Epileptic Seizure Detection and Prediction Based on Continuous Cerebral Blood Flow Monitoring – a Review

Abstract

Epilepsy is the third most common neurological illness, affecting 1% of the world’s population. Despite advances in medicine, about 25 to 30% of the patients do not respond to or cannot tolerate the severe side effects of medical treatment, and surgery is not an option for the majority of patients with epilepsy. The objective of this article is to review the current state of research on seizure detection based on cerebral blood flow (CBF) data acquired by thermal diffusion flowmetry (TDF), and CBF-based seizure prediction. A discussion is provided on the applications, advantages, and disadvantages of TDF in detecting and localizing seizure foci, as well as its role in seizure prediction. Also presented are an overview of the present challenges and possible future research directions (along with methodological guidelines) of the CBF-based seizure detection and prediction methods.

References

1. C. Baumgartner, W. Serles, F. Leutmezer et al., “Preictal SPECT in Temporal Lobe Epilepsy: Regional Cerebral Blood Flow is Increased Prior to Electroencephalography-Seizure Onset as process,” Medicine, vol. 39, pp. 978–982, 1998. View at: Google Scholar
2. L. Tyvaert, P. Levan, F. Dubeau, and J. Gotman, “Noninvasive Dynamic Imaging of Seizures in Epileptic Patients,” Human Brain Mapping, vol. 4011, pp. 3993–4011, 2009. View at: Google Scholar
3. L. D. Iasemidis, “Epileptic seizure prediction and control,” IEEE Transactions Biomedical Engineering, vol. 50, pp. 549–558, 2003. View at: Google Scholar
4. Curing the Epilepsies: The Promise of Research, National Institute of Neurological Disorders and Stroke, National Institutes of Health, USA, 2015, Accessed April 2015 http://www.ninds.nih.gov/disorders/epilepsy/epilepsy_research.htm.
5. B. Litt and J. Echauz, “Prediction of epileptic seizures,” Lancet Neurology, vol. 1, pp. 22–30, 2002. View at: Google Scholar
6. F. Mormann, R. G. Andrzejak, C. E. Elger, and K. Lehnertz, “Seizure prediction: the long and winding road,” Brain, vol. 130, pp. 314–333, 2007. View at: Google Scholar
7. B. Schelter, M. Winterhalder, T. Maiwald et al., “Testing statistical significance of multivariate time series analysis techniques for epileptic seizure prediction,” Chaos, vol. 16, Article ID 013108, 2006. View at: Google Scholar
8. M. J. Cook, T. J. O'Brien, S. F. Berkovic et al., “Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study,” The Lancet Neurology, vol. 12, no. 6, pp. 563–571, 2013. View at: Google Scholar
9. K. Gadhoumi, J. M. Lina, and J. Gotman, “Seizure prediction in patients with mesial temporal lobe epilepsy using EEG measures of state similarity,” Clinical Neurophysiology, vol. 124, pp. 1745–1754, 2013. View at: Google Scholar
10. R. G. Andrzejak, D. Chicharro, C. E. Elger, and F. Mormann, “Seizure prediction: any better than chance?” Clinical Neurophysiology, vol. 120, pp. 1465–1478, 2009. View at: Google Scholar
11. C. E. Elger and F. Mormann, “Seizure prediction and documentation - two important problems,” Neurology, vol. 12, pp. 531–532, 2013. View at: Google Scholar
12. A. Dahl, K. Lindegaard, D. Russell et al., “A comparison of transcranial Doppler and cerebral blood flow studies to assess cerebral vasoreactivity,” Stroke, vol. 23, pp. 15–19, 1992. View at: Google Scholar
13. M. E. Weinand, L. P. Carter, D. D. Patton, K. J. Oommen, D. M. Labiner, and D. Talwar, “Long-term surface cortical cerebral blood flow monitoring in temporal lobe epilepsy,” Neurosurgery, vol. 35, pp. 657–664, 1994. View at: Google Scholar
14. M. E. Weinand, L. P. Carter, W. F. El-Saadany, P. J. Sioutos, D. M. Labiner, and K. J. Oommen, “Cerebral blood flow and temporal lobe epileptogenicity,” Journal of Neurosurgery, vol. 86, pp. 226–232, 1997. View at: Google Scholar
