The future of deep brain stimulation (DBS) for Parkinson\u2019s disease (PD) lies in new closed-loop systems that continuously
supply the implanted stimulator with new settings obtained by analyzing a feedback signal related to the patient\u2019s current
clinical condition

Ardolino, Gianluca

Arlotti, Mattia

Cogiamanian, Filippo

Cortese, Francesca

Di Fonzo, Alessio

Marceglia, Sara Renata Francesca

Priori, Alberto

Rampini, Paolo M.

Rosa, Manuela

PubMed

M. Rosa

F. Cogiamanian

A. Di Fonzo

A. Priori

M. Arlotti

G. Ardolino

S. Marceglia

F. Cortese

P. M. Rampini

AIR Universita degli studi di Milano

Adaptive deep brain stimulation in a freely moving parkinsonian patient

Marceglia, Sara

Archivio della ricerca- Università di Roma La Sapienza

The future of deep brain stimulation (DBS) for Parkinson's disease (PD) lies in new closed‐loop systems that continuously supply the implanted stimulator with new settings obtained by analyzing a feedback signal related to the patient's current clinical condition.1 The most suitable feedback for PD is subthalamic local field potential (LFP) activity recorded from the stimulating electrode itself.2, 3, 4 This closed‐loop technology known as adaptive DBS (aDBS) recently proved superior to conventional open‐loop DBS (cDBS) in patients with PD.2

No studies have yet tested aDBS in freely moving humans for a prolonged time. This information is an essential prerequisite for developing new implantable aDBS devices for chronic PD treatment.

In this single‐case study, we tested whether a portable DBS device we developed is suitable to compare the clinical benefit in a freely moving PD patient induced by either aDBS or cDBS. To do so, after a first experimental session for extracting patient settings to personalize the aDBS algorithm, we treated a blinded patient (51 y old, male, 8 y PD history) with cDBS and aDBS in two separate experimental sessions each lasting 120 min, 5 and 6 d, respectively, after DBS electrode implant. To ensure reliable results, the patient underwent repeated clinical assessments every 20 min (T1‐T5) by two independent blinded neurologists through Unified Parkinson's Disease Rating Scale (UPDRS) III subsections and Rush Dyskinesia Rating Scale (see Supplemental Data for details)

ARLOTTI, MATTIA

Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna

Manuela Rosa

Mattia Arlotti

Gianluca Ardolino

Filippo Cogiamanian

Sara Marceglia

Alessio Di Fonzo

Francesca Cortese

Paolo M. Rampini

Alberto Priori

Crossref

Movement Disorders

The future of deep brain stimulation (DBS) for Parkinson’s disease (PD) lies in new closed-loop systems that continuously
supply the implanted stimulator with new settings obtained by analyzing a feedback signal related to the patient’s current
clinical condition

