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Neudorfer C, Kultas-Ilinsky K, Ilinsky I, Paschen S, Helmers AK, Cosgrove GR, Richardson RM, Horn A, Deuschl G. The role of the motor thalamus in deep brain stimulation for essential tremor. Neurotherapeutics 2024; 21:e00313. [PMID: 38195310 PMCID: PMC11103222 DOI: 10.1016/j.neurot.2023.e00313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 12/10/2023] [Accepted: 12/27/2023] [Indexed: 01/11/2024] Open
Abstract
The advent of next-generation technology has significantly advanced the implementation and delivery of Deep Brain Stimulation (DBS) for Essential Tremor (ET), yet controversies persist regarding optimal targets and networks responsible for tremor genesis and suppression. This review consolidates key insights from anatomy, neurology, electrophysiology, and radiology to summarize the current state-of-the-art in DBS for ET. We explore the role of the thalamus in motor function and describe how differences in parcellations and nomenclature have shaped our understanding of the neuroanatomical substrates associated with optimal outcomes. Subsequently, we discuss how seminal studies have propagated the ventral intermediate nucleus (Vim)-centric view of DBS effects and shaped the ongoing debate over thalamic DBS versus stimulation in the posterior subthalamic area (PSA) in ET. We then describe probabilistic- and network-mapping studies instrumental in identifying the local and network substrates subserving tremor control, which suggest that the PSA is the optimal DBS target for tremor suppression in ET. Taken together, DBS offers promising outcomes for ET, with the PSA emerging as a better target for suppression of tremor symptoms. While advanced imaging techniques have substantially improved the identification of anatomical targets within this region, uncertainties persist regarding the distinct anatomical substrates involved in optimal tremor control. Inconsistent subdivisions and nomenclature of motor areas and other subdivisions in the thalamus further obfuscate the interpretation of stimulation results. While loss of benefit and habituation to DBS remain challenging in some patients, refined DBS techniques and closed-loop paradigms may eventually overcome these limitations.
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Affiliation(s)
- Clemens Neudorfer
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA; Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
| | | | - Igor Ilinsky
- Department of Anatomy and Cell Biology, The University of Iowa, Iowa City, IA, USA
| | - Steffen Paschen
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
| | | | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Mark Richardson
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA; Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andreas Horn
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité -Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Günther Deuschl
- Department of Neurology, Christian-Albrechts-University, Kiel, Germany
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Hollunder B, Ostrem JL, Sahin IA, Rajamani N, Oxenford S, Butenko K, Neudorfer C, Reinhardt P, Zvarova P, Polosan M, Akram H, Vissani M, Zhang C, Sun B, Navratil P, Reich MM, Volkmann J, Yeh FC, Baldermann JC, Dembek TA, Visser-Vandewalle V, Alho EJL, Franceschini PR, Nanda P, Finke C, Kühn AA, Dougherty DD, Richardson RM, Bergman H, DeLong MR, Mazzoni A, Romito LM, Tyagi H, Zrinzo L, Joyce EM, Chabardes S, Starr PA, Li N, Horn A. Mapping dysfunctional circuits in the frontal cortex using deep brain stimulation. Nat Neurosci 2024; 27:573-586. [PMID: 38388734 PMCID: PMC10917675 DOI: 10.1038/s41593-024-01570-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 01/05/2024] [Indexed: 02/24/2024]
Abstract
Frontal circuits play a critical role in motor, cognitive and affective processing, and their dysfunction may result in a variety of brain disorders. However, exactly which frontal domains mediate which (dys)functions remains largely elusive. We studied 534 deep brain stimulation electrodes implanted to treat four different brain disorders. By analyzing which connections were modulated for optimal therapeutic response across these disorders, we segregated the frontal cortex into circuits that had become dysfunctional in each of them. Dysfunctional circuits were topographically arranged from occipital to frontal, ranging from interconnections with sensorimotor cortices in dystonia, the primary motor cortex in Tourette's syndrome, the supplementary motor area in Parkinson's disease, to ventromedial prefrontal and anterior cingulate cortices in obsessive-compulsive disorder. Our findings highlight the integration of deep brain stimulation with brain connectomics as a powerful tool to explore couplings between brain structure and functional impairments in the human brain.
