Neurocrit Care DOI 10.1007/s12028-015-0146-5
ORIGINAL ARTICLE
Assessment of Cerebrovascular Autoregulation Using Regional Cerebral Blood Flow in Surgically Managed Brain Trauma Patients Ryan Tackla1,2 • Jason M. Hinzman1 • Brandon Foreman3 • Mark Magner1,2 Norberto Andaluz1,2 • Jed A. Hartings1,2
•
Ó Springer Science+Business Media New York 2015
Abstract Background Impairment of cerebrovascular autoregulation is a risk factor for ischemic damage following severe brain injury. Autoregulation can be assessed indirectly using intracranial pressure monitoring as a surrogate of cerebral blood volume, but this measure may not be applicable to patients following decompressive craniectomy. Here, we describe assessment of autoregulation using regional cerebral blood flow (rCBF). Methods In seven patients with severe brain trauma who underwent neurological surgery, a HemedexÒ rCBF probe was placed intraoperatively in peri-lesional tissue. Autoregulation was assessed as a moving Pearson correlation between CPP and rCBF (rCBFx). Results Composite data from all patients showed relatively constant perfusion over a wide CPP range (50–90 mmHg) and a U-shaped autoregulation curve with maximal autoregulation (CPPopt) at 55–60 mmHg. All rCBF values fell below the ischemic threshold (0.3) and intact (Pearson correlation coefficient 50 mmHg, and patients with ICP measurements >20 mmHg for more than 20 min were treated with a standardized local protocol using 3 % hypertonic saline. Neuromonitoring was terminated and devices gently removed at the patient’s bedside when invasive neuromonitoring was no longer clinically required or a maximum of 7 days. No hemorrhagic or infectious complications were associated with the neuromonitoring devices. Clinical outcome at 6 months was assessed by a telephone interview or clinical visit using the extended Glasgow Outcome Score.
The parenchymal thermal diffusion rCBF probe (HemedexÒ) does not provide an uninterrupted perfusion data stream. Lapses in data collection occur during periods of an instable thermal conductive field (K > 6.5), significant pulsatility (PPA >5), and when the patient’s temperature exceeds 39.5 °C. These produce an error message on the monitor and prevent rCBF measures. Recalibrations every 2 h also interrupted continuous data collection. As such, the rCBFx was only calculated during 5 min periods of valid perfusion and CPP data, which was manually cleaned of artifacts (e.g., from arterial flushes). Acquisition of ICP data from the bedside monitors into the research system resulted in poor-quality ICP data (amplitude resolution ± 2 mmHg) that precluded us from calculating a valid pressure reactivity index (PRx). However, this had a minimal effect on CPP calculations, since CPP fluctuations are driven mainly by variations in MAP that are much larger than the limit of ICP resolution.
Data Acquisition and Analysis Statistical Analysis Analog signals of intracranial and arterial pressure were obtained through 8-bit pressure modules from Philips Intellivue bedside monitors, and rCBF data were obtained directly from the analog-out of the HemedexÒ monitor. The rCBF probe was set to recalibrate every 2 h. All physiological signals were acquired in a time-locked fashion and digitized with the g.USBamp (Guger
Statistical analyses were performed using GraphPad Prism 5 (GraphPad Software, Inc., LaJolla, CA). Data are reported as mean ± standard error of the mean. Kruskal– Wallis with Dunn’s Multiple Comparison post hoc tests were used for multiple group comparisons, and P < 0.05 was considered statistically significant.
