Abstract
Programming in deep brain stimulation (DBS) is a labour-intensive process for treating advanced motor symptoms. Specifically for patients with medication-refractory tremor in multiple sclerosis (MS). Wearable sensors are able to detect some manifestations of pathological signs, such as intention tremor in MS. However, methods are needed to visualise the response of tremor to DBS parameter changes in a clinical setting while patients perform the motor task finger-to-nose. To this end, we attended DBS programming sessions of a MS patient and intention tremor was effectively quantified by acceleration amplitude and frequency. A new method is introduced which results in the generation of therapeutic maps for a systematic review of the programming procedure in DBS. The maps visualise the combination of tremor acceleration power, clinical rating scores, total electrical energy delivered to the brain and possible side effects. Therapeutic maps have not yet been employed and could lead to a certain degree of standardisation for more objective decisions about DBS settings. The maps provide a base for future research on visualisation tools to assist physicians who frequently encounter patients for DBS therapy.
Funding source: Fonds National de la Recherche Luxembourg 10.13039/501100001866
Award Identifier / Grant number: 10086156 (PhD Grant)
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Research funding: This work was supported by the Fonds National de la Recherche Luxembourg with an PhD Grant (10086156, Rene Peter Bremm). The funding organization played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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Author contributions: All authors have accepted the responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: All authors state no conflict of interest.
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Informed consent: Informed consent has been obtained from all individuals included in this study.
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Ethical approval: The clinical study has complied with all the relevant national regulations, institutional policies, and in accordance with the tenets of the Helsinki Declaration, and has been approved by the Ethical Review Panel of the University of Luxembourg and Comité National d’Ethique de Recherche (N.201703/01, OptiStimDBS) of Luxembourg.
References
1. Bhatia, KP, Bain, P, Bajaj, N, Elble, RJ, Hallett, M, Louis, ED, et al.. Consensus Statement on the classification of tremors. Mov Disord 2018;33:75–87. https://doi.org/10.1002/mds.27121.Search in Google Scholar
2. McCreary, J, Rogers, J, Forwell, S. Upper limb intention tremor in multiple sclerosis: an evidence-based review of assessment and treatment. Int J MS Care 2018;20:211–23. https://doi.org/10.7224/1537-2073.2017-024.Search in Google Scholar
3. Odin, P, Chaudhuri, KR, Volkmann, J, Antonini, A, Storch, A, Dietrichs, E, et al.. Viewpoint and practical recommendations from a movement disorder specialist panel on objective measurement in the clinical management of Parkinson’s disease. NPJ Parkinsons Dis 2018;4:1–14. https://doi.org/10.1038/s41531-018-0051-7.Search in Google Scholar
4. Elble, R, Comella, C, Fahn, S, Hallett, M, Jankovic, J, Juncos, J, et al.. The essential tremor rating assessment scale (TETRAS). J Neurol Neuromed 2016;1:34–8. https://doi.org/10.29245/2572.942X/2016/4.1038.Search in Google Scholar
