Cerebral critical closing pressure in hydrocephalus patients undertaking infusion tests.

Varsos, Georgios V,Czosnyka, Marek,Smielewski, Peter,Garnett, Matthew R,Liu, Xiuyun,Kim, Dong-Joo,Donnelly, Joseph,Adams, Hadie,Pickard, John D,Czosnyka, Zofia Butterworths [etc.] 2015 Neurological research Vol.37 No.8

<P>Links between cerebrospinal fluid (CSF) compensation and cerebral blood flow (CBF) have been studied in many clinical scenarios. In hydrocephalus, disturbed CSF circulation seems to be a primary problem, having been linked to CBF disturbances, particularly in white matter close to surface of dilated ventricles. We studied possible correlations between cerebral haemodynamic indices using transcranial Doppler (TCD) ultrasonography and CSF compensatory dynamics assessed during infusion tests.</P>

Spectral analysis of intracranial pressure: Is it helpful in the assessment of shunt functioning in-vivo?

Kim, Dong-Joo,Kim, Hakseung,Jeong, Eun-Jin,Lee, Hack-Jin,Czosnyka, Marek,Son, Yunsik,Kim, Byung-Jo,Czosnyka, Zofia Van Gorcum 2016 Clinical neurology and neurosurgery Vol.142 No.-

<P><B>Abstract</B></P> <P><B>Objective</B></P> <P>Shunt failure is common in hydrocephalic patients. The cerebrospinal fluid (CSF) infusion test enables the assessment of CSF absorption capacity, which is represented by the resistance to CSF outflow (<I>R</I> <SUB>OUT</SUB>) However, shunt failure may not only affect the CSF absorption capacity but also the intracranial compliance or compensatory properties. Spectral analysis of the ICP signal obtained during the infusion test may enable the comprehensive assessment of the overall deterioration caused by shunt failure.</P> <P><B>Material and methods</B></P> <P>A total of 121 hydrocephalic shunted patients underwent the infusion test with continuous intracranial pressure (ICP) and arterial blood pressure (ABP) recording. The maximum amplitudes of three major frequency bandwidths (0.2–2.6, 2.6–4.0 and 4.0–15Hz, respectively) were calculated from the ICP. Statistical analyses were conducted to identify factors significantly associated with shunt failure, to construct an index (i.e., the shunt response parameter, SRP) for detecting shunt failure, and to define thresholds for <I>R</I> <SUB>OUT</SUB> and SRP.</P> <P><B>Results</B></P> <P>The <I>R</I> <SUB>OUT</SUB> threshold for detecting shunt failure was 7.59mmHg/ml/min, and this threshold showed an accuracy of 82.64%. All spectral parameters were found to be significantly associated with shunt patency (<I>p</I> <0.05). The SRP exhibited significantly better accuracy than <I>R</I> <SUB>OUT</SUB> in detecting shunt failure (91.74%).</P> <P><B>Conclusion</B></P> <P>The hydrodynamic assessment of shunted patients enhanced by spectral analysis during the infusion test detected shunt failure with high accuracy. Although further validation is needed, the SRP exhibited promising results.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Spectral analysis during infusion test detects shunt failure with high accuracy. </LI> <LI> We constructed shunt response parameter (SRP) by spectral analysis on ICP signal. </LI> <LI> SRP shows significantly better accuracy than <I>R</I> <SUB>OUT</SUB> in detecting shunt failure. </LI> </UL> </P>

Finite element analysis of periventricular lucency in hydrocephalus: extravasation or transependymal CSF absorption?

Kim, Hakseung,Jeong, Eun-Jin,Park, Dae-Hyeon,Czosnyka, Zofia,Yoon, Byung C.,Kim, Keewon,Czosnyka, Marek,Kim, Dong-Joo American Association of Neurological Surgeons 2016 Journal of Neurosurgery Vol.124 No.2

<B>OBJECT</B><P>Periventricular lucency (PVL) is often observed in the hydrocephalic brain on CT or MRI. Earlier studies have proposed the extravasation of ventricular CSF into the periventricular white matter or transependymal CSF absorption as possible causes of PVL in hydrocephalus. However, there is insufficient evidence for either theory to be conclusive.</P><B>METHODS</B><P>A finite element (FE) model of the hydrocephalic brain with detailed anatomical geometry was constructed to investigate the possible mechanism of PVL in hydrocephalus. The initiation of hydrocephalus was modeled by applying a transmantle pressure gradient (TPG). The model was exposed to varying TPGs to investigate the effects of different geometrical characteristics on the distribution of PVL. The edema map was derived based on the interstitial pore pressure.</P><B>RESULTS</B><P>The model simulated the main radiological features of hydrocephalus, i.e., ventriculomegaly and PVL. The degree of PVL, assessed by the pore pressure, was prominent in mild to moderate ventriculomegaly. As the degree of ventriculomegaly exceeded certain values, the pore pressure across the cerebrum became positive, thus inducing the disappearance of PVL.</P><B>CONCLUSIONS</B><P>The results are in accordance with common clinical findings of PVL. The degree of ventriculomegaly significantly influences the development of PVL, but two factors were not linearly correlated. The results are indicative of the transependymal CSF absorption as a possible cause of PVL, but the extravasation theory cannot be formally rejected.</P>