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Affiliation(s)
- Barbara Hollunder
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jill L Ostrem
- Movement Disorders and Neuromodulation Centre, Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Ilkem Aysu Sahin
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Nanditha Rajamani
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Simón Oxenford
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Konstantin Butenko
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Clemens Neudorfer
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Pablo Reinhardt
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Patricia Zvarova
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Mircea Polosan
- Université Grenoble Alpes, Grenoble, France
- Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
- Department of Psychiatry, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
| | - Harith Akram
- Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Matteo Vissani
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Chencheng Zhang
- Department of Neurosurgery, Rujin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Bomin Sun
- Department of Neurosurgery, Rujin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Pavel Navratil
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Martin M Reich
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Juan Carlos Baldermann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Till A Dembek
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Veerle Visser-Vandewalle
- Department of Stereotactic and Functional Neurosurgery, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | | | | | - Pranav Nanda
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Carsten Finke
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andrea A Kühn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- NeuroCure Cluster of Excellence, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hagai Bergman
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University, Hadassah Medical School, Jerusalem, Israel
- Department of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel
| | - Mahlon R DeLong
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Alberto Mazzoni
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Luigi M Romito
- Parkinson and Movement Disorders Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Himanshu Tyagi
- Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
- Department of Neuropsychiatry, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Ludvic Zrinzo
- Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Eileen M Joyce
- Unit of Functional Neurosurgery, UCL Queen Square Institute of Neurology, London, UK
- Department of Neuropsychiatry, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Stephan Chabardes
- Université Grenoble Alpes, Grenoble, France
- Inserm, U1216, Grenoble Institut des Neurosciences, Grenoble, France
- Department of Neurosurgery, Centre Hospitalier Universitaire Grenoble Alpes, Grenoble, France
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Ningfei Li
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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Elias GJB, Germann J, Boutet A, Beyn ME, Giacobbe P, Song HN, Choi KS, Mayberg HS, Kennedy SH, Lozano AM. Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation. Brain Stimul 2023; 16:1259-1272. [PMID: 37611657 DOI: 10.1016/j.brs.2023.08.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 08/02/2023] [Accepted: 08/19/2023] [Indexed: 08/25/2023] Open
Abstract
BACKGROUND Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome. OBJECTIVE/HYPOTHESIS We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort. METHODS Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures. RESULTS PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047). CONCLUSION(S) These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.
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Affiliation(s)
- Gavin J B Elias
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, M5T 2S8, Canada; Krembil Research Institute, University of Toronto, Toronto, M5T 0S8, Canada
| | - Jürgen Germann
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, M5T 2S8, Canada; Krembil Research Institute, University of Toronto, Toronto, M5T 0S8, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, M5T 2S8, Canada; Krembil Research Institute, University of Toronto, Toronto, M5T 0S8, Canada; Joint Department of Medical Imaging, University of Toronto, Toronto, M5T 1W7, Canada
| | - Michelle E Beyn
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, M5T 2S8, Canada
| | - Peter Giacobbe
- Department of Psychiatry, Sunnybrook Health Sciences Centre and University of Toronto, Toronto, M4N 3M5, Canada
| | - Ha Neul Song
- Nash Family Center for Advanced Circuit Therapeutics, Mount Sinai West, Icahn School of Medicine at Mount Sinai, New York, NY, 10019, USA
| | - Ki Sueng Choi
- Nash Family Center for Advanced Circuit Therapeutics, Mount Sinai West, Icahn School of Medicine at Mount Sinai, New York, NY, 10019, USA; Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Helen S Mayberg
- Nash Family Center for Advanced Circuit Therapeutics, Mount Sinai West, Icahn School of Medicine at Mount Sinai, New York, NY, 10019, USA; Departments of Neurology and Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sidney H Kennedy
- Krembil Research Institute, University of Toronto, Toronto, M5T 0S8, Canada; ASR Suicide and Depression Studies Unit, St. Michael's Hospital, University of Toronto, M5B 1M8, Canada; Department of Psychiatry, University Health Network and University of Toronto, Toronto, M5T 2S8, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, M5T 2S8, Canada; Krembil Research Institute, University of Toronto, Toronto, M5T 0S8, Canada.
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Hacker ML, Rajamani N, Neudorfer C, Hollunder B, Oxenford S, Li N, Sternberg AL, Davis TL, Konrad PE, Horn A, Charles D. Connectivity Profile for Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson Disease. Ann Neurol 2023; 94:271-284. [PMID: 37177857 PMCID: PMC10846105 DOI: 10.1002/ana.26674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/18/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023]
Abstract
OBJECTIVE This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial. METHODS To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baseline➔24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baseline➔24 months, MedON/StimON]). RESULTS Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort. INTERPRETATION These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.
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Affiliation(s)
- Mallory L Hacker
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nanditha Rajamani
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
| | - Clemens Neudorfer
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Barbara Hollunder
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt University of Berlin, Berlin, Germany
| | - Simon Oxenford
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
| | - Ningfei Li
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
| | - Alice L Sternberg
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - Thomas L Davis
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter E Konrad
- Department of Neurosurgery, West Virginia University, Morgantown, WV, USA
| | - Andreas Horn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurosurgery and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David Charles
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
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Muller J, Alizadeh M, Matias CM, Thalheimer S, Romo V, Martello J, Liang TW, Mohamed FB, Wu C. Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation. J Neurosurg 2022; 136:1371-1380. [PMID: 34624856 DOI: 10.3171/2021.5.jns21552] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 05/11/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Accurate electrode placement is key to effective deep brain stimulation (DBS). The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for the treatment of essential tremor (ET). Retrospective tractography-based analysis of electrode placement has associated successful outcomes with modulation of motor input to VIM, but no study has yet evaluated the feasibility and efficacy of prospective presurgical tractography-based targeting alone. Therefore, the authors sought to demonstrate the safety and efficacy of probabilistic tractography-based VIM targeting in ET patients and to perform a systematic comparison of probabilistic and deterministic tractography. METHODS Fourteen patients with ET underwent preoperative diffusion imaging. Probabilistic tractography was applied for preoperative targeting, and deterministic tractography was performed as a comparison between methods. Tractography was performed using the motor and sensory areas as initiation seeds, the ipsilateral thalamus as an inclusion mask, and the contralateral dentate nucleus as a termination mask. Tract-density maps consisted of voxels with 10% or less of the maximum intensity and were superimposed onto anatomical images for presurgical planning. Target planning was based on probabilistic tract-density images and indirect target coordinates. Patients underwent robotic image-guided, image-verified implantation of directional DBS systems. Postoperative tremor scores with and without DBS were recorded. The center of gravity and Dice similarity coefficients were calculated and compared between tracking methods. RESULTS Prospective probabilistic targeting of VIM was successful in all 14 patients. All patients experienced significant tremor reduction. Formal postoperative tremor scores were available for 9 patients, who demonstrated a mean 68.0% tremor reduction. Large differences between tracking methods were observed across patients. Probabilistic tractography-identified VIM fibers were more anterior, lateral, and superior than deterministic tractography-identified fibers, whereas probabilistic tractography-identified ventralis caudalis fibers were more posterior, lateral, and superior than deterministic tractography-identified fibers. Deterministic methods were unable to clearly distinguish between motor and sensory fibers in the majority of patients, but probabilistic methods produced distinct separation. CONCLUSIONS Probabilistic tractography-based VIM targeting is safe and effective for the treatment of ET. Probabilistic tractography is more precise than deterministic tractography for the delineation of VIM and the ventralis caudalis nucleus of the thalamus. Deterministic algorithms tended to underestimate separation between motor and sensory fibers, which may have been due to its limitations with crossing fibers. Larger studies across multiple centers are necessary to further validate this method.
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Affiliation(s)
- Jennifer Muller
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Mahdi Alizadeh
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Caio M Matias
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Sara Thalheimer
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Victor Romo
- 3Department of Anesthesia, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Justin Martello
- 4Department of Neurology, Christiana Care Health System, Newark, Delaware; and
| | - Tsao-Wei Liang
- 5Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Feroze B Mohamed
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Chengyuan Wu
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
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6
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Toward personalized medicine in connectomic deep brain stimulation. Prog Neurobiol 2021; 210:102211. [PMID: 34958874 DOI: 10.1016/j.pneurobio.2021.102211] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/15/2021] [Accepted: 12/22/2021] [Indexed: 02/08/2023]
Abstract
At the group-level, deep brain stimulation leads to significant therapeutic benefit in a multitude of neurological and neuropsychiatric disorders. At the single-patient level, however, symptoms may sometimes persist despite "optimal" electrode placement at established treatment coordinates. This may be partly explained by limitations of disease-centric strategies that are unable to account for heterogeneous phenotypes and comorbidities observed in clinical practice. Instead, tailoring electrode placement and programming to individual patients' symptom profiles may increase the fraction of top-responding patients. Here, we propose a three-step, circuit-based framework with the aim of developing patient-specific treatment targets that address the unique symptom constellation prevalent in each patient. First, we describe how a symptom network target library could be established by mapping beneficial or undesirable DBS effects to distinct circuits based on (retrospective) group-level data. Second, we suggest ways of matching the resulting symptom networks to circuits defined in the individual patient (template matching). Third, we introduce network blending as a strategy to calculate optimal stimulation targets and parameters by selecting and weighting a set of symptom-specific networks based on the symptom profile and subjective priorities of the individual patient. We integrate the approach with published literature and conclude by discussing limitations and future challenges.
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7
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Li N, Hollunder B, Baldermann JC, Kibleur A, Treu S, Akram H, Al-Fatly B, Strange BA, Barcia JA, Zrinzo L, Joyce EM, Chabardes S, Visser-Vandewalle V, Polosan M, Kuhn J, Kühn AA, Horn A. A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder. Biol Psychiatry 2021; 90:701-713. [PMID: 34134839 DOI: 10.1016/j.biopsych.2021.04.006] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/26/2021] [Accepted: 04/12/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Multiple deep brain stimulation (DBS) targets have been proposed for treating intractable obsessive-compulsive disorder (OCD). Here, we investigated whether stimulation effects of different target sites would be mediated by one common or several segregated functional brain networks. METHODS First, seeding from active electrodes of 4 OCD patient cohorts (N = 50) receiving DBS to anterior limb of the internal capsule or subthalamic nucleus zones, optimal functional connectivity profiles for maximal Yale-Brown Obsessive Compulsive Scale improvements were calculated and cross-validated in leave-one-cohort-out and leave-one-patient-out designs. Second, we derived optimal target-specific connectivity patterns to determine brain regions mutually predictive of clinical outcome for both targets and others predictive for either target alone. Functional connectivity was defined using resting-state functional magnetic resonance imaging data acquired in 1000 healthy participants. RESULTS While optimal functional connectivity profiles showed both commonalities and differences between target sites, robust cross-predictions of clinical improvements across OCD cohorts and targets suggested a shared network. Connectivity to the anterior cingulate cortex, insula, and precuneus, among other regions, was predictive regardless of stimulation target. Regions with maximal connectivity to these commonly predictive areas included the insula, superior frontal gyrus, anterior cingulate cortex, and anterior thalamus, as well as the original stereotactic targets. CONCLUSIONS Pinpointing the network modulated by DBS for OCD from different target sites identified a set of brain regions to which DBS electrodes associated with optimal outcomes were functionally connected-regardless of target choice. On these grounds, we establish potential brain areas that could prospectively inform additional or alternative neuromodulation targets for obsessive-compulsive disorder.
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Affiliation(s)
- Ningfei Li
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Berlin, Germany.
| | - Barbara Hollunder
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Berlin, Germany; Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany; Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Juan Carlos Baldermann
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne; Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Astrid Kibleur
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut des Neurosciences (AK, SC, MP), Grenoble; and OpenMind Innovation (AK), Paris, France; OpenMind Innovation, Paris, France
| | - Svenja Treu
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain
| | - Harith Akram
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom; National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust (UCLH), London, United Kingdom
| | - Bassam Al-Fatly
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Berlin, Germany
| | - Bryan A Strange
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Madrid, Spain
| | - Juan A Barcia
- Neurosurgery Department, Hospital Clínico San Carlos, Universidad Complutense de Madrid, Madrid, Spain
| | - Ludvic Zrinzo
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom; National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust (UCLH), London, United Kingdom
| | - Eileen M Joyce
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom; National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Trust (UCLH), London, United Kingdom
| | - Stephan Chabardes
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut des Neurosciences (AK, SC, MP), Grenoble; and OpenMind Innovation (AK), Paris, France
| | | | - Mircea Polosan
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut des Neurosciences (AK, SC, MP), Grenoble; and OpenMind Innovation (AK), Paris, France
| | - Jens Kuhn
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, Cologne, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, Johanniter Hospital Oberhausen, Evangelisches Klinikum Niederrhein, Oberhausen, Germany
| | - Andrea A Kühn
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Berlin, Germany; Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany; Berlin School of Mind and Brain, Faculty of Philosophy, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Andreas Horn
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Berlin, Germany; Charité - Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin, Germany
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Davidson B, Lipsman N, Meng Y, Rabin JS, Giacobbe P, Hamani C. The Use of Tractography-Based Targeting in Deep Brain Stimulation for Psychiatric Indications. Front Hum Neurosci 2020; 14:588423. [PMID: 33304258 PMCID: PMC7701283 DOI: 10.3389/fnhum.2020.588423] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 10/27/2020] [Indexed: 12/15/2022] Open
Abstract
Deep Brain Stimulation (DBS) has been investigated as a treatment option for patients with refractory psychiatric illness. Over the past two decades, neuroimaging developments have helped to advance the field, particularly the use of diffusion tensor imaging (DTI) and tractographic reconstruction of white-matter pathways. In this article, we review translational considerations and how DTI and tractography have been used to improve targeting during DBS surgery for depression, obsessive compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).
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Affiliation(s)
- Benjamin Davidson
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Nir Lipsman
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Ying Meng
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Jennifer S. Rabin
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Peter Giacobbe
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Psychiatry, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Clement Hamani
- Sunnybrook Research Institute, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Division of Neurosurgery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
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9
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Horn A, Fox MD. Opportunities of connectomic neuromodulation. Neuroimage 2020; 221:117180. [PMID: 32702488 PMCID: PMC7847552 DOI: 10.1016/j.neuroimage.2020.117180] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 06/12/2020] [Accepted: 07/16/2020] [Indexed: 12/14/2022] Open
Abstract
The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.
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Affiliation(s)
- Andreas Horn
- Neurology Department, Movement Disorders and Neuromodulation Sectio Charité - University Medicine Berlin,, Charitéplatz 1, D-10117 Berlin, Germany.
| | - Michael D Fox
- Berenson-Allen Center for Non-invasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, United States; Martinos Center for Biomedical Imaging, Departments of Neurology and Radiology, Harvard Medical School and Massachusetts General Hospital, United States; Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Harvard Medical School and Brigham and Women's Hospital, United States.
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10
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Normative vs. patient-specific brain connectivity in deep brain stimulation. Neuroimage 2020; 224:117307. [PMID: 32861787 DOI: 10.1016/j.neuroimage.2020.117307] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2020] [Revised: 08/17/2020] [Accepted: 08/22/2020] [Indexed: 11/22/2022] Open
Abstract
Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and their ability to predict clinical improvement. Data from 33 patients suffering from Parkinson's Disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely patient-specific diffusion-MRI data, age- and disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were calculated and used to estimate clinical improvement in out of sample data. All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on this present novel multi-center cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) and a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made. Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Still, although results were not significantly different, they hint at the fact that patient-specific connectivity may bear the potential of explaining slightly more variance than group connectomes. Furthermore, use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.
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11
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Zhang H, Bao Y, Feng Y, Hu H, Wang Y. Evidence for Reciprocal Structural Network Interactions Between Bilateral Crus Lobes and Broca's Complex. Front Neuroanat 2020; 14:27. [PMID: 32625067 PMCID: PMC7316155 DOI: 10.3389/fnana.2020.00027] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 05/05/2020] [Indexed: 11/24/2022] Open
Abstract
While the proximal dentatothalamocortical tracts are considered pivotal in the occurrence of cerebellar mutism syndrome (CMS) after medulloblastoma resection, how the cerebellum participates in motor–speech networks through direct structural connectivity is still unclear. Via tractography, we provide evidence of cerebellar streamlines projecting into the left inferior frontal gyrus majorly connecting Broca’s complex and the bilateral Crus lobes. The streamlines, named Crus–Broca tracts, originated from the bilateral Crus lobes, synapsed onto the dentate nucleus, ascended into the superior cerebellar peduncle (where these streamlines were closely superior to the superior border of the supratonsillar cleft and the superolateral roof of the fourth ventricle), surprisingly bypassed the left red nucleus and the left thalamus, and ended at the subregions of Broca’s complex. The streamlines, named Broca–Crus tracts, originated from the subregions of Broca’s complex and ended predominantly at the right Crus lobes. If verified, the existence of these connections would support the notion of the bilateral cerebellums’ participation in motor–speech planning, and the anatomical relationship of Broca–Crus tracts with the supratonsillar cleft would merit consideration for further studies aimed at further elucidating CMS mechanisms.
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Affiliation(s)
- Hui Zhang
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China.,Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yue Bao
- Department of Neurosurgery, Qingdao Municipal Hospital, School of Medicine, Qingdao University, Qingdao, China
| | - Yuan Feng
- Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Haijun Hu
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China
| | - Yibao Wang
- Department of Neurosurgery, The First Affiliated Hospital of China Medical University, China Medical University, Shenyang, China
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12
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A unified connectomic target for deep brain stimulation in obsessive-compulsive disorder. Nat Commun 2020; 11:3364. [PMID: 32620886 PMCID: PMC7335093 DOI: 10.1038/s41467-020-16734-3] [Citation(s) in RCA: 149] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Accepted: 05/21/2020] [Indexed: 02/06/2023] Open
Abstract
Multiple surgical targets for treating obsessive-compulsive disorder with deep brain stimulation (DBS) have been proposed. However, different targets may modulate the same neural network responsible for clinical improvement. We analyzed data from four cohorts of patients (N = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens or the subthalamic nucleus (STN). The same fiber bundle was associated with optimal clinical response in cohorts targeting either structure. This bundle connected frontal regions to the STN. When informing the tract target based on the first cohort, clinical improvements in the second could be significantly predicted, and vice versa. To further confirm results, clinical improvements in eight patients from a third center and six patients from a fourth center were significantly predicted based on their stimulation overlap with this tract. Our results show that connectivity-derived models may inform clinical improvements across DBS targets, surgeons and centers. The identified tract target is openly available in atlas form. Li et al. analyzed structural connectivity of deep brain stimulation electrodes in 50 patients suffering from obsessive-compulsive disorder operated at four centers. Connectivity to a specific tract within the anterior limb of the internal capsule was associated with optimal treatment response across cohorts, surgeons and centers.
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13
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Gravbrot N, Saranathan M, Pouratian N, Kasoff W. Advanced Imaging and Direct Targeting of the Motor Thalamus and Dentato-Rubro-Thalamic Tract for Tremor: A Systematic Review. Stereotact Funct Neurosurg 2020; 98:220-240. [DOI: 10.1159/000507030] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 02/27/2020] [Indexed: 11/19/2022]
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Abstract
The thalamus is a neural processor and integrator for the activities of the forebrain. Surprisingly, little is known about the roles of the "cerebellar" thalamus despite the anatomical observation that all the cortico-cerebello-cortical loops make relay in the main subnuclei of the thalamus. The thalamus displays a broad range of electrophysiological responses, such as neuronal spiking, bursting, or oscillatory rhythms, which contribute to precisely shape and to synchronize activities of cortical areas. We emphasize that the cerebellar thalamus deserves a renewal of interest to better understand its specific contributions to the cerebellar motor and associative functions, especially at a time where the anatomy between cerebellum and basal ganglia is being rewritten.
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15
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Dario A, Armocida GO, Locatelli D. An ancestor of the stereotactic atlases: the Tabulae Anatomicae of Bartolomeo Eustachio. Neurosurg Focus 2019; 47:E11. [PMID: 31473670 DOI: 10.3171/2019.6.focus19339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 06/17/2019] [Indexed: 11/06/2022]
Abstract
The authors report the history of the Tabulae Anatomicae of Bartolomeo Eustachio (ca. 1510-1574). In the tables, the anatomical illustrations were drawn inside a numerical frame, with pairs of numbers on the y- and x-axes to identify single anatomical details in the reference table. The measures and the references could be calculated using the graduated margins divided by 5 units for each the x-axis and y-axis. The Tabulae Anatomicae can be considered a precursor to modern anatomical reference systems that are the basis of studies on cerebral localization mainly used for stereotactic procedures.
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16
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Dimov A, Patel W, Yao Y, Wang Y, O'Halloran R, Kopell BH. Iron concentration linked to structural connectivity in the subthalamic nucleus: implications for deep brain stimulation. J Neurosurg 2019; 132:197-204. [PMID: 30660115 DOI: 10.3171/2018.8.jns18531] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Accepted: 08/31/2018] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The objective of this study was to investigate the relationship between iron and white matter connectivity in the subthalamic nucleus (STN) in patients undergoing deep brain stimulation (DBS) of the STN for treatment of Parkinson's disease. METHODS Nine Parkinson's disease patients underwent preoperative 3T MRI imaging which included acquisition of T1-weighted anatomical images along with diffusion tensor imaging (DTI) and quantitative susceptibility mapping (QSM). MR tractography was performed for the seed voxels located within the STN, and the correlations between normalized QSM values and the STN's connectivity to a set of a priori chosen regions of interest were assessed. RESULTS A strong negative correlation was found between STN connectivity and QSM intensity for the thalamus, premotor, motor, and sensory regions, while a strong positive correlation was found for frontal, putamen, and brain stem areas. CONCLUSIONS Quantitative susceptibility mapping not only accurately delineates the STN borders but is also able to provide functional information about the STN functional subdivisions. The observed iron-to-connectivity correlation patterns may aid in planning DBS surgery to avoid unwanted side effects associated with DBS.
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Affiliation(s)
- Alexey Dimov
- 1Weill Medical College of Cornell University, New York
- 2Meinig School of Biomedical Engineering, Cornell University, Ithaca
| | - Wahaj Patel
- 3Department of Radiology, Icahn School of Medicine at Mount Sinai, New York
- 4The City College of the City University of New York, New York
| | - Yihao Yao
- 5Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- 1Weill Medical College of Cornell University, New York
- 2Meinig School of Biomedical Engineering, Cornell University, Ithaca
| | - Rafael O'Halloran
- 3Department of Radiology, Icahn School of Medicine at Mount Sinai, New York
- 6Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York; and
| | - Brian H Kopell
- 7Departments of Neurosurgery, Neurology, Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York
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Lateral geniculate nucleus volumetry at 3T and 7T: Four different optimized magnetic-resonance-imaging sequences evaluated against a 7T reference acquisition. Neuroimage 2018; 186:399-409. [PMID: 30342237 DOI: 10.1016/j.neuroimage.2018.09.046] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 08/24/2018] [Accepted: 09/17/2018] [Indexed: 11/20/2022] Open
Abstract
PURPOSE The lateral geniculate nucleus (LGN) is an essential nucleus of the visual pathway, occupying a small volume (60-160 mm3) among the other thalamic nuclei. The reported LGN volumes vary greatly across studies due to technical limitations and due to methodological differences of volume assessment. Yet, structural and anatomical alterations in ophthalmologic and neurodegenerative pathologies can only be revealed by a precise and reliable LGN representation. To improve LGN volume assessment, we first implemented a reference acquisition for LGN volume determination with optimized Contrast to Noise Ratio (CNR) and high spatial resolution. Next, we compared CNR efficiency and rating reliability of 3D Magnetization Prepared Rapid Gradient Echo (MPRAGE) images using white matter nulled (WMn) and grey matter nulled (GMn) sequences and its subtraction (WMn-GMn) relative to the clinical standard Proton Density Turbo Spin Echo (PD 2D TSE) and the reference acquisition. We hypothesized that 3D MPRAGE should provide a higher CNR and volume determination accuracy than the currently used 2D sequences. MATERIALS AND METHODS In 31 healthy subjects, we obtained at 3 and 7 T the following MR sequences: PD-TSE, MPRAGE with white/grey matter signal nulled (WMn/GMn), and a motion-corrected segmented MPRAGE sequence with a resolution of 0.4 × 0.4 × 0.4 mm3 (reference acquisition). To increase CNR, GMn were subtracted from WMn (WMn-GMn). Four investigators manually segmented the LGN independently. RESULTS The reference acquisition provided a very sharp depiction of the LGN and an estimated mean LGN volume of 124 ± 3.3 mm3. WMn-GMn had the highest CNR and gave the most reproducible LGN volume estimations between field strengths. Even with the highest CNR efficiency, PD-TSE gave inconsistent LGN volumes with the weakest reference acquisition correlation. The LGN WM rim induced a significant difference between LGN volumes estimated from WMn and GMn. WMn and GMn LGN volume estimations explained most of the reference acquisition volumes' variance. For all sequences, the volume rating reliability were good. On the other hand, the best CNR rating reliability, LGN volume and CNR correlations with the reference acquisition were obtained with GMn at 7 T. CONCLUSION WMn and GMn MPRAGE allow reliable LGN volume determination at both field strengths. The precise location and identification of the LGN (volume) can help to optimize neuroanatomical and neurophysiological studies, which involve the LGN structure. Our optimized imaging protocol may be used for clinical applications aiming at small nuclei volumetric and CNR quantification.
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18
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Lee Y, Callaghan MF, Acosta-Cabronero J, Lutti A, Nagy Z. Establishing intra- and inter-vendor reproducibility of T1
relaxation time measurements with 3T MRI. Magn Reson Med 2018; 81:454-465. [DOI: 10.1002/mrm.27421] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/28/2018] [Accepted: 06/04/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Yoojin Lee
- Laboratory for Social and Neural Systems Research; University of Zurich; Zürich Switzerland
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging; UCL Institute of Neurology; London United Kingdom
| | - Julio Acosta-Cabronero
- Wellcome Centre for Human Neuroimaging; UCL Institute of Neurology; London United Kingdom
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience,; Lausanne University Hospital and University of Lausanne; Lausanne Switzerland
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research; University of Zurich; Zürich Switzerland
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Tian Q, Wintermark M, Jeffrey Elias W, Ghanouni P, Halpern CH, Henderson JM, Huss DS, Goubran M, Thaler C, Airan R, Zeineh M, Pauly KB, McNab JA. Diffusion MRI tractography for improved transcranial MRI-guided focused ultrasound thalamotomy targeting for essential tremor. NEUROIMAGE-CLINICAL 2018; 19:572-580. [PMID: 29984165 PMCID: PMC6029558 DOI: 10.1016/j.nicl.2018.05.010] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Revised: 05/03/2018] [Accepted: 05/08/2018] [Indexed: 01/07/2023]
Abstract
Purpose To evaluate the use of diffusion magnetic resonance imaging (MRI) tractography for neurosurgical guidance of transcranial MRI-guided focused ultrasound (tcMRgFUS) thalamotomy for essential tremor (ET). Materials and methods Eight patients with medication-refractory ET were treated with tcMRgFUS targeting the ventral intermediate nucleus (Vim) of the thalamus contralateral to their dominant hand. Diffusion and structural MRI data and clinical evaluations were acquired pre-treatment and post-treatment. To identify the optimal target location, tractography was performed on pre-treatment diffusion MRI data between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus. The tractography-identified locations were compared to the lesion location delineated on 1 year post-treatment T2-weighted MR image. Their overlap was correlated with the clinical outcomes measured by the percentage change of the Clinical Rating Scale for Tremor scores acquired pre-treatment, as well as 1 month, 3 months, 6 months and 1 year post-treatment. Results The probabilistic tractography was consistent from subject-to-subject and followed the expected anatomy of the thalamocortical radiation and the dentatothalamic tract. Higher overlap between the tractography-identified location and the tcMRgFUS treatment-induced lesion highly correlated with better treatment outcome (r = −0.929, −0.75, −0.643, p = 0.00675, 0.0663, 0.139 for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus, respectively, at 1 year post-treatment). The correlation for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex is the highest for all time points (r = −0.719, −0.976, −0.707, −0.929, p = 0.0519, 0.000397, 0.0595, 0.00675 at 1 month, 3 months, 6 months and 1 year post-treatment, respectively). Conclusion Our data support the use of diffusion tractography as a complementary approach to current targeting methods for tcMRgFUS thalamotomy. Retrospectively used tractography to define a target for MRgFUS thalamotomy for ET. Larger overlap between tractography and lesion correlates with better outcomes. Strongest correlations for tract between the thalamus and motor hand-knob region Diffusion tractography is a complementary approach to current targeting methods.
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Affiliation(s)
- Qiyuan Tian
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States; Department of Radiology, Stanford University, Stanford, CA, United States.
| | - Max Wintermark
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - W Jeffrey Elias
- Department of Neurosurgery, University of Virginia, Charlottesville, VA, United States
| | - Pejman Ghanouni
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Casey H Halpern
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Jaimie M Henderson
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Diane S Huss
- Department of Physical Therapy, University of Virginia, Charlottesville, VA, United States
| | - Maged Goubran
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Christian Thaler
- Department of Radiology, Stanford University, Stanford, CA, United States; Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Raag Airan
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Michael Zeineh
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Kim Butts Pauly
- Department of Electrical Engineering, Stanford University, Stanford, CA, United States; Department of Radiology, Stanford University, Stanford, CA, United States
| | - Jennifer A McNab
- Department of Radiology, Stanford University, Stanford, CA, United States
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Abstract
Diffusion tensor imaging (DTI) is a noninvasive neuroimaging tool assessing the organization of white-matter tracts and brain microstructure in vivo. The technique takes into account the three-dimensional (3D) direction of diffusion of water in space, the brownian movements of water being constrained by the brain microstructure. The main direction of diffusion in the brain is extracted to obtain the principal direction of axonal projection within a given voxel. Overall, the diffusion tensor is a mathematic analysis of the magnitude/directionality (anisotropy) of the movement of water molecules in 3D space. Tracts running in the white matter are subsequently reconstructed graphically with fiber tractography. Tractography can be applied to myelinated and unmyelinated fibers or axonopathy. Decreased fractional anisotropy in white-matter tracts occurs in cases of injury with disorganized or disrupted myelin sheaths. Furthermore, high angular resolution methods enable detection of fiber crossings or convergence. DTI is a modern tool which complements conventional magnetic resonance techniques and is particularly relevant to assess the organization of cerebellar tracts. Indeed, both the afferent and efferent pathways of the cerebellar circuitry passing through the inferior, middle, and superior cerebellar peduncles can be visualized in vivo, including in children. The microanatomy of the cerebellar cortex and cerebellar nuclei is also emerging as a future assessment. Applications in the field of cerebellar disorders are multiple, ranging from developmental disorders to adult-onset cerebellar ataxias.
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Treatment of the ventral intermediate nucleus for medically refractory tremor: A cost-analysis of stereotactic radiosurgery versus deep brain stimulation. Radiother Oncol 2017; 125:136-139. [PMID: 28818305 DOI: 10.1016/j.radonc.2017.07.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 07/26/2017] [Accepted: 07/31/2017] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Medically refractory tremor treatment has evolved over the past half-century from intraoperative thalamotomy to deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus (VIM). Within the past 15years, unilateral radiosurgical VIM thalamotomy has emerged as a comparably efficacious treatment modality. METHODS An extensive literature search of VIM DBS series was performed; the total cost of VIM DBS was calculated from hospitals geographically representative of the entire United States using current procedural terminology and work relative value unit (RVU) codes. The 2016 Medicare Ambulatory Payment Classification for stereotactic radiosurgery (SRS) was added to the work RVU to determine the total cost of VIM SRS for both Gamma Knife and linear accelerator SRS. Cost estimates assumed that VIM DBS was performed without intraoperative microelectrode recording. RESULT The mean unilateral VIM DBS cost was $17,932.41 per patient. For SRS VIM, the total costs for Gamma Knife ($10,811.77) and linear accelerator ($10,726.40) were 40% less expensive than for unilateral VIM DBS. CONCLUSION Radiosurgery of the VIM is 40% less expensive than unilateral VIM DBS in treatment of medically refractory tremor, regardless of radiosurgical modality. This finding argues for increased radiation oncology involvement in the management of medically refractory tremor patients.
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Jakab A, Tuura R, Kellenberger C, Scheer I. In utero diffusion tensor imaging of the fetal brain: A reproducibility study. NEUROIMAGE-CLINICAL 2017; 15:601-612. [PMID: 28652972 PMCID: PMC5477067 DOI: 10.1016/j.nicl.2017.06.013] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Revised: 01/25/2017] [Accepted: 06/08/2017] [Indexed: 02/06/2023]
Abstract
Our purpose was to evaluate the within-subject reproducibility of in utero diffusion tensor imaging (DTI) metrics and the visibility of major white matter structures. Images for 30 fetuses (20-33. postmenstrual weeks, normal neurodevelopment: 6 cases, cerebral pathology: 24 cases) were acquired on 1.5 T or 3.0 T MRI. DTI with 15 diffusion-weighting directions was repeated three times for each case, TR/TE: 2200/63 ms, voxel size: 1 ∗ 1 mm, slice thickness: 3-5 mm, b-factor: 700 s/mm2. Reproducibility was evaluated from structure detectability, variability of DTI measures using the coefficient of variation (CV), image correlation and structural similarity across repeated scans for six selected structures. The effect of age, scanner type, presence of pathology was determined using Wilcoxon rank sum test. White matter structures were detectable in the following percentage of fetuses in at least two of the three repeated scans: corpus callosum genu 76%, splenium 64%, internal capsule, posterior limb 60%, brainstem fibers 40% and temporooccipital association pathways 60%. The mean CV of DTI metrics ranged between 3% and 14.6% and we measured higher reproducibility in fetuses with normal brain development. Head motion was negatively correlated with reproducibility, this effect was partially ameliorated by motion-correction algorithm using image registration. Structures on 3.0 T had higher variability both with- and without motion correction. Fetal DTI is reproducible for projection and commissural bundles during mid-gestation, however, in 16-30% of the cases, data were corrupted by artifacts, resulting in impaired detection of white matter structures. To achieve robust results for the quantitative analysis of diffusivity and anisotropy values, fetal-specific image processing is recommended and repeated DTI is needed to ensure the detectability of fiber pathways.
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Key Words
- AD, axial diffusivity
- CCA, corpus callosum agenesis
- CV, coefficient of variation
- Connectome
- DTI, diffusion tensor imaging
- Diffusion tensor imaging
- FA, fractional anisotropy
- Fetal brain connectivity
- Fetal diffusion MRI
- GW, gestational week
- MD, mean diffusivity
- Prenatal development
- RD, radial diffusivity
- ROI, region of interest
- SSIM, structural similarity index
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Affiliation(s)
- András Jakab
- Center for MR-Research, University Children's Hospital, Zürich, Switzerland; Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria.
| | - Ruth Tuura
- Center for MR-Research, University Children's Hospital, Zürich, Switzerland
| | | | - Ianina Scheer
- Department of Diagnostic Imaging, University Children's Hospital, Zürich, Switzerland
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