Faculty DirectoryLaleh Rad
Assistant Professor of Biomedical Engineering and Radiology and (by courtesy) Electrical and Computer Engineering
Contact
2145 Sheridan RoadTech
Evanston, IL 60208-3109
Email Laleh Rad
Departments
Education
Post-Doctoral Fellow, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
Post-Doctoral Fellow, University of Toronto, Toronto, Canada
PhD in Electrical Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland
MSc in Electrical Engineering, University of Tehran, Tehran, Iran
Research Interests
- Computational electromagnetics in magnetic resonance imaging (MRI)
- Developing novel MRI technologies for imaging patients with medical implants
- Computational modeling of electric and magnetic brain stimulation techniques
- Deep brain stimulation neuroimaging
- Neural engineering
Positions
Rad Lab is currently looking for postdoctoral fellows with experience in MRI methods and simulations. Applicants should send their CV to laleh.rad1@northwestern.edu
Selected Publications
Nguyen, B.T., Bhusal, B., Rahsepar, A.A., Fawcett, K., Lin, S., Marks, D.S., Passman, R., Nieto, D., Niemzcura, R. and Golestanirad, L., 2021. Safety of MRI in patients with retained cardiac leads. Magnetic resonance in medicine.
Vu, J., Nguyen, B.T., Bhusal, B., Baraboo, J., Rosenow, J., Bagci, U., Bright, M.G. and Golestanirad, L., 2021. Machine Learning-Based Prediction of MRI-Induced Power Absorption in the Tissue in Patients With Simplified Deep Brain Stimulation Lead Models. IEEE Transactions on Electromagnetic Compatibility, 63(5), pp.1757-1766
Kazemivalipour, E., Bhusal, B., Vu, J., Lin, S., Nguyen, B.T., Kirsch, J., Nowac, E., Pilitsis, J., Rosenow, J., Atalar, E. and Golestanirad, L., 2021. Vertical open‐bore MRI scanners generate significantly less radiofrequency heating around implanted leads: A study of deep brain stimulation implants in 1.2 T OASIS scanners versus 1.5 T horizontal systems. Magnetic resonance in medicine, 86(3), pp.1560-1572.
Makarov, S.N., Golestanirad, L., Wartman, W.A., Nguyen, B.T., Noetscher, G.M., Ahveninen, J.P., Fujimoto, K., Weise, K. and Nummenmaa, A.R., 2021. Boundary element fast multipole method for modeling electrical brain stimulation with voltage and current electrodes. Journal of Neural Engineering, 18(4), p.0460d4.
Bhusal, B., Nguyen, B.T., Sanpitak, P.P., Vu, J., Elahi, B., Rosenow, J., Nolt, M.J., Lopez‐Rosado, R., Pilitsis, J., DiMarzio, M. and Golestanirad, L., 2021. Effect of Device Configuration and Patient's Body Composition on the RF Heating and Nonsusceptibility Artifact of Deep Brain Stimulation Implants During MRI at 1.5 T and 3T. Journal of Magnetic Resonance Imaging, 53(2), pp.599-610.
Kazemivalipour, E., Keil, B., Vali, A., Rajan, S., Elahi, B., Atalar, E., Wald, L.L., Rosenow, J., Pilitsis, J. and Golestanirad, L., 2019. Reconfigurable MRI technology for low-SAR imaging of deep brain stimulation at 3T: Application in bilateral leads, fully-implanted systems, and surgically modified lead trajectories. NeuroImage, 199, pp.18-29.
Golestanirad, L., Kirsch, J., Bonmassar, G., Downs, S., Elahi, B., Martin, A., Iacono, M.I., Angelone, L.M., Keil, B., Wald, L.L. and Pilitsis, J., 2019. RF-induced heating in tissue near bilateral DBS implants during MRI at 1.5 T and 3T: The role of surgical lead management. Neuroimage, 184, pp.566-576.
Patents
Rad, L.G., Wald, L.L. and Bonmassar, G., General Hospital Corp, 2021. Mri-safe implantable leads with high-dielectric coating. U.S. Patent Application 16/970,550.
