Suresh E. Joel, PhD is a Lead Scientist, Diagnostics and Biomedical Technologies, GE Global Research.
While used within the research
community for over 20 years, fMRI
has not had widespread clinical
impact, primarily being limited to
pre-surgical planning. This is due in
part to complexity of conducting and
interpreting fMRI experiments including
the stimulus and response setup
(visual, auditory, olfactory, gustatory,
tactile, motor, cognitive, and several
others that have been studied), the
need for patient compliance, the fact
that functional information is obtained
only for regions associated with the
task, and advanced post-processing/
Within the research community,
fMRI has helped gain a tremendous
understanding of brain function. Over
25,000 peer-reviewed journal articles
indicate the significant impact in the
areas of cognitive, social neuroscience,
and understanding brain diseases.
So, how can fMRI overcome the limitations
for clinical use? A potential and promising
technique is called resting state fMRI
(rs-fMRI). rs-fMRI does not require
stimulation, is less sensitive to patient
compliance, and provides functional
information of the entire brain. Resting
state fMRI is acquired using a standard
EPI scan while the patient simply lies
in the scanner. Advanced processing
methods can then be applied to identify
various networks (e.g. visual, auditory,
executive control, and motor).
Initial rs-fMRI research using different
methodologies has identified several
potential biomarkers that may be able
to aid in the diagnosis of a disease
(Table 1). Beyond fMRI, rs-fMRI has led
to significant findings in understanding
brain function1, 2, 3 and differences in
various disease states.
4, 5, 6, 7, 8, 9, 10 In the
last few years, cognitive neuroscientists,
neurologists, psychiatrists, and
psychologists have begun to use
rs-fMRI to study the brain.
Given these attributes, rs-fMRI appears
to have great potential for implementation
in a clinical setting. Through continued
development of tools to process rs-fMRI
images and extract novel biomarkers
for specific diseases, rs-fMRI could
provide a score—similar to a lab test—
to help clinicians detect brain diseases
that today have no definitive diagnosis,
such as Alzheimer’s disease (AD). In
fact, several recent studies reliably
demonstrate one specific biomarker
extracted from rs-fMRI that distinguishes
AD from other cognitive impairments
and neurodegenerative diseases.
4, 5, 6
At GE Healthcare, we are investing in
the development of software solutions
to simplify image processing and
further automate rs-fMRI workflow.
1. Kelly AMC, Uddin LQ, Biswal BB, Castellanos FX, Milham MP.
Competition between functional brain networks mediates
behavioral variability. NeuroImage. 2008; 39(1):527-537.
doi: 10.1016/ j.neuroimage.2007.08.008.
2. Monti MM, Vanhaudenhuyse A, Coleman MR, et al. Willful
modulation of brain activity in disorders of consciousness.
The New England Journal of Medicine. 2010;362( 7):579-
589. doi: 10.1056/NEJMoa0905370.
3. Boly M, Tshibanda L, Vanhaudenhuyse A, et al. Functional
connectivity in the default network during resting state is
preserved in a vegetative but not in a brain dead patient.
Human Brain Mapping. 2009; 30( 8):2393-2400. doi: 10.1002/
4. Rombouts SARB, Barkhof F, Goekoop R, Stam CJ, Scheltens
P. Altered resting state networks in mild cognitive
impairment and mild Alzheimer’s disease: An fMRI study.
Hum Brain Mapp. 2005 Dec; 26( 4):231-239.
5. Seeley WW, Crawford, R. K., Zhou, J., Miller, B. L., & Greicius,
M.D. (2009). Neurodegenerative diseases target large-scale
human brain networks. Neuron, 62(1), 42-52. doi: 10.1016/j.
6. Chen, G., Ward, B. D., Xie, C., Li, W., Wu, Z., Jones, J. L.,
Franczak, M., et al. (2011). Classification of Alzheimer
disease, mild cognitive impairment, and normal cognitive
status with large-scale network analysis based on
resting-state functional MR imaging. Radiology, 259(1),
213-221. doi: 10.1148/radiol.10100734.
7. Greicius MD, Flores BH, Menon V, et al. Resting-State
Functional Connectivity in Major Depression: Abnormally
Increased Contributions from Subgenual Cingulate Cortex
and Thalamus. Biol Psychiatry. 2007 September
1; 62( 5):429-437. doi: 10.1016/ j.biopsych.2006.09.020.
8. Zhou Y, Shu N, Liu Y, et al. Altered resting-state functional
connectivity and anatomical connectivity of hippocampus
in schizophrenia. Schizophrenia Research 100. 2008;120-132.
9. Greicius, M. (2008). Resting-state functional connectivity in
neuropsychiatric disorders. Current opinion in neurology,
21( 4), 424.
10. Lowe MJ, Beall EB, Sakaie KE, et al. Resting state sensorimotor
functional connectivity in multiple sclerosis inversely
correlates with transcallosal motor pathway transverse
diffusivity. Hum Brain Mapp. 2008 Jul; 29( 7):818-27.