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Adaptive Deep Brain Stimulation

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Adaptive Deep Brain Stimulation (aDBS), also known as Closed Loop Deep Brain stimulation (clDBS), is a neuro-modulatory technique currently under investigation for the treatment of neurodegenerative diseases.[1]

Conventional DBS delivers constant electrical stimulation to regions of the brain that control movement through a surgically implanted wire, or lead, that is connected to an implantable pulse generator (IPG). Programming adjustments to the pulse generator are frequently made by the treating neurologist based on what the patient is doing and the medication they take over time to optimize the patient's symptoms.[2] However, it can lead to side effects.[3] aDBS and differs from conventional DBS systems (that provide constant stimulation) in that it can both sense the brain activity and deliver the appropriate stimulation in real time. Of note, in the early days of Deep Brain Stimulation, closed loop applications were carried out by multiple pioneers, such as José Delgado,[4] Robert Heath,[5] Natalia Bechtereva[6] and Carl Wilhelm Sem-Jacobsen long before the advent of 'modern' DBS. Perhaps the earliest closed-loop experiment in an animal model was performed by Delgado and colleagues in 1969.[4][7] In the modern era of DBS following the introduction of the method by Alim Louis Benabid, after a demonstration of efficacy of aDBS in the macaque by the team of Hagai Bergman in 2011,[8] the first in-human application of aDBS was carried out by the team of Peter Brown in 2013,[9] followed by the team of Alberto Priori in the same year.[10]

History in Parkinson's disease

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After being developed in the 1950s, and modern versions introduced by the team of Alim Louis Benabid in the 1980ies, DBS received recognition as a treatment method for tremor and later Parkinson's disease, dystonia, obsessive–compulsive disorder and epilepsy.[11] However, the working mechanism of conventional DBS involved the continuous stimulation of the target structure, which is an approach that cannot adapt to patients' changing symptoms or functional status in real-time.[12]

Keeping in view this unwanted side effect of DBS, concepts that have the capability to sense brain activity and automatically adjust the stimulation in response to fluctuating biomarkers, were re-introduced by multiple teams, with a first peer-reviewed publication in modern times by the teams of Hagai Bergman (in primates)[8] and Peter Brown (in humans),[9] followed by the team of Alberto Priori in the same year.[10] The study, followed by others testing more patients in longer time windows (up to 24 hours) supported the hypothesis that aDBS is effective in controlling PD symptoms while reducing side effects of constant stimulation.[13][14]

The device used in these studies was the external component of the AlphaDBS system developed by Newronika.[15] While these advancements were ongoing, Medtronic published the architecture of an implantable aDBS device for application in humans.[16][17] This design was embedded in Medtronic's Activa PC + S research device, allowing LFP sensing and recording while delivering targeted DBS therapy. This device was used in 2018 by a research team led by Philip A. Starr at the University of California, San Francisco, in a public-private partnership with Medtronic. The researchers inserted the device into two patients with Parkinson's disease who had traditional DBS but continued to experience dyskinesia after adjustment by a neurologist. Later on, they compared the results of the adaptive stimulation system with traditional stimulation set manually on two patients, and found that the adaptive approach was as effective at controlling symptoms as constant stimulation.[18][19] The AlphaDBS implantable system by Newronika was developed and CE-marked in 2021. A systematic study was also conducted to highlight safety and efficacy of aDBS vs cDBS using this new generation of DBS IPG in PD.[20]

