The radiopaque dye was extracted over an approximately 30-second period. ICP generally decreased to preballoon inflation levels; from 9.56 ± 3.56 mm Hg to 8.1 ± 3.47 mm Hg. Because of the small size of the balloon, this pressure change was not statistically significant but was detectable. Predeflation pressure was higher than immediate postballoon inflation. Automatic ROI selection was possible in all cases except experiment 8. Experiment 8 suffered from CSF leaking onto the electrodes that changed the imaging domain, causing erroneous data to be collected during deflation and was omitted from the mean calculation. This, however, did not affect the other manipulations performed on experiment 8. Mean ROI Δσ increased to +9.4 ± 8.8 mS/m with experiment 8 omitted (Fig. 4, Table 2). Again, the SD of the means from the group of all experiments was high, but the SD within a single experiment was quite low. All 7 remaining animal experiments showed this manipulation to be statistically significant at a P < 0.0001 level. The ROI locations appeared similarly located in the central left hemisphere of the reconstruction.
Intraventricular Injection of Blood
Following the injection of 1 mL of unclotted arterial blood into the white matter above the left lateral ventricle, ICP increased from an average baseline of 9.1 ± 3.1 mm Hg to a peak of 24.4 ± 7.17 mm Hg. It stabilized initially then began to climb after a few minutes. A marked increase in conductivity is seen as a red circular region in the EIT tomogram (Fig. 5). The mean conductivity difference increase for the pigs was +19.5 ± 11.5 mS/m (Table 3). The SD of the means from the group of all experiments seen in the table is high, but low within single experiments as is expected. A decrease in conductivity is seen in the cortical margins on the same side. Six animal experiments showed this manipulation to be statistically significant (P < 0.0001), with 2 experiment outliers being omitted. Although significant in the ROI test, the conductivity change of experiments 1 and 5 were opposite in magnitude to the other experiments and not physiologically realistic. These 2 results were therefore omitted from the mean. The ROIs in this manipulation appear more central to the reconstruction than in the mass effect injuries due to migration and distribution of the blood into the subdural space.
Cerebral Blood Flow Arrest by Heart Stoppage
Euthanasia by IV injection of Euthasol demonstrated an almost immediate, marked, and symmetric decrease in cerebral conductivity over the entire image for each animal (Fig. 7); ROI analysis was not used because the effect was global. The decrease in conductivity continued for up to 10 minutes postmortem until data recording ended. ICP after a minimum of 5 minutes postmortem was 6.38 ± 3.01 mm Hg. Mean Δσ between the period just before euthanasia and at a minimum of 5 minutes postmortem throughout the region sensed was −12.6 ± 13.2 mS/m.
This study investigated pathophysiologic effects common to severe human head injury to determine sensitivity to detection by enhanced EIT using a central electrode that doubled as an ICP sensor. The manipulations included mass effect by intraparenchymal balloon inflation, injection of freshly drawn, nonclotted arterial blood into the parenchyma to simulate delayed intracerebral hemorrhage, and cessation of cerebral blood flow by heart stoppage during euthanasia. Each of these effects showed a statistically significant change in electrical conductivity and rendered anatomically correct regions of change in the axial tomogram. It is interesting to note that the balloon mass effect and localization was statistically detectable with volume injections of only 0.15 mL contrast dye, but the rise in ICP was both statistically and clinically insignificant (7.9–8.8 mm Hg). Although one could expect a much larger ICP rise if a 1-mL volume of dye were injected (this remains to be established in subsequent studies), this sensitivity points to the potential usefulness of the difference imaging approach for early detection of worrisome change. It was expected, and we believe, that the rapid inflation of the balloon was injurious to the tissue promoting cerebral edema, which was evidenced by gradual increases in ICP until the time of balloon deflation.
Despite the statistically significant changes observed, there is relatively large variability in conductivity difference for the group of experiments (i.e., the means between animals undergoing the same injury do not tightly cluster). This is simply due to the fact that no 2 experimental setups are alike. However, variability within a single experiment is potentially attributable to several factors such as drift, which may be inherent to the EIT instrumentation, electrode drift due to gel ionic transport, and cable movement.
EIT system drift is not a likely source based on our previous laboratory investigations of saline tank phantoms and resistor phantoms that showed good repeatability in measurements over many hours, an essential requirement for difference imaging. Electrode drift due to gel ionic transport across the skin or oxidation could have influenced stability if data sets were far removed temporally from the event of interest. Such drift usually occurs over extended periods of time. Each experimental manipulation was ≤10 minutes and not far removed from the baseline measurements. Cable movement is also not a significant contributor because each cable is actively shielded and carefully fixed in place during the experiments.