MARCEGLIA, SARA RENATA FRANCESCA

Archivio istituzionale della ricerca - Università di Trieste

Gavin Giovannoni, FRCP, PhD,5 Andrew J. Lees, FRCP,MD,1,2 and John Hardy, PhD*1,21Reta Lila Weston Institute, UCL Institute of Neurology2Department of Molecular Neuroscience, UCL Institute ofNeurology3Department of Clinical Neuroscience, UCL Institute ofNeurology4Wolfson Institute of Preventive Medicine, Queen MaryUniversity of London5Blizard Institute, Barts and the London School of Medicineand Dentistry, Queen Mary University of LondonReferences1. Sieber B-A, Landis S, Koroshetz W, et al. Prioritized research rec-ommendations from the National Institute of Neurological Disor-ders and Stroke Parkinson’s Disease 2014 conference. Ann Neurol2014;76:469-472.2. Noyce AJ, Bestwick JP, Silveira-Moriyama L, et al. Meta-analysisof early nonmotor features and risk factors for Parkinson disease.Ann Neurol 2012;72:893-901.3. Noyce AJ, Bestwick JP, Silveira-Moriyama L, et al. PREDICT-PD:identifying risk of Parkinson’s disease in the community: methodsand baseline results. J Neurol Neurosurg Psychiatry 2014;85:31-37.4. Winder-Rhodes SE, Evans JR, Ban M, et al. Glucocerebrosidasemutations influence the natural history of Parkinson’s disease in acommunity-based incident cohort. Brain 2013;136:392-399.5. Duran R, Mencacci NE, Angeli AV, et al. The glucocerobrosidaseE326K variant predisposes to Parkinson’s disease, but does notcause Gaucher’s disease. Mov Disord 2012;28:232-236.6. Walker JM, Lwin A, Tayebi N, et al. Glucocerebrosidase mutationT369M appears to be another polymorphism. Clin Genet 2003;63:237-238.7. Healy DG, Falchi M, O’Sullivan SS, et al. Phenotype, genotype,and worldwide genetic penetrance of LRRK2-associated Parkin-son’s disease: a case-control study. Lancet Neurol 2008;7:583-590.Supporting DataAdditional Supporting Information may be found in theonline version of this article.Adaptive Deep BrainStimulation in a FreelyMoving ParkinsonianPatientThe future of deep brain stimulation (DBS) for Parkinson’sdisease (PD) lies in new closed-loop systems that continuouslysupply the implanted stimulator with new settings obtainedby analyzing a feedback signal related to the patient’s currentclinical condition.1 The most suitable feedback for PD is sub-thalamic local field potential (LFP) activity recorded from thestimulating electrode itself.2-4 This closed-loop technologyknown as adaptive DBS (aDBS) recently proved superior toconventional open-loop DBS (cDBS) in patients with PD.2No studies have yet tested aDBS in freely moving humansfor a prolonged time. This information is an essential prereq-uisite for developing new implantable aDBS devices forchronic PD treatment.In this single-case study, we tested whether a portableDBS device we developed is suitable to compare the clinicalbenefit in a freely moving PD patient induced by eitheraDBS or cDBS. To do so, after a first experimental sessionfor extracting patient settings to personalize the aDBS algo-rithm, we treated a blinded patient (51 y old, male, 8 y PDhistory) with cDBS and aDBS in two separate experimentalsessions each lasting 120 min, 5 and 6 d, respectively, afterDBS electrode implant. To ensure reliable results, the patientunderwent repeated clinical assessments every 20 min (T1-T5) by two independent blinded neurologists through Uni-fied Parkinson’s Disease Rating Scale (UPDRS) III subsec-tions and Rush Dyskinesia Rating Scale (see SupplementalData for details).The aDBS portable device we used was equipped with an adhoc algorithm that analyzed patient’s LFP beta band power(13-17 Hz) and adapted voltage stimulation linearly each sec-ond (Fig. 1A).The patient during aDBS experienced a more stable con-dition than during cDBS, with better control of symptomsand dyskinesias over time (Fig. 1; video 1). In particular,aDBS and cDBS improved patient’s axial symptoms to asimilar extent (Fig. 1B), but compared with cDBS, aDBS sig-nificantly improved his main symptom, bradykinesia(Fig. 1C). aDBS did not elicit side effects and was welltolerated.Because we evaluated the patient a few days after surgerywhen he probably manifested a stunning effect,5 the aDBS-and cDBS-induced improvements were lower than thosereported by others in follow-up DBS studies.6 A major clini-cal achievement was that compared with cDBS, aDBSgreatly reduced the patient’s dyskinesias during gait and atrest (Fig. 1B; Fig. 1D). Presumably it did so because wedesigned the adaptive algorithm to avoid dyskinesias relatedto hyperstimulation: when L-dopa reduced beta-band LFPactivity, the voltage linearly diminished, avoidinghyperstimulation.