I am an Assistant Professor at the
A. A. Martinos Center for Biomedical Imaging
, Department of Radiology at
Massachusetts General Hospital
and
Harvard Medical School.
My research is funded through an NIH K99/R00 Pathway to Independence Career Award from the
National Institute on Drug Abuse.
I completed my PhD in the
Electrical Engineering and Computer Science Department
at
Massachusetts Institute of Technology
in 2014.
My research focuses on multi-modal imaging with combined MRI (magnetic resonance imaging) and PET (positron emission tomography). My main interests are to advance multi-modal imaging techniques, develop new experimental approaches and devise quantitative models with the goal to map signaling pathways of the living brain, and link molecular dynamics to distributed brain function. I envision to bridge the gap between engineering and neuroscientific applications, transforming state-of-the-art imaging approaches into new clinical applications and diagnostic practices for brain disorders.
I pursue an integrated approach to non-invasively image the brain. My goal is to develop in vivo molecular and functional imaging techniques in order to build a molecular-level understanding of whole-brain function, physiology and networks. While my research is driven by neuroscientific or clinical questions, my approach uses technical expertise and quantitative approaches.
Specifically, my research focuses on (i) creating novel multi-modal experimental imaging techniques for imaging neuroreceptors in the living brain (ii) developing biomarkers through quantitative biophysical and biochemical models and (iii) apply these methods to investigate the interplay between neurochemistry and neural circuit function, or dysfunction, in the living brain. Ultimately, my goal is to translate these non-invasive techniques into the clinic to advance diagnosis and treatment of brain disorders.
Some of my key research areas in multi-modal imaging with combined PET and functional MRI are:
Neuroreceptors are the gateways to the transmission of information in the brain. They can be dynamically activated or inhibited by neurotransmitters as well as exogenous drugs. Using combined PET/fMRI, we observe dynamic changes in receptor occupancy and functional signaling in order to pursue answers the questions above.
Dynamic imaging signals are 4D datasets that contain both physiological and instrumentation noise. In order to extract relevant biological parameters, we need to accurately analyze and model the acquired data. This involves not only simulations but also quantification and validation of experimental data signal through relevant biophysical models.
Email: csander (at) mgh (dot) harvard (dot) edu
Athinoula A. Martinos Center for Biomedical Imaging
149 Thirteenth Street, Suite 2301
Charlestown, MA 02129
Athinoula A. Martinos
Center for Biomedical Imaging
Massachusetts General Hospital
Harvard Medical School