Poster No:
2504
Submission Type:
Abstract Submission
Authors:
Sarasa Tohyama1,2, Michael Datko1,2,3, Mackenzie Hyman2, Alison Goldstein1,2, Kassandra Round1,2,3, Lillian Kinder1,2,3, Ludovica Brusaferri2, Ronald Garcia2, Randy Gollub2, Robert Edwards4, Bruce Rosen2, Nouchine Hadjikhani2, Cheng Hsinlin5, Zev Schuman-Olivier3, Marco Loggia2, Vitaly Napadow1,2
Institutions:
1Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, 2A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 3Center for Mindfulness and Compassion, Cambridge Health Alliance, Harvard Medical School, Boston, MA, 4Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 5Massachusetts General Hospital, Harvard Medical School, Boston, MA
First Author:
Sarasa Tohyama, PhD
Spaulding Rehabilitation Hospital, Harvard Medical School|A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA|Boston, MA
Co-Author(s):
Michael Datko, PhD
Spaulding Rehabilitation Hospital, Harvard Medical School|A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School|Center for Mindfulness and Compassion, Cambridge Health Alliance, Harvard Medical School
Boston, MA|Boston, MA|Boston, MA
Mackenzie Hyman
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA
Alison Goldstein
Spaulding Rehabilitation Hospital, Harvard Medical School|A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA|Boston, MA
Kassandra Round
Spaulding Rehabilitation Hospital, Harvard Medical School|A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School|Center for Mindfulness and Compassion, Cambridge Health Alliance, Harvard Medical School
Boston, MA|Boston, MA|Boston, MA
Lillian Kinder
Spaulding Rehabilitation Hospital, Harvard Medical School|A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School|Center for Mindfulness and Compassion, Cambridge Health Alliance, Harvard Medical School
Boston, MA|Boston, MA|Boston, MA
Ludovica Brusaferri
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA
Ronald Garcia, MD, PhD
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA
Randy Gollub, MD, PhD
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA
Bruce Rosen, MD, PhD
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA
Zev Schuman-Olivier, MD
Center for Mindfulness and Compassion, Cambridge Health Alliance, Harvard Medical School
Boston, MA
Marco Loggia, PhD
A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA
Vitaly Napadow
Spaulding Rehabilitation Hospital, Harvard Medical School|A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School
Boston, MA|Boston, MA
Introduction:
Migraine, a highly prevalent neurological condition, involves sensitization of the trigeminal nerve system (Charles, 2018; Noseda and Burstein, 2013). Magnetic resonance imaging (MRI) offers an in-vivo, non-invasive avenue to examine the trigeminal nerve in humans, and in particular, diffusion tensor imaging (DTI) can be used to assess white matter microstructural tissue characteristics (Alexander et al., 2007). Previous DTI studies have shown microstructural abnormalities of the trigeminal nerve root in neurological conditions such as trigeminal neuralgia (DeSouza et al., 2014) and temporomandibular disorder (Moayedi et al., 2012). Such abnormalities in migraine, however, have not been adequately studied. Here, we employed 7 Tesla DTI, allowing for improved spatial resolution, to investigate the microstructural properties of the trigeminal nerve root in patients with episodic migraine.
Methods:
Our ongoing longitudinal study has enrolled 45 patients with episodic migraine (43F, mean age +/- SD: 35.98 +/- 11.57 years) and 18 age- and sex-matched healthy individuals (17F, mean age +/- SD: 35.82 +/- 13.83 years). All subjects completed a 4-week period of electronic daily headache diaries to confirm eligibility (i.e., 4-20 headache days for migraine patients and no headaches characteristic of migraine for healthy individuals). Each subject underwent a brainstem-focused diffusion-weighted imaging scan (7T MAGNETOM Terra equipped with an in-house built 64-channel coil, 64 directions, b = 1,000, repetition time = 5,900 ms, echo time = 68 ms, resolution = 1 mm isotropic) and two b0 scans with reversed phase-encode blips. The b0 images were used for susceptibility-induced distortion correction, followed by eddy current and motion correction. Scalar maps of fractional anisotropy (FA), radial diffusivity (RD), mean diffusivity (MD), and axial diffusivity (AD) were calculated. The four DTI metrics were manually extracted from the left and right trigeminal nerve roots in individual space and compared between migraine patients and healthy individuals. For multiple testing correction, false discovery rate correction was used.
Results:
Ultra-high field 7 Tesla DTI successfully delineated the small-scale structure of the trigeminal nerve roots and enabled customization of the region-of-interest based on each subject's nerve root geometry. Migraine patients showed significantly reduced FA (U = 109, p = 2.8 x 10-5), and increased RD (U = 189, p = 0.0020) and MD (U = 231, p = 0.011), in the trigeminal nerve root compared with healthy individuals. No significant differences were found for AD (U = 320, p = 0.20). To assess laterality effects based on headache presentation, the left and right trigeminal nerve roots were compared for all four DTI metrics, which revealed no significant differences in both migraine patients and healthy individuals (p > 0.20 for all comparisons).
Conclusions:
Our findings demonstrate that patients with episodic migraine have white matter microstructural abnormalities in the trigeminal nerve root, characterized by reduced FA, and increased RD and MD, and highlight the importance of DTI as a tool to investigate anatomopathological substrates of migraine disease that are not distinguishable on conventional MRI. Elevated RD and MD in migraine patients suggest myelin degeneration and inflammation-induced edema as previously described (Alexander et al., 2007) and shown in histological studies (Song et al., 2005, 2002). Trigeminal nerve root remodeling may be an important aspect of the dynamics underlying migraine pathophysiology.
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Diffusion MRI
Perception, Attention and Motor Behavior:
Perception: Pain and Visceral 1
Keywords:
Brainstem
DISORDERS
Headache
HIGH FIELD MR
MRI
Nerves
Neurological
Pain
STRUCTURAL MRI
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review
Provide references using author date format
Alexander, A.L., Lee, J.E., Lazar, M., Field, A.S., 2007. Diffusion tensor imaging of the brain. Neurotherapeutics 4, 316–329.
Charles, A., 2018. The pathophysiology of migraine: implications for clinical management. Lancet Neurol. 17, 174–182.
DeSouza, D.D., Hodaie, M., Davis, K.D., 2014. Abnormal trigeminal nerve microstructure and brain white matter in idiopathic trigeminal neuralgia. PAIN® 155, 37–44.
Moayedi, M., Weissman-Fogel, I., Salomons, T.V., Crawley, A.P., Goldberg, M.B., Freeman, B.V., Tenenbaum, H.C., Davis, K.D., 2012. White matter brain and trigeminal nerve abnormalities in temporomandibular disorder. PAIN® 153, 1467–1477.
Noseda, R., Burstein, R., 2013. Migraine pathophysiology: anatomy of the trigeminovascular pathway and associated neurological symptoms, cortical spreading depression, sensitization, and modulation of pain. PAIN® 154, S44–S53.
Song, S.-K., Sun, S.-W., Ramsbottom, M.J., Chang, C., Russell, J., Cross, A.H., 2002. Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 17, 1429–1436.
Song, S.-K., Yoshino, J., Le, T.Q., Lin, S.-J., Sun, S.-W., Cross, A.H., Armstrong, R.C., 2005. Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage 26, 132–140.