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Neurocrit Care
A rCBF (ml/100g/min)
60 40 20
Results
35 40-40 45-45 50-50 55-55 60-60 65-65 70-70 75-75 80-80 85-85 90-90 9 105-195 100-100 115-105 110-110 125-155 0- 20 12 5
0
B
0.5
rCBFx
0.4 0.3 0.2 0.1
35 40-40 45-45 50-50 55-55 60-60 65-65 70-70 75-75 80-80 85-85 9 -90 950-9 10 -1 5 0 100-1 0 0 115-1 5 10 0 1 1 -1 5 125-1 5 0- 20 12 5
C
100 80 60 40 20 0
D Composite Autoregulation Curve
60
123
% Time Ideal
50 40
*
30 20 10 0 35 40-40 45-45 50-50 55-55 60-60 65-65 70-70 75-75 80-80 85-85 9 -90 950-9 1 0 -1 5 0 10 0-1 0 0 115-1 5 10 0 11 -1 5 1 2 5-1 5 0- 20 12 5
First we examined the relationship between rCBF and CPP, ‘‘Lassen’s Curve,’’ using composite data from all patients across the entire range of recorded CPPs (35–125 mmHg in 5-mmHg increments) (Fig. 2a). This plot shows relatively constant perfusion over a wide range of CPPs (50–90 mmHg) with a slight upward trend, identifying the range of intact cerebrovascular autoregulation. When CPP fell below this autoregulatory range (18 ml/100 g/min). Above the autoregulatory range (>90 mmHg), rCBF became dependent on CPP likely through force-mediated dilation of the vessels. The composite autoregulation index (rCBFx) over this range of CPPs exhibited a U-shaped curve with increasing rCBFx values at both the lower and upper CPP extremes (Fig. 2b),
#
0.0
% Time Ischemic
Patients’ clinical and neuromonitoring data are summarized in Table 1. Patients had a mean age of 41 ± 4.3 years and 57 % were male. All patients underwent surgical decompression and/or evacuation of mass lesion. Five patients underwent unilateral hemicraniectomy, one had a bifrontal craniectomy, and one patient underwent craniotomy. Decompression with sedation was sufficient to maintain ICP 18 ml/100 g/min) as a function of CPP (% Time Ideal). The CPP with the highest % Time Ideal is 75–80 mmHg (CPPideal indicated by *) for the composite data. Note that CPPideal is greater than CPPopt
CPP (mmHG)
crossing a threshold of 0.3 that has been used previously to indicate impaired autoregulation [5, 24, 25]. Over the range of CPPs with intact autoregulation (50–90 mmHg), the
Neurocrit Care
rCBFx was maintained below this threshold with a clear trough corresponding to an optimal CPP range for preserved autoregulation. This range (55–60 mmHg) was defined as the CPPopt for the composite dataset. Low CPP is Associated with Ischemia Based on the impaired autoregulation (rCBFx >0.3) observed when CPP fell below 45 mmHg, we expected an increase in the incidence of cerebral ischemia due to maximal vessel dilatation and a passive perfusion/pressure relationship. Figure 2c shows the proportion of rCBF values 18 ml/100 g/min) and autoregulation was intact (rCBFx 50 mmHg. However, we found that individualized CPPopt, the CPP range with maximal autoregulation, was above the recommended 70 mmHg threshold in 4 of 7 cases. Prior studies have raised concerns that targeting higher CPP may increase complications, such as acute respiratory distress syndrome [27]. Yet a growing body of evidence suggests that maintaining CPP within a narrow range based on the individualized CPPopt may lead to significant improvements in long-term outcomes after severe TBI [9, 14]. These data suggest that patients may benefit from more narrowly targeted, personalized management within the recommended 50–70 mmHg CPP range, and in some cases above it. CPP-targeted management is based solely on pressure– volume dynamics, but has not previously been linked with tissue perfusion. We computed a measure of CPPideal that