------------------------------------------------------------VC 2014 The Authors. Movement Disorders published by Wiley Periodi-cals, Inc. on behalf of International Parkinson and Movement DisorderSociety. This is an open access article under the terms of the CreativeCommons Attribution License, which permits use, distribution and repro-duction in any medium, provided the original work is properly cited.*Correspondence to: Dr. Manuela Rosa, MS, Universita degli Studi diMilano, Centro Clinico per la Neurostimolazione, le Neurotecnologie ed iDisordini del Movimento Fondazione IRCCS, Ca’ Granda Ospedale Mag-giore Policlinico, Via Francesco Sforza 35, Milano, 20122 Italy, e-mail:manuela.rosa@policlinico.mi.itFunding agencies: This study was supported by Fondazione IRCCS Ca’Granda Ospedale Maggiore Policlinico and by Universita degli Studi diMilano (Italy).Relevant conflicts of interest/financial disclosures: Filippo Cogiama-nian, Sara Marceglia, Paolo M Rampini e Alberto Priori are shareholdersof Newronika s.r.l., a spin-off company of Fondazione IRCCS Ca’ GrandaOspedale Maggiore Policlinico, Milan and Universita degli Studi di Milano.Full financial disclosures and author roles may be found in the online ver-sion of this article.Received: 6 October 2014; Revised: 20 February 2015; Accepted: 21March 2015Published online 21 May 2015 in Wiley Online Library(wileyonlinelibrary.com). DOI: 10.1002/mds.26241L E T T E R S : N E W O B S E R V A T I O N SMovement Disorders, Vol. 30, No. 7, 2015 1003Our results, besides corroborating findings reported by Lit-tle and colleagues2 showing that aDBS promises to be moreefficient and effective than cDBS, expand them for two impor-tant reasons. First, we tested aDBS for a longer observationtime than Little et al., and in a more ecological condition(freely moving patient). Second, the personalized algorithmcontinuously adapts stimulation settings according to LFPbeta changes, instead of providing an on–off strategy.The aDBS device we used here can assess large patientseries in real clinical settings, testing different LFP-basedadaptive strategies other than those controlled by the betaactivity to find the frequency that is more suitable to reflectpatient clinical state.7In conclusion, the approach and device we used provedeligible for prolonged use in a freely moving parkinsonianpatient and disclosed new opportunities to study aDBSduring patients’ daily activities, providing new insightsinto how this novel DBS strategy should improve patients’quality of life. Although we await future studies to con-firm our findings and to test other aDBS LFP-based algo-rithms, our observation is a step toward developing a newgeneration of implantable aDBS devices for chronic treat-ment of PD.Video legendVideo: The video shows a section of patient clinical assess-ments performed 120 min after the experiment began (T5)during standard DBS (cDBS) on the left and during adaptiveDBS (aDBS) on the right. Standard DBS was delivered at 2V, 130 Hz, 60 ms; aDBS was delivered at a stimulation volt-age that automatically changes according to the online LFPbeta recording analysis (voltage range, 0-2 V), 130 Hz, 60ms. The video shows the patient during the execution ofitems 29, 23, 24, and 31 of unified parkinson’s disease rat-ing scale (UPDRS) III scale.Manuela Rosa, MS,*1,2 Mattia Arlotti, MS,1,3 Gianluca Ardo-lino, MD,1 Filippo Cogiamanian, MD,1 Sara Marceglia, MS,PhD,1 Alessio Di Fonzo, MD, PhD,1 Francesca Cortese, MD,1,2,4Paolo M. Rampini, MD,1 and