4.5 Article

Nucleus basalis of Meynert predicts cognition after deep brain stimulation in Parkinson's disease

Journal

PARKINSONISM & RELATED DISORDERS
Volume 94, Issue -, Pages 89-95

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.parkreldis.2021.12.002

Keywords

Parkinson's disease; Deep brain stimulation; Cognition; Nucleus basalis of meynert; Basal forebrain

Funding

  1. BIH-Charite Clinician Scientist Program - Charite-Universit atsmedizin Berlin
  2. Berlin Institute of Health
  3. German Research Foundation (DFG) [389563835, TRR 265/A07, CRC 1404/A05, 424778381, TRR 295, KU 2261/13-1, EXC 2049/1]
  4. Brain & Behavior Research Foundation (NARSAD grant, USA)
  5. Bundesministerium fur Bildung und Forschung [iDBS FKZ01GQ1802]
  6. BIH/Wellcome Trust SPOKES Fellowship
  7. HERTIE Excellence in Clinical Neuroscience Fellowship

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NBM volume can be used as a simple non-invasive predictor for cognitive outcome after DBS in Parkinson's disease, especially when combined with other clinically relevant parameters.
Introduction: Subthalamic DBS in Parkinson's disease has been associated with cognitive decline in few cases. Volume reduction of the nucleus basalis of Meynert (NBM) seems to precede cognitive impairment in Parkinson's disease. In this retrospective study, we evaluated NBM volume as a predictor of cognitive outcome 1 year after subthalamic DBS. Methods: NBM volumes were calculated from preoperative MRIs using voxel-based morphometry. Cognitive outcome was defined as the relative change of MMSE or DemTect scores from pre-to 1 year postoperatively. A multiple linear regression analysis adjusted for the number of cognitive domains affected in the preoperative neuropsychological testing and UPDRS III was conducted. To account for other variables and potential non-linear effects, an additional machine learning analysis using random forests was applied. Results: 55 patients with Parkinson's disease (39 male, age 61.4 +/- 7.5 years, disease duration 10.8 +/- 4.7 years) who received bilateral subthalamic DBS electrodes at our center were included. Although overall cognition did not change significantly, individual change in cognitive abilities was variable. Cognitive outcome could be predicted based on NBM size (B = 208.98, p = 0.022*) in the regression model (F(3,49) = 2.869; R-2 of 0.149; p = 0.046*). Using random forests with more variables, cognitive outcome could also be predicted (average root mean squared error between predicted and true cognitive change 11.28 +/- 9.51, p = 0.039*). Also in this model, NBM volume was the most predictive variable. Conclusion: NBM volume can be used as a simple non-invasive predictor for cognitive outcome after DBS in Parkinson's disease, especially when combined with other clinical parameters that are prognostically relevant.

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