The most dominant cause of variability in conductivity measurements within the 10 windows is likely attributable to respiratory effects. Depending on ventilator settings, 100 EIT signal averages may cover a fraction of or >1 breathing cycle. A bias in the averaged data will occur when less than a whole breathing cycle is used for analysis or the effects are otherwise mitigated (e.g., temporarily halting ventilation). Inspiration impedes blood outflow through the jugular, thereby momentarily causing bloodlogging or engorgement of the brain and holding ICP at higher values.
This source of variability was explored in 1 experiment by creating a new set of measurements using ABP data to determine diastolic and systolic phases of the heart. By averaging EIT frames acquired during the 2 phases over several seconds of data, a difference image could be created between the diastole and systole data sets. The breathing signal was removed by rejecting data points with ICP excursions clearly caused by ventilation. The method appeared to refine the blood perfusion pattern in the anterior and middle cerebral arterial regions (Fig. 8).
The method is sensitive to physiologic changes, but the variability presents a challenge for specificity. Ways of decreasing variability in mean Δσ by normalizing parameters to individual cases, instead of looking at the data as a whole, as done here, may be advantageous and should be explored. Another option, once sufficient data are collected, will be to look at data trends and establish statistical thresholds that suggest significance in image conductivity. Another option, suggested by Gómez-Laberge et al.,21 may be to use a pixel-grouping algorithm in conjunction with threshold values, as demonstrated in a study of ventilated pigs.
Mean resting ABP was observed to vary from animal to animal. Several animals appear to be hypotensive. Low blood pressure may affect the change in conductivity beat-to-beat as blood flow is limited, but this was not explored. Mass effect by balloon inflation, intracerebral hematoma, and blood flow cessation are large effects unlikely to be affected by low ABP.
A limitation of the computational method used here is that a 2D circular rendering was used to represent a more complex 3-dimensional (3D) geometry, in which not all electrodes were coplanar and the imaging domain is not circular. Forcing these data acquired from the 3D environment to fit a 2D solution will cause some distortion in the tomogram and localization of the ROIs. Simulation and laboratory experiments have demonstrated that objects tend to move more centrally in such circumstances.20 Three-dimensional models for EIT are becoming more common in the research setting as computational power has improved. However, these implementations are typically performed postacquisition and not in real time using expensive high-end computational hardware and sophisticated computationally intensive algorithms. Our approach represents a technology capable of performing EIT in real time using a midrange portable computer. Although this approach has been demonstrated to provide information regarding pathologic changes in the cranium, localization is not perfect. As higher speed, lower cost computation platforms become available, it would be worth incorporating more anatomically correct 3D renderings into this technology to enhance precision of localization.
Another limitation of the method is that difference imaging requires a baseline. It is difficult to generate images of injury if a preinjury baseline is unavailable. Therefore, the method of difference imaging must be seen as a trend monitor to observe deterioration and the effects of intervention. To be optimally useful in a clinical environment, we anticipate that the baseline data and image obtained following instrumentation with the ICP and EIT central catheter should be closely correlated to timing and perhaps overlaid as an anatomic graphic to the baseline CT scan of the head. Such graphical overlays highlighting areas of functional change are familiar to intensivists, neurologists, and neurosurgeons and include examples of functional magnetic resonance imaging and electroencephalography maps.
Absolute imaging in EIT is an option when baseline or standard reference values of impedance are not available. This method, however, is more sensitive to noise, model inaccuracies, and electrode position and condition (e.g., contact impedance). It is also a much more computationally intensive problem making rapid tomographic rendering a challenge. In the environment of craniocerebral trauma, where scalp and cranium are injured with evolving patterns of edema and hematoma, such absolute imaging may be of less value than trend detection within the cranium.
This animal study was designed to explore the potential benefits and feasibility of a continuous axial image rendering of the human brain. The manipulated variables of mass effect by balloon inflation, intracranial hemorrhage, and cerebral blood flow cessation represent challenging issues of urgent recognition in the intensive care environment in patients who have suffered severe head injuries. At present, such patients undergo intermittent CT imaging with repeat imaging based on the clinical course and protocols for discernment of otherwise unrecognized changes by clinical examination or routinely measured parameters, e.g., ICP and TcO2. As these patients are often deeply sedated or induced into pharmacologic coma and muscular relaxation to optimize control of ICP, a means of monitoring is desirable that can more effectively signal dangerous changes. Furthermore, no transducers presently provide a cross-sectional map of the brain. Local sensing such as TcO2 and thermal or laser cerebral blood flow monitoring cannot be confidently generalized to the brain. CT and magnetic resonance imaging normally require transportation to a radiology center with the attendant risks of detachment from monitoring and the stress of movement.
