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Intraoperative mapping of the sensory cortex by time-resolved thermal imaging

  • Nico Hoffmann EMAIL logo , Yordan Radev , Edmund Koch , Uwe Petersohn , Gerald Steiner and Matthias Kirsch
Published/Copyright: September 29, 2018

Abstract

The resection of brain tumor requires a precise distinction between eloquent areas of the brain and pathological tumor tissue in order to improve the extent of resection as well as the patient’s progression free survival time. In this study, we discuss mathematical tools necessary to recognize neural activity using thermal imaging cameras. The main contribution to thermal radiation of the exposed human cortex is regional cerebral blood flow (CBF). In fact, neurovascular coupling links neural activity to changes in regional CBF which in turn affects the cortical temperature. We propose a statistically sound framework to visualize neural activity of the primary somatosensory cortex. The framework incorporates a priori known experimental conditions such as the thermal response to neural activity as well as unrelated effects induced by random neural activity and autoregulation. These experimental conditions can be adopted to certain electrical stimulation protocols so that the framework allows to unveil arbitrary evoked neural activity. The method was applied to semisynthetic as well as two intraoperative cases with promising results as we were able to map the eloquent sensory cortex with high sensitivity. Furthermore, the results were validated by anatomical localization and electrophysiological measurements.

Acknowledgments

This work was supported by the European Social Fund (Funder Id: 10.13039/501100004895, Grant no. 100087783) and the Free State of Saxony. The authors would also like to thank all other organizations and individuals, especially the surgical and nursing staff, who supported this research project.

  1. Author Statement

  2. Research funding: This work was supported by the European Social Fund (project no. 100270108) and the Saxonian Ministry of Science and Art.

  3. Conflict of interest: Authors state no conflict of interest.

  4. Informed consent: Informed consent is not applicable.

  5. Ethical approval: The conducted research is not related to either human or animals use.

References

[1] Ottenhausen M, Krieg SM, Meyer B, Ringel F. Functional preoperative and intraoperative mapping and monitoring: increasing safety and efficacy in glioma surgery. Neurosurg Focus 2015;38:1–13.10.3171/2014.10.FOCUS14611Search in Google Scholar PubMed

[2] Saito T, Muragaki Y, Maruyama T, Tamura M, Nitta M, Okada Y. Intraoperative functional mapping and monitoring during glioma surgery. Neurol Med Chir 2015;55:1–13.10.2176/nmc.ra.2014-0215Search in Google Scholar PubMed PubMed Central

[3] De Witt Hamer PC, Robles SG, Zwinderman AH, Duffau H, Berger MS. Impact of intraoperative stimulation brain mapping on glioma surgery outcome: a meta-analysis. J Clin Oncol 2012;30:2559–65.10.1200/JCO.2011.38.4818Search in Google Scholar PubMed

[4] Chang EF, Clark A, Smith JS, Polley MY, Chang SM, Barbaro NM, et al. Functional mapping? Guided resection of low-grade gliomas in eloquent areas of the brain: improvement of long-term survival. J Neurosurg 2011;114:566–73.10.3171/2010.6.JNS091246Search in Google Scholar PubMed PubMed Central

[5] Cedzich C, Taniguchi M, Schramm J. Somatosensory evoked potential phase reversal and direct motor cortex stimulation during surgery in and around the central region. Neurosurgery 1996;38:962–70.10.1097/00006123-199605000-00023Search in Google Scholar PubMed

[6] Morone KA, Neimat JS, Roe AW, Friedman RM. Review of functional and clinical relevance of intrinsic signal optical imaging in human brain mapping. Neurophotonics 2017;4:031220-1.10.1117/1.NPh.4.3.031220Search in Google Scholar PubMed PubMed Central

[7] Meyer T, Sobottka SB, Kirsch M, Schackert G, Steinmeier R, Koch E, et al. Intraoperative optical imaging of functional brain areas for improved image-guided surgery. Biomed Tech 2013;58:225–36.10.1515/bmt-2012-0072Search in Google Scholar PubMed

[8] Shevelev IA, Tsicalov EN, Gorbach AM, Budko KP, Sharaev GA. Thermoimaging of the brain. J Neurosci Methods 1993;46: 49–9.10.1016/0165-0270(93)90140-MSearch in Google Scholar

[9] Suzuki T, Ooi Y, Seki J. Infrared thermal imaging of rat somatosensory cortex with whisker stimulation. J Appl Physiol 2012;112:1215–22.10.1152/japplphysiol.00867.2011Search in Google Scholar PubMed

[10] Gorbach AM, Heiss J, Kufta C, Sato S, Fedio P, Kammerer WA, et al. Intraoperative infrared functional imaging of human brain. Ann Neurol 2003;54:297–309.10.1002/ana.10646Search in Google Scholar PubMed

[11] Parrish T, Iorga M. Application of IR thermometry to understanding brain function. Proc. SPIE 10540, Quantum Sensing and Nano Electronics and Photonics XV 2018; 1054002-1.10.1117/12.2297486Search in Google Scholar

[12] Ruppert D, Wand MP, Carroll RJ. Semiparametric Regression. New York: Cambridge University Press; 2003.10.1017/CBO9780511755453Search in Google Scholar

[13] DeBoor C. A Practical Guide to Splines. New York: Springer-Verlag; 1978.10.1007/978-1-4612-6333-3Search in Google Scholar

[14] Eilers PH, Currie ID, Durbán M. Fast and compact smoothing on large multidimensional grids. Comput Stat Data Anal 2006;50:61–76.10.1016/j.csda.2004.07.008Search in Google Scholar

Received: 2017-12-13
Accepted: 2018-08-30
Published Online: 2018-09-29
Published in Print: 2018-10-25

©2018 Walter de Gruyter GmbH, Berlin/Boston

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