identifies the CPP range in which both autoregulation is maximized and ischemia is minimized. In 4 of 7 patients CPPideal was higher than CPPopt, and the CPPideal was greater than 70 mmHg in a majority of the patients. Obtaining absolute measures of tissue perfusion is a distinct advantage of using the rCBF monitor for autoregulatory assessment, and targeting CPP values based on consideration of both factors may optimize the microvascular circulation to meet energy demands in changing conditions. Study Limitations This was a small study of only seven severe TBI patients, all of whom underwent surgical decompression or lesion evacuation; as such, the deleterious effects of maintaining CPP above the upper limit of autoregulation were less obvious as surgery was adequate to maintain ICPs in their normal physiological range (0.3) used here was based on prior work [5, 24, 25] as our sample size was too small to empirically determine an optimal threshold value. Nonetheless, our data (Fig. 2a,b) suggest that 0.3 is likely near the actual value, and minor adjustments to this threshold would not likely affect our qualitative results. Lastly, this was a retrospective analysis and required timeintensive data processing to manually remove artifacts and lapses in data collection from auto-calibration of the rCBF probe. The development and validation of automated software is still needed so that data processing can be performed for use of autoregulatory assessment in active, personalized CPP management. Conclusions rCBF monitoring provides a continuous and direct assessment of cerebrovascular autoregulation that could be used to personalize CPP management to maximize autoregulation and avoid ischemia. Future studies are required to determine if maintaining the CPP near the CPPideal
123
Neurocrit Care
enhances the ability of microvascular circulation to meet the energy demands of the brain tissue (i.e., lactate/pyruvate ratio) and improves long-term outcomes. Acknowledgments This work was funded by the Mayfield Education and Research Foundation and thermal diffusion probes were donated by Hemedex, Inc. Conflict of interest On behalf of all authors, the corresponding author states that there are no conflict of interest.
References 1. Werner C, Engelhard K. Pathophysiology of traumatic brain injury. Br J Anaesth. 2007;99:4–9. 2. Paulson OB, Strandgaard S, Edvinsson L. Cerebral autoregulation. Cerebrovasc Brain Metab Rev. 1990;2:161–92. 3. Bouma GJ, Muizelaar JP, Bandoh K, Marmarou A. Blood pressure and intracranial pressure-volume dynamics in severe head injury: relationship with cerebral blood flow. J Neurosurg. 1992;77:15–9. 4. Czosnyka M, Smielewski P, Piechnik S, Steiner LA, Pickard JD. Cerebral autoregulation following head injury. J Neurosurg. 2001;95:756–63. 5. Zweifel C, Lavinio A, Steiner LA, Radolovich D, Smielewski P, Timofeev I, Hiler M, Balestreri M, Kirkpatrick PJ, Pickard JD, Hutchinson P, Czosnyka M. Continuous monitoring of cerebrovascular pressure reactivity in patients with head injury. Neurosurg Focus. 2008;25:E2. 6. Lam JM, Hsiang JN, Poon WS. Monitoring of autoregulation using laser Doppler flowmetry in patients with head injury. J Neurosurg. 1997;86:438–45. 7. Jaeger M, Schuhmann MU, Soehle M, Meixensberger J. Continuous assessment of cerebrovascular autoregulation after traumatic brain injury using brain tissue oxygen pressure reactivity. Crit Care Med. 2006;34:1783–8. 8. Reinert M, Andres RH, Fuhrer M, Muller A, Schaller B, Widmer H. Online correlation of spontaneous arterial and intracranial pressure fluctuations in patients with diffuse severe head injury. Neurol Res. 2007;29:455–62. 9. Steiner LA, Czosnyka M, Piechnik SK, Smielewski P, Chatfield D, Menon DK, Pickard JD. Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury. Crit Care Med. 2002;30:733–8. 10. Dewey RC, Pieper HP, Hunt WE. Experimental cerebral hemodynamics. Vasomotor tone, critical closing pressure, and vascular bed resistance. J Neurosurg. 1974;41:597–606. 11. Czosnyka M, Miller C, (2014) Monitoring of Cerebral Autoregulation. Neurocrit Care. 12. Steiner LA, Coles JP, Johnston AJ, Chatfield DA, Smielewski P, Fryer TD, Aigbirhio FI, Clark JC, Pickard JD, Menon DK, Czosnyka M. Assessment of cerebrovascular autoregulation in head-injured patients: a validation study. Stroke. 2003;34: 2404–9. 13. Czosnyka M, Smielewski P, Kirkpatrick P, Piechnik S, Laing R, Pickard JD. Continuous monitoring of cerebrovascular pressurereactivity in head injury. Acta Neurochir Suppl. 1998;71:74–7.