The AlphaDBS represents a new generation commercially available DBS implantable pulse generator (IPG) for DBS and sensing, with aDBS capabilities. A systematic multicentre international study consisted of six investigational sites (in Italy, Poland and The Netherlands) was also conducted to highlight safety and efficacy of aDBS vs cDBS using this a new generation of DBS IPG in PD (AlphaDBS system by Newronika SpA, Milan, Italy).[10] The Medtronic PC+S device was also developed in a commercial IPG allowing stimulation and sensing, the Percept PC, which is approved for aDBS delivery in Japan. Nobutaka Hattori and the group performed a research study, focused on exploring the case of a 51-year-old man with Parkinson's disease (PD) presenting with motor fluctuations, who received bilateral subthalamic deep brain stimulation (DBS) the Percept PC device, showing the feasibility of the approach. While these new devices seem to have various applications in terms of facilitating condition-dependent stimulation, and providing new insights into the pathophysiological mechanisms of PD, they are currently under investigation in larger clinical studies, to definitely allow their use in clinical practice

Mechanism of action

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In order to adapt to the stimulation parameters, adaptive DBS (aDBS) employs the local field potential (LFP) of the target structure recorded through the implanted electrodes that deliver stimulation.[21] The present application of adaptive DBS (aDBS) technique is primarily based on the detection of increased beta oscillations in the subthalamic nucleus (STN),[22] on account of which it has the capability to change the current depending on the strength of the beta band oscillation, and can, therefore, overcome conventional DBS (cDBS) therapy limitations, including stimulation-induced long term side effects, such as dyskinesia[13] or speech deterioration.[23]

Medical use

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Adaptive Deep Brain Stimulation (aDBS) is a treatment modality that is being studied for the treatment of multiple neuropsychiatric and movement disorders.

Parkinson's disease (PD)

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Since 2015, several experiments were carried out to assess the efficacy of aDBS, that uses beta-band power of the subthalamic Local Field Potentials (LFPs) as target to adapt DBS parameters to motor fluctuations. Results of the experiments proved that aDBS is highly effective in controlling the patients PD symptoms in addition to the normal Levodopa therapy, reducing dyskinesias.[24]

Tourette syndrome (TS)

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Adaptive deep brain stimulation (aDBS) is currently being studied to be used as a potential treatment for TS. A 2017 research study presented a review on the available literature supporting the feasibility of an LFP-based aDBS approach in patients with TS. In addition to that, researchers have put forward several explorative findings regarding LFP data recently acquired and analysed in patients with TS after DBS electrode implantation at rest, during voluntary and involuntary movements (tics), and during ongoing DBS. It was found out that LFPs recorded from DBS targets can be used to control new aDBS devices capable of adaptive stimulation responsive to the symptoms of TS.[25][26]

Dystonia

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The applications of aDBS in the treatment of dystonia have significantly evolved over the past few years. Low-frequency oscillations (LFO) detected in the internal globus pallidus of dystonia patients have been identified as a physiomarker for adaptive Deep Brain Stimulation (aDBS).[22] Moreover, the characteristics of pallidal low-frequency and beta bursts can be helpful in implementing adaptive brain stimulation in the context of parkinsonian and dystonic internal globus pallidus.[23] A significant amount of scientific research to date on pathological oscillations in dystonia has been focused to address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.[24]

Essential tremor (ET)

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Adaptive deep brain stimulation (aDBS) may be an effective tool in the treatment of essential tremor (ET), which is one of the most common neurological movement disorders. aDBS for ET is however more focused on a closed-loop technology based on external sensors.[27][28] In a recent study, H J Chizeck presented the first translation-ready training procedure for a fully embedded aDBS control system for MDs and one of the first examples of such a system in ET.[29]

Comparison with conventional DBS (cDBS)

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In a 2021 research study conducted by Alberto Priori, a comparative analysis was presented between the impacts on motor symptoms between conventional deep brain stimulation (cDBS) and closed-loop adaptive deep brain stimulation (aDBS) in patients with Parkinson's disease. This work highlighted the safety and effectiveness of aDBS stimulation compared to cDBS in a daily session, both in terms of motor performance and TEED to the patient.[2] Simon Little has regarded aDBS approach to be superior to conventional DBS in PD in primates using cortical neuronal spike triggering and in humans employing local field potential biomarkers.[3] While presenting a protocol for a pseudo-randomised clinical study for adaptive deep brain stimulation as advanced Parkinson's disease treatment, it was shown that aDBS do not induce dysarthria, in contrast to cDBS.[22] Also it has been suggested that aDBS and cDBS can improve patient's axial symptoms to a similar extent, but compared with cDBS, aDBS significantly improves its main symptom, bradykinesia.[30]

