- -

3D patient-specific spinal cord computational model for SCS management: potential clinical applications

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

3D patient-specific spinal cord computational model for SCS management: potential clinical applications

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: Solanes;Dura;Canós ...
Tamaño: 3.310Mb
Formato: PDF
Descripción: Versión del Autor.
Abrir
[Cerrado]
Nombre: jne_18_3_036017.pdf
Tamaño: 5.261Mb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor
dc.contributor.author Solanes, Carmen es_ES
dc.contributor.author Dura, Jose L. es_ES
dc.contributor.author Canós, M.A. es_ES
dc.contributor.author De Andres, Jose es_ES
dc.contributor.author Marti-Bonmati, Luis es_ES
dc.contributor.author Saiz Rodríguez, Francisco Javier es_ES
dc.date.accessioned 2021-05-27T03:34:19Z
dc.date.available 2021-05-27T03:34:19Z
dc.date.issued 2021-06 es_ES
dc.identifier.issn 1741-2560 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166831
dc.description.abstract [EN] Objective. Although spinal cord stimulation (SCS) is an established therapy for treating neuropathic chronic pain, in tonic stimulation, postural changes, electrode migration or badly-positioned electrodes can produce annoying stimulation (intercostal neuralgia) in about 35% of the patients. SCS models are used to study the effect of electrical stimulation to better manage the stimulation parameters and electrode position. The goal of this work was to develop a realistic 3D patient-specific spinal cord model from a real patient and develop a future clinical application that would help physicians to optimize paresthesia coverage in SCS therapy. Approach. We developed two 3D patient-specific models from a high-resolution MRI of two patients undergoing SCS treatment. The model consisted of a finite element model of the spinal cord and a sensory myelinated nerve fiber model. The same simulations were performed with a generalized spinal cord model and we compared the results with the clinical data to evaluate the advantages of a patient-specific model. To identify the geometrical parameters that most influence the stimulation predictions, a sensitivity analysis was conducted. We used the patient-specific model to perform a clinical application involving the pre-implantation selection of electrode polarity and study the effect of electrode offset. Main results. The patient-specific model correlated better with clinical data than the generalized model. Electrode-dura mater distance, dorsal cerebrospinal fluid (CSF) thickness, and CSF diameter are the geometrical parameters that caused significant changes in the stimulation predictions. Electrode polarity could be planned and optimized to stimulate the patient's painful dermatomes. The addition of offset in parallel electrodes would not have been beneficial for one of the patients of this study because they reduce neural activation displacement. Significance. This is the first study to relate the activation area model prediction in dorsal columns with the clinical effect on paresthesia coverage. The outcomes show that 3D patient-specific models would help physicians to choose the best stimulation parameters to optimize neural activation and SCS therapy in tonic stimulation. es_ES
dc.description.sponsorship The authors are grateful to Surgicen S. L. for providing financial assistance, also to thank Joaquin Bosque Hernandez (nurse from the Magnetic Resonance Unit of the Hospital Universitari i Politecnic La Fe) for readjusting the MRI acquisition protocol based on the capacity of the MR equipment, which made the study possible. Finally, the authors wish to express their gratitude to Virginie Callot for providing us with all the spinal cord measurements of her research group's study. es_ES
dc.language Inglés es_ES
dc.publisher IOP Publishing es_ES