Cerebrovascular pressure reactivity monitoring using wavelet analysis in traumatic brain injury patients: A retrospective study

Liu, Xiuyun,Donnelly, Joseph,Czosnyka, Marek,Aries, Marcel J. H.,Brady, Ken,Cardim, Danilo,Robba, Chiara,Cabeleira, Manuel,Kim, Dong-Joo,Haubrich, Christina,Hutchinson, Peter J.,Smielewski, Peter Public Library of Science 2017 PLoS medicine Vol.14 No.7

<▼1><P><B>Background</B></P><P>After traumatic brain injury (TBI), the ability of cerebral vessels to appropriately react to changes in arterial blood pressure (pressure reactivity) is impaired, leaving patients vulnerable to cerebral hypo- or hyperperfusion. Although, the traditional pressure reactivity index (PRx) has demonstrated that impaired pressure reactivity is associated with poor patient outcome, PRx is sometimes erratic and may not be reliable in various clinical circumstances. Here, we introduce a more robust transform-based wavelet pressure reactivity index (wPRx) and compare its performance with the widely used traditional PRx across 3 areas: its stability and reliability in time, its ability to give an optimal cerebral perfusion pressure (CPPopt) recommendation, and its relationship with patient outcome.</P><P><B>Methods and findings</B></P><P>Five hundred and fifteen patients with TBI admitted in Addenbrooke’s Hospital, United Kingdom (March 23rd, 2003 through December 9th, 2014), with continuous monitoring of arterial blood pressure (ABP) and intracranial pressure (ICP), were retrospectively analyzed to calculate the traditional PRx and a novel wavelet transform-based wPRx. wPRx was calculated by taking the cosine of the wavelet transform phase-shift between ABP and ICP. A time trend of CPPopt was calculated using an automated curve-fitting method that determined the cerebral perfusion pressure (CPP) at which the pressure reactivity (PRx or wPRx) was most efficient (CPPopt_PRx and CPPopt_wPRx, respectively).</P><P>There was a significantly positive relationship between PRx and wPRx (r = 0.73), and wavelet wPRx was more reliable in time (ratio of between-hour variance to total variance, wPRx 0.957 ± 0.0032 versus PRx and 0.949 ± 0.047 for PRx, <I>p</I> = 0.002). The 2-hour interval standard deviation of wPRx (0.19 ± 0.07) was smaller than that of PRx (0.30 ± 0.13, <I>p</I> < 0.001). wPRx performed better in distinguishing between mortality and survival (the area under the receiver operating characteristic [ROC] curve [AUROC] for wPRx was 0.73 versus 0.66 for PRx, <I>p</I> = 0.003). The mean difference between the patients’ CPP and their CPPopt was related to outcome for both calculation methods. There was a good relationship between the 2 CPPopts (r = 0.814, <I>p</I> < 0.001). CPPopt_wPRx was more stable than CPPopt_PRx (within patient standard deviation 7.05 ± 3.78 versus 8.45 ± 2.90; <I>p</I> < 0.001).</P><P>Key limitations include that this study is a retrospective analysis and only compared wPRx with PRx in the cohort of patients with TBI. Prior prospective validation is required to better assess clinical utility of this approach.</P><P><B>Conclusions</B></P><P>wPRx offers several advantages to the traditional PRx: it is more stable in time, it yields a more consistent CPPopt recommendation, and, importantly, it has a stronger relationship with patient outcome. The clinical utility of wPRx should be explored in prospective studies of critically injured neurological patients.</P></▼1><▼2><P>Using continuous monitoring data in traumatic brain inury patients, Xiuyun Liu and colleagues compare the performance of cerebrovascular pressure reactivity monitoring using wavelet analysis to the pressure reactivity index.</P></▼2><▼3><P><B>Author summary</B></P><P><B>Why was this study done?</B></P><P>The brain is vulnerable to damage from too little (ischemia) or too much (hyperemia) blood flow following traumatic brain injury (TBI).</P><P>A physiological mechanism called cerebral autoregulation (CA) exists to maintain stable blood flow even if cerebral perfusion pressure (CPP) is changing, and an assessment of CA as part of bedside neuro-monitoring of patients with TBI could facilitate individualized treatment.</P><P>A robust method for assessing CA in TBI is not yet available. The traditional measure used, the pressure reactivity index (PRx), provides inherently noisy estimates and

