Neuroimaging for Depression
The investigators seek to determine whether brain imaging techniques can be used to help detect depression, assess its severity, and/or monitor or predict responses to treatment. Subjects with minor or major depression will be randomly assigned to a wait-list control group or to treatment with a new computer-based cognitive behavior therapy developed by Dr. James Cartriene. Brain imaging will be performed before and during treatment using both magnetic resonance imaging (MRI) and near-infrared spectroscopy (NIRS). The investigators hypothesize that brain activity, particularly in the lateral frontal areas of the brain, will provide biomarkers for depression, depression severity, and treatment response.
|Study Design:||Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single Blind (Outcomes Assessor)
Primary Purpose: Diagnostic
|Official Title:||Objective Detection, Evaluation and Countermeasures for In-flight Depression|
- Functional magnetic resonance imaging [ Time Frame: Pre-therapy and 4 weeks after therapy initiation ] [ Designated as safety issue: No ]
- Functional near infrared neuroimaging [ Time Frame: Pre-therapy and 2 and 4 weeks after therapy initiation ] [ Designated as safety issue: No ]
- MRI-based brain perfusion [ Time Frame: Pre-therapy and 4 weeks after therapy initiation ] [ Designated as safety issue: No ]
- MRI-based brain morphology [ Time Frame: Pre-therapy and 4 weeks after therapy initiation ] [ Designated as safety issue: No ]
- MRI-based diffusion imaging [ Time Frame: Pre-therapy and 4 weeks after therapy initiation ] [ Designated as safety issue: No ]
|Study Start Date:||September 2010|
|Estimated Study Completion Date:||December 2011|
|Estimated Primary Completion Date:||October 2011 (Final data collection date for primary outcome measure)|
|No Intervention: Wait list|
|Experimental: Computer-based problem solving therapy||
Behavioral: Computer-based problem solving therapy
Computer program developed by Dr. James Cartriene at Beth Israel Deaconess Hospital, Boston, MA.
Depression can significantly disrupt one's ability to function effectively and efficiently, and the associated performance deficits can seriously jeopardize space mission success. The incidence of serious depression in Earth based analogues of the spaceflight environment has been reported as up to 13% per person per year. Extrapolating from existing reports of depressive episodes during short-duration spaceflight, depression is thus a probable condition in one or more members of a five to seven person crew during a long duration spaceflight (e.g., a 30 month mission to Mars). Mission success can be jeopardized by depression either directly, from the potentially life threatening consequences of lapses in performance, or indirectly, by adding to the workload and stress of other crewmembers. The likelihood and potentially serious consequences of depression during spaceflight explains why the risk of human performance failure due to mood alterations such as depression, anxiety, or other psychiatric and cognitive problems is a Priority 1 risk for all mission types (International Space Station, Moon, Mars). Certain countermeasures are already in place: medications and psychological consultations with ground-crews. However, current in-flight methods to decide whether a countermeasure should be used rely heavily on subjective self-reports. The biological basis of mood disorders suggests neural biomarkers may provide a more objective method for assessing depression. Aim 1 of this proposal, therefore, seeks to identify neural biomarkers sensitive to, and specific for, depression. These measures will be used in evaluating and validating a flight-capable, noninvasive neuroimaging technology (near-infrared spectroscopy and imaging, or NIRS imaging) for its ability to detect biomarkers of depression and its severity. As an initial step towards developing novel select-out criteria, Aim 2 will then evaluate which neural biomarkers appear most promising in detecting an endophenotype that identifies individuals at heightened risk for treatment resistance. Finally, when depression is objectively identified, an appropriate countermeasure needs to be selected. Aim 3 will focus on the ability of brain imaging to help predict the efficacy of Dr. Cartriene's computer based problem solving therapy.
|United States, Massachusetts|
|Massachusetts General Hospital|
|Charlestown, Massachusetts, United States, 02129|
|Principal Investigator:||Gary E Strangman, PhD||Massachusetts General Hospital|