123
14. Aries MJ, Czosnyka M, Budohoski KP, Steiner LA, Lavinio A, Kolias AG, Hutchinson PJ, Brady KM, Menon DK, Pickard JD, Smielewski P. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit Care Med. 2012;40:2456–63. 15. Timofeev I, Czosnyka M, Nortje J, Smielewski P, Kirkpatrick P, Gupta A, Hutchinson P. Effect of decompressive craniectomy on intracranial pressure and cerebrospinal compensation following traumatic brain injury. J Neurosurg. 2008;108:66–73. 16. Czosnyka M, Smielewski P, Kirkpatrick P, Menon DK, Pickard JD. Monitoring of cerebral autoregulation in head-injured patients. Stroke. 1996;27:1829–34. 17. Soehle M, Jaeger M, Meixensberger J. Online assessment of brain tissue oxygen autoregulation in traumatic brain injury and subarachnoid hemorrhage. Neurol Res. 2003;25:411–7. 18. Radolovich DK, Czosnyka M, Timofeev I, Lavinio A, Hutchinson P, Gupta A, Pickard JD, Smielewski P. Reactivity of brain tissue oxygen to change in cerebral perfusion pressure in head injured patients. Neurocrit Care. 2009;10:274–9. 19. Zweifel C, Castellani G, Czosnyka M, Helmy A, Manktelow A, Carrera E, Brady KM, Hutchinson PJ, Menon DK, Pickard JD, Smielewski P. Noninvasive monitoring of cerebrovascular reactivity with near infrared spectroscopy in head-injured patients. J Neurotrauma. 2010;27:1951–8. 20. Vajkoczy P, Roth H, Horn P, Lucke T, Thome C, Hubner U, Martin GT, Zappletal C, Klar E, Schilling L, Schmiedek P. Continuous monitoring of regional cerebral blood flow: experimental and clinical validation of a novel thermal diffusion microprobe. J Neurosurg. 2000;93:265–74. 21. Dias C, Silva MJ, Pereira E, Monteiro E, Maia I, Barbosa S, Silva S, Honrado T, Cerejo A, Aries MJ, Smielewski P, Paiva JA, Czosnyka M, (2015) Optimal cerebral perfusion pressure management at bedside: a single-center pilot study. Neurocrit Care. 22. Bratton SL, Chestnut RM, Ghajar J, McConnell Hammond FF, Harris OA, Hartl R, Manley GT, Nemecek A, Newell DW, Rosenthal G, Schouten J, Shutter L, Timmons SD, Ullman JS, Videtta W, Wilberger JE, Wright DW. Guidelines for the management of severe traumatic brain injury IX. Cerebral perfusion thresholds. J Neurotrauma. 2007;24(Suppl 1):S59–64. 23. Wilson JA, Shutter LA, Hartings JA. COSBID-M3: a platform for multimodal monitoring, data collection, and research in neurocritical care. Acta Neurochir Suppl. 2013;115:67–74. 24. Lang EW, Mehdorn HM, Dorsch NW, Czosnyka M. Continuous monitoring of cerebrovascular autoregulation: a validation study. J Neurol Neurosurg Psychiatry. 2002;72:583–6. 25. Sorrentino E, Budohoski KP, Kasprowicz M, Smielewski P, Matta B, Pickard JD, Czosnyka M. Critical thresholds for transcranial Doppler indices of cerebral autoregulation in traumatic brain injury. Neurocrit Care. 2011;14:188–93. 26. Naqvi J, Yap KH, Ahmad G, Ghosh J. Transcranial Doppler ultrasound: a review of the physical principles and major applications in critical care. Int J Vasc Med. 2013;2013:629378. 27. Juul N, Morris GF, Marshall SB, Marshall LF. Intracranial hypertension and cerebral perfusion pressure: influence on neurological deterioration and outcome in severe head injury. The Executive Committee of the International Selfotel Trial. J Neurosurg. 2000;92:1–6.