15. M. E. Weinand, I. Takacs, D. M. Labiner, and G. L. Ahern, “Nonepileptic cortical cerebral blood flow and temporal lobe epileptogenicity,” Pathophysiology, vol. 6, pp. 135–141, 1999. View at: Google Scholar
16. M. E. Weinand, D. Labiner, and G. L. Ahern, “Temporal lobe seizure interhemispheric propagation time depends on nonepileptic cortical cerebral blood flow,” Epilepsy research, vol. 44, pp. 33–39, 2001. View at: Google Scholar
17. G. Gonzalez-Portillo, S. Rivero, G. L. Ahern, D. M. Labiner, and M. E. Weinand, “Normalization of periictal bihemispheric cerebral perfusion in temporal lobe epilepsy,” Pathophysiology, vol. 11, pp. 31–34, 2004. View at: Google Scholar
18. C. la Fougère, A. Rominger, S. Förster, J. Geisler, and P. Bartenstein, “PET and SPECT in epilepsy: a critical review,” Epilepsy & Behavior, vol. 15, pp. 50–55, 2009. View at: Google Scholar
19. L. P. Carter, “Thermal diffusion flowmetry,” Neurosurgery Clinics of North America, vol. 7, pp. 749–754, 1996. View at: Google Scholar
20. P. Vajkoczy, M. Schomacher, M. Czabanka, and P. Horn, “Monitoring Cerebral Blood Flow in Neurosurgical Intensive Care,” European Neurological Disease, Issue II, 2007. View at: Google Scholar
21. V. Rajan, B. Varghese, T. G. van Leeuwen, and W. Steenbergen, “Review of methodological developments in laser Doppler flowmetry,” Lasers in Medical Science, vol. 24, pp. 269–283, 2009. View at: Google Scholar
22. K. Krakow, “Imaging epileptic activity using functional MRI,” Neurodegenerative Diseases, vol. 5, pp. 286–295, 2008. View at: Google Scholar
23. H. Laufs, “A personalized history of EEG-fMRI integration,” NeuroImage, vol. 62, pp. 1056–1067, 2012. View at: Google Scholar
24. P. D. Griffiths, N. Hoggard, W. R. Dannels, and D. Wilkinson, “In vivo measurement of cerebral blood flow: a review of methods and applications,” Vascular Medicine, vol. 6, pp. 51–60, 2001. View at: Google Scholar
25. N. Vongsavan and B. Matthews, “Some aspects of the use of laser doppler flow meters for recording tissue blood flow,” Experimental Physiology, vol. 78, pp. 1–14, 1993. View at: Google Scholar
26. C. Kesavadas and B. Thomas, “Clinical applications of functional MRI in epilepsy,” Indian Journal of Radiology Imaging, vol. 18, pp. 210–217, 2008. View at: Google Scholar
27. L. P. Carter, W. L. White, and J. R. Atkinson, “Regional cortical blood flow at craniotomy,” Neurosurgery, vol. 2, pp. 223–229, 1978. View at: Google Scholar
28. J. Grayson, “Internal calorimetry in the determination of thermal conductivity and blood flow,” Journal of Physiology, vol. 118, pp. 54–72, 1952. View at: Google Scholar
29. F. Verdú-López, J. M. González-Darder, P. Gonzalez-Lopez, and L. B. Macia, “Using thermal diffusion flowmetry in the assessment of regional cerebral blood flow in cerebral aneurysm microsurgery,” Neurosurgery Murcia, vol. 21, pp. 373–380, 2010. View at: Google Scholar
30. A. Zauner and J. P. Muizelaar, “Measuring cerebral blood flow and metabolism,” in Head Injury, P. Reilly and R. Bullock, Eds., Chapman and Hall Publishing, London, 1997. View at: Google Scholar
31. L. P. Carter, M. E. Weinand, and K. J. Oommen, “Cerebral blood flow (CBF) monitoring in intensive care by thermal diffusion,” in Monitoring of Cerebral Blood Flow and Metabolism in Intensive Care, pp. 43–46, Springer, Vienna, 1993. View at: Google Scholar
32. P. D. Le Roux, J. Levine, and W. A. Kofke, Monitoring in Neurocritical Care: Expert Consult: Online. Elsevier Health Sciences, 2013.
33. Hemedex Inc. BPM Neuromonitoring Guide. 2006-2011.
34. H. F. Bowman, U.S. Patent Application 13/999, 906, 2014.
35. C. T. Leondes, Biomechanical Systems: Techniques and Applications, Volume IV: Biofluid Methods in Vascular and Pulmonary Systems. Vol. 4. CRC Press, 2002.
36. Z. Idris, M. Mustapha, and J. M. Abdullah, Neurointensive Care Monitoring for Severe Traumatic Brain Injury, Amit Agrawal (Ed), 2012, 213.
