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Reply to: Bridging predictive algorithms and clinical practice in DBS contact selection

npj Parkinson s Disease, vol. 12

Abstract

) for their evaluation of our algorithm, which predicts optimal deep-brain stimulation contact points in Parkinson's disease. Their analysis on an independent dataset highlights practical challenges of translating predictive tools into routine clinical use. Here, we clarify key methodological points, discuss the robustness of the algorithm, and emphasize the need for broader validation across diverse clinical centers to fully demonstrate its utility.

Authors 4

  1. Leiden University Medical Center · Haga Hospital

    Affiliation as printed

    Department of Neurology, Haga Teaching Hospital, The Hague, the Netherlands

    Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands

  2. University of Würzburg · Universitätsklinikum Würzburg

    Affiliation as printed

    Department of Neurology, University Hospital of Wuerzburg and Julius Maximilian University of Wuerzburg, Wuerzburg, Germany

    Parkinson Institute of Milan, ASST G.Pini-CTO, Milan, Italy

  3. Centre Hospitalier Universitaire Vaudois · École Polytechnique Fédérale de Lausanne · University of Lausanne

    Affiliation as printed

    Defitech Center for Interventional Neurotherapies (NeuroRestore), University Hospital Lausanne and Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Department of Clinical Neurosciences, University of Lausanne (UNIL) and University Hospital Lausanne (CHUV), Lausanne, Switzerland

  4. Leiden University Medical Center · Haga Hospital

    Affiliation as printed

    Department of Neurology, Haga Teaching Hospital, The Hague, the Netherlands. m.f.contarino@lumc.nl

    Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands. m.f.contarino@lumc.nl

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