Hemodynamic Instability and Cardiovascular Events After Traumatic Brain Injury Predict Outcome After Artifact Removal With Deep Belief Network Analysis

Kim, Hakseung,Lee, Seung-Bo,Son, Yunsik,Czosnyka, Marek,Kim, Dong-Joo Wolters Kluwer Health, Inc. All rights reserved 2018 Journal of neurosurgical anesthesiology Vol.30 No.4

BACKGROUND:: Hemodynamic instability and cardiovascular events heavily affect the prognosis of traumatic brain injury. Physiological signals are monitored to detect these events. However, the signals are often riddled with faulty readings, which jeopardize the reliability of the clinical parameters obtained from the signals. A machine-learning model for the elimination of artifactual events shows promising results for improving signal quality. However, the actual impact of the improvements on the performance of the clinical parameters after the elimination of the artifacts is not well studied. MATERIALS AND METHODS:: The arterial blood pressure of 99 subjects with traumatic brain injury was continuously measured for 5 consecutive days, beginning on the day of admission. The machine-learning deep belief network was constructed to automatically identify and remove false incidences of hypotension, hypertension, bradycardia, tachycardia, and alterations in cerebral perfusion pressure (CPP). RESULTS:: The prevalences of hypotension and tachycardia were significantly reduced by 47.5% and 13.1%, respectively, after suppressing false incidents (P=0.01). Hypotension was particularly effective at predicting outcome favorability and mortality after artifact elimination (P=0.015 and 0.027, respectively). In addition, increased CPP was also statistically significant in predicting outcomes (P=0.02). CONCLUSIONS:: The prevalence of false incidents due to signal artifacts can be significantly reduced using machine-learning. Some clinical events, such as hypotension and alterations in CPP, gain particularly high predictive capacity for patient outcomes after artifacts are eliminated from physiological signals.

Cerebral Vasospasm Affects Arterial Critical Closing Pressure

Varsos, Georgios V,Budohoski, Karol P,Czosnyka, Marek,Kolias, Angelos G,Nasr, Nathalie,Donnelly, Joseph,Liu, Xiuyun,Kim, Dong-Joo,Hutchinson, Peter J,Kirkpatrick, Peter J,Varsos, Vassilis G,Smielewski SAGE Publications 2015 Journal of cerebral blood flow and metabolism Vol.35 No.2

<P> The effect of cerebral vasospasm (CVS) after aneurysmal subarachnoid hemorrhage (SAH) on critical closing pressure (CrCP) has not been fully delineated. Using cerebral impedance methodology, we sought to assess the behavior of CrCP during CVS. As CrCP expresses the sum of intracranial pressure (ICP) and vascular wall tension, we also explored its role in reflecting changes in vascular tone occurring in small vessels distal to spasm. This retrospective analysis was performed using recordings from 52 patients, diagnosed with CVS through transcranial Doppler measurements. Critical closing pressure was calculated noninvasively using arterial blood pressure and blood flow velocity. Outcome was assessed at both discharge and 3 months after ictus with the Glasgow Outcome Scale. The onset of CVS caused significant decreases in CrCP ( P=0.025), without any observed significant changes in ICP ( P=0.134). Vasospasm induced asymmetry, with CrCP ipsilateral to CVS becoming significantly lower than contralateral ( P=0.025). Unfavorable outcomes were associated with a significantly lower CrCP after the onset of CVS (discharge: P=0.014; 3 months after SAH: P=0.020). Critical closing pressure is reduced in the presence of CVS in both temporal and spatial assessments. As ICP remained unchanged during CVS, reduced CrCP most probably reflects a lower wall tension in dilated small vessels distal to spasm. </P>

Monitoring of Optimal Cerebral Perfusion Pressure in Traumatic Brain Injured Patients Using a Multi-Window Weighting Algorithm

Liu, Xiuyun,Maurits, Natasha M.,Aries, Marcel J.H.,Czosnyka, Marek,Ercole, Ari,Donnelly, Joseph,Cardim, Danilo,Kim, Dong-Joo,Dias, Celeste,Cabeleira, Manuel,Smielewski, Peter Mary Ann Liebert, Inc. Publishers 2017 Journal of Neurotrauma Vol. No.

