scholarly journals Estimation of critical closing pressure and cerebral perfusion pressure using transcranial Doppler

2003 ◽  
Vol 90 (3) ◽  
pp. 396-397 ◽  
Author(s):  
L.A. Steiner ◽  
M. Czosnyka
2015 ◽  
Vol 123 (3) ◽  
pp. 638-648 ◽  
Author(s):  
Georgios V. Varsos ◽  
Angelos G. Kolias ◽  
Peter Smielewski ◽  
Ken M. Brady ◽  
Vassilis G. Varsos ◽  
...  

OBJECT Cerebral blood flow is associated with cerebral perfusion pressure (CPP), which is clinically monitored through arterial blood pressure (ABP) and invasive measurements of intracranial pressure (ICP). Based on critical closing pressure (CrCP), the authors introduce a novel method for a noninvasive estimator of CPP (eCPP). METHODS Data from 280 head-injured patients with ABP, ICP, and transcranial Doppler ultrasonography measurements were retrospectively examined. CrCP was calculated with a noninvasive version of the cerebrovascular impedance method. The eCPP was refined with a predictive regression model of CrCP-based estimation of ICP from known ICP using data from 232 patients, and validated with data from the remaining 48 patients. RESULTS Cohort analysis showed eCPP to be correlated with measured CPP (R = 0.851, p < 0.001), with a mean ± SD difference of 4.02 ± 6.01 mm Hg, and 83.3% of the cases with an estimation error below 10 mm Hg. eCPP accurately predicted low CPP (< 70 mm Hg) with an area under the curve of 0.913 (95% CI 0.883–0.944). When each recording session of a patient was assessed individually, eCPP could predict CPP with a 95% CI of the SD for estimating CPP between multiple recording sessions of 1.89–5.01 mm Hg. CONCLUSIONS Overall, CrCP-based eCPP was strongly correlated with invasive CPP, with sensitivity and specificity for detection of low CPP that show promise for clinical use.


2002 ◽  
Vol 96 (3) ◽  
pp. 595-599 ◽  
Author(s):  
Christof Thees ◽  
Martin Scholz ◽  
Carlo Schaller ◽  
Annette Gass ◽  
Christos Pavlidis ◽  
...  

Background The driving pressure gradient for cerebral perfusion is the difference between mean arterial pressure (MAP) and critical closing pressure (CCP = zero flow pressure). Therefore, determination of the difference between MAP and CCP should provide an appropriate monitoring of the effective cerebral perfusion pressure (CPP(eff)). Based on this concept, the authors compared conventional measurements of cerebral perfusion pressure by MAP and intracranial pressure (CPP(ICP)) with CPP(eff). Methods Simultaneous synchronized recordings of pressure waveforms of the radial artery and blood flow velocities of the middle cerebral artery were performed in 70 head trauma patients. CCP was calculated from pressure-flow velocity plots by linear extrapolation to zero flow. Results Intracranial pressure measured by intraventricular probes and CCP ranged from 3 to 71 and 4 to 70 mmHg, respectively. Linear correlation between ICP and CCP was r = 0.91. CPP(ICP) was 77 +/- 20 mmHg and did not differ from CPP(eff); linear correlation was r = 0.92. However, limits of agreement were only +/- 16.2 mmHg. Therefore, in 51.4% of the patients, CPP(ICP) overestimated CPP(eff) by 19.8 mmHg at most. Conclusion Assuming that CPP(eff) (MAP - CCP) takes into account more determinants of cerebral downstream pressure, in individual cases, the actual gold standard of CPP determination (MAP - ICP) might overestimate the CPP(eff) of therapeutic significance.


1988 ◽  
Vol 68 (5) ◽  
pp. 745-751 ◽  
Author(s):  
Werner Hassler ◽  
Helmuth Steinmetz ◽  
Jan Gawlowski

✓ Transcranial Doppler ultrasonography was used to monitor 71 patients suffering from intracranial hypertension with subsequent brain death. Among these, 29 patients were also assessed for systemic arterial pressure and epidural intracranial pressure, so that a correlation between cerebral perfusion pressure and the Doppler ultrasonography waveforms could be established. Four-vessel angiography was also performed in 33 patients after clinical brain death. With increasing intracranial pressure, the transcranial Doppler ultrasonography waveforms exhibited different characteristic high-resistance profiles with first low, then zero, and then reversed diastolic flow velocities, depending on the relationship between intracranial pressure and blood pressure (that is, cerebral perfusion pressure). This study shows that transcranial. Doppler ultrasonography may be used to assess the degree of intracranial hypertension. This technique further provides a practicable, noninvasive bedside monitor of therapeutic measures.


