Use of individualized neuroimaging for the analysis of the connectomic profile in Parkinson’s disease patients undergoing deep brain stimulation (DBS

The Movement Disorders Unit, part of the Neurology Department at Hospital de la Santa Creu i Sant Pau (Barcelona), is a multidisciplinary clinical research group with extensive experience in the diagnosis and management of movement disorders, particularly Parkinson’s disease. The research team consists of neurologists, neuropsychologists, basic researchers, laboratory technicians, and engineers. The Unit develops a variety of research programs focused on cognitive impairment, neuropsychiatric disorders, and the development of new therapies for movement disorders. Among advanced treatments, deep brain stimulation (DBS) is one of the core aspects of both clinical and research activity, with the Unit being a pioneer in this field in Spain.


DBS is an efficacious procedure that allows for decreases in medication quantity, motor improvement and lessened adverse effects in patients with advanced Parkinson’s disease (1). With this treatment, an electric field is applied near a brain target, usually the subthalamic nucleus, using a variety of parameters such as voltage, pulse width or frequency. While clinical response is generally very good, some patients do not benefit completely from the procedure, while others experience surgery related side effects and there is currently no established method to predict the onset of complications, or select the patients who will show greater improvements. Recently, the appearance of software suites that can obtain precise 3D representations of the spatial position of the leads related to neurological structures has improved the understanding of the effects of DBS in these patients (2). Furthermore, it is now possible to combine this information with tractography data (i.e., a precise depiction of the structural connections of the brain via white matter) and functional connectivity (informing how the activity of brain regions is coordinated on a time dependent basis) to understand how the electrical currents disseminate through white matter and how the brain connectivity is changed by the stimulation. All these tools can be optimized to improve the clinical results of DBS in Parkinson’s disease patients. However, they are mostly based on the analysis of so called normative connectomes: high quality imaging leveraged
from hundreds of healthy subjects that accurately depict the wiring and functional connections between different parts of the human brain. However, there is a need to understand the role that individual differences in disease severity and intrinsic brain connectivity play in response to treatment, which can be explored by the use of patient--specific tractography and functional MRI.

The student will join a collaborative project between UPF and the Movement Disorders Unit, working within a translational team with expertise in both clinical and engineering fields. They will have the opportunity to interact with DBS--implanted patients, as well as collaborate with neurologists, neuropsychologists, engineers, and other healthcare professionals. The project will involve management and processing of neuroimaging data and integration with clinical information from patients treated with DBS. Specific tools such as Lead--DBS software in the Matlab environment will be used to obtain 3D maps of lead localization and to relate this information with both normative and patient--specific connectomes.

Important Notice: All clinical and neuroimaging data are highly sensitive and subject to strict confidentiality and intellectual property protocols. Any manipulation of the data outside the scope of the initial study protocol must be communicated to the project supervisor and will be individually evaluated.


Project Goals

To advance our knowledge of connectomic profiles and clinical responses to DBS in patients with Parkinson’s disease. Specifically:

  1. To manage and process structural (T1), tractographic (DTI), and functional (fMRI) neuroimaging data.
  2. To integrate clinical and imaging information using specialized software.
  3. To become familiar with standard connectomic approaches (fiber filtering, DBS network mapping).
  4. To compare connectomic analysis based on normative connectomes with patient--specific connectomics.
  5. To move towards personalized therapy by characterizing individual brain connectivity and clinical response to DBS.

 

Required Computational Skills: The student will have close support and supervision from the clinical technical team for data analysis and biomedical reasoning. Preferred experience or interest in:

  • Programming Languages: MATLAB (required), Python (desirable).
  • Image Processing: Experience with Lead DBS, MATLAB.
  • Data Analysis: Use of statistical packages, supervised machine learning (classification), integration of neuroimaging and clinical data.
  • Other Skills: Development or adaptation of signal processing and connectomic algorithms, interest in computational neuroscience and medical image analysis.


References:
1. Krack P, Volkmann J, Tinkhauser G. Deep Brain Stimulation in Movement Disorders: From Experimental Surgery to Evidence-Based Therapy. 2019;1–16.
2. Treu S, Strange B, Oxenford S, Kühn A, Li N. Deep Brain Stimulation: Imaging on a group level. Neuroimage 2020.

 

Supervisors: Ignacio Aracil