References

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  1. ^ Marceglia, Sara; Guidetti, Matteo; Harmsen, Irene E; Loh, Aaron; Meoni, Sara; Foffani, Guglielmo; Lozano, Andres M; Volkmann, Jens; Moro, Elena; Priori, Alberto (December 2021). "Deep brain stimulation: is it time to change gears by closing the loop?". Journal of Neural Engineering. 18 (6): 061001. Bibcode:2021JNEng..18f1001M. doi:10.1088/1741-2552/ac3267. hdl:2434/877893. PMID 34678794. S2CID 239472558.
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  3. ^ a b Beudel, Martijn; Cagnan, Hayriye; Little, Simon (2018). "Adaptive Brain Stimulation for Movement Disorders". Current Concepts in Movement Disorder Management. Progress in Neurological Surgery. Vol. 33. pp. 230–242. doi:10.1159/000481107. ISBN 978-3-318-06201-4.
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  19. ^ Swann, Nicole C.; de Hemptinne, Coralie; Thompson, Margaret C.; Miocinovic, Svjetlana; Miller, Andrew M.; Gilron, Ro'ee; Ostrem, Jill L.; Chizeck, Howard J.; Starr, Philip A. (August 18, 2018). "Adaptive deep brain stimulation for Parkinson's disease using motor cortex sensing". Journal of Neural Engineering. 15 (4): 046006. Bibcode:2018JNEng..15d6006S. doi:10.1088/1741-2552/aabc9b. PMC 6021210. PMID 29741160.
  20. ^ Arlotti, Mattia; Colombo, Matteo; Bonfanti, Andrea; Mandat, Tomasz; Lanotte, Michele Maria; Pirola, Elena; Borellini, Linda; Rampini, Paolo; Eleopra, Roberto; Rinaldo, Sara; Romito, Luigi; Janssen, Marcus L. F.; Priori, Alberto; Marceglia, Sara (November 18, 2021). "A New Implantable Closed-Loop Clinical Neural Interface: First Application in Parkinson's Disease". Frontiers in Neuroscience. 15: 763235. doi:10.3389/fnins.2021.763235. PMC 8689059. PMID 34949982.
  21. ^ Nakajima, Asuka; Shimo, Yasushi; Fuse, Atsuhito; Tokugawa, Joji; Hishii, Makoto; Iwamuro, Hirokazu; Umemura, Atsushi; Hattori, Nobutaka (November 18, 2021). "Case Report: Chronic Adaptive Deep Brain Stimulation Personalizing Therapy Based on Parkinsonian State". Frontiers in Human Neuroscience. 15: 702961. doi:10.3389/fnhum.2021.702961. PMC 8414587. PMID 34483867.
  22. ^ a b Piña-Fuentes, Dan; Beudel, Martijn; Little, Simon; Brown, Peter; Oterdoom, D L Marinus; van Dijk, J Marc C (June 2019). "Adaptive deep brain stimulation as advanced Parkinson's disease treatment (ADAPT study): protocol for a pseudo-randomised clinical study". BMJ Open. 9 (6): e029652. doi:10.1136/bmjopen-2019-029652. PMC 6575861. PMID 31201193.
  23. ^ Little, Simon; Tripoliti, Elina; Beudel, Martijn; Pogosyan, Alek; Cagnan, Hayriye; Herz, Damian; Bestmann, Sven; Aziz, Tipu; Cheeran, Binith; Zrinzo, Ludvic; Hariz, Marwan; Hyam, Jonathan; Limousin, Patricia; Foltynie, Tom; Brown, Peter (December 18, 2016). "Adaptive deep brain stimulation for Parkinson's disease demonstrates reduced speech side effects compared to conventional stimulation in the acute setting". Journal of Neurology, Neurosurgery, and Psychiatry. 87 (12): 1388–1389. doi:10.1136/jnnp-2016-313518. PMC 5136720. PMID 27530809.
