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Investigating CBF and ICP Using DCS

Investigating the Relationship Between Intracranial Pressure and Cerebral Blood Flow Using Near-infrared Diffuse Correlation Spectroscopy

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06039098
Acronym
ICP-CBF
Enrollment
17
Registered
2023-09-15
Start date
2023-01-05
Completion date
2023-08-20
Last updated
2024-02-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Intracranial Hypertension, Traumatic Brain Injury

Brief summary

We aim to acquire data using DCS on patients who are undergoing invasive ICP and ABP monitoring on ITU as part of their normal treatment. Data will then be correlated to derive various parameters including CBF and BFI. All interventions are entirely non-invasive.

Detailed description

Cerebral Autoregulation (CA) is the complex process whereby the body maintains constant blood flow to the brain (cerebral blood flow, CBF) over a wide range of mean arterial pressures (MAP) in order to provide constant oxygenation and nutrition supply to cerebral tissue. By balancing blood and cerebrospinal fluid (CSF) pressures, CA dynamically stabilises cerebral perfusion pressure (CPP) and hence blood flow. Disordered CA may result in reduced oxygen and nutrient delivery to the brain tissue leading to hypoxic and ischaemic damage resulting in significant morbidity and mortality. High intracranial pressure (ICP) is frequently associated with failing CA. Hence ICP is routinely monitored in patients suffering from traumatic brain injury (TBI) and other conditions which may result in CA failure. Raised ICP contributes to the majority of mortalities following severe TBI. All currently available ICP monitoring systems require insertion of an electrical or pneumatic transducer into the cranial cavity, usually sited within the brain parenchyma but occasionally into the subdural space (between the brain and the skull) or into the ventricles. This is currently only performed by neurosurgeons and carries a small but significant risk of haemorrhage or infection. Non-invasive ICP and hence CA monitoring would eliminate the risk of complications, could be used by all healthcare professionals, would extend the use to outside a hospital settings and may extend the range of conditions to benefit from ICP monitoring. This project pilots an approach to expand our understanding of the basic physiological interplay between intracranial pressure, arterial blood pressure, and cerebral blood flow in adult in-patients. A recently-developed form of near-infrared (NIR) optical sensing known as Diffuse Correlation Spectroscopy (DCS) offers an opportunity to investigate cerebral blood flow at the bed-side continuously. DCS measures blood flow in the microvasculature of the brain by determining a blood flow index (BFi). A similar technology based on near-infrared spectroscopy (NIRS), was recently successfully applied by the Chief Investigator in the same population in the same manner as in the current proposal (IRAS ID: 219476, approved by the East of England - Cambridge Central Research Ethics Committee (18/EE/0276) on 14/02/19). We therefore have extensive experience working with optical instruments in these patient groups. In this proposal we will use a custom DCS research instrument. This research instrument is designed to measure microvascular cerebral blood flow for neuroscience and neurological research applications. While this device is a bespoke instrument, built with this study in mind, it is based on established research technologies and has been tested successfully in more than 20 healthy volunteers and in a range of quality-control experiments to date. It uses a forehead-mounted optical probe that contains near-infrared light sources that can illuminate the brain tissue non-invasively and continuously. The light's path within brain tissue is modulated by the flow of blood in the cerebral microvasculature and it is ultimately absorbed or backscattered. The backscattered light is collected at a different point within the probe. The interplay between mean arterial blood (MAP) (measured by means of an intra-arterial catheter (part of normal medical care for patients on ITU) or a non-invasive finger-cuff) and ICP affects the morphology of the pulsatile flow in the cerebral microvascular, so the analysis of these signals in unison will help us better understand the relationship between ICP (which is measured clinically), MAP (which is measured clinically) and cerebral blood flow (which is not). This in turn could help support new research into head injury management, notably ICP-targeted treatment regimes. Ultimately this could lead to significant improvements in secondary injury-related mortality, length of hospital stay and reduced post-trauma disability. In addition the non-invasive nature of the monitor could extend the range of medical conditions that may benefit from ICP and CA monitoring including stroke, brain tumour surveillance, hydrocephalus, pre-hospital care of trauma patients, routine anaesthetic and ICU monitoring systems and screening of patients with headache in primary care. In addition, if successfully developed, this technology is likely to be extremely relevant to low and middle income countries where access to neurosurgeons (and hence ICP monitoring) is extremely limited.

Interventions

DEVICEDCS

DCS monitoring of brain

Sponsors

Barts & The London NHS Trust
CollaboratorOTHER
Queen Mary University of London
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
16 Years to No maximum
Healthy volunteers
No

Inclusion criteria

* Invasive monitoring of ICP and ABP as part of normal treatment

Exclusion criteria

* Not meeting inclusion criteria.

Design outcomes

Primary

MeasureTime frameDescription
DCS signal acquisition12 monthsSuccessful acquisition of DCS signals from brain tissue

Secondary

MeasureTime frameDescription
Correlation of DCS signals with routine physiological data measurements10 monthsCorrelation of DCS signals with routine physiological data measurements
ML approach to derive secondary parameters10 monthsMachine learning approach to derive additional parameters non-invasively

Countries

United Kingdom

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026