37. H. F. Bowman and W. H. Newman, “Method to quantify thermal dissipative mechanisms in biomaterials,” U.S. Patent No. 4, 852, 027. Washington, DC: U.S. Patent and Trademark Office, 1989. View at: Google Scholar
38. W. Perl, “Heat and matter distribution in body tissues and the determination of tissue blood flow by local clearance methods,” Journal of Theoretical Biology, vol. 2, no. 3, pp. 201–235, 1962. View at: Google Scholar
39. D. Wei, G. M. Saidel, and S. C. Jones, “Optimal Design of a Thermistor Probe for Surface Measurement of Cerebral Blood Flow,” IEEE Transactions on Biomedical Eng, vol. 37, pp. 1159–1172, 1990. View at: Google Scholar
40. J. C. Chato, “A Method for the measurement of thermal properties of biologic materials,” in Symposium on thermal problems in biotechnology, J. C. Chato, Ed., pp. 16–25, ASME, New York, 1968. View at: Google Scholar
41. J. W. Valvano, J. T. Allen, and H. F. Bowman, “The simultaneous measurement of thermal conductivity, thermal diffusivity, and perfusion in small volumes of tissue,” Journal of Biomechanical Engineering, vol. 106, no. 3, pp. 192–197, 1984. View at: Google Scholar
42. G. T. Martin and H. F. Bowman, “Validation of real-time continuous perfusion measurement,” Medical and Biological Engineering and Computing, vol. 38, no. 3, pp. 319–325, 2000. View at: Google Scholar
43. H. F. Bowman and T. A. Balasubramaniam, “A new technique utilizing thermistor probes for the measurement of thermal properties of biomaterials,” Cryobiology, vol. 13, no. 5, pp. 572–580, 1976. View at: Google Scholar
44. T. A. Balasubramaniam and H. F. Bowman, “Thermal conductivity and thermal diffusivity of biomaterials: A simultaneous measurement technique,” Journal of Biomechanical Engineering, vol. 99, no. 3, pp. 148–154, 1977. View at: Google Scholar
45. J. W. Valvano, “Bioheat transfer,” in Encyclopedia of Medical Devices and Instrumentation, J. G. Webster, Ed., John Wiley & Sons, Inc, 2006. View at: Google Scholar
46. P. A. Patel, J. W. Valvano, J. A. Pearce, and S. A. Prahl, “A self-heated thermistor technique to measure effective thermal properties from the tissue surface,” Journal of Biomechanical Engineering, vol. 109, pp. 330–335, 1987. View at: Google Scholar
47. M. M. Chen and K. R. Holmes, “The thermal pulse-decay method for simultaneous measurement the thermal conductivity and local blood perfusion rate of living tissues,” Advances in Bioengineering, pp. 113–115, 1980. View at: Google Scholar
48. H. PENNES, “Analysis of tissue and arterial blood temperatures in the resting human forearm,” Journal of Applied Physiology, vol. 1, no. 2, pp. 93–122, 1948. View at: Google Scholar
49. D. Wei, G. M. Saidel, and S. C. Jones, “Thermal method for continuous measurement of cerebral perfusion,” Med. and Biol. Eng. and Computer, vol. 32, pp. 481–488, 1994. View at: Google Scholar
50. O. Foerster, “Operative Behandlung des Torticollis spastica,” Zentralbl. Chir, vol. 44, pp. 2804–2805, 1926. View at: Google Scholar
51. W. Penfield, “The Evidence for a Cerebral Vascular Mechanism in Epilepsy,” Annals of Internal Medicine, vol. 7, no. 303, 1933. View at: Google Scholar
52. F. A. Gibbs, “A Thermoelectric Blood Flow Recorder in the Form of a Needle,” Experimental Biology and Medicine, vol. 31, pp. 141–146, 1933. View at: Google Scholar
53. F. A. Gibbs, W. G. Lennox, and E. L. Gibbs, “Cerebral blood flow preceding and accompanying epileptic seizures in man,” Arch Neurology Psychiatry, vol. 32, pp. 257–272, 1934. View at: Google Scholar
54. W. Penfield, “Cerebral Blood Flow during Induced Epileptiform Seizures in Animals and Man,” Journal of Neurophysiology, vol. 2, no. 257, 1939. View at: Google Scholar
55. W. Penfield, “Remarks on incomplete hypotheses for the control of cerebral circulation,” Journal of Neurosurgery, vol. 35, pp. 124–127, 1971. View at: Google Scholar