The electrical path of the very low-level, high-frequency current used in EIT is not straight between 2 electrodes but rather it constitutes a diffuse field following the path of least electrical impedance. This nature of EIT makes high-resolution images (such as in x-ray tomography) difficult. No practical algorithm to fully address this physical limitation is presently anticipated. However, its resolution can be improved by increasing the number of electrodes used, keeping in mind however, that an excessive number may become encumbering to care. The simplicity of 8 circumferential contacts by corkscrew, staple, or adhesive electrodes in the clinical context of typical scalp swelling, lacerations, postoperative scars, skull fracture, or even decompressive craniectomy becomes a limiting necessity. A further practicality is that our present 8 × 1 array can render 100 image updates per second with the computational power of a portable bedside computer. Bedside manipulations such as transient venous occlusion increase in positive end-expiratory pressure, and injection into an external ventricular drain of saline for clearance or compliance testing should become readily apparent in the continuously rendered tomogram.
From an electrical safety stand point, the described levels of current used in this study are noninjurious and are within accepted safety guidelines for externally applied currents22 although long-term effects of an active internal electrode on brain tissue should be established in further studies. By way of comparison, EIT currents may be smaller in magnitude and lower in duty cycle than typical deep-brain stimulators.
While several other EIT research groups have explored the effects of intraperitoneal and intracranial hemorrhage,22–24 to the best of our knowledge, the novel EIT implementation described in this article is at present the only study to show in vivo, real-time, tomographic reconstructions of mass effect, hemorrhage, and cessation of blood flow. Xu et al.25 show in vivo hematoma creation and detection with 16 external electrodes. It is interesting to note that their results show a decrease in conductivity with injection of 5 mL of blood. In contrast, this study shows an increase, which corresponds well with literature indicating that blood is more conductive than brain.
Our adaptation of the external ventricular drain or ICP monitor into a central electrode may be promising to extend the depth of resolution and sensitivity into the central brain region. This technology may improve monitoring and guidance for therapeutic intervention in other pathological conditions beyond head injury where edema, sodium shifts, and mass effect participate. These include stroke, hydrocephalus, and postoperative changes.
We have described a novel and practical combination of a simple circumferential and intracranial electrode EIT system with a standard of care pressure transducer that for the first time, has been used to monitor intracranial injuries in vivo, in real time, with statistically significant detectability.
Name: Preston K. Manwaring, PhD.
Contribution: This author was responsible for the study design, conduction of the study, data collection, data analysis, and manuscript preparation.
Attestation: Preston K. Manwaring approves this manuscript and attests to the originality of the work and integrity of the data collection and analysis. This author is also the archival author.
Name: Karen L. Moodie, DVM.
Contribution: This author assisted in the conduction of the study and data collection.
Name: Alexander Hartov, PhD.
Contribution: This author assisted in the study design and data analysis.
Name: Kim H. Manwaring, MD.
Contribution: This author assisted in the study design and manuscript preparation.
Name: Ryan J. Halter, PhD.
Contribution: This author assisted in the study design, data collection, data analysis, and manuscript preparation. This author is also the study principal investigator on the R21 research grant.
Attestation: Ryan Halter attests to the originality of the work and integrity of the data collection and analysis.
This manuscript was handled by: Dwayne R. Westenskow, PhD.
a CSF External Drainage Devices. Available at: http://emedicine.medscape.com/article/1982472-overview#aw2aab6b2. Accessed February 11, 2012. Cited Here...
b LICOX INFO. Available at: http://www.integra-ls.com/home/search.aspx?qry=licox. Accessed October 19, 2009. Cited Here...
c Intraoperative Cerebral Blood Flow Measurement: Quantitative CBF Monitoring Techniques. Available at: http://www.medscape.com/viewarticle/405659_3. Accessed February 12, 2012. Cited Here...
d Conductivity change due to blood injection represents the limiting manipulation; inflation of an insulative balloon has an almost infinite conductivity contrast compared with brain. Nominal conductivity of brain and blood are 127 mS/m and 680 mS/m, respectively. The conductivity estimation algorithms used in EIT typically do not recover the full contrast actually present; to account for this, the mean expected contrast between preinjury and postinjury Δσ was conservatively assumed to be 1:3 with SDs of 50% (e.g., blood injection would be detected as 3 times the background conductivity irrespective of the actual value). SD represents an estimate of variation between animals for 1 particular injury (e.g., hematoma creation by blood injection). Five samples are necessary to achieve a power of 0.80 with a 95% confidence interval for a 2-tailed Student t test. Eight samples provide added assurance. Cited Here...
