Magnetic Resonance Imaging and Spectroscopy Section
Richard Spencer, Ph.D., M.D., Chief
The Magnetic Resonance Imaging and Spectroscopy Section focuses primarily on studies of brain, muscle, and cartilage in normative aging and in the setting of specific pathologies of particular interest in the aging population.
This involves studies of human subjects, experimental animals, and tissue and cellular preparations, with techniques ranging from established conventional analysis techniques to highly specialized advanced mathematical approaches to extract tissue information from the magnetic resonance signal.
The brain studies primarily involve novel methods for myelin mapping and cerebral blood flow determination in an attempt to establish correlates and possible causal links with cognitive impairment and Alzheimer’s disease. Muscle studies center on quantifying diffusion and perfusion in response to exercise, again with an emphasis on normative aging and sarcopenia. Bioenergetic studies using phosphorus-31 magnetic resonance spectroscopy also form a substantial part of the muscle work; these bioenergetics studies are ideal for investigations incorporating endpoints from the Baltimore Longitudinal Study on Aging, a major ongoing research initiative at the NIA. In addition to these human studies, extensive animal work is also performed. For this, investigations of cerebral blood flow, brain volumetrics, and metabolite quantification are of primary interest. Much of this research is done in collaboration with other basic science groups at the NIA.
The group works actively in the area of linear and non-linear inverse problems that arise in magnetic resonance relaxometry ; this involves stability considerations and the effect of regularization on derived parameter values. Working from this viewpoint, we initiated the systematic study of multiexponential spin relaxation in cartilage, introducing methodology which is now widely used in connective tissue analysis. Further development has demonstrated the stabilization of MR parameter estimates in multi-compartment models through use of Bayesian techniques. All of this work and two-dimensional extensions are now being applied to studies of muscle, cartilage, and spinal cord.
Human studies are performed on a research-dedicated whole-body 3T Philips Achieva scanner with spectroscopy and multinuclear capability. Animal and tissue studies are performed on our 7T 30 cm Bruker Biospec horizontal bore scanner and our Bruker 9.4T wide-bore vertical system, all equipped with modern electronics and a wide range of high-quality magnetic resonance probes.
- Clinical Research
- Computational Biology/Bioinformatics/Biostatistics/Mathematics
Findings and Publications
Ashinsky, B.A., Coletta, C.E., Bouhrara M., Lukas, V.A., Boyle, J.M., Reiter, D.A., Neu, C.P., Goldberg, I.G., and Spencer, R.G. Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging. Osteoarthritis and Cartilage 23(10):704–1712, 2015.
Bouhrara M., Bonny, J.M., Ashinsky B.A., Maring M.C., and Spencer R.G. Noise estimation and reduction in magnetic resonance imaging using a new multispectral nonlocal maximum-likelihood filter. IEEE Transactions in Medical Imaging 36(1):181-193, 2016.
Bohrara M. and Spencer R. G. Rapid Simultaneous High-resolution Mapping of Myelin Water Fraction and Relaxation Times in Human Brain using BMC-mcDESPOT. NeuroImage 147:800-811, 2016.
Ashinsky B.G., Bouhrara M., Coletta C.E., Lehallier B., Urish K.L., Goldberg I.G., and Spencer R.G. Predicting early symptomatic osteoarthritis in the human knee using machine learning classification of magnetic resonance images from the Osteoarthritis Initiative. Journal of Orthopaedic Research, Jan 13. doi: 10.1002/jor.23519, 2017.
Cameron D., Bouhrara M., Reiter D.A., Fishbein K.W., Choi S., Bergeron C. M., Ferrucci L., and Spencer R.G. The Effect of Noise and Lipid Signals on Determination of Gaussian and Non-Gaussian Diffusion Parameters in Skeletal Muscle. NMR in Biomedicine Jul;30(7). doi: 10.1002/nbm.3718, 2017.