2001 ◽  
Vol 20 (1) ◽  
pp. 139-140
Author(s):  
Michael A. Belfort ◽  
Cathy Tooke-Miller ◽  
Michael Varner ◽  
George Saade ◽  
Charlotta Grunewald ◽  
...  

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_4) ◽  
Author(s):  
Minjung K Chae ◽  
Sung Eun Lee ◽  
Sumin Cho ◽  
Taeyoung Kim ◽  
Dukyong Yoon

Introduction: Hypoxic ischemic brain injury (HIBI) is the leading cause of mortality and long-term neurologic disability in survivors of cardiac arrest. Recently, the role of cerebral monitoring is emphasized for individualizing therapy and mitigating secondary brain injury in HIBI patients after return of spontaneous circulation (ROSC). The first step of cerebral monitoring is checking the driving force by cerebral perfusion pressure (CPP). However, as CPP is calculated by mean arterial pressure (MAP) minus intracranial pressure (ICP), the process of obtaining ICP is invasive. Noninvasive CPP can be estimated by parameters obtained from transcranial doppler (TCD). Therefore, we aimed to investigate non-invasively measured CPP from TCD and its association with neurologic outcome in post cardiac arrest patients that underwent targeted temperature management (TTM). Methods: This retrospective single-center study included patients who had been treated with TTM following cardiac arrest and who underwent TCD evaluation between July 2017 and July 2019. We aimed to perform TCD evaluation within 48h of ROSC, but sometimes this could not be achieved due to limited resources. Patients with TCD that was performed after 72 hours were excluded. The MFV was calculated using the peak systolic flow velocity (PSV) and the end-diastolic flow velocity (EDV) as below. Two methods of estimating CPP non-invasively was calculated as below.MFV = PSV+(EDVх2) / 3 eCPP_A= MAP*diastolic FVmca/MFVmca + 14eCPP_B= MFVmca*(MAP-DBP)/FVmean-FVdia Results: Table 1. Baseline characteristics of study population Data are presented as mean (standard deviation), number (%) or median (interquartile range).OHCA, out of hospital cardiac arrest; CPR, cardiopulmonary resuscitation; AED, automated external defibrillator; TCD, transcranial doppler; CPP, cerebral perfusion pressure. Table 2. Cut off values and diagnostic values in predicting poor neurologic outcome with 100% specificityCPP, cerebral perfusion pressure. Conclusion: eCPP cut off values of <50 mmHg and <60mmHg predicted poor neurological outcome with high specificity. This study suggests that eCPP obtained from TCD may be feasible to predict neurologic outcome.


2000 ◽  
Vol 19 (3) ◽  
pp. 331-340 ◽  
Author(s):  
Michael A. Belfort ◽  
Cathy Tooke-Miller ◽  
Michael Varner ◽  
George Saade ◽  
Charlotta Grunewald ◽  
...  

2017 ◽  
Vol 14 (02/03) ◽  
pp. 152-155
Author(s):  
Rajagopal Ramanan ◽  
Mathew Joseph

Abstract Title Utility of transcranial Doppler (TCD) in estimating cerebral perfusion pressure (eCPP) in traumatic brain injury—a prospective observational trial. Aim To validate the utility of a noninvasive technique of eCPP estimation using transcranial Doppler (TCD). Materials and Methods Eighteen patients with severe traumatic brain injury (TBI) requiring intracranial pressure (ICP) monitoring as per the Brain Trauma Foundation guidelines were prospectively recruited for the study. ICP was measured in all patients using an intraventricular catheter. Mean arterial pressure (MAP) was recorded from an intra-arterial catheter. Cerebral perfusion pressure (CPP) was calculated as the difference between MAP and ICP. Middle cerebral blood flow velocities were recorded using TCD, and CPP was estimated from the middle cerebral artery (MCA) flow velocities (eCPP) using the formula eCPP = (MAP × end diastolic velocity [EDV]/mean velocity [MV]) + 14. Total 185 simultaneous readings of CPP and eCPP were available for analysis. Reliability statistics between CPP and eCPP were computed to calculate the intraclass correlation (ICC). Results The average CPP measured using intraventricular catheter was 73.2 (+/−12.4), and the mean estimated eCPP was 76.7 (+/−10.9). We found a very good Pearson's correlation between CPP and eCPP (r = 0.743) with a Cronbach's α of 0.843. In 86.2% of examinations, the estimation error of measuring CPP was within 10 mm Hg, and in 93.1% examinations, it was within 15 mm Hg. Conclusion eCPP estimated using TCD can serve as reliable noninvasive alternative in situations in which ICP monitoring is not available, even in moderate or mild head injury.


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