5. Bain, PG. The management of tremor. J Neurol Neurosurg Psychiatry 2002;72(Suppl 1):3–9. https://doi.org/10.1136/jnnp.72.suppl_1.i3.Search in Google Scholar
6. Sanes, JN, Lewitt, PA, Mauritz, KH. Visual and mechanical control of postural and kinetic tremor in cerebellar system disorders. J Neurol Neurosurg Psychiatry 1988;51:934–43. https://doi.org/10.1136/jnnp.51.7.934.Search in Google Scholar
7. Western, D, Neild, SA, Hyde, RA, Jones, R, Davies-Smith, A. Relating sensor-based tremor metrics to a conventional clinical scale. In: IEEE Healthcare Innovation Conference, Seattle, WA, USA; 2014. https://doi.org/10.1109/hic.2014.7038900.Search in Google Scholar
8. Rovini, E, Maremmani, C, Cavallo, F. How wearable sensors can support Parkinson’s disease diagnosis and treatment: a systematic review. Front Neurosci 2017;11:1–41. https://doi.org/10.3389/fnins.2017.00555.Search in Google Scholar
9. Timmer, J, Lauk, M, Deuschl, G. Quantitative analysis of tremor time series. Electroencephalogr Clin Neurophysiol 1996;101:461–8. https://doi.org/10.1016/0924-980x(96)94658-5.Search in Google Scholar
10. Grimaldi, G, Manto, M. Mechanisms and emerging therapies in tremor disorders, 1st ed. New York: Springer; 2013.10.1007/978-1-4614-4027-7Search in Google Scholar
11. Alusi, SH. A study of tremor in multiple sclerosis. Brain 2001;124:720–30. https://doi.org/10.1093/brain/124.4.720.Search in Google Scholar
12. Bötzel, K, Tronnier, V, Gasser, T. The differential diagnosis and treatment of tremor. Dtsch Aerztebl Int 2014;111:225–36. https://doi.org/10.3238/arztebl.2014.0225.Search in Google Scholar
13. Feys, PG, Davies-Smith, A, Jones, R, Romberg, A, Ruutiainen, J, Helsen, WF, et al.. Intention tremor rated according to different finger-to-nose test protocols: a survey. Arch Phys Med Rehabil 2003;84:79–82. https://doi.org/10.1053/apmr.2003.50068.Search in Google Scholar
14. Diener, H‐C, Dichgans, J, Guschlbauer, B, Bacher, M, Rapp, H, Klockgether, T. The coordination of posture and voluntary movement in patients with cerebellar dysfunction. Mov Disord 1992;7:14–22. https://doi.org/10.1002/mds.870070104.Search in Google Scholar
15. Jang, SH, Kwon, HG, Rajasekharan, C. Injury of the dentato-rubro-thalamic tract in patients with cerebellar infarct: case report. Medicine 2017;96:e7220. https://doi.org/10.1097/md.0000000000007220.Search in Google Scholar
16. Boonstra, F, Florescu, G, Evans, A, Steward, C, Mitchell, P, Desmond, P, et al.. Tremor in multiple sclerosis is associated with cerebello-thalamic pathology. J Neural Transm 2017;124:1509–14. https://doi.org/10.1007/s00702-017-1798-4.Search in Google Scholar
17. Deuschl, G. Essential tremor and cerebellar dysfunction clinical and kinematic analysis of intention tremor. Brain 2000;123:1568–80. https://doi.org/10.1093/brain/123.8.1568.Search in Google Scholar
18. Thenganatt, MA, Louis, ED. Distinguishing essential tremor from Parkinson’s disease: bedside tests and laboratory evaluations. Expert Rev Neurother 2012;12:687–96. https://doi.org/10.1586/ern.12.49.Search in Google Scholar
19. Pittock, SJ, McClelland, RL, Mayr, WT, Rodriguez, M, Matsumoto, JY. Prevalence of tremor in multiple sclerosis and associated disability in the Olmsted County population. Mov Disord 2004;12:1485. https://doi.org/10.1002/mds.20227.Search in Google Scholar
