Catherine D. Chong

Functional MRI of migraine

Migraine is a disabling neurological condition manifesting with attacks of headache, hypersensitivities to visual, auditory, olfactory and somatosensory stimuli, nausea, and vomiting. Exposure to sensory stimuli, such as odours, visual stimuli, and sounds, commonly triggers migraine attacks, and hypersensitivities to sensory stimuli are prominent during migraine attacks, but can persist with less magnitude between attacks. Functional MRI (fMRI) has been used to investigate the mechanisms that lead to migraine sensory hypersensitivities by measuring brain responses to visual, olfactory, and painful cutaneous stimulation, and functional connectivity analyses have investigated the functional organisation of specific brain regions and networks responsible for sensory processing. These studies have consistently shown atypical brain responses to sensory stimuli, absence of the normal habituating response between attacks, and atypical functional connectivity of sensory processing regions. Identification of the mechanisms that lead to migraine sensory hypersensitivities and that trigger migraine attacks in response to sensory stimuli might help to better understand neural dysfunction in migraine and provide new targets for migraine prevention, and could provide fMRI biomarkers that indicate early responses to preventive therapy.

Enhanced pain-induced activity of pain-processing regions in a case-control study of episodic migraine

Objective The objective of this study was to identify brain regions having aberrant pain-induced activation in migraineurs, thereby gaining insight into particular aspects of pain processing that are atypical in migraineurs. Methods Functional magnetic resonance imaging assessed whole brain responses to painful heat in 24 adult episodic migraineurs who were at least 48 hours pain free and 27 healthy controls. Regions differentially activated in migraineurs compared to controls were identified. Activation intensities in these regions were correlated with headache frequency, number of migraine years, and time to next migraine attack. Results Migraineurs had greater pain-induced activation of lentiform nucleus, fusiform gyrus, subthalamic nucleus, hippocampus, middle cingulate cortex, premotor cortex, somatosensory cortex, and dorsolateral prefrontal cortex, and less activation in precentral gyrus and superior temporal gyrus. There were significant correlations between activation strength and headache frequency for middle cingulate (r = 0.627, p = 0.001), right dorsolateral prefrontal cortex (r = 0.568, p = 0.004), left fusiform gyrus (r = 0.487, p = 0.016), left precentral gyrus (r = 0.415, p = 0.044), and left hippocampus (r = 0.404, p = 0.050) and with number of migraine years for left fusiform gyrus (r = 0.425, p = 0.038). There were no significant correlations between activation strength and time to next migraine attack. Conclusions The majority of regions with enhanced pain-induced activation in headache-free migraineurs participate in cognitive aspects of pain perception such as attending to pain and pain memory. Enhanced cognitive pain processing by migraineurs might reflect cerebral hypersensitivity related to high expectations and hypervigilance for pain.

Accurate classification of chronic migraine via brain magnetic resonance imaging

The International Classification of Headache Disorders provides criteria for the diagnosis and subclassification of migraine. Since there is no objective gold standard by which to test these diagnostic criteria, the criteria are based on the consensus opinion of content experts. Accurate migraine classifiers consisting of brain structural measures could serve as an objective gold standard by which to test and revise diagnostic criteria. The objectives of this study were to utilize magnetic resonance imaging measures of brain structure for constructing classifiers: (1) that accurately identify individuals as having chronic vs episodic migraine vs being a healthy control; and (2) that test the currently used threshold of 15 headache days/month for differentiating chronic migraine from episodic migraine.

Low heat pain thresholds in migraineurs between attacks.

Background/Objective Between attacks, migraine is associated with hypersensitivities to sensory stimuli. The objective of this study was to investigate hypersensitivity to pain in migraineurs between attacks. Methods Cutaneous heat pain thresholds were measured in 112 migraineurs, migraine free for ≥48 hours, and 75 healthy controls. Pain thresholds at the head and at the arm were compared between migraineurs and controls using two-tailed t-tests. Among migraineurs, correlations between heat pain thresholds and headache frequency, allodynia symptom severity, and time interval until next headache were calculated. Results Migraineurs had lower pain thresholds than controls at the head (43.9℃ ± 3.2℃ vs. 45.1℃ ± 3.0℃, p = 0.015) and arm (43.2℃ ± 3.4℃ vs. 44.8℃ ± 3.3℃, p < 0.001). There were not significant correlations between pain thresholds and headache frequency or allodynia symptom severity. For the 41 migraineurs for whom time to next headache was known, there were positive correlations between time to next headache and pain thresholds at the head (r = 0.352, p = 0.024) and arm (r = 0.312, p = 0.047). Conclusions This study provides evidence that migraineurs have low heat pain thresholds between migraine attacks. Mechanisms underlying these lower pain thresholds could also predispose migraineurs to their next migraine attack, a hypothesis supported by finding positive correlations between pain thresholds and time to next migraine attack.