ORIGINAL ARTICLE
Assessment of Cerebrovascular Autoregulation Using Regional Cerebral Blood Flow in Surgically Managed Brain Trauma Patients Ryan Tackla1,2 • Jason M. Hinzman1 • Brandon Foreman3 • Mark Magner1,2 Norberto Andaluz1,2 • Jed A. Hartings1,2
•
Ó Springer Science+Business Media New York 2015
Abstract Background Impairment of cerebrovascular autoregulation is a risk factor for ischemic damage following severe brain injury. Autoregulation can be assessed indirectly using intracranial pressure monitoring as a surrogate of cerebral blood volume, but this measure may not be applicable to patients following decompressive craniectomy. Here, we describe assessment of autoregulation using regional cerebral blood flow (rCBF). Methods In seven patients with severe brain trauma who underwent neurological surgery, a HemedexÒ rCBF probe was placed intraoperatively in peri-lesional tissue. Autoregulation was assessed as a moving Pearson correlation between CPP and rCBF (rCBFx). Results Composite data from all patients showed relatively constant perfusion over a wide CPP range (50–90 mmHg) and a U-shaped autoregulation curve with maximal autoregulation (CPPopt) at 55–60 mmHg. All rCBF values fell below the ischemic threshold (0.3) and intact (Pearson correlation coefficient 50 mmHg, and patients with ICP measurements >20 mmHg for more than 20 min were treated with a standardized local protocol using 3 % hypertonic saline. Neuromonitoring was terminated and devices gently removed at the patient’s bedside when invasive neuromonitoring was no longer clinically required or a maximum of 7 days. No hemorrhagic or infectious complications were associated with the neuromonitoring devices. Clinical outcome at 6 months was assessed by a telephone interview or clinical visit using the extended Glasgow Outcome Score.
The parenchymal thermal diffusion rCBF probe (HemedexÒ) does not provide an uninterrupted perfusion data stream. Lapses in data collection occur during periods of an instable thermal conductive field (K > 6.5), significant pulsatility (PPA >5), and when the patient’s temperature exceeds 39.5 °C. These produce an error message on the monitor and prevent rCBF measures. Recalibrations every 2 h also interrupted continuous data collection. As such, the rCBFx was only calculated during 5 min periods of valid perfusion and CPP data, which was manually cleaned of artifacts (e.g., from arterial flushes). Acquisition of ICP data from the bedside monitors into the research system resulted in poor-quality ICP data (amplitude resolution ± 2 mmHg) that precluded us from calculating a valid pressure reactivity index (PRx). However, this had a minimal effect on CPP calculations, since CPP fluctuations are driven mainly by variations in MAP that are much larger than the limit of ICP resolution.
Data Acquisition and Analysis Statistical Analysis Analog signals of intracranial and arterial pressure were obtained through 8-bit pressure modules from Philips Intellivue bedside monitors, and rCBF data were obtained directly from the analog-out of the HemedexÒ monitor. The rCBF probe was set to recalibrate every 2 h. All physiological signals were acquired in a time-locked fashion and digitized with the g.USBamp (Guger
Statistical analyses were performed using GraphPad Prism 5 (GraphPad Software, Inc., LaJolla, CA). Data are reported as mean ± standard error of the mean. Kruskal– Wallis with Dunn’s Multiple Comparison post hoc tests were used for multiple group comparisons, and P < 0.05 was considered statistically significant.