dc.relation.ispartof Journal of Neural Engineering es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject 3D patient-specific model es_ES
dc.subject Spinal cord stimulation therapy es_ES
dc.subject Paresthesia coverage es_ES
dc.subject Clinical applications es_ES
dc.subject Computational model es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title 3D patient-specific spinal cord computational model for SCS management: potential clinical applications es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1088/1741-2552/abe44f es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.description.bibliographicCitation Solanes, C.; Dura, JL.; Canós, M.; De Andres, J.; Marti-Bonmati, L.; Saiz Rodríguez, FJ. (2021). 3D patient-specific spinal cord computational model for SCS management: potential clinical applications. Journal of Neural Engineering. 18(3):1-19. https://doi.org/10.1088/1741-2552/abe44f es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1088/1741-2552/abe44f es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 19 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 18 es_ES
dc.description.issue 3 es_ES
dc.identifier.pmid 33556926 es_ES
dc.relation.pasarela S\429586 es_ES
dc.contributor.funder Surgicen, S.L. es_ES
dc.description.references Lee, A. W., & Pilitsis, J. G. (2006). Spinal cord stimulation: indications and outcomes. Neurosurgical Focus, 21(6), 1-6. doi:10.3171/foc.2006.21.6.6 es_ES
dc.description.references Guan, Y. (2012). Spinal Cord Stimulation: Neurophysiological and Neurochemical Mechanisms of Action. Current Pain and Headache Reports, 16(3), 217-225. doi:10.1007/s11916-012-0260-4 es_ES
dc.description.references Kleiber, J.-C., Marlier, B., Bannwarth, M., Theret, E., Peruzzi, P., & Litre, F. (2016). Is spinal cord stimulation safe? A review of 13 years of implantations and complications. Revue Neurologique, 172(11), 689-695. doi:10.1016/j.neurol.2016.09.003 es_ES
dc.description.references Kim, C. H. (2013). Importance of Axial Migration of Spinal Cord Stimulation Trial Leads with Position. November 2103, 6;16(6;11), E763-E768. doi:10.36076/ppj.2013/16/e763 es_ES
dc.description.references Caylor, J., Reddy, R., Yin, S., Cui, C., Huang, M., Huang, C., … Lerman, I. (2019). Spinal cord stimulation in chronic pain: evidence and theory for mechanisms of action. Bioelectronic Medicine, 5(1). doi:10.1186/s42234-019-0023-1 es_ES
dc.description.references Linderoth, B., & Foreman, R. D. (2017). Conventional and Novel Spinal Stimulation Algorithms: Hypothetical Mechanisms of Action and Comments on Outcomes. Neuromodulation: Technology at the Neural Interface, 20(6), 525-533. doi:10.1111/ner.12624 es_ES
dc.description.references Holsheimer, J., & Buitenweg, J. R. (2015). Review: Bioelectrical Mechanisms in Spinal Cord Stimulation. Neuromodulation: Technology at the Neural Interface, 18(3), 161-170. doi:10.1111/ner.12279 es_ES
dc.description.references Oakley, J. C., & Prager, J. P. (2002). Spinal Cord Stimulation. Spine, 27(22), 2574-2583. doi:10.1097/00007632-200211150-00034 es_ES
dc.description.references Melzack, R., & Wall, P. D. (1965). Pain Mechanisms: A New Theory. Science, 150(3699), 971-979. doi:10.1126/science.150.3699.971 es_ES
dc.description.references Manola, L., Holsheimer, J., & Veltink, P. (2005). Technical Performance of Percutaneous Leads for Spinal Cord Stimulation: A Modeling Study. Neuromodulation: Technology at the Neural Interface, 8(2), 88-99. doi:10.1111/j.1525-1403.2005.00224.x es_ES
dc.description.references Manola, L., Holsheimer, J., Veltink, P. H., Bradley, K., & Peterson, D. (2007). Theoretical Investigation Into Longitudinal Cathodal Field Steering in Spinal Cord Stimulation. Neuromodulation: Technology at the Neural Interface, 10(2), 120-132. doi:10.1111/j.1525-1403.2007.00100.x es_ES
