7 Biomechanical Modelling of the Brain for Neuronavigation in Epilepsy Surgery
179
their insertion. Surgeons may benefit from the ability to predict how the needle will
behave in the tissue or be able to practise using haptic feedback simulations before
they conduct the operation on the patient.
Acknowledgements The funding from the Australian government through the Australian
Research Council (ARC) (Discovery Project Grants DP160100714, DP1092893 and
DP120100402) and National Health and Medical Research Council (NHMRC) (Project Grants
APP1006031, APP1144519 and APP1162030) is greatly acknowledged. We thank the Raine
Medical Research Foundation, for supporting G. R. Joldes through a Raine Priming Grant, and the
Department of Health, Western Australia, for funding G. R. Joldes through a Merit Award. This
investigation was also supported in part by NIH grants R01 NS079788, R01 EB019483 and R42
MH086984 and by a research grant from the Boston Children’s Hospital Translational Research
Program.
References
1. ABAQUS: ABAQUS Theory Manual Version 6.13. Dassault Systèmes Simulia Corp, Providence (2013)
2. Akhondi-Asl, A., Warfield, S.K.: Simultaneous truth and performance level estimation through
fusion of probabilistic segmentations. IEEE Trans. Med. Imaging. 32(10), 1840–1852 (2013)
3. Akhondi-Asl, A., Hoyte, L., Lockhart, M.E., Warfield, S.K.: A logarithmic opinion pool based
STAPLE algorithm for the fusion of segmentations with associated reliability weights. IEEE
Trans. Med. Imaging. 33(10), 1997–2009 (2014)
4. Bauman, J.A., Feoli, E., Romanelli, P., Doyle, W.K., Devinsky, O., Weiner, H.L.: Multistage
epilepsy surgery: safety, efficacy, and utility of a novel approach in pediatric extratemporal
epilepsy. Neurosurgery. 62(Suppl 2), 489–505 (2008)
5. Bilston, L.E. (ed.): Neural Tissue Biomechanics. Studies in Mechanobiology, Tissue Engineering and Biomaterials. Springer-Verlag, Berlin, Heidelberg (2011)
6. Curry, D.J., Gowda, A., McNichols, R.J., Wilfong, A.A.: MR-guided stereotactic laser ablation
of epileptogenic foci in children. Epilepsy Behav. E&B. 24(4), 408–414 (2012)
7. Engel Jr., J.: A greater role for surgical treatment of epilepsy: why and when? Epilepsy Curr.
3(2), 37–40 (2003)
8. Gerard, I.J., Kersten-Oertel, M., Petrecca, K., Sirhan, D., Hall, J.A., Collins, D.L.: Brain shift
in neuronavigation of brain tumors: a review. Med. Image Anal. 35, 403–420 (2017)
9. Joldes, G.R.: Scattered Transform – a 3D Slicer Extension, from https://github.com/
grandwork2/ScatteredTransform (2017)
10. Joldes, G.R., Wittek, A., Miller, K.: Real-time nonlinear finite element computations on GPU –
application to neurosurgical simulation. Comput. Methods Appl. Mech. Eng. 199, 3305–3314
(2010)
11. Joldes, G.R., Bourantas, G., Zwick, B., Chowdhury, H., Wittek, A., Agrawal, S., Mountris, K.,
Hyde, D., Warfield, S.K., Miller, K.: Suite of meshless algorithms for accurate computation of
soft tissue deformation for surgical simulation. Med. Image Anal. 56, 152–171 (2019)
12. Menagé, L.P.M.: Computer Simulation of Brain Deformations for the Surgical Treatment of
Paediatric Epilepsy. Master of Engineering, The University of Western Australia, Perth, WA
(2017)
13. Miga, M.I., Sun, K., Chen, I., Clements, L.W., Pheiffer, T.S., Simpson, A.L., Thompson, R.C.:
Clinical evaluation of a model-updated image-guidance approach to brain shift compensation:
experience in 16 cases. Int. J. Comput. Assist. Radiol. Surg. 11(8), 1467–1474 (2016)
14. Miller, K. (ed.): Biomechanics of the Brain. New York, Springer (2011)
179
their insertion. Surgeons may benefit from the ability to predict how the needle will
behave in the tissue or be able to practise using haptic feedback simulations before
they conduct the operation on the patient.
