Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT03229915 |
| Other study ID # |
B2017:029 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
October 1, 2017 |
| Est. completion date |
September 30, 2022 |
Study information
| Verified date |
February 2023 |
| Source |
University of Manitoba |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
Posttraumatic stress disorder (PTSD) is prevalent mental illness (~9% life-time) that results
from exposure to trauma. As it is associated with vastly heterogeneous origins, accurate
diagnosis and optimal treatment strategies are sometimes very difficult to achieve. No known
biomarker exists, which makes it difficult to assess treatment response and functional
outcomes. The recent brain imaging studies have suggested that PTSD patients show abnormal
brain connectivity measured by functional magnetic resonance imaging (fMRI). The
investigators propose that cognitive processing therapy may ameliorate this functional
connectivity abnormality which may be related with their symptomatic improvement.
Description:
Posttraumatic stress disorder (PTSD) develops when a constellation of symptoms persist
following exposure to traumatic events such as actual or threatened death, serious injury,
and sexual violation, leading to significant interference with occupational and social
functioning. Epidemiological data indicate that the rate of lifetime PTSD in Canada is
approximately 9.2%, with a rate of current PTSD (symptoms for 1 month) estimated to be 2.4%.
Although significant advances have been made in the treatment of PTSD, e.g.,
cognitive-behavioural therapy; pharmacological interventions, a sizable proportion of
individuals do not respond to treatment. The lack of biomarkers and poor understanding of the
pathophysiology has hindered the efforts for advancing treatment of this disorder.
The meta-analysis on functional magnetic resonance imaging (fMRI) studies demonstrated that
patients with PTSD show reliable hyper-activity in the limbic brain regions including the
amygdala and hippocampus, while prefrontal brain regions associated with top-down executive
control, show decreased activity. These findings were in line with traditional neurocircuitry
models proposing that PTSD-related deficits in attention or awareness, including the
inability to suppress attention to trauma-related stimuli, are mediated by decreased
recruitment of the medial prefrontal cortex (PFC) whereas vivid and intrusive trauma
recollections are mediated by exaggerated amygdala activity. While the traditional
neurocircuity model proposed more of a unidirectional relationship (i.e., loss of top-down
prefrontal control results in exaggerated amygdala activity), later research suggested that
dysfunction in the PFC and limbic brain areas may stem from bidirectional alterations in
functional connectivity. An increasingly emerging body of studies has revealed PTSD symptoms
may arise from a breakdown in the interaction between larger-scale, neurocognitive networks.
Recent advances in fMRI methodology have allowed for a more comprehensive assessment of
network interactions in PTSD. Newly developed network analysis techniques have shifted the
focus toward a perspective that views the brain as a network system, and have suggested that
disconnection or hyper-connection between brain regions is more relevant to clinical symptom
expression than regional dysfunction itself. Relatively lower frontal connectivity and
hyper-connectivity of limbic-amygdala circuitry have been found in PTSD. However, due to the
unstable nature of the conventional brain imaging analysis techniques, replication studies
are generally lacking and test-retest variability is too high to be qualified as a
"biomarker" to be used in clinical settings. In the current study, the investigators have
proposed using a novel method that can identify reliable brain network topography and
quantify the degree of abnormality which has great potential to be used as a biomarker for
PTSD.
In a preliminary study, the investigators analyzed the resting state fMRI data of 11 PTSD and
11 trauma-exposed control (TEC) subjects using a novel approach that combines graph theory
and scaled subprofile modeling (SSM), which identifies eigenvector centrality and its
group-discriminating topographical pattern, respectively. The eigenvector centrality
represents how a node is neighboring other important nodes with respect to information flow.
The resulting pattern was characterized by increased eigenvector centrality in the
orbitofrontal regions, left amygdala, left anterior cingulate, right middle frontal and right
angular cortices (Ko & Patel, in preparation). Moreover, the degree of pattern expression was
significantly higher in PTSD patients compared to TEC (t(20)=2.165, p=0.043) and this pattern
expression was correlated with memory performance for negative versus positive information
only in the PTSD group (r=0.641, p=0.034). As SSM typically focuses on the principal
components with >10% variance-accounted-for, it has historically demonstrated high
replicability which lends the proposed method to be a potentially more useful biomarker.
In the proposed project, the investigators will recruit 40 patients with PTSD, 20 patients
with trauma exposure but without PTSD (TEC; 1st control group) and 20 healthy normal subjects
(HC; 2nd control group). All participants will undergo a comprehensive assessment (including
a psychodiagnostic and neuropsychological assessment) followed by resting state fMRI. The
PTSD and TEC groups will then be re-scanned with resting-state fMRI after undergoing 12
sessions of cognitive-processing therapy (CPT; 1 session/week). The HC group will be
rescanned 12 weeks later but no intervention will be introduced. The investigators expect
that the investigators will be able to replicate the preliminary finding described above
(i.e., identifying a PTSD-related network configuration that is not present in the control
groups) and demonstrate that changes within the PTSD-related network pattern expression will
be correlated with clinical improvement after CPT. The anticipated neuroimaging results are
expected to reveal a reliable neurobiological biomarker associated with the treatment (i.e.,
symptom reduction) of PTSD. The use of objective neuroimaging-based biomarkers will benefit
clinicians, patients and caregivers by significantly advancing the ability to establish a
connection between brain-related changes and an improvement in clinical symptoms.