dc.description.references Lee, D., Hershey, B., Bradley, K., & Yearwood, T. (2011). Predicted effects of pulse width programming in spinal cord stimulation: a mathematical modeling study. Medical & Biological Engineering & Computing, 49(7). doi:10.1007/s11517-011-0780-9 es_ES
dc.description.references Holsheimer, J., & Wesselink, W. A. (1997). Effect of Anode-Cathode Configuration on Paresthesia Coverage in Spinal Cord Stimulation. Neurosurgery, 41(3), 654-660. doi:10.1097/00006123-199709000-00030 es_ES
dc.description.references Huang, Q., Oya, H., Flouty, O. E., Reddy, C. G., Howard, M. A., Gillies, G. T., & Utz, M. (2014). Comparison of spinal cord stimulation profiles from intra- and extradural electrode arrangements by finite element modelling. Medical & Biological Engineering & Computing, 52(6), 531-538. doi:10.1007/s11517-014-1157-7 es_ES
dc.description.references Howell, B., Lad, S. P., & Grill, W. M. (2014). Evaluation of Intradural Stimulation Efficiency and Selectivity in a Computational Model of Spinal Cord Stimulation. PLoS ONE, 9(12), e114938. doi:10.1371/journal.pone.0114938 es_ES
dc.description.references Durá, J. L., Solanes, C., De Andrés, J., & Saiz, J. (2018). Computational Study of the Effect of Electrode Polarity on Neural Activation Related to Paresthesia Coverage in Spinal Cord Stimulation Therapy. Neuromodulation: Technology at the Neural Interface, 22(3), 269-279. doi:10.1111/ner.12909 es_ES
dc.description.references Fradet, L., Arnoux, P.-J., Ranjeva, J.-P., Petit, Y., & Callot, V. (2014). Morphometrics of the Entire Human Spinal Cord and Spinal Canal Measured From In Vivo High-Resolution Anatomical Magnetic Resonance Imaging. Spine, 39(4), E262-E269. doi:10.1097/brs.0000000000000125 es_ES
dc.description.references Khadka, N., Liu, X., Zander, H., Swami, J., Rogers, E., Lempka, S. F., & Bikson, M. (2020). Realistic anatomically detailed open-source spinal cord stimulation (RADO-SCS) model. Journal of Neural Engineering, 17(2), 026033. doi:10.1088/1741-2552/ab8344 es_ES
dc.description.references Viljoen, S. (2013). Journal of Medical and Biological Engineering, 33(2), 193. doi:10.5405/jmbe.1317 es_ES
dc.description.references Lempka, S. F., Zander, H. J., Anaya, C. J., Wyant, A., Ozinga, J. G., & Machado, A. G. (2019). Patient‐Specific Analysis of Neural Activation During Spinal Cord Stimulation for Pain. Neuromodulation: Technology at the Neural Interface, 23(5), 572-581. doi:10.1111/ner.13037 es_ES
dc.description.references Levy, R. M. (2014). Anatomic Considerations for Spinal Cord Stimulation. Neuromodulation: Technology at the Neural Interface, 17, 2-11. doi:10.1111/ner.12175 es_ES
dc.description.references Holsheimer, J. (2002). Which Neuronal Elements are Activated Directly by Spinal Cord Stimulation. Neuromodulation: Technology at the Neural Interface, 5(1), 25-31. doi:10.1046/j.1525-1403.2002._2005.x es_ES
dc.description.references Ladenbauer, J., Minassian, K., Hofstoetter, U. S., Dimitrijevic, M. R., & Rattay, F. (2010). Stimulation of the Human Lumbar Spinal Cord With Implanted and Surface Electrodes: A Computer Simulation Study. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 18(6), 637-645. doi:10.1109/tnsre.2010.2054112 es_ES
dc.description.references Arle, J. E., Carlson, K. W., Mei, L., & Shils, J. L. (2013). Modeling Effects of Scar on Patterns of Dorsal Column Stimulation. Neuromodulation: Technology at the Neural Interface, 17(4), 320-333. doi:10.1111/ner.12128 es_ES
dc.description.references Struijk, J. J., Holsheimer, J., & Boom, H. B. K. (1993). Excitation of dorsal root fibers in spinal cord stimulation: a theoretical study. IEEE Transactions on Biomedical Engineering, 40(7), 632-639. doi:10.1109/10.237693 es_ES
dc.description.references McCann, H., Pisano, G., & Beltrachini, L. (2019). Variation in Reported Human Head Tissue Electrical Conductivity Values. Brain Topography, 32(5), 825-858. doi:10.1007/s10548-019-00710-2 es_ES