20. Hooper, J, Taylor, R, Pentland, B, Whittle, IR. Rater reliability of Fahn’s Tremor Rating Scale in patients with multiple sclerosis. Arch Phys Med Rehabil 1998;79:1076–9. https://doi.org/10.1016/s0003-9993(98)90174-5.Search in Google Scholar
21. Ondo, W, Hashem, V, LeWitt, PA, Pahwa, R, Shih, L, Tarsy, D, et al.. Comparison of the Fahn-Tolosa-Marin clinical rating scale and the essential tremor rating assessment scale. Mov Disord Clin Pract 2018;5:60–5. https://doi.org/10.1002/mdc3.12560.Search in Google Scholar
22. Benabid, AL, Pollak, P, Hoffmann, D, Gervason, C, Hommel, M, Perret, JE, et al.. Long-term suppression of tremor by chronic stimulation of the ventral intermediate thalamic nucleus. Lancet 1991;337:403–6. https://doi.org/10.1016/0140-6736(91)91175-t.Search in Google Scholar
23. Miocinovic, S, Somayajula, S, Chitnis, S, Vitek, JL. History, applications, and mechanisms of deep brain stimulation. JAMA Neurol 2013;70:163–71. https://doi.org/10.1001/2013.jamaneurol.45.Search in Google Scholar
24. Brandmeir, NJ, Murray, A, Cheyuo, C, Ferari, C, Rezai, AR. Deep brain stimulation for multiple sclerosis tremor: a meta-analysis. Neuromodulation 2020;23:463–8. https://doi.org/10.1111/ner.13063.Search in Google Scholar
25. Ashkan, K, Rogers, P, Bergman, H, Ughratdar, I. Insights into the mechanisms of deep brain stimulation. Nat Rev Neurol 2017;13:548–54. https://doi.org/10.1038/nrneurol.2017.105.Search in Google Scholar
26. Lozano, AM, Lipsman, N, Bergman, H, Brown, P, Chabardes, S, Chang, JW, et al.. Deep brain stimulation: current challenges and future directions. Nat Rev Neurol 2019;15:148–60. https://doi.org/10.1038/s41582-018-0128-2.Search in Google Scholar
27. Okun, MS. Deep-brain stimulation for Parkinson’s disease. N Engl J Med 2012;367:1529–38. https://doi.org/10.1056/nejmct1208070.Search in Google Scholar
28. Follett, KA, Torres-Russotto, D. Deep brain stimulation of globus pallidus interna, subthalamic nucleus, and pedunculopontine nucleus for Parkinson’s disease: which target? Parkinsonism Relat Disord 2012;18(Suppl 1):165–7. https://doi.org/10.1016/S1353-8020(11)70051-7.Search in Google Scholar
29. Wharen, RE, Okun, MS, Guthrie, BL, Uitti, RJ, Larson, P, Foote, K, et al.. Thalamic DBS with a constant-current device in essential tremor: a controlled clinical trial. Parkinsonism Relat Disord 2017;40:18–26. https://doi.org/10.1016/j.parkreldis.2017.03.017.Search in Google Scholar PubMed
30. Volkmann, J, Moro, E, Pahwa, R. Basic algorithms for the programming of deep brain stimulation in Parkinson’s disease. Mov Disord 2006;21:284–9. https://doi.org/10.1002/mds.20961.Search in Google Scholar PubMed
31. Bronstein, JM, Tagliati, M, Alterman, RL, Lozano, AM, Volkmann, J, Stefani, A, et al.. Deep brain stimulation for Parkinson disease an expert consensus and review of key issues. Arch Neurol 2011;68:165–71. https://doi.org/10.1001/archneurol.2010.260.Search in Google Scholar PubMed PubMed Central
32. Anderson, DN, Osting, B, Vorwerk, J, Dorval, AD, Butson, CR. Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes. J Neural Eng 2018;15:1–18. https://doi.org/10.1088/1741-2552/aaa14b.Search in Google Scholar PubMed
33. Shukla, A, Zeilman, P, Fernandez, H, Bajwa, JA, Mehanna, R. DBS programming: an evolving approach for patients with Parkinson’s disease. Parkinsons Dis 2017;2017:8492619. https://doi.org/10.1155/2017/8492619.Search in Google Scholar PubMed PubMed Central
34. Grimaldi, G, Manto, M. Neurological tremor: sensors, signal processing and emerging applications. Sensors 2010;10:1399–422. https://doi.org/10.3390/s100201399.Search in Google Scholar PubMed PubMed Central
