Major depressive disorder (MDD) affects 6.7 % of the U.S. adult population and costs an estimated $104 billion per year. Despite this tremendous impact on society, the biological mechanisms of MDD are still poorly understood and consequently treatment options are limited and often ineffective. There is a clear need to establish the abnormalities in the regions and circuits of the brain associated with MDD in order to enable the development of more effective, bio- logically targeted treatments. Magnetic Resonance Imaging (MRI) can be used to measure various properties of brain tissue, however, current MRI methods possess insuf?cient resolution and sensitivity to capture many of the subtle, yet critical, changes that can serve as neurobiological markers for MDD. Ultrahigh ?eld MRI scanners, such as those oper- ating at 7 Tesla (7T), are now making it possible to noninvasively visualize smaller, more subtle abnormalities in human brain structure, connectivity and metabolism. Highly stress-sensitive structures such as the hippocampus and its tiny sub?elds, which are important in MDD pathology, can be brought beyond the threshold of detectability and quanti?ed in volume at 7T. Given these clear advantages, there are still several physical limitations and technical issues that prevent the bene?ts offered at 7T from being fully exploited. In this proposal, the goal is to overcome these limitations with the development of specialized MRI pulse sequences and novel radiofrequency (RF) pulses. From these technical devel- opments a comprehensive, multimodal 7T MRI protocol will be built that can be used to establish imaging biomarkers for MDD. Speci?cally, the aims of this proposal are: 1) Develop innovative 7T tools to target structural, connectomic and metabolic changes associated with MDD pathology and 2) Generate a comprehensive 7T MDD multi-modal imaging protocol and perform a pilot study on patients to establish neuroimaging biomarkers for MDD and its symptoms. The design goal for the proposed 7T imaging sequences is to achieve 20?40% greater signal-to-noise ratio in important brain regions, while remaining within safety limits. The hypothesis is that the high-resolution, multimodal imaging data obtained utilizing these methods will reveal grey matter volume reduction, disruptions in neuronal connectivity and neuronal and glial loss in substructures of the hippocampus and medial prefrontal cortex in MDD patients when com- pared to healthy controls. These quantitative imaging biomarkers for MDD will have signi?cant value in noninvasively assessing treatment response and tailoring new therapies based on the fundamental underlying biology of MDD. This will ultimately lead to the development of more targeted and effective treatments for MDD, enhancing the quality of life of the millions of people who suffer from this disabling disease. Furthermore, because they are developed to address fundamental problems in 7T imaging, the tools produced in this study will be generally applicable to high-?eld MRI imaging of the brain, and so could be used to improve diagnosis, treatment and neurosurgical planning for a wide range of other neurological diseases.

Public Health Relevance

Ultrahigh ?eld (7 Tesla) magnetic resonance imaging (MRI) scanners are now making it possible to noninvasively visualize subtle changes in human brain structure and metabolism. We propose developing and applying a comprehen- sive 7 Tesla MRI protocol to reveal imaging markers for the underlying biology of major depressive disorder, enabling more effective and targeted treatment approaches that will improve quality of life for the 15.7 million Americans suffering from this disabling disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH109544-03
Application #
9502372
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Friedman, Fred K
Project Start
2016-09-23
Project End
2021-06-30
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
3
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
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