Excessive fatigue in stroke survivors, referred to as poststroke fatigue, is a common and disabling problem. The cause of poststroke fatigue is unknown and there is no effective treatment. Several observations point to a role of brain inflammation in poststroke fatigue. Among these observations, experimental manipulations that cause brain inflammation result in fatigue. Stroke is also known to cause brain inflammation, initially in the area of brain damage, then spreading to distant brain regions that are physically connected to the stroke-damaged tissue by neural pathways. While inflammation has been observed in brain regions distant from the damaged tissue in chronic stroke patients, no study has tested whether this inflammation is linked to poststroke fatigue. The proposed project will test, for the first time, the overall hypothesis that brain inflammation and associated changes in brain connectivity play an important role in poststroke fatigue in chronic stroke patients. To test this hypothesis, we will enroll 24 patients who had a stroke 1-year earlier, have good motor, cognitive and mood outcomes, and do not have a comorbid condition that might be expected to cause fatigue. The selected patients will have a range of fatigue, from low to high. Brain imaging will be performed by an integrated Positron Emission Tomography / Magnetic Resonance Imaging (PET/MRI) scanner and [11C]PBR28, a high sensitivity and specificity marker of brain inflammation. Use of the integrated PET/MRI scanner will allow us to acquire PET and MRI data simultaneously, which shortens scan time for patients, and also allows us to implement advanced methods for using the MRI data to improve the quality of the [11C]PBR28 PET data.
Our first aim will be to localize brain regions where increased [11C]PBR28 signal, meaning increased inflammation, is associated with greater fatigue severity in the chronic stroke patients.
Our second aim will be to evaluate whether brain inflammation is associated with changes in brain connectivity. To address this aim, we will measure brain connectivity in two ways. One way will be to measure the strength of white matter connections, commonly referred to as structural connectivity, using high angular resolution diffusion MRI. The other way will be to measure the strength of correlated neural signaling, commonly referred to as functional connectivity, using resting-state functional MRI. Together, the [11C]PBR28 PET and multi-modality MRI data will allow us to identify inflammatory and brain connectivity changes linked to poststroke fatigue. This new information will lay the groundwork for developing an effective treatment for poststroke fatigue. More broadly, our findings would open the door to examining the functional impact of chronic brain inflammation in stroke patients, a condition long known to exist but largely ignored in the context of understanding and treating persistent poststroke deficits. Our findings would also provide insight to biological mechanisms of the fatigue that is common in many other neurological conditions.

Public Health Relevance

Despite several lines of evidence pointing to the possibility that brain inflammation underlies the excessive fatigue that stroke patients often feel, this has never been tested. The proposed study will use PET/MRI scanning to test for the first time whether brain inflammation, and associated abnormalities in brain connectivity, play an important role in poststroke fatigue. Our findings could lead to treating poststroke fatigue by modifying inflammation in the brain, which would significantly improve the quality of life for millions of stroke survivors in the United States.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21NS110982-01
Application #
9721510
Study Section
Acute Neural Injury and Epilepsy Study Section (ANIE)
Program Officer
Chen, Daofen
Project Start
2019-06-01
Project End
2021-05-31
Budget Start
2019-06-01
Budget End
2021-05-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114