35. Mansur, PHG, Cury, LKP, Andrade, AO, Pereira, AA, Miotto, GAA, Soares, AB, et al.. A review on techniques for tremor recording and quantification. Crit Rev Biomed Eng 2007;35:343–62. https://doi.org/10.1615/critrevbiomedeng.v35.i5.10.Search in Google Scholar PubMed
36. Gao, JB. Analysis of amplitude and frequency variations of essential and Parkinsonian tremors. Med Biol Eng Comput 2004;42:345–9. https://doi.org/10.1007/bf02344710.Search in Google Scholar
37. Western, DG, Neild, SA, Jones, R, Davies-Smith, A. Personalised profiling to identify clinically relevant changes in tremor due to multiple sclerosis. BMC Med Inform Decis Mak 2019;19:1–18. https://doi.org/10.1186/s12911-019-0881-1.Search in Google Scholar PubMed PubMed Central
38. Mera, T, Vitek, JL, Alberts, JL, Giuffrida, JP. Kinematic optimization of deep brain stimulation across multiple motor symptoms in Parkinson’s disease. J Neurosci Methods 2011;198:280–6. https://doi.org/10.1016/j.jneumeth.2011.03.019.Search in Google Scholar PubMed PubMed Central
39. Koch, M, Mostert, J, Heersema, D, De Keyser, J. Tremor in multiple sclerosis. J Neurol 2007;254:133–45. https://doi.org/10.1007/s00415-006-0296-7.Search in Google Scholar PubMed PubMed Central
40. Reich, MM, Steigerwald, F, Sawalhe, AD, Reese, R, Gunalan, K, Johannes, S, et al.. Short pulse width widens the therapeutic window of subthalamic neurostimulation. Ann Clin Transl Neurol 2015;2:427–32. https://doi.org/10.1002/acn3.168.Search in Google Scholar PubMed PubMed Central
41. Paschen, S, Forstenpointner, J, Becktepe, J, Heinzel, S, Hellriegel, H, Witt, K, et al.. Long-term efficacy of deep brain stimulation for essential tremor. Neurology 2019;92:1378–86. https://doi.org/10.1212/WNL.0000000000007134.Search in Google Scholar PubMed
42. Bezruchko, BP, Smirnov, DA. Extracting knowledge from time series, 1st ed. New York: Springer; 2010.10.1007/978-3-642-12601-7Search in Google Scholar
43. Cagnan, H, Pedrosa, D, Little, S, Pogosyan, A, Cheeran, B, Aziz, T, et al.. Stimulating at the right time: phase-specific deep brain stimulation. Brain 2017;140:132–45. https://doi.org/10.1093/brain/aww286.Search in Google Scholar PubMed PubMed Central
44. Thanawattano, C, Pongthornseri, R, Anan, C, Dumnin, S, Bhidayasiri, R. Temporal fluctuations of tremor signals from inertial sensor: a preliminary study in differentiating Parkinson’s disease from essential tremor. Biomed Eng Online 2015;14:1–13. https://doi.org/10.1186/s12938-015-0098-1.Search in Google Scholar PubMed PubMed Central
45. Beurter, A, Glass, L, Mackey, MC, Titcombe, MS. Nonlinear dynamics in physiology and medicine, 1st ed. New York: Springer; 2013.Search in Google Scholar
46. Griffin, DW, Lim, JS. Signal estimation from modified short-time Fourier transform. IEEE Trans Acoust 1984;32:236–43. https://doi.org/10.1109/tassp.1984.1164317.Search in Google Scholar
47. Gresty, M, Buckwell, D. Spectral analysis of tremor: understanding the results. J Neurol Neurosurg Psychiatry 1990;53:976–81. https://doi.org/10.1136/jnnp.53.11.976.Search in Google Scholar PubMed PubMed Central
48. Koss, AM, Alterman, RL, Tagliati, M, Shils, JL. Calculating total electrical energy delivered by deep brain stimulation systems. Ann Neurol 2005;58:168–9. https://doi.org/10.1002/ana.20525.Search in Google Scholar PubMed