  24. ^ Bocci, T.; Arlotti, M.; Marceglia, S.; Prenassi, M.; Ardolino, G.; Cogiamanian, F.; Borrellini, L.; Rampini, P.; Locatelli, M.; Barbieri, S.; Priori, A. (January 2019). "Adaptive Deep Brain Stimulation for Parkinson's disease: Safety and effectiveness". Clinical Neurophysiology. 130 (1): e17. doi:10.1016/j.clinph.2018.09.098. S2CID 56569946.
  25. ^ Marceglia, Sara; Rosa, Manuela; Servello, Domenico; Porta, Mauro; Barbieri, Sergio; Moro, Elena; Priori, Alberto (January 18, 2018). "Adaptive Deep Brain Stimulation (aDBS) for Tourette Syndrome". Brain Sciences. 8 (1): 4. doi:10.3390/brainsci8010004. PMC 5789335. PMID 29295486.
  26. ^ Molina, Rene; Okun, Michael S.; Shute, Jonathan B.; Opri, Enrico; Rossi, P. Justin; Martinez-Ramirez, Daniel; Foote, Kelly D.; Gunduz, Aysegul (August 18, 2018). "Report of a patient undergoing chronic responsive deep brain stimulation for Tourette syndrome: proof of concept". Journal of Neurosurgery. 129 (2): 308–314. doi:10.3171/2017.6.JNS17626. PMC 7007215. PMID 28960154.
  27. ^ Fra̧czek, Tomasz M.; Ferleger, Benjamin I.; Brown, Timothy E.; Thompson, Margaret C.; Haddock, Andrew J.; Houston, Brady C.; Ojemann, Jeffrey G.; Ko, Andrew L.; Herron, Jeffrey A.; Chizeck, Howard J. (November 18, 2021). "Closing the Loop With Cortical Sensing: The Development of Adaptive Deep Brain Stimulation for Essential Tremor Using the Activa PC+S". Frontiers in Neuroscience. 15: 749705. doi:10.3389/fnins.2021.749705. PMC 8695120. PMID 34955714.
  28. ^ Priori, Alberto; Maiorana, Natale; Dini, Michelangelo; Guidetti, Matteo; Marceglia, Sara; Ferrucci, Roberta (2021). "Adaptive deep brain stimulation (ADBS)". Emerging Horizons in Neuromodulation: New Frontiers in Brain and Spine Stimulation. International Review of Neurobiology. Vol. 159. pp. 111–127. doi:10.1016/bs.irn.2021.06.006. ISBN 978-0-12-822298-0. PMID 34446243.
  29. ^ Ferleger, B I; Houston, B; Thompson, M C; Cooper, S S; Sonnet, K S; Ko, A L; Herron, J A; Chizeck, H J (October 2020). "Fully implanted adaptive deep brain stimulation in freely moving essential tremor patients". Journal of Neural Engineering. 17 (5): 056026. Bibcode:2020JNEng..17e6026F. doi:10.1088/1741-2552/abb416. PMID 33055369. S2CID 219166717.
  30. ^ Rosa, Manuela; Arlotti, Mattia; Ardolino, Gianluca; Cogiamanian, Filippo; Marceglia, Sara; Di Fonzo, Alessio; Cortese, Francesca; Rampini, Paolo M.; Priori, Alberto (June 18, 2015). "Adaptive deep brain stimulation in a freely moving parkinsonian patient". Movement Disorders. 30 (7): 1003–1005. doi:10.1002/mds.26241. PMC 5032989. PMID 25999288.
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