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Neurocrit Care
A rCBF (ml/100g/min)
60 40 20
Results
35 40-40 45-45 50-50 55-55 60-60 65-65 70-70 75-75 80-80 85-85 90-90 9 105-195 100-100 115-105 110-110 125-155 0- 20 12 5
0
B
0.5
rCBFx
0.4 0.3 0.2 0.1
35 40-40 45-45 50-50 55-55 60-60 65-65 70-70 75-75 80-80 85-85 9 -90 950-9 10 -1 5 0 100-1 0 0 115-1 5 10 0 1 1 -1 5 125-1 5 0- 20 12 5
C
100 80 60 40 20 0
D Composite Autoregulation Curve
60
123
% Time Ideal
50 40
*
30 20 10 0 35 40-40 45-45 50-50 55-55 60-60 65-65 70-70 75-75 80-80 85-85 9 -90 950-9 1 0 -1 5 0 10 0-1 0 0 115-1 5 10 0 11 -1 5 1 2 5-1 5 0- 20 12 5
First we examined the relationship between rCBF and CPP, ‘‘Lassen’s Curve,’’ using composite data from all patients across the entire range of recorded CPPs (35–125 mmHg in 5-mmHg increments) (Fig. 2a). This plot shows relatively constant perfusion over a wide range of CPPs (50–90 mmHg) with a slight upward trend, identifying the range of intact cerebrovascular autoregulation. When CPP fell below this autoregulatory range (18 ml/100 g/min). Above the autoregulatory range (>90 mmHg), rCBF became dependent on CPP likely through force-mediated dilation of the vessels. The composite autoregulation index (rCBFx) over this range of CPPs exhibited a U-shaped curve with increasing rCBFx values at both the lower and upper CPP extremes (Fig. 2b),
#
0.0
% Time Ischemic
Patients’ clinical and neuromonitoring data are summarized in Table 1. Patients had a mean age of 41 ± 4.3 years and 57 % were male. All patients underwent surgical decompression and/or evacuation of mass lesion. Five patients underwent unilateral hemicraniectomy, one had a bifrontal craniectomy, and one patient underwent craniotomy. Decompression with sedation was sufficient to maintain ICP 18 ml/100 g/min) as a function of CPP (% Time Ideal). The CPP with the highest % Time Ideal is 75–80 mmHg (CPPideal indicated by *) for the composite data. Note that CPPideal is greater than CPPopt
CPP (mmHG)
crossing a threshold of 0.3 that has been used previously to indicate impaired autoregulation [5, 24, 25]. Over the range of CPPs with intact autoregulation (50–90 mmHg), the
Neurocrit Care
rCBFx was maintained below this threshold with a clear trough corresponding to an optimal CPP range for preserved autoregulation. This range (55–60 mmHg) was defined as the CPPopt for the composite dataset. Low CPP is Associated with Ischemia Based on the impaired autoregulation (rCBFx >0.3) observed when CPP fell below 45 mmHg, we expected an increase in the incidence of cerebral ischemia due to maximal vessel dilatation and a passive perfusion/pressure relationship. Figure 2c shows the proportion of rCBF values 18 ml/100 g/min) and autoregulation was intact (rCBFx 50 mmHg. However, we found that individualized CPPopt, the CPP range with maximal autoregulation, was above the recommended 70 mmHg threshold in 4 of 7 cases. Prior studies have raised concerns that targeting higher CPP may increase complications, such as acute respiratory distress syndrome [27]. Yet a growing body of evidence suggests that maintaining CPP within a narrow range based on the individualized CPPopt may lead to significant improvements in long-term outcomes after severe TBI [9, 14]. These data suggest that patients may benefit from more narrowly targeted, personalized management within the recommended 50–70 mmHg CPP range, and in some cases above it. CPP-targeted management is based solely on pressure– volume dynamics, but has not previously been linked with tissue perfusion. We computed a measure of CPPideal that
identifies the CPP range in which both autoregulation is maximized and ischemia is minimized. In 4 of 7 patients CPPideal was higher than CPPopt, and the CPPideal was greater than 70 mmHg in a majority of the patients. Obtaining absolute measures of tissue perfusion is a distinct advantage of using the rCBF monitor for autoregulatory assessment, and targeting CPP values based on consideration of both factors may optimize the microvascular circulation to meet energy demands in changing conditions. Study Limitations This was a small study of only seven severe TBI patients, all of whom underwent surgical decompression or lesion evacuation; as such, the deleterious effects of maintaining CPP above the upper limit of autoregulation were less obvious as surgery was adequate to maintain ICPs in their normal physiological range (0.3) used here was based on prior work [5, 24, 25] as our sample size was too small to empirically determine an optimal threshold value. Nonetheless, our data (Fig. 2a,b) suggest that 0.3 is likely near the actual value, and minor adjustments to this threshold would not likely affect our qualitative results. Lastly, this was a retrospective analysis and required timeintensive data processing to manually remove artifacts and lapses in data collection from auto-calibration of the rCBF probe. The development and validation of automated software is still needed so that data processing can be performed for use of autoregulatory assessment in active, personalized CPP management. Conclusions rCBF monitoring provides a continuous and direct assessment of cerebrovascular autoregulation that could be used to personalize CPP management to maximize autoregulation and avoid ischemia. Future studies are required to determine if maintaining the CPP near the CPPideal
123
Neurocrit Care
enhances the ability of microvascular circulation to meet the energy demands of the brain tissue (i.e., lactate/pyruvate ratio) and improves long-term outcomes. Acknowledgments This work was funded by the Mayfield Education and Research Foundation and thermal diffusion probes were donated by Hemedex, Inc. Conflict of interest On behalf of all authors, the corresponding author states that there are no conflict of interest.
