Training in Structural, Physiologic and Functional MRI

Rajapakse CS, Leonard MB, Bhagat YA, Sun W, Magland JF, Wehrli FW. Micro–MR Imaging–based Computational Biomechanics Demonstrates Reduction in Cortical and Trabecular Bone Strength after Renal Transplantation. Radiology 2012 Mar; 262(3):912-20.

Since its inception four decades ago, magnetic resonance imaging (MRI) has continued to evolve and is far from having reached its ultimate potential. MRI is unquestionably the most complex but also the richest and most versatile imaging method therefore requiring systematic training. Although inherently quantitative, MRI has been used largely as a qualitative imaging technique practiced by radiologists utilizing predominantly qualitative criteria for establishing a diagnosis or excluding disease. This approach is fraught with problems, its main limitation being the subjective nature of the result, i.e. sensitivity to reader experience and judgment.  An increasing number of problems in medicine require a quantitative assessment of tissue structure, physiology and function. Moreover, for many diagnostic or staging problems quantification of an observation is not merely a better option but the qualitative approach is entirely unsuited.  Examples are measurement of tissue perfusion, quantification of metabolite concentration by spectroscopic imaging, the assessment of non-focal systemic disorders such as degenerative neurologic or metabolic bone disease where a quantitative measurement of some structural or functional parameter has to be made.

Over the years MRI has become ever more complex with the ongoing emergence of new methodologies, providing increasingly detailed insight into tissue function. Many of these new methods are conceived and reduced to practice years before being implemented by equipment manufacturers. Successful participation in these developments demands in-depth, modality-specific training to enable future scientists to effectively deploy the myriad of mathematical tools for pulse sequence design and data reconstruction. Translation of new methods from the bench to the clinic is equally important and highlighted as one of NIH’s key priorities. The training process therefore needs to be multidisciplinary, requiring close cooperation among MR physicists, engineers, computer scientists and physicians in the various subspecialties. Basic science trainees often understand the medical problem incompletely and typically have difficulties in translating abstract technical concepts to the practicing physician. This program will train two predoctoral and two postdoctoral candidates in MRI physics and engineering, with particular focus on structural, physiologic and functional applications, for a period of two years.  Training modalities involve a combination of colloquia, structured teaching and hands-on laboratory training, and emphasis on preceptor-directed research. The training faculty consists of MR imaging and physician scientists with a record of successful multidisciplinary research training as well as basic and translational research excellence.

Program Director

  • Felix W. Wehrli, Ph.D. Development of MRI-based methods for the visualization and analysis of tissue microarchitecture, physiology and function and their translation to the clinic

Training Faculty

  • Christos Davatzikos, Ph.D. – Computational medical image analysis
  • Jim Delikatny, Ph.D. – New methods and imaging probes to study treatment in cancer by MRS and MRI
  • John Detre, M.D. – Imaging regional brain function by MR and other imaging modalities
  • Charles L. Epstein, Ph.D. – Pulse design based on inverse scattering
  • James C. Gee, Ph.D. – Development of methods for biomedical image analysis
  • Jerry D. Glickson, Ph.D. – In vivo NMR spectroscopy and imaging of tumors
  • Despina Kontos, Ph.D. – Image analysis, pattern recognition and data mining in clinically relevant breast imaging
  • Ravinder Reddy, Ph.D. – High-field MRI and MRS methods development
  • Rahim Rizi, Ph.D. – Functional and metabolic imaging of the lungs
  • Mitchell Schnall, M.D., Ph.D. – Development and evaluation of new breast cancer imaging techniques
  • Hee Kwon Song, Ph.D. – Development of dynamic imaging strategies in MRI
  • Andrew Tsourkas, Ph.D. – Design and development of molecular probes for various imaging modalities
  • Ragini Verma, Ph.D. – Computational neuroanatomy and image analysis
  • Beth Winkelstein, Ph.D. – Pathomechanisms of chronic neck pain
  • Walter Witschey, Ph.D. – Cardiovascular MRI applications and development of advanced imaging technologies
  • Rong Zhou, Ph.D. – Biology-driven research that employs imaging technologies

Predoctoral trainee candidates must have been accepted into a biomedical or bioengineering graduate program at the University of Pennsylvania.

Postdoctoral candidates must have an advanced degree (Ph.D. or M.D./Ph.D.) in bioengineering, biophysics, physics, chemistry, or electrical engineering. Applicants with hands-on experience in MR imaging or spectroscopy data acquisition and processing methods, MRI hardware, or advanced applications are given preference but such prior training is not a requirement for being considered. NIH Training Grantee candidates must be U.S. citizens or have permanent resident status ("green card" holders).

The University of Pennsylvania is an equal opportunity employer and candidates of underrepresented minorities are particularly encouraged to apply. Interested candidates should contact the Program Director. Applicants are requested to submit their curriculum vitae along with three letters of recommendation as email attachments to:

Felix W. Wehrli, Ph.D.
Director, Laboratory for Structural NMR Imaging
Department of Radiology
University of Pennsylvania Medical Center
3400 Spruce Street
Philadelphia, PA 19104
Contact email: wehrli@mail.med.upenn.edu