Atypical age-related cortical thinning in episodic migraine.

Background Prior studies demonstrate reduced cortical thickness and volume in migraineurs. However, the effect of age on cortical thickness has not been assessed in migraineurs. In this study we investigated whether the process of aging on cortical thickness affects migraineurs differently compared to age-matched healthy controls, i.e. whether aging exacerbates cortical thinning in migraineurs. Methods Cortical thickness was estimated using a general linear model vertex-by-vertex approach for 32 healthy controls (mean age = 35.3 years; SD = 11.6) and 27 episodic migraine patients (mean age = 33.6 years; SD = 12.3). Results were modeled using a main effect analysis to estimate the effect of age on cortical thickness for each group separately, and an age-by-group analysis to estimate differences in age-related cortical thinning between migraine patients and normal controls. Results Although migraineurs and normal controls both have expected age-related thinning in many regions along the cortical mantle, migraineurs have age-related thinning of regions that do not thin in healthy controls, including: bilateral postcentral, right fusiform, and right temporal pole areas. Cortical thinning of these regions is more prominent with advancing age. Conclusion Results suggest that migraine is associated with atypical cortical aging, suggesting that the migraine disease process interacts with aging to affect cortical integrity.

Correlations between Brain Cortical Thickness and Cutaneous Pain Thresholds Are Atypical in Adults with Migraine

Background/Objective Migraineurs have atypical pain processing, increased expectations for pain, and hypervigilance for pain. Recent studies identified correlations between brain structure and pain sensation in healthy adults. The objective of this study was to compare cortical thickness-to-pain threshold correlations in migraineurs to healthy controls. We hypothesized that migraineurs would have aberrant relationships between the anatomical neurocorrelates of pain processing and pain thresholds. Methods Pain thresholds to cutaneously applied heat were determined for 31 adult migraineurs and 32 healthy controls. Cortical thickness was determined from magnetic resonance imaging T1-weighted sequences. Regional cortical thickness-to-pain threshold correlations were determined for migraineurs and controls separately using a general linear model whole brain vertex-wise analysis. A pain threshold-by-group interaction analysis was then conducted to estimate regions where migraineurs show alterations in the pain threshold-to-cortical thickness correlations relative to healthy controls. Results Controls had negative correlations (p<0.01 uncorrected) between pain thresholds and cortical thickness in left posterior cingulate/precuneus, right superior temporal, right inferior parietal, and left inferior temporal regions, and a negative correlation (p<0.01 Monte Carlo corrected) with a left superior temporal/inferior parietal region. Migraineurs had positive correlations (p<0.01 uncorrected) between pain thresholds and cortical thickness in left superior temporal/inferior parietal, right precuneus, right superior temporal/inferior parietal, and left inferior parietal regions. Cortical thickness-to-pain threshold correlations differed between migraine and control groups (p<0.01 uncorrected) for right superior temporal/inferior parietal, right precentral, left posterior cingulate/precuneus, and right inferior parietal regions and (p<0.01 Monte Carlo corrected) for a left superior temporal/inferior parietal region. Conclusions Unlike healthy control subjects who have a significant negative correlation between cortical thickness in a superior temporal/inferior parietal region with pain thresholds, migraineurs have a non-significant positive correlation between cortical thickness in a superior temporal/inferior parietal region with pain thresholds. Since this region participates in orienting and attention to painful stimuli, absence of the normal correlation might represent a migraineurs inability to inhibit pain sensation via shifting attention away from the painful stimulus.

