CPT-fMRI Study for PTSD

NCT ID: NCT03229915

Last Updated: 2023-02-15

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 68 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2017-10-01
• Study Completion Date: 2022-09-30

Brief 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.

Detailed 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.

Conditions

Stress Disorders, Post-Traumatic

Study Design

• Allocation Method: NON_RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: TREATMENT
• Blinding Strategy: NONE

Study Groups

PTSD

Will receive Cognitive Processing Therapy

Group Type: ACTIVE_COMPARATOR

cognitive processing therapy

Intervention Type: BEHAVIORAL

Group therapy for PTSD patients

Trauma-exponsed control

Will receive Cognitive Processing Therapy

Group Type: ACTIVE_COMPARATOR

cognitive processing therapy

Intervention Type: BEHAVIORAL

Group therapy for PTSD patients

no trauma healthy control

Scanned twice (13 weeks apart) without any intervention

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

cognitive processing therapy

Group therapy for PTSD patients

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

1. Current diagnosis of PTSD as assessed by the Clinician Administered PTSD Scale (CAPS) for the DSM-V [30]; CAPS ≥ 15

2. Presence of at least one intrusion symptom, two negative cognition and mood symptoms, and two arousal symptoms.

Trauma Exposed Controls

1. experienced a traumatic event (as assessed by criterion A of the CAPS)

2. CAPS < 15 Health Controls

1. Not experienced a traumatic event (as assessed by criterion A of the CAPS ≤15)

EXCLUSION All

1. substance dependence not in remission for at least three months

2. current uncontrolled bipolar or psychotic disorder, or severe cognitive impairment.

3. Contraindications for MRI (e.g., no metal implants, not pregnant)

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Workers Compensation Board of Manitoba

UNKNOWN

Sponsor Role: collaborator

University of Manitoba

OTHER

Sponsor Role: lead

Responsible Party

Ji Hyun Ko, PhD

Assistant Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

University of Manitoba

Winnipeg, Manitoba, Canada

Countries

Canada

References

Yakemow G, Kolesar TA, Wright N, Beheshti I, Choi EH, Ryner L, Chaulk S, Patel R, Ko JH. Investigating neural markers of Alzheimer's disease in posttraumatic stress disorder using machine learning algorithms and magnetic resonance imaging. Front Neurol. 2024 Nov 7;15:1470727. doi: 10.3389/fneur.2024.1470727. eCollection 2024.

Reference Type: DERIVED

PMID: 39574505 (View on PubMed)

Other Identifiers

B2017:029

Identifier Type: -

Identifier Source: org_study_id