Mentor: Carlo Pierpaoli, MD.Ph.D. | carlo.pierpaoli@nih.gov
Lab: Laboratory on Quantitative Medical Imaging (QMI)
NIBIB
Mentor: Amritha Nayak, M.E. |
Lab: Laboratory on Quantitative Medical Imaging (QMI)
NIBIB

Improving pre-surgical planning of focused–ultrasound therapy for essential tremor using diffusion Magnetic Resonance Imaging (MRI)

Magnetic resonance guided focused ultrasound (MRgFUS) is a procedure that produces a selective and targeted ablation in the brain to reduce the severity of symptoms in essential tremor (ET). The lesion is produced by high temperature in a specific region of interest (ROI) in the Thalamus. Obviously, a proper localization of the target ROI is essential.  The aim of this project is to analyze longitudinally retrospective MRI data to learn how to produce an optimal pre-surgical localization of the target. With advanced imaging techniques such as diffusion tensor imaging (DTI) and accurate tensor-based registration, it is possible to evaluate with high accuracy microstructural and volume changes for each individual and relate the changes to their clinical improvement or occurrence of undesirable outcomes. 

In the proposed retrospective study, the incoming BESIP intern will

  1. Get familiarized with brain anatomy.
  2. Learn the basis of MRgFUS, a clinical procedure used in the treatment of essential tremor (ET).
  3. Learn the fundamentals of Magnetic Resonance Imaging (MRI) and Diffusion MRI 
  4. Be introduced to DTI data processing in a longitudinal study. 
  5. Gain an understanding about longitudinal MRI data analysis. 
  6. Gain an understanding about the use of neuroimaging tools in personalized medicine. 
  7. Get trained in using available white and gray matter region of interest (ROI) or get trained on drawing specific ROIs. 
  8. Present preliminary results of the analysis at the annual summer poster day. 

Throughout the project, mentors will guide the intern about data processing and its analysis. The intern will also participate in weekly lab meetings and gain a perspective about quantitative neuroimaging research.