Acknowledgements The funding from the Australian government through the Australian
Research Council (ARC) (Discovery Project Grants DP160100714, DP1092893 and
DP120100402) and National Health and Medical Research Council (NHMRC) (Project Grants
APP1006031, APP1144519 and APP1162030) is greatly acknowledged. We thank the Raine
Medical Research Foundation, for supporting G. R. Joldes through a Raine Priming Grant, and the
Department of Health, Western Australia, for funding G. R. Joldes through a Merit Award. This
investigation was also supported in part by NIH grants R01 NS079788, R01 EB019483 and R42
MH086984 and by a research grant from the Boston Children’s Hospital Translational Research
Program.
References
1. ABAQUS: ABAQUS Theory Manual Version 6.13. Dassault Systèmes Simulia Corp, Providence (2013)
2. Akhondi-Asl, A., Warfield, S.K.: Simultaneous truth and performance level estimation through
fusion of probabilistic segmentations. IEEE Trans. Med. Imaging. 32(10), 1840–1852 (2013)
3. Akhondi-Asl, A., Hoyte, L., Lockhart, M.E., Warfield, S.K.: A logarithmic opinion pool based
STAPLE algorithm for the fusion of segmentations with associated reliability weights. IEEE
Trans. Med. Imaging. 33(10), 1997–2009 (2014)
4. Bauman, J.A., Feoli, E., Romanelli, P., Doyle, W.K., Devinsky, O., Weiner, H.L.: Multistage
epilepsy surgery: safety, efficacy, and utility of a novel approach in pediatric extratemporal
epilepsy. Neurosurgery. 62(Suppl 2), 489–505 (2008)
5. Bilston, L.E. (ed.): Neural Tissue Biomechanics. Studies in Mechanobiology, Tissue Engineering and Biomaterials. Springer-Verlag, Berlin, Heidelberg (2011)
6. Curry, D.J., Gowda, A., McNichols, R.J., Wilfong, A.A.: MR-guided stereotactic laser ablation
of epileptogenic foci in children. Epilepsy Behav. E&B. 24(4), 408–414 (2012)
7. Engel Jr., J.: A greater role for surgical treatment of epilepsy: why and when? Epilepsy Curr.
3(2), 37–40 (2003)
8. Gerard, I.J., Kersten-Oertel, M., Petrecca, K., Sirhan, D., Hall, J.A., Collins, D.L.: Brain shift
in neuronavigation of brain tumors: a review. Med. Image Anal. 35, 403–420 (2017)
9. Joldes, G.R.: Scattered Transform – a 3D Slicer Extension, from https://github.com/
grandwork2/ScatteredTransform (2017)
10. Joldes, G.R., Wittek, A., Miller, K.: Real-time nonlinear finite element computations on GPU –
application to neurosurgical simulation. Comput. Methods Appl. Mech. Eng. 199, 3305–3314
(2010)
11. Joldes, G.R., Bourantas, G., Zwick, B., Chowdhury, H., Wittek, A., Agrawal, S., Mountris, K.,
Hyde, D., Warfield, S.K., Miller, K.: Suite of meshless algorithms for accurate computation of
soft tissue deformation for surgical simulation. Med. Image Anal. 56, 152–171 (2019)
12. Menagé, L.P.M.: Computer Simulation of Brain Deformations for the Surgical Treatment of
Paediatric Epilepsy. Master of Engineering, The University of Western Australia, Perth, WA
(2017)
13. Miga, M.I., Sun, K., Chen, I., Clements, L.W., Pheiffer, T.S., Simpson, A.L., Thompson, R.C.:
Clinical evaluation of a model-updated image-guidance approach to brain shift compensation:
experience in 16 cases. Int. J. Comput. Assist. Radiol. Surg. 11(8), 1467–1474 (2016)
14. Miller, K. (ed.): Biomechanics of the Brain. New York, Springer (2011)