1. Metherall P, Barber DC, Smallwood RH, Brown BH. Three-dimensional electrical impedance tomography. Nature. 1996;380:509–12
2. Bayford R, Tizzard A. Bioimpedance imaging: an overview of potential clinical applications. Analyst. 2012;137:4635–43
3. Holder D Electrical Impedance Tomography: Methods, History, and Applications. 2005 London The Institute of Physics Publishing
4. da Silva JE, de Sá JP, Jossinet J. Classification of breast tissue by electrical impedance spectroscopy. Med Biol Eng Comput. 2000;38:26–30
5. Poplack SP, Tosteson TD, Wells WA, Pogue BW, Meaney PM, Hartov A, Kogel CA, Soho SK, Gibson JJ, Paulsen KD. Electromagnetic breast imaging: results of a pilot study in women with abnormal mammograms. Radiology. 2007;243:350–9
6. Gonçalves S, de Munck JC, Verbunt JP, Heethaar RM, da Silva FH. In vivo
measurement of the brain and skull resistivities using an EIT-based method and the combined analysis of SEF/SEP data. IEEE Trans Biomed Eng. 2003;50:1124–8
7. Yerworth RJ, Bayford RH, Brown B, Milnes P, Conway M, Holder DS. Electrical impedance tomography spectroscopy (EITS) for human head imaging. Physiol Meas. 2003;24:477–89
8. Bayford RH, Boone KG, Hanquan Y, Holder DS. Improvement of the positional accuracy of EIT images of the head using a Lagrange multiplier reconstruction algorithm with diametric excitation. Physiol Meas. 1996;17:A49–57
9. Shi X, Dong X, Shuai W, You F, Fu F, Liu R. Pseudo-polar drive patterns for brain electrical impedance tomography. Physiol Meas. 2006;27:1071–80
10. Tidswell T, Gibson A, Bayford RH, Holder DS. Three-dimensional electrical impedance tomography of human brain activity. Neuroimage. 2001;13:283–94
11. Tidswell AT, Gibson A, Bayford RH, Holder DS. Validation of a 3D reconstruction algorithm for EIT of human brain function in a realistic head-shaped tank. Physiol Meas. 2001;22:177–86
12. Tidswell AT, Gibson A, Bayford RH, Holder DS. Electrical impedance tomography of human brain activity with a two-dimensional ring of scalp electrodes. Physiol Meas. 2001;22:167–75
13. Halter R, Hartov A, Paulsen K. Video rate electrical impedance tomography of vascular changes: preclinical development. Physiol Meas. 2008;29:349–64
14. Manwaring PK, Halter RJ, Borsic A, Hartov A. A modified electrode configuration for brain EIT. J Phys Conf Ser. 2010;224:012062
15. Holder DS, Rao A, Hanquan Y. Imaging of physiologically evoked responses by electrical impedance tomography with cortical electrodes in the anaesthetized rabbit. Physiol Meas. 1996;17(Suppl 4A):A179–86
16. Maas AI, Stocchetti N, Bullock R. Moderate and severe traumatic brain injury in adults. Lancet Neurol. 2008;7:728–41
17. Soni NK, Paulsen KD, Dehghani H, Hartov A. Finite element implementation of Maxwell’s equations for image reconstruction in electrical impedance tomography. IEEE Trans Med Imaging. 2006;25:55–61
18. Proschan MA. On the distribution of the unpaired t-statistic with paired data. Stat Med. 1996;15:1059–63
19. Diehr P, Martin DC, Koepsell T, Cheadle A. Breaking the matches in a paired t-test for community interventions when the number of pairs is small. Stat Med. 1995;14:1491–504
20. Halter RJ, Hartov A, Paulsen KD. Experimental justification for using 3D conductivity reconstructions in electrical impedance tomography. Physiol Meas. 2007;28:115–27
21. Gómez-Laberge C, Hogan MJ, Elke G, Weiler N, Frerichs I, Adler A. Data-driven classification of ventilated lung tissues using electrical impedance tomography. Physiol Meas. 2011;32:903–15
22. International Electrotechnical Commission. IEC-6060–1 Medical Equipment: Part 1: General Requirements for Basic Safety and Essential Performance. Geneva, Switzerland International Electrotechnical Commission, 2005
23. Xu C, Dai M, You F, Shi X, Fu F, Liu R, Dong X. An optimized strategy for real-time hemorrhage monitoring with electrical impedance tomography. Physiol Meas. 2011;32:585–98
24. Sadleir RJ, Tang T, Tucker AS, Borum P, Weiss M. Detection of intraventricular blood using EIT in a neonatal piglet model. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:3169–72
© 2013 International Anesthesia Research Society
25. Xu CH, Wang L, Shi XT, You FS, Fu F, Liu RG, Dai M, Zhao ZW, Gao GD, Dong XZ. Real-time imaging and detection of intracranial haemorrhage by electrical impedance tomography in a piglet model. J Int Med Res. 2010;38:1596–604