Deep brain stimulation in Parkinson's disease: analysis of brain fractional anisotropy differences in operated patients

Deep brain stimulation (DBS) of the subthalamic nucleus is currently an evidence-based therapeutic option for motor symptoms in patients with Parkinson's disease (PD), although other non-motor symptoms can be affected by stimulation. Our objective is to evaluate the global changes in the connec...

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Veröffentlicht in:Revista de neurologiá 2022-02, Vol.74 (4), p.125
Hauptverfasser: Arévalo-Sáenz, A, López-Manzanares, L, Navas-García, M, Pastor, J, Vega-Zelaya, L, Torres, C V
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Sprache:eng ; spa
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Zusammenfassung:Deep brain stimulation (DBS) of the subthalamic nucleus is currently an evidence-based therapeutic option for motor symptoms in patients with Parkinson's disease (PD), although other non-motor symptoms can be affected by stimulation. Our objective is to evaluate the global changes in the connectivity of the large-scale structural network in PD patients that have obtained a benefit from subthalamic DBS. Retrospective study of 31 subjects: 7 PD patients with subthalamic DBS (group A), 12 age and gender-matched non-operated PD (B) and 12 healthy controls (C). All subjects had undergone a 1.5 T brain MRI with DTI. DICOM images were processed with the FSL5.0 software and TBSS tool. The study group comprised 23 men and 8 women. No statistically significant differences in age, gender, scores on the HandY scale and mean follow-up between group A and B were found, and in age and gender between groups A and C. Statistical analysis revealed differences in the fractional anisotropy of the different groups in certain areas: bilateral corticospinal tract, anterior thalamic radiations, bilateral fronto-occipital fascicle, both superior longitudinal fascicles, and left inferior longitudinal fascicle. In our series, PD patients treated with bilateral subthalamic DBS showed a significantly higher fractional anisotropy in widespread areas of the cerebral white matter; suggesting that neuromodulation produces connectivity changes in different neural networks.
ISSN:1576-6578
1576-6578
DOI:10.33588/rn.7404.2021196