Can Dopamine Responsiveness Be Predicted in Parkinson’s Disease Without an Acute Administration Test?

Article type: Research Article

Authors: Betrouni, Nacim^{a; *} | Moreau, Caroline^{a; b} | Rolland, Anne-Sophie^a | Carrière, Nicolas^{a; b; c} | Viard, Romain^{a; c} | Lopes, Renaud^{a; c} | Kuchcinski, Gregory^{a; d} | Eusebio, Alexandre^e | Thobois, Stephane^f | Hainque, Elodie^g | Hubsch, Cecile^h | Rascol, Olivierⁱ | Brefel, Christineⁱ | Drapier, Sophie^j | Giordana, Caroline^k | Durif, Franck^k | Maltête, David^l | Guehl, Dominique^m | Hopes, Lucieⁿ | Rouaud, Tiphaine^o | Jarraya, Bechir^p | Benatru, Isabelle^q | Tranchant, Christine^r | Tir, Melissa^s | Chupin, Marie^t | Bardinet, Eric^u | Defebvre, Luc^{a; b} | Corvol, Jean-Christophe^{g; v} | Devos, David^{a; b} | the PREDISTIM Study Group

Affiliations: [a] University Lille, INSERM, CHU Lille, U1172 – LilNCog – Lille Neuroscience & Cognition, LICEND, Lille, France | [b] CHU Lille, Neurology and Movement Disorders Department, Reference Center for Parkinson’s Disease, Lille, France; NS-Park French Network | [c] University Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, Lille, France; NS-Park French Network | [d] CHU Lille, Neuroradioloy Department, Lille, France | [e] Aix Marseille Universitë, AP-HM, Hôpital de La Timone, Service de Neurologie et Pathologie du Mouvement, UMR CNRS 7289, Institut de Neuroscience de La Timone, Marseille, France; NS-Park French Network | [f] Hospices Civils de Lyon, Hôpital Neurologique Pierre Wertheimer, Neurologie C, Bron, France | [g] Dëpartement de Neurologie, Hôpital Pitië-Salpêtrière, AP-HP, Paris, France; NS-Park French Network | [h] Fondation Ophtalmologique A de Rothschild, Unitë James Parkinson, Paris, France; NS-Park French Network | [i] University of Toulouse 3, University Hospital of Toulouse, INSERM, Departments of Neuroscience and Clinical Pharmacology, Clinical Investigation Center CIC 1436, Toulouse Parkinson Expert Center, NS-NeuroToul Center of Excellence for Neurodegenerative Disorders (COEN), Toulouse, France; NS-Park French Network | [j] Service de Neurologie, CHU Pont Chaillou, 2 rue Henri le Guilloux, Rennes cedex, France; NS-Park French Network | [k] Universitë Clermont Auvergne, EA7280, Clermont-Ferrand University Hospital, Neurology Department, Clermont-Ferrand, France; NS-Park French Network | [l] Department of Neurology, Rouen University Hospital and University of Rouen, France; INSERM U1239, Laboratory of Neuronal and Neuroendocrine Differentiation and Communication, Mont-Saint-Aignan, France; NS-Park French Network | [m] Service d’Explorations Fonctionnelles du Système Nerveux, Institut des Maladies Neurodëgënëratives Cliniques, CHU de Bordeaux, Bordeaux, France; NS-Park French Network | [n] Neurology Department, Nancy University Hospital, Nancy, France; NS-Park French Network | [o] Clinique Neurologique, Hôpital Guillaume et Renë Laennec, Boulevard Jacques Monod, Nantes Cedex, France; NS-Park French Network | [p] Movement Disorders Unit, Foch Hospital, Universitë Paris-Saclay (UVSQ), INSERM U992, NeuroSpin, CEA Paris-Saclay, Suresnes, France; NS-Park French Network | [q] Service de Neurologie, Centre Expert Parkinson, CIC-INSERM 1402, CHU Poitiers, Poitiers, France; NS-Park French Network | [r] Service de Neurologie, Hôpitaux Universitaires de Strasbourg, Strasbourg, France; Institut de Gënëtique et de Biologie Molëculaire et Cellulaire (IGBMC), INSERM-U964/CNRS-UMR7104/Universitë de Strasbourg, Illkirch, France; Fëdëration de Mëdecine Translationnelle de Strasbourg (FMTS), Universitë de Strasbourg, Strasbourg, France; NS-Park French Network | [s] Department of Neurosurgery, Amiens University Hospital, Amiens, France; Medical Imaging Unit, Amiens University Hospital, Amiens, France; BioFlowImage Research Group, Jules Verne University of Picardie, Amiens, France; NS-Park French Network | [t] CATI, Institut du Cerveau et de le Moelle Epinière, ICM, INSERM U1127, CNRS UMR7225, Sorbonne Universitë, Paris, France | [u] Institut du Cerveau et de le Moelle Epinière, ICM, INSERM U1127, CNRS UMR7225, Sorbonne Universitë, Paris, France | [v] Facultë de Mëdecine de Sorbonne Universitë, UMR S 1127, INSERM U 1127, and CNRS UMR 7225, and Institut du Cerveau et de la Moëlle Epinière, Paris, France; NS-Park French Network

Correspondence: [*] Correspondence to: Nacim Betrouni, PhD, INSERM, U1172, CHU de Lille, F-59037 Lille, France. Tel.: +33 3 20 44 63 54; E-mail: nacim.betrouni@inserm.fr.

Abstract: Background:Dopamine responsiveness (dopa-sensitivity) is an important parameter in the management of patients with Parkinson’s disease (PD). For quantification of this parameter, patients undergo a challenge test with acute Levodopa administration after drug withdrawal, which may lead to patient discomfort and use of significant resources. Objective:Our objective was to develop a predictive model combining clinical scores and imaging. Methods:350 patients, recruited by 13 specialist French centers and considered for deep brain stimulation, underwent an acute L-dopa challenge (dopa-sensitivity > 30%), full assessment, and MRI investigations, including T1w and R2* images. Data were randomly divided into a learning base from 10 centers and data from the remaining centers for testing. A machine selection approach was applied to choose the optimal variables and these were then used in regression modeling. Complexity of the modelling was incremental, while the first model considered only clinical variables, the subsequent included imaging features. The performances were evaluated by comparing the estimated values and actual values Results:Whatever the model, the variables age, sex, disease duration, and motor scores were selected as contributors. The first model used them and the coefficients of determination (R2) was 0.60 for the testing set and 0.69 in the learning set (p < 0.001). The models that added imaging features enhanced the performances: with T1w (R2 = 0.65 and 0.76, p < 0.001) and with R2* (R2 = 0.60 and 0.72, p < 0.001). Conclusion:These results suggest that modeling is potentially a simple way to estimate dopa-sensitivity, but requires confirmation in a larger population, including patients with dopa-sensitivity < 30%

Keywords: Dopamine, dopa-sensitivity, prediction modelling, MRI

DOI: 10.3233/JPD-223334

Journal: Journal of Parkinson's Disease, vol. 12, no. 7, pp. 2179-2190, 2022