References 1. Werner C, Engelhard K. Pathophysiology of traumatic brain injury. Br J Anaesth. 2007;99:4–9. 2. Paulson OB, Strandgaard S, Edvinsson L. Cerebral autoregulation. Cerebrovasc Brain Metab Rev. 1990;2:161–92. 3. Bouma GJ, Muizelaar JP, Bandoh K, Marmarou A. Blood pressure and intracranial pressure-volume dynamics in severe head injury: relationship with cerebral blood flow. J Neurosurg. 1992;77:15–9. 4. Czosnyka M, Smielewski P, Piechnik S, Steiner LA, Pickard JD. Cerebral autoregulation following head injury. J Neurosurg. 2001;95:756–63. 5. Zweifel C, Lavinio A, Steiner LA, Radolovich D, Smielewski P, Timofeev I, Hiler M, Balestreri M, Kirkpatrick PJ, Pickard JD, Hutchinson P, Czosnyka M. Continuous monitoring of cerebrovascular pressure reactivity in patients with head injury. Neurosurg Focus. 2008;25:E2. 6. Lam JM, Hsiang JN, Poon WS. Monitoring of autoregulation using laser Doppler flowmetry in patients with head injury. J Neurosurg. 1997;86:438–45. 7. Jaeger M, Schuhmann MU, Soehle M, Meixensberger J. Continuous assessment of cerebrovascular autoregulation after traumatic brain injury using brain tissue oxygen pressure reactivity. Crit Care Med. 2006;34:1783–8. 8. Reinert M, Andres RH, Fuhrer M, Muller A, Schaller B, Widmer H. Online correlation of spontaneous arterial and intracranial pressure fluctuations in patients with diffuse severe head injury. Neurol Res. 2007;29:455–62. 9. Steiner LA, Czosnyka M, Piechnik SK, Smielewski P, Chatfield D, Menon DK, Pickard JD. Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury. Crit Care Med. 2002;30:733–8. 10. Dewey RC, Pieper HP, Hunt WE. Experimental cerebral hemodynamics. Vasomotor tone, critical closing pressure, and vascular bed resistance. J Neurosurg. 1974;41:597–606. 11. Czosnyka M, Miller C, (2014) Monitoring of Cerebral Autoregulation. Neurocrit Care. 12. Steiner LA, Coles JP, Johnston AJ, Chatfield DA, Smielewski P, Fryer TD, Aigbirhio FI, Clark JC, Pickard JD, Menon DK, Czosnyka M. Assessment of cerebrovascular autoregulation in head-injured patients: a validation study. Stroke. 2003;34: 2404–9. 13. Czosnyka M, Smielewski P, Kirkpatrick P, Piechnik S, Laing R, Pickard JD. Continuous monitoring of cerebrovascular pressurereactivity in head injury. Acta Neurochir Suppl. 1998;71:74–7.