Automated artifact elimination of physiological signals using a deep belief network: An application for continuously measured arterial blood pressure waveforms

Son, Yunsik,Lee, Seung-Bo,Kim, Hakseung,Song, Eun-Suk,Huh, Hyub,Czosnyka, Marek,Kim, Dong-Joo Elsevier science 2018 Information sciences Vol.456 No.-

<P>Artifacts in physiological signals acquired during intensive care have the potential to be recognized as critical pathological events and lead to misdiagnosis or mismanagement. Manual artifact removal necessitates significant labor-time intensity and is subject to inter and intra-observer variability. Various methods have been proposed to automate the task; however, the methods are yet to be validated, possibly due to the diversity of artifact types. Deep belief networks (DBNs) have been shown to be capable of learning generative and discriminative feature extraction models, hence suitable for classifying signals with multiple features. This study proposed a DBN-based model for artifact elimination in pulse waveform signals, which incorporates pulse segmentation, pressure normalization and decision models using DBN, and applied the model to artifact removal in monitoring arterial blood pressure (ABP). When compared with a widely used ABP artifact removal algorithm (signal abnormality index; SAI), the DBN model exhibited significantly higher classification performance (net prediction of optimal DBN = 95.9%, SAI = 84.7%). In particular, DBN exhibited greater sensitivity than SAl for identifying various types of artifacts (motion = 93.6%, biological 95.4%, cuff inflation = 89.1%, transducer flushing = 97%). The proposed model could significantly enhance the quality of signal analysis, hence may be beneficial for use in continuous patient monitoring in clinical practice. (C) 2018 Published by Elsevier Inc.</P>

Morphological Feature Extraction From a Continuous Intracranial Pressure Pulse via a Peak Clustering Algorithm

Lee, Hack-Jin,Jeong, Eun-Jin,Kim, Hakseung,Czosnyka, Marek,Kim, Dong-Joo IEEE 2016 IEEE Transactions on Biomedical Engineering Vol.63 No.10

<P>Objective: An increase in intracranial pressure (ICP) is frequently observed in patients with severe traumatic brain injury (TBI). The information derived from the observation of temporal changes in the mean ICP is insufficient for assessment of the compensatory reserve of the injured brain. This assessment can be achieved via continuous morphological analysis of the pulse waveform of the ICP. Methods: Continuous arterial blood pressure (ABP) and ICP recordings from 292 TBI patients were analyzed. The algorithm extracted morphological landmarks (peaks, troughs, and flats) from the ICP. Among the extracted peaks, P1, P2, and P3 were assigned through peak clustering. The performance of the proposed method was validated through a comparison of the algorithm-defined peaks and those manually identified by experienced observers. Results: The proposed algorithm successfully identified the three distinguishing peaks of the ICP with satisfactory accuracy (95.3%, 87.8%, and 87.5% for P1, P2, and P3, respectively), even from minimally filtered raw signals. Conclusion: The algorithm extracted the morphological features from both ABP and ICP recordings with high accuracy. Significance: The ABP and ICP pulse waveforms can be simultaneously analyzed in real time using the proposed algorithm. The morphological features from these signals may aid the continuous care of patients with TBI.</P>

Impaired cerebral compensatory reserve is associated with admission imaging characteristics of diffuse insult in traumatic brain injury

Zeiler, Frederick A.,Kim, Dong-Joo,Cabeleira, Manuel,Calviello, Leanne,Smielewski, Peter,Czosnyka, Marek Springer-Verlag 2018 Acta neurochirurgica Vol. No.

<P><B>Background</B></P><P>Continuous assessment of cerebral compensatory reserve is possible using the moving correlation between pulse amplitude of intra-cranial pressure (AMP) and intra-cranial pressure (ICP), called RAP. Little is known about the behavior and associations of this index in adult traumatic brain injury (TBI). The goal of this study is to evaluate the association between admission cerebral imaging findings and RAP over the course of the acute intensive care unit stay.</P><P><B>Methods</B></P><P>We retrospectively reviewed 358 adult TBI patients admitted to the Addenbrooke’s Hospital, University of Cambridge, from March 2005 to December 2016. Only non-craniectomy patients were studied. Using archived high frequency physiologic signals, RAP was derived and analyzed over the first 48 h and first 10 days of recording in each patient, using grand mean, percentage of time above various thresholds, and integrated area under the curve (AUC) of RAP over time. Associations between these values and admission computed tomography (CT) injury characteristics were evaluated.</P><P><B>Results</B></P><P>The integrated AUC, based on various thresholds of RAP, was statistically associated with admission CT markers of diffuse TBI and cerebral edema. Admission CT findings of cortical gyral effacement, lateral ventricle compression, diffuse cortical subarachnoid hemorrhage (SAH), thickness of cortical SAH, presence of bilateral contusions, and subcortical diffuse axonal injury (DAI) were all associated with AUC of RAP over time. Joncheere-Terpstra testing indicated a statistically significant increase in mean RAP AUC across ordinal categories of the abovementioned associated CT findings.</P><P><B>Conclusions</B></P><P>RAP is associated with cerebral CT injury patterns of diffuse injury and edema, providing some confirmation of its potential measurement of cerebral compensatory reserve in TBI.</P><P><B>Electronic supplementary material</B></P><P>The online version of this article (10.1007/s00701-018-3681-y) contains supplementary material, which is available to authorized users.</P>