Alberto Priori, MD, PhD1,2FIG. 1. (A) Sample of aDBS functioning lasting 10 min. Upper panel, the local field potential (LFP) beta band (13-17 Hz) power and below the stimu-lation voltage. The dotted line represents the time levodopa (L-dopa) took to achieve its clinical effect. The voltage delivered by aDBS followed thebeta-band changes: When L-dopa reduced beta-band LFP activity, the voltage linearly diminished. (B) Clinical results for axial symptoms and dyski-nesias during gait. Mean Unified Parkinson’s Disease Rating Scale (UPDRS) III subsection (items 28, 29, 30) and mean Rush Dyskinesias RatingScale (DRS) (during gait) percentage score changes from baseline evaluated at T5 (120 min after the experiment began) for cDBS and aDBS.Assessment at T5 showed that the patient’s axial symptoms improved to a similar extent after aDBS and cDBS, but dyskinesias during gait reducedmore during aDBS than during cDBS. (C) Clinical results for bradykinesia. Mean changes from baseline in the UPDRS III subsection (items 23, 24,31) percentage score changes from baseline for the upper limb contralateral to the stimulation side for cDBS and aDBS from T1 to T5. The UPDRSIII subscore improved significantly more during aDBS than during cDBS (Wilcoxon matched pairs test; *P< 0.05). (D) Clinical results for dyskinesiasat rest. Mean Rush DRS (at rest) percentage score changes from baseline for cDBS and aDBS from T1 to T5. Except at T3, aDBS induced a lowermean Rush DRS increase than cDBS (Wilcoxon matched pairs test; P> 0.05) (see Supplemental Data for data analysis details).L E T T E R S : N E W O B S E R V A T I O N S1004 Movement Disorders, Vol. 30, No. 7, 20151Fondazione IRCCS Ca’ Granda Ospedale MaggiorePoliclinico, Milan, Italy2Universita degli Studi di Milano, Milan, Italy3Department of Electrical, Electronic and Information Engineer-ing ‘Guglielmo Marconi’, Universita di Bologna, Cesena, Italy4Universita la Sapienza di Roma, Polo Pontino, Latina, ItalyAcknowledgments: We thank the neurosurgery staff for the preciouscollaboration: Marco Locatelli, Giorgio Carrabba and Vincenzo Levi.References1. Hebb AO, Zhang JJ, Mahoor MH, et al. Creating the feedbackloop: closed-loop neurostimulation. Neurosurg Clin North Am2014;25:187-204.2. Little S, Pogosyan A, Neal S, et al. Adaptive deep brain stimulationin advanced Parkinson disease. Ann Neurol 2013;74:449-457.3. Priori A, Foffani G, Rossi L, inventors. Apparatus for treating neu-rological disorders by means of adaptive electro-stimulation retro-acted by biopotentials. U.P patent 8,078,281. 2005.4. Priori A, Foffani G, Rossi L, Marceglia S. Adaptive deep brainstimulation (aDBS) controlled by local field potential oscillations.Exp Neurol 2013;245:77-86.5. Mann JM, Foote KD, Garvan CW, et al. Brain penetration effectsof microelectrodes and DBS leads in STN or GPi. J Neurol Neuro-surg Psychiatry 2009;80:794-797.6. Deuschl G, Schade-Brittinger C, Krack P, et al. A randomized trialof deep-brain stimulation for Parkinson’s disease. N Engl J Med2006;355:896-908.7. Rosa M, Giannicola G, Marceglia S, Fumagalli M, Barbieri S,Priori A. Neurophysiology of deep brain stimulation. Int Rev Neu-robiol 2012;107:23-55.Supporting DataAdditional supporting information may be found in theonline version of this article at the publisher’s web-site.Temporal Processing ofPerceived Body Movementin Cervical DystoniaPatients with idiopathic dystonia exhibit changes in thecognitive processing of movement.1-3 We showed thatpatients with writer’s cramp are less accurate than normalsubjects in temporally predicting perceived handwriting.4Whether this is selectively linked to the body area affectedby dystonia or is a generalized cognitive feature of dystoniaremains unclear. We addressed this issue by applying thesame experimental paradigm to patients with focal cervicaldystonia (CD).Fifteen patients with focal CD, aged 56.26 13.9 y andtreatment-free for at least 6 mo, and 15 age-matched healthysubjects were recruited in the Department of Neuroscience,University of Genoa. Patients’ disease duration was 