dc.description.references McIntyre, C. C., Mori, S., Sherman, D. L., Thakor, N. V., & Vitek, J. L. (2004). Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus. Clinical Neurophysiology, 115(3), 589-595. doi:10.1016/j.clinph.2003.10.033 es_ES
dc.description.references De Leener, B., Cohen-Adad, J., & Kadoury, S. (2015). Automatic Segmentation of the Spinal Cord and Spinal Canal Coupled With Vertebral Labeling. IEEE Transactions on Medical Imaging, 34(8), 1705-1718. doi:10.1109/tmi.2015.2437192 es_ES
dc.description.references Zander, H. J., Graham, R. D., Anaya, C. J., & Lempka, S. F. (2020). Anatomical and technical factors affecting the neural response to epidural spinal cord stimulation. Journal of Neural Engineering, 17(3), 036019. doi:10.1088/1741-2552/ab8fc4 es_ES
dc.description.references Wesselink, W. A., Holsheimer, J., & Boom, H. B. K. (1999). A model of the electrical behaviour of myelinated sensory nerve fibres based on human data. Medical & Biological Engineering & Computing, 37(2), 228-235. doi:10.1007/bf02513291 es_ES
dc.description.references Richardson, A. G., McIntyre, C. C., & Grill, W. M. (2000). Modelling the effects of electric fields on nerve fibres: Influence of the myelin sheath. Medical & Biological Engineering & Computing, 38(4), 438-446. doi:10.1007/bf02345014 es_ES
dc.description.references Schalow, G., Zäch, G. A., & Warzok, R. (1995). Classification of human peripheral nerve fibre groups by conduction velocity and nerve fibre diameter is preserved following spinal cord lesion. Journal of the Autonomic Nervous System, 52(2-3), 125-150. doi:10.1016/0165-1838(94)00153-b es_ES
dc.description.references Van Veen, B. K., Schellens, R. L. L. A., Stegeman, D. F., Schoonhoven, R., & Gabreëls-Festen, A. A. W. M. (1995). Conduction velocity distributions compared to fiber size distributions in normal human sural nerve. Muscle & Nerve, 18(10), 1121-1127. doi:10.1002/mus.880181008 es_ES
dc.description.references Ranck, J. B. (1975). Which elements are excited in electrical stimulation of mammalian central nervous system: A review. Brain Research, 98(3), 417-440. doi:10.1016/0006-8993(75)90364-9 es_ES
dc.description.references Tackmann, W., & Lehmann, H. J. (1974). Refractory Period in Human Sensory Nerve Fibres. European Neurology, 12(5-6), 277-292. doi:10.1159/000114626 es_ES
dc.description.references Feirabend, H. K. P., Choufoer, H., Ploeger, S., Holsheimer, J., & van Gool, J. D. (2002). Morphometry of human superficial dorsal and dorsolateral column fibres: significance to spinal cord stimulation. Brain, 125(5), 1137-1149. doi:10.1093/brain/awf111 es_ES
dc.description.references Makino, M., Mimatsu, K., Saito, H., Konishi, N., & Hashizume, Y. (1996). Morphometric Study of Myelinated Fibers in Human Cervical Spinal Cord White Matter. Spine, 21(9), 1010-1016. doi:10.1097/00007632-199605010-00002 es_ES
dc.description.references Wesselink, W. A., Holsheimer, J., Nuttin, B., Boom, H. B. K., King, G. W., Gybels, J. M., & de Sutter, P. (1998). Estimation of fiber diameters in the spinal dorsal columns from clinical data. IEEE Transactions on Biomedical Engineering, 45(11), 1355-1362. doi:10.1109/10.725332 es_ES
dc.description.references Lempka, S. F., McIntyre, C. C., Kilgore, K. L., & Machado, A. G. (2015). Computational Analysis of Kilohertz Frequency Spinal Cord Stimulation for Chronic Pain Management. Anesthesiology, 122(6), 1362-1376. doi:10.1097/aln.0000000000000649 es_ES
dc.description.references McIntyre, C. C., Richardson, A. G., & Grill, W. M. (2002). Modeling the Excitability of Mammalian Nerve Fibers: Influence of Afterpotentials on the Recovery Cycle. Journal of Neurophysiology, 87(2), 995-1006. doi:10.1152/jn.00353.2001 es_ES
dc.description.references McNeal, D. R. (1976). Analysis of a Model for Excitation of Myelinated Nerve. IEEE Transactions on Biomedical Engineering, BME-23(4), 329-337. doi:10.1109/tbme.1976.324593 es_ES
