The research proposed herein aims at obtaining robust estimates of diffusion representations (images, tensors, spectra) from diffusion-weighted magnetic resonance (MR) data, by compensating for the high levels of noise and distortions in the data. Although the algorithms will be widely applicable to diffusion MRI, the application of interest is the imaging of cerebral white-matter structures. The proposed approach is that of a penalized likelihood (PL) framework, where the diffusion representations are estimated by maximizing an objective function that consists of a likelihood term that fits the solution to the raw MR data plus a regularization term that penalizes overly noisy solutions. The algorithms will utilize the raw time-domain data from the scanner, avoiding the oversimplified Fourier transform data model. The first components of the framework, involving a PL approach to tensor estimation with magnetic field inhomogeneity correction, are being prototyped and will be completed during the mentored phase of the award. In later stages, these components will be incorporated in diffusion spectrum estimation. In parallel to development, high-resolution ex vivo data will be used as a gold standard to evaluate the methods and optimize the relative weighting of the likelihood and regularization terms, i.e., the amount of smoothing. The project fits the candidate's long-term career goal of establishing a high-quality independent research program on inverse problems in medical imaging that spans different modalities. It will also facilitate the candidate's immediate goals of becoming an expert in diffusion MR data analysis and advancing this field by translating the skills acquired in her previous work in statistical reconstruction for emission tomography. The mentored phase will be performed at the MGH/Harvard/MIT Martinos Center for Biomedical Imaging. The candidate will take advantage of the cutting-edge MRI facilities and expertise at the Center, as well as the world-class educational opportunities at its collaborating institutions. Her career development plan includes training in MR data acquisition; consultations with experts of the field; coursework in MR physics and neuroscience; seminars and scientific meetings. As part of launching her own independent research program, the candidate will mentor a graduate student who will be expected to contribute to this project. Relevance: Information extracted from diffusion-weighted MR data is used in medicine, e.g., to monitor brain function in stroke patients; to detect the effects of diseases such as schizophrenia, multiple sclerosis and Alzheimer's; to assess newborn brain development; and to research connectivity of brain regions. The long- term objective of this work is to develop algorithms that enhance the quality of the measures estimated from diffusion-weighted MR data. As such, it has the potential to benefit this wide and growing range of medical applications and promote important areas of public health.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Transition Award (R00)
Project #
4R00EB008129-03
Application #
8059859
Study Section
Special Emphasis Panel (NSS)
Program Officer
Luo, James
Project Start
2010-07-01
Project End
2013-06-30
Budget Start
2010-07-01
Budget End
2011-06-30
Support Year
3
Fiscal Year
2010
Total Cost
$249,000
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Fjell, Anders M; Sneve, Markus H; Grydeland, HÃ¥kon et al. (2017) Relationship between structural and functional connectivity change across the adult lifespan: A longitudinal investigation. Hum Brain Mapp 38:561-573
Yendiki, Anastasia; Reuter, Martin; Wilkens, Paul et al. (2016) Joint reconstruction of white-matter pathways from longitudinal diffusion MRI data with anatomical priors. Neuroimage 127:277-286
Fjell, Anders M; Sneve, Markus H; Storsve, Andreas B et al. (2016) Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity. Cereb Cortex 26:1272-1286
Yendiki, Anastasia; Koldewyn, Kami; Kakunoori, Sita et al. (2014) Spurious group differences due to head motion in a diffusion MRI study. Neuroimage 88:79-90
Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin et al. (2013) Fast dictionary-based reconstruction for diffusion spectrum imaging. IEEE Trans Med Imaging 32:2022-33
Saygin, Zeynep M; Norton, Elizabeth S; Osher, David E et al. (2013) Tracking the roots of reading ability: white matter volume and integrity correlate with phonological awareness in prereading and early-reading kindergarten children. J Neurosci 33:13251-8
Walton, Esther; Geisler, Daniel; Hass, Johanna et al. (2013) The impact of genome-wide supported schizophrenia risk variants in the neurogranin gene on brain structure and function. PLoS One 8:e76815
Bilgic, Berkin; Setsompop, Kawin; Cohen-Adad, Julien et al. (2012) Accelerated diffusion spectrum imaging with compressed sensing using adaptive dictionaries. Magn Reson Med 68:1747-54
Yendiki, Anastasia; Panneck, Patricia; Srinivasan, Priti et al. (2011) Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy. Front Neuroinform 5:23