Rad, L.G., Bonmassar, G. and Pascual-Leone, A., General Hospital Corp, 2021. Systems and methods for ultra-focal transcranial magnetic stimulation. U.S. Patent Application 16/971,080.
Golestanirad, L. and Graham, S.J., Sunnybrook Research Institute, 2016. Electrode designs for efficient neural stimulation. U.S. Patent 9,526,890.
Projects
Patient-adjustable MRI technology for high-resolution imaging of deep brain stimulation
In this NIH-funded multidisciplinary project we seek to develop an innovative MRI coil technology that can be adjusted for individual patients with deep brain stimulation implants to allow for a safe and high-resolution imaging of the target nuclei. The project is an exciting collaboration between Northwestern Department of Radiology, US Food and Drug Administration (FDA), and Institute of Medical Physics and Radiation Protection in Germany.
Students and postdoctoral fellows will have a unique opportunity to work with top-notch scientists, engineers and clinicians in diverse fields including RF instrumentation, medical physics, neurology, and neurosurgery as well as interacting with medical device regulatory experts in the FDA.
For related publications look at:
Golestanirad, L., Iacono, M.I., Keil, B., Angelone, L.M., Bonmassar, G., Fox, M.D., Herrington, T., Adalsteinsson, E., LaPierre, C., Mareyam, A. and Wald, L.L., 2017. Construction and modeling of a reconfigurable MRI coil for lowering SAR in patients with deep brain stimulation implants. Neuroimage, 147, pp.577-588.
Golestanirad, L., Kazemivalipour, E., Keil, B., Downs, S., Kirsch, J., Elahi, B., Pilitsis, J. and Wald, L.L., 2019. Reconfigurable MRI coil technology can substantially reduce RF heating of deep brain stimulation implants: First in-vitro study of RF heating reduction in bilateral DBS leads at 1.5 T. PloS one, 14(8), p.e0220043. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220043
Application of machine learning for fast prediction of MRI-induced RF heating in patients with implanted conductive leads
In this exciting NIH funded project, MRI physicists and machine learning experts have come together to develop, optimize, and experimentally validate a deep learning approach that predicts MRI-induced RF heating of electronic implants with elongated leads with <2 error.
If successful, this work will introduce a paradigm shift in the practice of MRI RF heating assessment, reducing simulation times from tens of hours to a few minutes. This will democratize a practice that is currently afforded by only a handful of well-resourced companies and opens the door to a plethora of novel implant designs and patient-specific safety guidelines.
For related publications look at:
Vu, J., Nguyen, B.T., Bhusal, B., Baraboo, J., Rosenow, J., Bagci, U., Bright, M.G. and Golestanirad, L., 2021. Machine Learning-Based Prediction of MRI-Induced Power Absorption in the Tissue in Patients with Simplified Deep Brain Stimulation Lead Models. IEEE Transactions on Electromagnetic Compatibility, 63(5), pp.1757-1766
Safe and Effective Cardiovascular MRI of Pediatric Patients with a Cardiac Implantable Electronic Device
Many infants and children with congenital heart disease need cardiac implantable electronic devices (CIEDs) such as pacemakers. Some infants receive a CIED within hours, or even minutes, of birth. The optimal approach to affixing a CIED to the heart of a young patient is to open the chest and sew the cardiac lead directly to the myocardium (“epicardial leads”) as opposed to passing it through veins and affix to the inside of the heart (“endocardial leads”). Unfortunately, however, once epicardial leads have been implanted, the patient is no longer eligible to receive an MRI exam due to the unknown risk of radiofrequency (RF) heating at the tip of epicardial leads. This leaves the most vulnerable patient population unable to receive the care that they need the most, as children with heart disease require complex decision making which highly benefits from MRI’s unrivaled sensitivity and accuracy.
In this project a multidisciplinary team of scientists and clinicians have come together to do an innovative study that establishes MRI safety in children with existing devices and develops physics based surgical CIED implantation techniques that eliminate risk of RF heating in future populations. Students and postdocs involved in this project will work experts in MRI biophysics and wideband cardiac MRI, as well as closely collaborating with pediatric cardiologists and cardiothoracic surgeons.