Migraine classification using magnetic resonance imaging resting-state functional connectivity data

Background This study used machine-learning techniques to develop discriminative brain-connectivity biomarkers from resting-state functional magnetic resonance neuroimaging (rs-fMRI) data that distinguish between individual migraine patients and healthy controls. Methods This study included 58 migraine patients (mean age = 36.3 years; SD = 11.5) and 50 healthy controls (mean age = 35.9 years; SD = 11.0). The functional connections of 33 seeded pain-related regions were used as input for a brain classification algorithm that tested the accuracy of determining whether an individual brain MRI belongs to someone with migraine or to a healthy control. Results The best classification accuracy using a 10-fold cross-validation method was 86.1%. Resting functional connectivity of the right middle temporal, posterior insula, middle cingulate, left ventromedial prefrontal and bilateral amygdala regions best discriminated the migraine brain from that of a healthy control. Migraineurs with longer disease durations were classified more accurately (>14 years; 96.7% accuracy) compared to migraineurs with shorter disease durations (≤14 years; 82.1% accuracy). Conclusions Classification of migraine using rs-fMRI provides insights into pain circuits that are altered in migraine and could potentially contribute to the development of a new, noninvasive migraine biomarker. Migraineurs with longer disease burden were classified more accurately than migraineurs with shorter disease burden, potentially indicating that disease duration leads to reorganization of brain circuitry.

Temporal Lobe Cortical Thickness Correlations Differentiate the Migraine Brain from the Healthy Brain

Background Interregional cortical thickness correlations reflect underlying brain structural connectivity and functional connectivity. A few prior studies have shown that migraine is associated with atypical cortical brain structure and atypical functional connectivity amongst cortical regions that participate in sensory processing. However, the specific brain regions that most accurately differentiate the migraine brain from the healthy brain have yet to be determined. The aim of this study was to identify the brain regions that comprised interregional cortical thickness correlations that most differed between migraineurs and healthy controls. Methods This was a cross-sectional brain magnetic resonance imaging (MRI) investigation of 64 adults with migraine and 39 healthy control subjects recruited from tertiary-care medical centers and their surrounding communities. All subjects underwent structural brain MRI imaging on a 3T scanner. Cortical thickness was determined for 70 brain regions that cover the cerebral cortex and cortical thickness correlations amongst these regions were calculated. Cortical thickness correlations that best differentiated groups of six migraineurs from controls and vice versa were identified. Results A model containing 15 interregional cortical thickness correlations differentiated groups of migraineurs from healthy controls with high accuracy. The right temporal pole was involved in 13 of the 15 interregional correlations while the right middle temporal cortex was involved in the other two. Conclusions A model consisting of 15 interregional cortical thickness correlations accurately differentiates the brains of small groups of migraineurs from those of healthy controls. Correlations with the right temporal pole were highly represented in this classifier, suggesting that this region plays an important role in migraine pathophysiology.

Migraine affects white-matter tract integrity: A diffusion-tensor imaging study.

Background Specific white-matter tract alterations in migraine remain to be elucidated. Using diffusion tensor imaging (DTI), this study investigated whether the integrity of white-matter tracts that underlie regions of the “pain matrix” is altered in migraine and interrogated whether the number of years lived with migraine modifies fibertract structure. Methods Global probabilistic tractography was used to assess the anterior thalamic radiations, the corticospinal tracts and the inferior longitudinal fasciculi in 23 adults with migraine and 18 healthy controls. Results Migraine patients show greater mean diffusivity (MD) in the left and right anterior thalamic radiations, the left corticospinal tract, and the right inferior longitudinal fasciculus tract. Migraine patients also show greater radial diffusivity (RD) in the left anterior thalamic radiations, the left corticospinal tract as well as the left and right inferior longitudinal fasciculus tracts. No group fractional anisotropy (FA) differences were identified for any tracts. Migraineurs showed a positive correlation between years lived with migraine and MD in the right anterior thalamic radiations (r = 0.517; p = 0.012) and the left corticospinal tract (r = 0.468; p = 0.024). Conclusion Results indicate that white-matter integrity is altered in migraine and that longer migraine history is positively correlated with greater alterations in tract integrity.

White Matter Damage and Brain Network Alterations in Concussed Patients: A Review of Recent Diffusion Tensor Imaging and Resting-State Functional Connectivity Data

Over 2 million people are diagnosed with concussion each year in the USA, resulting in substantial individual and societal burdens. Although ‘routine’ clinical neuroimaging is useful for the diagnosis of more severe forms of traumatic brain injury, it is insensitive for detecting pathology associated with concussion. Diffusion tensor imaging (DTI) and blood-oxygenation-level-dependent (BOLD) resting-state functional connectivity magnetic resonance imaging (rs-fMRI) are techniques that allow for investigation of brain structural and functional connectivity patterns. DTI and rs-fMRI may be more sensitive than routine neuroimaging for detecting brain sequelae of concussion. This review summarizes recent DTI and rs-fMRI findings of altered structural and functional connectivity patterns in concussed patients.