56. B. W. Brawley, “The pathophysiology of intracerebral steal following carbon dioxide inhalation, an experimental study,” Scand J Clin Lab Invest, vol. 22, no. 102, 1968. View at: Google Scholar
57. L. P. Carter and J. R. Atkinson, “Cortical blood flow in controlled hypotension as measured by thermal diffusion,” Journal of Neurology, Neurosurgery, and Psychiatry, vol. 36, pp. 906–991, 1973a. View at: Google Scholar
58. L. P. Carter and J. R. Atkinson, “Auto-regulation and Hyperemia of Cerebral Blood Flow as Evaluated by Thermal Diffusion,” Stroke, vol. 4, pp. 917–922, 1973b. View at: Google Scholar
59. L. P. Carter, R. Erspamer, and W. Bro, “Cortical blood flow: thermal diffusion vs isotope clearance,” Stroke, vol. 12, pp. 513–518, 1981. View at: Google Scholar
60. K. J. Oommen, M. Weinand, and L. Carter, “Cerebral Blood Flow over the Epileptogenic Cortex, Before, During and After Seizure,” Epilepsia, vol. 34, pp. 127–128, 1993, (abstract). View at: Google Scholar
61. P. Federico, D. F. Abbott, R. S. Briellmann, S. Harvey, and G. D. Jackson, “Functional MRI of the pre-ictal state,” Brain: a Journal of Neurology, vol. 128, pp. 1811–1817, 2005. View at: Google Scholar
62. K. J. Oommen, S. Saba, J. A. Oommen, P. C. Francel, C. D. Arnold, and D. A. Wilson, “The Relative Localizing Value of Interictal and Immediate Postictal SPECT In Seizures of Temporal Lobe Origin,” J Nucl Med, vol. 45, pp. 2021–2025, 2004. View at: Google Scholar
63. K. J. Oommen, J. A. Oommen, D. Y. C. Lie, S. Imam, M. Chyu, and Y. Zhang, “Relationship between Cerebral Perfusion and EEG in the Rat Brain,” in Int IEEE EMBS Conf Neural Eng, pp. 174–177, 2011. View at: Google Scholar
64. A. Aarabi, R. Fazel-Rezai, and Y. Aghakhani, “EEG seizure prediction: measures and challenges,” in Conf Proc IEEE Eng Med Biol Soc, pp. 1864–1867, 2009. View at: Google Scholar
65. S. Arthurs, H. P. Zaveri, M. G. Frei, and I. Osorio, “Patient and caregiver perspectives on seizure prediction,” Epilepsy & Behavior, vol. 19, no. 3, pp. 474–477. View at: Google Scholar
66. C. J. Christopher and K. B. Gregory, “Characterization of early partial seizure onset: Frequency, complexity and entropy,” Clinical Neurophysiology, vol. 123, pp. 658–669, 2012. View at: Google Scholar
67. J. Gotman, E. Kobayashi, A. P. Bagshaw, C. G. Bénar, and F. Dubeau, “Combining EEG and fMRI: a multimodal tool for epilepsy research,” Journal of Magnetic Resonance Imaging, vol. 23, pp. 906–920, 2006. View at: Google Scholar
68. N. Moghim and W. C. David, “Predicting Epileptic Seizures in Advance,” PloS One, vol. 9, no. 6, Article ID e99334, 2014. View at: Google Scholar
69. M. Bandarabadi, C. A. Teixeira, J. Rasekhi, and A. Dourado, “Epileptic seizure prediction using relative spectral power features,” Clinical Neurophysiology, vol. 126, no. 2, pp. 237–248, 2015. View at: Google Scholar
70. D. E. Snyder, J. Echauz, D. B. Grimes, and B. Litt, “The statistics of a practical seizure warning system,” Journal of Neural Engineering, vol. 5, no. 4, p. 392, 2008. View at: Google Scholar
71. S. Ramgopal, S. Thome-Souza, M. Jackson et al., “Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy,” Epilepsy & Behavior, vol. 37, pp. 291–307, 2014. View at: Google Scholar
72. M. Winterhalder, T. Maiwald, H. U. Voss, R. Aschenbrenner-Scheibe, J. Timmer, and A. Schulze-Bonhage, “The seizure prediction characteristic: a general framework to assess and compare seizure prediction methods,” Epilepsy & Behavior, vol. 4, no. 3, pp. 318–325, 2003. View at: Google Scholar
73. A. Schulze-Bonhage, F. Sales, K. Wagner et al., “Views of patients with epilepsy on seizure prediction devices,” Epilepsy & Behavior, vol. 18, no. 4, pp. 388–396, 2010. View at: Google Scholar
74. J. C. Sackellares, “Seizure prediction and monitoring,” Epilepsy Behavior, vol. 18, pp. 106–109, 2010. View at: Google Scholar

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