Despite disappointing results in terms of modelling ICP, the ICP and ABP waveform data collected as part of the BioTBI Study have been a valuable
research resource. They have been used as pilot data to test some of the models described in the introductory chapter and bring them closer to implementation in clinical practice. Examples of recent and ongoing projects that are using the data to develop novel ICP analysis, address issues related to artifact in high volume data capture and embed these complex analyses into the clinical environment are provided below.
5.5.2 Multi-resolution Convolution Analysis of the ICP Waveform
From the database of ICP waveforms collected as part of the BioTBI Study, examples of the recognised ICP states of high and low compliance and ‘a’ and ‘b’ waves were selected(145). Multi-resolution convolution analysis was used to identify features of the ICP waveform associated with each of the clinical states that could then be used to create an impulse function. It was then possible to identify these waveform features in a separate study dataset. These pilot results require further optimisation on a larger ICP waveform dataset. As with the previously discussed work on morphological clustering and analysis of continuous intracranial pressure (MOCAIP)(103), they do suggest that automated analysis of the ICP waveform may be able to identify clinically important ICP states.
5.5.3 Calculation of Optimal CPP
There has already been detailed discussion of the potential use of indices of cerebral autoregulation (CA) to calculate optimal cerebral perfusion pressure (CPPopt) in TBI. One of the potential limitations of this approach is the fact that the most established techniques to calculate CPPopt fail to successfully find a value in a significant percentage of monitoring episodes(100). Arterial blood pressure (ABP) and ICP waveforms collected during the BioTBI Study have been used to compare indices of CA(146) and explore alternative methods of
estimating CPPopt(147). If targeting of CPPopt in the management of TBI is to be tested by RCT, there will need to be consensus agreement on the most
appropriate means of its estimation.
5.5.4 Detecting Artifact in Physiological Waveforms
The BioTBI Study tested a new system for high frequency data capture on the NICU (ixTrends(133)). One of the well recognised problems with automatic high frequency data capture is the inadvertent collection of artifactual data(148). The ABP data collected during the BioTBI Study were used as pilot data for a Chief Scientist Office (Scotland) funded project (CHZ/4/801) into the automatic detection of artifactual events in vital signs monitoring data(149, 150). As high frequency data capture becomes the norm in ICU there will be a requirement for systems to ensure the quality of these data.
5.5.5 Embedding Automatic Data Analysis into the NICU
At around the same time that the IMPACT Group were addressing issues surrounding the failure of multiple large RCTs to confirm the efficacy of promising therapies in TBI, the Brain monitoring with Information Technology (BrainIT) Group were suggesting an alternative solution(96). As a collaboration across 22 NICUs in 11 European countries (coordinated from the Institute of Neurological Sciences in Glasgow), the group have worked towards development of more information technology based tools for collection and analysis of
standardised high resolution data in TBI. By sharing and analysing these high resolution data it is expected that a better understanding of variations in patient physiology and treatment will lead to more targeted therapies in the future. In the BrainIT projects, the data collection frequency was 1 Hz. In the BioTBI project, the data collection frequency of the ICP and ABP waveforms was 128 Hz, while the frequency for the electrocardiogram (ECG) signal was 512 Hz. The collection of this resolution of data means that analyses of brain physiology, for example the assessments of cerebral autoregulation mentioned above, can be performed. However, the vast quantities of data generated require specialised infrastructure for transfer, storage and analysis. The Connecting Healthcare and Research Through A Data-Analysis Provisioning Technology (CHART-ADAPT) Project has been funded by Innovate UK (Reference: 102113) to address these issues along with the unique challenge of returning results to the patient bedside in a clinically useful timeframe(151).
5.5.6 Alternative Monitors of Brain Physiology
In the context of managing TBI, the importance of ICP monitoring relates to the information it can provide clinicians in terms of indicating the extent of the pathological process and guiding interventions. The interventions can be targeted at reducing ICP and optimising CPP as a means of ensuring adequate cerebral blood flow (CBF) and consequently maintaining oxygen and nutrient delivery to the injured brain. Direct measures of these endpoints exist but a review of their function and efficacy is outwith the scope of this thesis. The Brain Trauma Foundation (BTF) guidelines acknowledge the current low level of evidence surrounding devices designed to monitor CBF, brain oxygenation and the metabolic state of the brain. Despite this, the future of TBI care will
potentially involve integrating ICP measurement with multiple additional monitors of brain physiology.
5.5.7 Alternative Applications for TCB Measurement
All of the applications of TCB measurement described above have been in the monitoring and investigation of acute pathologies. As an estimate of ICP it may be more appropriate in future studies to consider a role for TCB in monitoring more chronic conditions. For example, idiopathic intracranial hypertension (IIH) is a syndrome of raised intracranial pressure without identifiable aetiology(152) and hydrocephalus is a disorder of excessive accumulation of CSF with multiple aetiologies(153). In both of these clinical conditions there is often an indication for measurement of CSF pressure in individuals over a long period of time,
frequently resulting in multiple invasive procedures. Therefore the need for new techniques to assist with the diagnosis of hydrocephalus is recognised as an opportunity for hydrocephalus research(154). In IIH and hydrocephalus, TCB would benefit from the lack of soft tissue injury, the potential to make a calibrating invasive measurement at the time of diagnosis, followed by the ability to trend non-invasive measures over time.