96 6.5y, and mean6 standard deviation score on the TorontoWestern Spasmodic Torticollis Rating Scale was 14.364.8.The experimental paradigm, previously published in Avan-zino et al.,4 consisted of the perception on a screen of twovideos, one showing a right hand writing a sentence (targettask), and another showing a ball reaching a target (controltask). After a variable interval from its onset (6, 9, and 12seconds), videos were darkened. Subjects were asked to indi-cate when the perceived movement reached its end by click-ing on the keyboard space-bar (Supplemental Data). Thetiming error (Reproduced Interval – Dark Interval), the nor-malized absolute timing error ([Timing Error/Dark Interval]3 100), and the coefficient of variability (standard devia-tion/mean of Reproduced Intervals) were measured and ana-lyzed with a repeated-measures analysis of variance with thefactors GROUP, TASK, and DARK INTERVAL.Repeated-measures analysis of variance showed a signifi-cant GROUP*TASK interaction only for the normalizedabsolute timing error (F[1,28]5 5.85; P50.022; Fig. 1). Onpost hoc, this parameter was greater at all dark intervalsonly in CD patients (P50.006) and exclusively for the tar-get task (P50.024).In both groups of subjects, consistently with what wasobserved in our previous work,4 the ability to temporallypredict the end of the perceived movement was influencedby the duration of the target interval and the type of motion.Shorter dark intervals were associated with a tendency tooverestimate the duration of movement (F[2,56]5136.61;P< 0.001), greater variability (F[2,56]5 50.60, P< 0.001),and greater absolute timing error (F[2,56]5 26.06;P< 0.001). Finally, a tendency to overestimate the durationof movement was observed for the target task comparedwith the control task (F[1,28]56.38, P5 0.017). Absolutetiming error did not correlate with disease severity (Spear-man’s rho5 –0.161; P5 0.58) or duration (Spearman’srho5 0.040; P5 0.89).Our findings suggest that the abnormal timing of visuallyperceived human body motion is not exclusive to movementstopographically related to dystonia. Brain regions relevant tothe pathophysiology of dystonia, for example, sensorimotorregions of premotor and parietal cortices and cerebellum,modulate the spatiotemporal prediction of dynamic visualstimuli, and could be involved in the detected abnormal-ity.5,6 Despite the relatively small sample size, the lack ofcorrelation between timing performance and severity/dura-tion of CD suggests that the observed abnormality may notbe a direct expression of the dystonia.The selectivity of the timing abnormality might depend inpart on the difference in complexity between handwritingand the inanimate object motion. However, if motion com-plexity is the main determinant of implicit timing perform-ance, timing error should decrease at the increase of taskcomplexity also in control subjects, but this was notobserved. This notwithstanding, future studies shouldexplore temporal processing of motion in dystonia, using------------------------------------------------------------*Correspondence to: Dr. Davide Martino, PhD, MD, International Parkin-son’s Centre of Excellence, King’s College and King’s College Hospital,Denmark Hill Campus, London, UK, E-mail: davidemartino@nhs.netRelevant conflicts of interest/financial disclosures: Nothing to report.Full financial disclosures and author roles may be found in the online ver-sion of this article.Received: 11 December 2014; Revised: 5 March 2015; Accepted: 8March 2015Published online 16 April 2015 in Wiley Online Library(wileyonlinelibrary.com). DOI: 10.1002/mds.26225L E T T E R S : N E W O B S E R V A T I O N SMovement Disorders, Vol. 30, No. 7, 2015 1005

Adaptive deep brain stimulation in a freely moving parkinsonian patient

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AIR Universita degli studi di Milano

Archivio della ricerca- Università di Roma La Sapienza

Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna

Crossref

Archivio istituzionale della ricerca - Università di Trieste