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Construction and validation of a multimodal database for deep brain stimulation

Abstract : Deep brain stimulation (DBS) is an effective treatment for patients with severe disabled Parkinson's disease refractory to medical treatments. DBS surgery consists of the accurate implantation of an electrode in a deep brain nucleus. The quality of the surgical planning can be improved by developing a multimodal database based on anatomical, clinical and electrophysiologial data. The first step was to develop a specific magnetic resonance imaging (MRI) template of Parkinson's disease patients' anatomy, and to validate the segmentation of the 24 deep brain structures made on this template. Secondly, we focused on identifying optimum sites for subthalamic nucleus (STN) stimulation by studying symptomatic motor improvement along with neuropsychological side effects in 30 patients with PD. Each clinical score produced one anatomo-clinical atlas, associating the degree of improvement or worsening of the patient with its active contacts.We showed a discrepancy between a good motor improvement and an invevitable deterioration of the fluencies by targeting the postero-superior region of the STN. Finally, we developed new statistical anatomo-clinical maps the better to visualize the motor and neuropsychological consequences at 6 months of GPm stimulation in 20 patients with PD. These maps provided us with the motor improvement of GPm stimulation without cognitive impairments. We also proposed a new more lateral targeting of the GPm in PD because of the cortico-subcortical atrophy induced by the disease. Our goal is to use these statistical maps prospectively in further patients to improve their targeting, thus ensuring a shorter planning step on the day of the surgery as well as better outcomes from motor and neuropsychological point of view.
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Submitted on : Thursday, October 9, 2014 - 8:53:08 AM
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  • HAL Id : tel-01073108, version 1

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Claire Haegelen. Construction and validation of a multimodal database for deep brain stimulation. Imaging. Université Rennes 1, 2014. English. ⟨NNT : 2014REN1B003⟩. ⟨tel-01073108⟩

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