123
14. Aries MJ, Czosnyka M, Budohoski KP, Steiner LA, Lavinio A, Kolias AG, Hutchinson PJ, Brady KM, Menon DK, Pickard JD, Smielewski P. Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury. Crit Care Med. 2012;40:2456–63. 15. Timofeev I, Czosnyka M, Nortje J, Smielewski P, Kirkpatrick P, Gupta A, Hutchinson P. Effect of decompressive craniectomy on intracranial pressure and cerebrospinal compensation following traumatic brain injury. J Neurosurg. 2008;108:66–73. 16. Czosnyka M, Smielewski P, Kirkpatrick P, Menon DK, Pickard JD. Monitoring of cerebral autoregulation in head-injured patients. Stroke. 1996;27:1829–34. 17. Soehle M, Jaeger M, Meixensberger J. Online assessment of brain tissue oxygen autoregulation in traumatic brain injury and subarachnoid hemorrhage. Neurol Res. 2003;25:411–7. 18. Radolovich DK, Czosnyka M, Timofeev I, Lavinio A, Hutchinson P, Gupta A, Pickard JD, Smielewski P. Reactivity of brain tissue oxygen to change in cerebral perfusion pressure in head injured patients. Neurocrit Care. 2009;10:274–9. 19. Zweifel C, Castellani G, Czosnyka M, Helmy A, Manktelow A, Carrera E, Brady KM, Hutchinson PJ, Menon DK, Pickard JD, Smielewski P. Noninvasive monitoring of cerebrovascular reactivity with near infrared spectroscopy in head-injured patients. J Neurotrauma. 2010;27:1951–8. 20. Vajkoczy P, Roth H, Horn P, Lucke T, Thome C, Hubner U, Martin GT, Zappletal C, Klar E, Schilling L, Schmiedek P. Continuous monitoring of regional cerebral blood flow: experimental and clinical validation of a novel thermal diffusion microprobe. J Neurosurg. 2000;93:265–74. 21. Dias C, Silva MJ, Pereira E, Monteiro E, Maia I, Barbosa S, Silva S, Honrado T, Cerejo A, Aries MJ, Smielewski P, Paiva JA, Czosnyka M, (2015) Optimal cerebral perfusion pressure management at bedside: a single-center pilot study. Neurocrit Care. 22. Bratton SL, Chestnut RM, Ghajar J, McConnell Hammond FF, Harris OA, Hartl R, Manley GT, Nemecek A, Newell DW, Rosenthal G, Schouten J, Shutter L, Timmons SD, Ullman JS, Videtta W, Wilberger JE, Wright DW. Guidelines for the management of severe traumatic brain injury IX. Cerebral perfusion thresholds. J Neurotrauma. 2007;24(Suppl 1):S59–64. 23. Wilson JA, Shutter LA, Hartings JA. COSBID-M3: a platform for multimodal monitoring, data collection, and research in neurocritical care. Acta Neurochir Suppl. 2013;115:67–74. 24. Lang EW, Mehdorn HM, Dorsch NW, Czosnyka M. Continuous monitoring of cerebrovascular autoregulation: a validation study. J Neurol Neurosurg Psychiatry. 2002;72:583–6. 25. Sorrentino E, Budohoski KP, Kasprowicz M, Smielewski P, Matta B, Pickard JD, Czosnyka M. Critical thresholds for transcranial Doppler indices of cerebral autoregulation in traumatic brain injury. Neurocrit Care. 2011;14:188–93. 26. Naqvi J, Yap KH, Ahmad G, Ghosh J. Transcranial Doppler ultrasound: a review of the physical principles and major applications in critical care. Int J Vasc Med. 2013;2013:629378. 27. Juul N, Morris GF, Marshall SB, Marshall LF. Intracranial hypertension and cerebral perfusion pressure: influence on neurological deterioration and outcome in severe head injury. The Executive Committee of the International Selfotel Trial. J Neurosurg. 2000;92:1–6.