dc.description.references Rattay, F. (1986). Analysis of Models for External Stimulation of Axons. IEEE Transactions on Biomedical Engineering, BME-33(10), 974-977. doi:10.1109/tbme.1986.325670 es_ES
dc.description.references Jensen, M. P., & Brownstone, R. M. (2018). Mechanisms of spinal cord stimulation for the treatment of pain: Still in the dark after 50 years. European Journal of Pain, 23(4), 652-659. doi:10.1002/ejp.1336 es_ES
dc.description.references Miller, J. P., Eldabe, S., Buchser, E., Johanek, L. M., Guan, Y., & Linderoth, B. (2016). Parameters of Spinal Cord Stimulation and Their Role in Electrical Charge Delivery: A Review. Neuromodulation: Technology at the Neural Interface, 19(4), 373-384. doi:10.1111/ner.12438 es_ES
dc.description.references Bossetti, C. A., Birdno, M. J., & Grill, W. M. (2007). Analysis of the quasi-static approximation for calculating potentials generated by neural stimulation. Journal of Neural Engineering, 5(1), 44-53. doi:10.1088/1741-2560/5/1/005 es_ES
dc.description.references Molnar, G., & Barolat, G. (2014). Principles of Cord Activation During Spinal Cord Stimulation. Neuromodulation: Technology at the Neural Interface, 17, 12-21. doi:10.1111/ner.12171 es_ES
dc.description.references Taghva, A., Karst, E., & Underwood, P. (2017). Clinical Paresthesia Atlas Illustrates Likelihood of Coverage Based on Spinal Cord Stimulator Electrode Location. Neuromodulation: Technology at the Neural Interface, 20(6), 582-588. doi:10.1111/ner.12594 es_ES
dc.description.references Russo, M., & Van Buyten, J.-P. (2015). 10-kHz High-Frequency SCS Therapy: A Clinical Summary. Pain Medicine, 16(5), 934-942. doi:10.1111/pme.12617 es_ES
dc.description.references Al-Kaisy, A., Palmisani, S., Smith, T. E., Carganillo, R., Houghton, R., Pang, D., … Lucas, J. (2017). Long-Term Improvements in Chronic Axial Low Back Pain Patients Without Previous Spinal Surgery: A Cohort Analysis of 10-kHz High-Frequency Spinal Cord Stimulation over 36 Months. Pain Medicine, 19(6), 1219-1226. doi:10.1093/pm/pnx237 es_ES
dc.description.references Barolat, G. (1998). Epidural Spinal Cord Stimulation: Anatomical and Electrical Properties of the Intraspinal Structures Relevant to Spinal Cord Stimulation and Clinical Correlations. Neuromodulation: Technology at the Neural Interface, 1(2), 63-71. doi:10.1111/j.1525-1403.1998.tb00019.x es_ES
dc.description.references Capogrosso, M., Wenger, N., Raspopovic, S., Musienko, P., Beauparlant, J., Bassi Luciani, L., … Micera, S. (2013). A Computational Model for Epidural Electrical Stimulation of Spinal Sensorimotor Circuits. Journal of Neuroscience, 33(49), 19326-19340. doi:10.1523/jneurosci.1688-13.2013 es_ES
dc.description.references Anaya, C. J., Zander, H. J., Graham, R. D., Sankarasubramanian, V., & Lempka, S. F. (2019). Evoked Potentials Recorded From the Spinal Cord During Neurostimulation for Pain: A Computational Modeling Study. Neuromodulation: Technology at the Neural Interface, 23(1), 64-73. doi:10.1111/ner.12965 es_ES
dc.description.references Struijk, J. J., Holsheimer, J., van Veen, B. K., & Boom, H. B. K. (1991). Epidural spinal cord stimulation: calculation of field potentials with special reference to dorsal column nerve fibers. IEEE Transactions on Biomedical Engineering, 38(1), 104-110. doi:10.1109/10.68217 es_ES
dc.description.references Chakravarthy, K., Fishman, M. A., Zuidema, X., Hunter, C. W., & Levy, R. (2019). Mechanism of Action in Burst Spinal Cord Stimulation: Review and Recent Advances. Pain Medicine, 20(Supplement_1), S13-S22. doi:10.1093/pm/pnz073 es_ES
dc.description.references Smits, H., van Kleef, M., & Joosten, E. A. (2012). Spinal cord stimulation of dorsal columns in a rat model of neuropathic pain: Evidence for a segmental spinal mechanism of pain relief. Pain, 153(1), 177-183. doi:10.1016/j.pain.2011.10.015 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem