Probabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy

Annals of Neurology - Tập 89 Số 3 - Trang 426-443 - 2021
Gavin J.B. Elias1,2, Alexandre Boutet1,3,2, Suresh E. Joel4, Jürgen Germann1, Dave Gwun1, Clemens Neudorfer1, Robert Gramer1, Musleh Algarni5,2, Vijayashankar Paramanandam5,2, Sreeram Prasad5,2, Michelle E. Beyn1, Andreas Horn6, Radhika Madhavan4, Manish Ranjan1, Caroline Lozano1, Andrea A. Kühn6, Jeffrey Ashe4, Walter Kucharczyk3,2, Renato P. Munhoz5,2, Peter Giacobbe7, Sidney H. Kennedy8,2, D. Blake Woodside8, Suneil K. Kalia1,2, Alfonso Fasano5,2, Mojgan Hodaie1,2, Andrés M. Lozano1,2
1Division of Neurosurgery, Department of Surgery, University Health Network and University of Toronto, Toronto, Ontario, Canada
2Krembil Research Institute, University of Toronto, Toronto, Ontario, Canada
3Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
4GE Global Research, Toronto, Ontario, Canada
5Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Clinic, University Health Network, Toronto, Ontario, Canada
6Movement Disorders and Neuromodulation Unit, Department for Neurology Charité‐Universitätsmedizin Berlin Germany
7Department of Psychiatry, Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
8Centre for Mental Health, University Health Network, Toronto, Ontario, Canada

Tóm tắt

Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (ntotal = 482 patients; nParkinson disease = 303; ndystonia = 64; ntremor = 39; ntreatment‐resistant depression/anorexia nervosa = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high‐resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above‐mean and below‐mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient‐specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426–443

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Annals of Neurology

Tập 89 Số 3

426-443

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