for instrumentation development and data analysis. We are seeking a motivated candidate with a background in engineering, physics, or computer science. Ideal candidates will have previous experience in electronics and/or systems control (or a willingness to learn these topics) and a passion for combining modelling and programming in biomedical engineering. Additional skills that will be beneficial include programming, mathematical proficiency, effective communication, and the ability to work collaboratively within a multidisciplinary team. The successful applicant will work within a supportive and dynamic interdisciplinary team specialised in optical neuroimaging methods. They will receive close supervision and have opportunities to interact and collaborate with researchers from other fields.

Funding notes

This PhD is funded through a scholarship within a grant that also sponsors the development of this device. Self-funded or externally sponsored students are also welcome to apply. Formal applications for research degree study can be emailed directly to the supervisor, Dr Rickson Mesquita (r.c.mesquita@bham.ac.uk), with a CV and a brief personal statement describing the applicant’s motivation to conduct such a project.

For more information, please contact Dr. Rickson Mesquita (r.c.mesquita@bham.ac.uk).