49. Swaine, BR, Sullivan, SJ. Reliability of the scores for the finger-to-nose test in adults with traumatic brain injury. Phys Ther 1993;73:71–8. https://doi.org/10.1093/ptj/73.2.71.Search in Google Scholar PubMed
50. Swaine, BR, Lortie, É, Gravel, D. The reliability of the time to execute various forms of the Finger-to-Nose Test in healthy subjects. Physiother Theory Pract 2005;21:271–9. https://doi.org/10.1080/09593980500321119.Search in Google Scholar PubMed
51. Steigerwald, F, Timmermann, L, Kühn, A, Schnitzler, A, Reich, MM, Kirsch, AD, et al.. Pulse duration settings in subthalamic stimulation for Parkinson’s disease. Mov Disord 2018;33:165–9. https://doi.org/10.1002/mds.27238.Search in Google Scholar PubMed PubMed Central
52. Labiano-Fontcuberta, A, Benito-León, J. Understanding tremor in multiple sclerosis: prevalence, pathological anatomy, and pharmacological and surgical approaches to treatment. Tremor Other Hyperkinet Mov 2012;2:1–10. https://doi.org/10.5334/tohm.109.Search in Google Scholar
53. Hartmann, CJ, Fliegen, S, Groiss, SJ, Wojtecki, L, Schnitzler, A. An update on best practice of deep brain stimulation in Parkinson’s disease. Ther Adv Neurol Disord 2019;12:1–20. https://doi.org/10.1177/1756286419838096.Search in Google Scholar PubMed PubMed Central
54. Shah, D, Shahed, JJ. Clinical manifestations of tolerance to deep brain stimulation. Neurology 2014;82(Suppl 1):1–3.Search in Google Scholar
55. Fasano, A, Helmich, RC. Tremor habituation to deep brain stimulation: underlying mechanisms and solutions. Mov Disord 2019;34:1761–73. https://doi.org/10.1002/mds.27821.Search in Google Scholar PubMed
56. Brittain, JS, Cagnan, H, Mehta, AR, Saifee, TA, Edwards, MJ, Brown, P. Distinguishing the central drive to tremor in Parkinson’s disease and essential tremor. J Neurosci 2015;35:795–806. https://doi.org/10.1523/jneurosci.3768-14.2015.Search in Google Scholar PubMed PubMed Central
57. Kuncel, AM, Cooper, SE, Wolgamuth, BR, Grill, WM. Amplitude- and frequency-dependent changes in neuronal regularity parallel changes in tremor with thalamic deep brain stimulation. IEEE Trans Neural Syst Rehabil Eng 2007;15:190–7. https://doi.org/10.1109/tnsre.2007.897004.Search in Google Scholar PubMed
58. Moldovan, AS, Hartmann, CJ, Trenado, C, Meumertzheim, N, Slotty, PJ, Vesper, J, et al.. Less is more – pulse width dependent therapeutic window in deep brain stimulation for essential tremor. Brain Stimul 2018;11:1132–9. https://doi.org/10.1016/j.brs.2018.04.019.Search in Google Scholar PubMed
59. Montuno, MA, Kohner, AB, Foote, KD, Okun, MS. An algorithm for management of deep brain stimulation battery replacements: devising a web-based battery estimator and clinical symptom approach. Neuromodulation 2013;16:147–53. https://doi.org/10.1111/j.1525-1403.2012.00457.x.Search in Google Scholar PubMed
60. Fakhar, K, Hastings, E, Butson, CR, Foote, KD, Zeilman, P, Okun, MS. Management of deep brain stimulator battery failure: battery estimators, charge density, and importance of clinical symptoms. PLoS One 2013;8:e58665. https://doi.org/10.1371/journal.pone.0058665.Search in Google Scholar PubMed PubMed Central
61. Butson, CR, Cooper, SE, Henderson, JM, McIntyre, CC. Patient-specific analysis of the volume of tissue activated during deep brain stimulation. Neuroimage 2007;34:661–70. https://doi.org/10.1016/j.neuroimage.2006.09.034.Search in Google Scholar PubMed PubMed Central
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